On 2016 May 02, Clive Bates commented:

It is worth drawing out the most telling criticism made by Hajek, McRobbie and Bullen (above) in their response in the Lancet Respiratory Medicine (above).

There are other problems—such as selective inclusion of studies, and selective reporting of data from studies that were included—and limitations the authors acknowledge in the text but ignore in their conclusions. Detailed criticism of the methods is, however, not needed, because lumping incongruous studies together—which were mostly not designed to evaluate the efficacy of e-cigarettes, and contain no useful information on this topic unless misinterpreted—makes no scientific sense in the first place.

The fundamental problem really is of lumping together completely different studies designed to observe different behaviours in different populations with different outcome measures (mostly not to see how well e-cigarettes help smokers quit). This problem is fatal, and has not been addressed convincingly anywhere, and cannot be, by the authors. Meta-anlaysis is fine for pooling, for example, several drug trials conducted in more with almost identical methodology, but not as it used here.

Once all the studies that should not be 'lumped together' are not lumped together, we come back to something more like the Cochrane review: Can electronic cigarettes help people stop smoking or reduce the amount they smoke, and are they safe to use for this purpose?, which is tentatively positive, but weak given the small numbers of relevant studies.

On 2016 May 01, Peter Hajek commented:

There are several serious problems with this review, see http://www.thelancet.com/pdfs/journals/lanres/PIIS2213-2600(16)30024-8.pdf

The most obvious issue is that the result is based on studies that have no bearing on whether e-cigarettes are effective or not. This is because vapers who successfully quit smoking were excluded and only those who failed to do so were retained. The studies were not at fault, they were just not set up to evaluate quit rates in smokers who try and not try vaping. The fault is with misinterpreting their results. The letter in LRM referenced above provides more details.

On 2016 Apr 25, Stanton A Glantz commented:

A detailed response to the "expert" criticism is available here: http://tobacco.ucsf.edu/our-new-meta-analysis-entire-relevant-literature-shows-e-cigarettes-used-are-associated-less-not-more-quit#comment-17171

On 2016 Apr 24, Clive Bates commented:

This meta-analysis has been subject to considerable criticism from the moment of its publication, see Expert reaction to meta-analysis looking at e-cigarette use and smoking cessation via the Science Media Centre.

For example, Professor Robert West, Professor of Health Psychology at University College London, commented: “Publication of this study represents a major failure of the peer review system in this journal.”

A pre-publication version of this meta-analysis was severely criticised in evidence to the U.S. Food and Drug Administration by experts at the Truth Initiative, which describes itself as "America’s largest non-profit public health organization dedicated to making tobacco use a thing of the past". In the Truth Initiative submission to FDA the examination of the methodological issues begins on page 8 and the following comment appears on page 12, referring to the analysis subsequently published in Lancet Respiratory Medicine.

"While the majority of the studies we reviewed are marred by poor measurement of exposures and unmeasured confounders, many of them have been included in a meta-analysis that claims to show that smokers who use e-cigarettes are less likely to quit smoking compared to those who do not. [73] This meta-analysis simply lumps together the errors of inference from these correlations. As described in detail above, quantitatively synthesizing heterogeneous studies is scientifically inappropriate and the findings of such meta-analyses are therefore invalid."

I hope that in due course The Lancet Respiratory Medicine will publish a critique and reconsider its decision to publish this paper. In the meantime, my own critique is available on my blog.

I would also like to draw readers' attention to a thoughtful discussion of the failings of this meta-analysis by Carl V. Phillips on his blog

On 2016 Jun 03, Ewen Gallagher commented:

Here we present a new genetic model (Lck^Cre/+ Map3k1^f/f) used to analyse Mekk1 (encoded by Map3k1) conditionally in T cells. Our research shows new roles for Map3k1 in T cell development and in unconventional T cells. There is also an expanded view on the research (1). This work continues the genetic analysis of Map3k1 in T cells (2-5). Other related works are available analysing Mekk1 activation by cytokines and hyperosmotic stress (6-8).

Related works. (1). Suddason T, Gallagher E. Genetic insights into Map3k-dependent proliferative expansion of T cells. Cell cycle 2016:0. (2). Gao M, Labuda T, Xia Y, Gallagher E, Fang D, Liu YC, Karin M. Jun turnover is controlled through JNK-dependent phosphorylation of the E3 ligase Itch. Science 2004; 306:271-5. (3). Gallagher E, Gao M, Liu YC, Karin M. Activation of the E3 ubiquitin ligase Itch through a phosphorylation-induced conformational change. Proceedings of the National Academy of Sciences of the United States of America 2006; 103:1717-22. (4). Venuprasad K, Elly C, Gao M, Salek-Ardakani S, Harada Y, Luo JL, Yang C, Croft M, Inoue K, Karin M, et al. Convergence of Itch-induced ubiquitination with MEKK1-JNK signaling in Th2 tolerance and airway inflammation. J Clin Invest 2006; 116:1117-26. (5). Gallagher E, Enzler T, Matsuzawa A, Anzelon-Mills A, Otero D, Holzer R, Janssen E, Gao M, Karin M. Kinase MEKK1 is required for CD40-dependent activation of the kinases Jnk and p38, germinal center formation, B cell proliferation and antibody production. Nature immunology 2007; 8:57-63. (6). Matsuzawa A, Tseng PH, Vallabhapurapu S, Luo JL, Zhang W, Wang H, Vignali DA, Gallagher E, Karin M. Essential cytoplasmic translocation of a cytokine receptor-assembled signaling complex. Science 2008; 321:663-8. (7). Steed E, Elbediwy A, Vacca B, Dupasquier S, Hemkemeyer SA, Suddason T, Costa AC, Beaudry JB, Zihni C, Gallagher E, et al. MarvelD3 couples tight junctions to the MEKK1-JNK pathway to regulate cell behavior and survival. The Journal of cell biology 2014; 204:821-38. (8). Charlaftis N, Suddason T, Wu X, Anwar S, Karin M, Gallagher E. The MEKK1 PHD ubiquitinates TAB1 to activate MAPKs in response to cytokines. The EMBO journal 2014; 33:2581-96.

On 2016 Apr 02, Arnaud Chiolero MD PhD commented:

A brief and excellent review to be updated on the tobacco epidemic

On 2017 Feb 07, Laura E Kwako commented:

Thank you for the question. We plan to administer the Digit Span task after the Trier Social Stress Test to explore the effects of stress on working memory, thus, included it in the Negative Emotionality domain (although it asures an aspect of Executive Function). We appreciate the opportunity to clarify this issue.

On 2017 Jan 30, Francisco Xavier Castellanos commented:

Can the authors clarify why Digit Span is included as part of the Negative Emotionality construct? It would seem to be better located within the Executive Function domain.

On 2016 Apr 26, Christopher Southan commented:

Update July 2016: team above have published the Zika virus protease structure http://www.ncbi.nlm.nih.gov/pubmed/27386922

Thanks to the author's response in sending InChI strings from compoounds reviewed, most are now mapped into PubChem http://cdsouthan.blogspot.se/2016/02/med-chem-starting-points-for-zika.html

On 2016 Jan 28, Donald Forsdyke commented:

HYPOTHESIS-DRIVEN RESEARCH

The discoveries of a cytosolic microbial adaptive immune system (CRISPR) and its applications to genome editing are major scientific advances. A review of the history of this magnificent achievement, made mainly by young people close to those with abundant research funds, is welcome. But the implication that this history supports the non-hypothesis-driven approach to research is questionable.

Backed by inexpensive bioinformatic analyses, a hypothesis of cytosolic innate immunity was developed in the 1990s [1-3]. Had this CRISPR-analogous hypothesis been backed by funding, CRISPR and its applications might have been achieved more expeditiously. Thus, there are many roads to Rome. Because the well-equipped army that took route A arrive first, it does not follow that route A is superior to route B. Likewise, this comment could have been written in prose or poetry. Your liking (perhaps) of the present prose rendition, does not disprove the proposition that a poetic version might have been superior.

[1] Forsdyke & Mortimer (2000) Chargaff’s legacy. Gene 261, 127-137.Forsdyke DR, 2000

[2] Cristillo et al. (2001) Double-stranded RNA as a not-self alarm signal: to evade, most viruses purine-load their RNAs, but some (HTLV-1, Epstein-Barr) pyrimidine-load. J Theor Biol 208, 475-491.Cristillo AD, 2001

[3] Forsdyke, Madill & Smith (2002) Immunity as a function of the unicellular state: implications of emerging genomic data. Trends Immunol 23, 575-579.Forsdyke DR, 2002

On 2016 Jan 26, Donald Forsdyke commented:

None

On 2016 Jan 24, Claudiu Bandea commented:

None

On 2016 Jan 19, Emmanuelle Charpentier commented:

I regret that the description of my and collaborators’ contributions is incomplete and inaccurate. The author did not ask me to check statements regarding me or my lab. I did not see any part of this paper prior to its submission by the author. And the journal did not involve me in the review process.

On 2016 Jan 18, JENNIFER DOUDNA commented:

From Cell editor: “…the author engaged in substantial fact checking directly with the relevant individuals.”

However, the description of my lab’s research and our interactions with other investigators is factually incorrect, was not checked by the author and was not agreed to by me prior to publication.

On 2017 Oct 21, Anju Anand commented:

This is a commentary from our online Twitter #rsjc discussions

On 2017 Oct 18, Ian Small commented:

We are in the process of setting up a new site to make this data accessible. In the meantime, you can contact me directly (ian.small@uwa.edu.au) for help.

On 2017 Oct 13, Kristian Ullrich commented:

The link to the web portal http://www.plantppr.com is not working! If it has moved to another location maybe the authors could add a comment on where this resources is now located.

On 2016 Jan 21, Mayer Brezis commented:

None

On 2016 Jan 21, Mayer Brezis commented:

The paper by Dr. Macy in fact says: "Physician-documented cephalosporin-associated anaphylaxis was about 2.9-fold more common in individuals with histories of penicillin allergy than in individuals with no history of drug allergy." A remote risk of anaphylaxis supports using recommended first line antibiotics for cystitis such as nitrofurantoin or trimethoprim-sulfamethoxazole - see international guidelines (Clin Infect Dis. 2011;52: e103-e120) which add: "The β-lactams [such as cephalexin] generally have inferior efficacy and more adverse effects, compared with other UTI antimicrobials".

On 2016 Jan 14, Eric Macy commented:

Recent research has shown no increased risk of anaphylaxis with cephalosporin use in individuals with a history of penicillin allergy.J Allergy Clin Immunol. 2015 Mar;135(3):745-52.e5. doi: 10.1016/j.jaci.2014.07.062. Epub 2014 Sep 26.

On 2016 Sep 17, ROBERT COMBES commented:

Professor Michael Balls and Dr Robert Combes respond to Dr Coral Gartner regarding concerns about possible conflicts of interest.

We thank Dr Gartner for her comments, and for the opportunity to clarify potential conflicts of interest relating to our paper [1]. This was written by us as independent individuals, free of any commercial influence or funding, and after both of us had ceased having close ties with FRAME. FRAME is a scientific charity that has openly received financial support from the chemical, cosmetic, household product, pharmaceutical and tobacco industries, to enable it to undertake independent research into the development, validation and acceptance of alternatives to animal experiments.<br> Some of this work included the development, characterisation and preliminary assessment of in vitro models of inhalation toxicology. While we are not in a position to say anything about FRAME’S current policy on industrial funding, we must stress that the tobacco industry funding enabled FRAME to investigate ways to replace highly invasive and complex animal experiments with urgently needed alternatives with the potential for producing more-relevant and more-reliable data for assessing human safety.

As far as personal remuneration is concerned, RDC has acted as an external consultant for the tobacco industry since retiring in 2007 from FRAME. This work was conducted under standard contract research agreements, the last of which terminated over 12 months prior to the writing of our article. The work referred to by Dr Gartner, that was co-authored by RDC with a named individual as lead, relates to research undertaken when this individual and RDC were employed by Inveresk Research International (IRI, now Charles River Laboratories), a contract research establishment. This can be directly verified by opening the authors’ affiliations in PubMed (http://9www.ncbi.nlm.nih.gov/pubmed)for each of the four respective abstracts (PMID: 9491389; PMID: 1600961; PMID: 1396612; and PMID: 7968569). This work was entirely funded by the US Government, as was acknowledged in each of the papers, and also by the inclusion of another co-author, then based at NIEHS (the National Institute of Environmental Health Sciences, Research Triangle Park, USA), who acted as project leader. It should be noted that the lead author of the publications arising from the work conducted at IRI subsequently went to work at BAT, and this might have added to any confusion.

MB has never been a paid consultant for any industrial company. He was honorary Chairman of the FRAME Trustees from 1981 to 2013, and has been honorary Editor of FRAME’s journal, Alternatives to Laboratory Animals, since 1983. He no longer has any influence on FRAME’s policies on the tobacco industry or on any other issue. None of FRAME’s industrial supporters ever attempted to dictate or limit FRAME’s activities, or influence the circulation and/or publication of the results of any FRAME research. While MB was head of the FRAME Alternatives Laboratory at the University of Nottingham Medical School, no tobacco product, or chemical, other material or product of interest to the tobacco industry was involved in FRAME’s research. He left the University of Nottingham in 1993, to become the first head of the European Commission’s European Centre for the Validation of Alternative Methods, a position from which he retired in 2002. We consider that there is a distinction between the above situation, in which, despite previous links of various kinds with the tobacco industry, we wrote our critique [1](ref) without any form of external influence, and that which we referred to, involving alleged conflicts of interest in the MCDA study. However, while we acknowledge that conflicts of interest and their consequences are complex, we hope that we have taken into account as much relevant information as possible to permit a fair and balanced appraisal of the information on which PHE's policy on electronic cigarettes is based. We consider it crucial that scientific opinions, and the policies which result from them, are based on freely-available evidence of high quality, which has been openly conducted and independently assessed. We know of no such evidence to support PHE’s claim that e-cigarettes are 95% safer than tobacco cigarettes.

We welcome Dr Gartner’s comment, we hope that others will address the scientific arguments that we have used to justify our position, since, the validity, or otherwise, of these should be unaffected by any conflicts of interest. There is a great deal at stake, including the future well-being of those who have opted for vaping as an alternative to tobacco smoking. We stand by our belief, expressed in a letter published in The Times on 18 February 2016, that “The human respiratory system is a delicate vehicle, on the which the length and quality of our lives depend. For governments and companies to condone, or even suggest, the regular and repeated inhaling of a complex mixture of chemicals with addictive and toxic properties, but without comprehensive data, is irresponsible and could have serious consequences.”

1. Combes, R D. & Balls, M. On the safety of e-cigarettes: "I can resist anything except temptation". ATLA. (2015) 43, 417-425.

On 2016 Sep 15, Coral Gartner commented:

Combes and Balls raise the issue of potential conflicts of interest in their critique of the PHE-commissioned report on e-cigarettes.

Indeed, links between scientists and industry are regularly raised in the debate concerning tobacco harm reduction, and Tobacco Industry funding is of particular concern generally. For example, Simon Chapman writes, "Tobacco-funded research and the conduct of the industry which oversees it has arguably the worst of all reputations. This explains why that industry is unique among all others in being barred from funding research and scholarships at many universities."

Given this context and the general sensitivity around tobacco-industry funded researchers, I was somewhat surprised that Robert Combes didn't address his own history of being a paid consultant for British American Tobacco over at least two decades (Combes R, 2013 ; Combes R, 2012 ; Dillon D, 1994; Dillon D, 1998 ; Dillon D, 1992 ; Dillon D, 1992) when raising the issue of conflicts of interest in this article.

It would be very helpful if both authors could clarify the nature of their past and present relationships with BAT, and any other tobacco companies they have performed consultancy work for, and confirm when they last performed consultancy work for a tobacco company. Also could they advise what their current position is on undertaking further consultancy work for the tobacco industry in the future?

Similarly, it would be helpful to know if FRAME currently or previously has received funds from a tobacco company and what the organisation's current official policy on receipt of tobacco industry funds is.

On 2016 Apr 13, NephJC - Nephrology Journal Club commented:

This trial was discussed on March 15th and 16th 2016 in the open online nephrology journal club, #NephJC, on twitter. Introductory comments are available at the NephJC website.<br> The discussion was quite dynamic, with more than 75 participants, including nephrologists, gastroenterologists, geriatricians, clinical pharmacists, fellows, residents and patients, and included one of the authors (F. Perry Wilson). The transcript of the entire tweetchat is available on the NephJC website.<br> Some of the highlights of the tweetchat were:

• The team of investigators should be commended for designing and conducting this trial, and the NIH for funding the investigators, specifically the NHLBI for funding the ARIC study.

• The research team leveraged an existing study (ARIC) to test the association between PPI use and kidney disease, and went on validate the findings in another cohort (Geisinger). Along with the detailed statistical analysis and the robustness across various subgroups, this data does suggest a link between PPI use and chronic kidney disease (the link with acute kidney injury has been made before, and was also found in this study) with a very concerning number needed to harm (~ 30 in the ARIC cohort and 59 with the Geisinger cohort).

• However, given the wide prevalence of PPI use and quite likely some residual confounding for unmeasured factors (such as frailty), as also the lack of a firm biological basis for chronic kidney damage, most participants felt further replication of these findings would be more convincing. Despite the relatively low number needed to harm, PPIs have a remarkably lower number needed to treat (eg NNT 4, compared to ranitidine for reflux esophagitis). Nevertheless, deprescribing PPIs, especially with a useful algorithm such as this, could be incorporated into practice.

Interested individuals can track and join in the conversation by following @NephJC on twitter, liking #NephJC on facebook, signing up for the mailing list, or visit the webpage at NephJC.com.

On 2016 Jan 20, Rafael Najmanovich commented:

Anyone interested in creating annotated human kinome images similar to those presented in this article may wish to take a look at the free kinome render tool: Chartier M, 2013.

On 2017 Feb 08, Tony Gardner-Medwin commented:

This paper (Gomes et al., 2016) raises a dilemma for readers. If well founded, it clearly merits much work to understand it and its implications. But the conclusions conflict so strongly with conventional wisdom that it is tempting to dismiss it as probably somehow incorrect. All credit therefore to Barbour (2016) for critiquing it and pinpointing questions that clearly need answering. Hopefully, both the authors and others with their own perspectives may contribute to clarify the situation.

Broadly I concur with the points Barbour raises. I would add however what seems possibly a key oversight in the papers from Gomes' group. This is in the argument that observed filter characteristics and cell input impedances that fall off with the square root of frequency at high frequencies are indicative of diffusion processes, rather than R-C elements as in conventional modelling. Cable equations for the input impedance of even the simplest dendritic model (with uniform characteristics and a length of many space constants: V'' = Λ^-2 (1+ jωτ) V, I= -V'/R, Z = RΛ / √(1+jωτ), |Z| = RΛ (1+ω² τ² )^-0.25 ) predict just such a relation (Rall & Rinzel, 1973: see equations A13, A15 for the more general solution with dendrites of any length). So the argument of Gomes et al. that the data implicate diffusion processes (which can also lead to square root relationships) seems to collapse.

Though the external pathway for current generated by neurons is usually regarded as largely within interstitial space, it is not exclusively so, even at low frequencies or DC. Around 6% of DC current passed through rat cortex is accounted for by K⁺ flux (Gardner-Medwin, 1983). Since current in interstitial space would only account for a K⁺ flux of 1.2%, the difference is presumably due to trans-cellular passage of at least 5% of long distance current flow, probably largely through the astrocytic syncytium. This is a small adjustment to the notion that low frequency currents are largely extracellular, but it does represent a 5-fold enhancement of K⁺ flux driven by an electro-chemical gradient, which when applied to chemical (concentration) gradients implies greatly enhanced K⁺ dispersal around regions of build up in interstitial space, compared with diffusion alone - the so-called 'spatial buffer' mechanism for K⁺ .

An additional, larger, component of macroscopic cortical conductance appears to arise from extracellular but not interstitial pathways, possibly via perivascular tissue. This may not have been studied in detail, but is indicated by the fact that measured cortical impedance is in at least some circumstances only around half what would be expected on the basis of measurements of the volume and tortuosity of local interstitial space around a microelectrode (Gardner-Medwin, 1980; Nicholson & Phillips, 1981). Barbour (2016) points out that these two ways of approaching impedance both give an order of magnitude hugely below that of Gomes et al. (2016). Taking account of interstitial tortuosity shows, however, that they do differ by a factor of about 2.

Barbour B. (2016) Analysis of claims that the brain extracellular impedance is high and non-resistive. https://arxiv.org/abs/1612.08457

Gardner-Medwin A.R. (1980) Membrane transport and solute migration affecting the brain cell microenvironment. Neurosci. Res. Progr. Bull. 18:208-226

Gardner-Medwin A.R. (1983) A study of the mechanisms by which potassium moves through brain tissue in the rat. J Physiol 335:353-374

Gomes J.-M., C. Bédard, S. Valtcheva, M. Nelson, V. Khokhlova, P. Pouget, L. Venance, T. Bal, and A. Destexhe (2016) Intracellular impedance measurements reveal non-ohmic properties of the extracellular medium around neurons. Biophysical Journal, 110(1):234-246

Nicholson C. & Phillips J.M. (1981) Ion diffusion modified by tortuosity and volume fraction in the extracellular microenvironment of the rat cerebellum. J. Physiol. 321:225-257

Rall W. & Rinzel J. (1973) Branch input resistance and steady attenuation for input to one branch of a dendritic neuron model. Biophysical Journal 13(7):648-688

On 2018 Feb 01, Alain Destexhe commented:

I see your points but I have no idea whether they are valid or not. Why don't you try to publish your model? At the moment, you have a model drawn on the back of the envelope, and for which we don't know if it is valid or flawed. You use this model to criticize a series of papers published in journals like Biophysical Journal or Physical Review, so having been reviewed by biophysicists and physicists. I suggest you do the same to give more credibility to your criticism, otherwise it seems a bit easy...

About the issue of ohmic or non-ohmic, as said above, this paper is not alone, it is part of a series of papers which bring evidence based on other signals, such as intracellular recordings, LFP, EEG, MEG... This is the impedance-measurement part of the story. You can of course say - in non peer-reviewed media - that these peer-reviewed papers are all wrong, but frankly it is not very credible.

(and also not very constructive - as you do not propose anything to go forward)

In you read our review paper published in J. Integrative Neurosci (preprint copy at https://arxiv.org/abs/1611.10047), we review all these elements, and propose new experiments to go forward. In my opinion, this is the only way to go.

On 2018 Jan 31, Tony Gardner-Medwin commented:

Destexhe suggests here (and in his published response to Barbour) that conventional modelling of their data must predict a resistive impedance at high frequencies, which they did not see. The argument is that a capacitative membrane impedance must become negligible at sufficiently high frequencies compared with a series extracellular resistance. This is an incomplete argument and misleading, as I thought was clear to Destexhe early in our correspondence.

The conclusion would indeed be true (though only evident at frequencies orders of magnitude higher than the 1kHz maximum in the data) if it were possible to directly measure an impedance between cytoplasm and an extra-cellular site. However, real measurements require electrodes with resistance and capacitance that need to be included in a model. Gomes et al. used a single patch electrode for both current passage and voltage measurement, which further limits the interpretation. When capacitance of electrode walls and amplifier input are included, impedance phase tends towards -90deg at moderately high frequencies, while compensation in the amplifier using negative capacitance can push it towards +90deg, as may explain the steeply increasing phase in Fig. 8. These effects can be explored in the model I provide, and I thought they were acknowledged by Destexhe many months ago.

My model of course makes simplifying assumptions. The parameters set in the download are only examples of sets that can fit well to the data of Figs 2,8 in the paper. Indeed they rather arbitrarily use equal time constants for soma and dendrite membranes since Destexhe thought for some unstated reason that this should be a constraint. It is not at all clear that implausible parameters are needed to fit the data using conventional electrophysiological analysis, though of course there are many unknown details about the preparations used. Destexhe coments (26 Jan) that more experiments could settle matters. It is indeed possible of course that new experiments could overturn conventional electrophysiological understanding. But the point at issue at present is not whether conventional understanding is wrong, but whether the paper of Gomes et al. (2016) shows that it is wrong, as claimed in the title.

Gomes J.-M. et al. (2016) Intracellular impedance measurements reveal non-ohmic properties of the extracellular medium around neurons. Biophysical Journal, 110(1):234-246

On 2018 Jan 26, Alain Destexhe commented:

Thanks Tony for sharing your model, which indeed reproduces part of our measurements. As pointed in our discussions, this match concerns the impedance amplitude (modulus), which can be reproduced by different resistive models. However, this is not true for the phase, no resistive model can account for the phase converging to -45 degrees that we observed. These points were detailed in our commentary in Biophys. J:

http://www.cell.com/biophysj/fulltext/S0006-3495(17)30914-1

So to your question, can resistive models fit our data, our answer is no.

As we said before, there is no point in discussing this any further now. The only way we can agree is to do the right experiment that everybody will fully accept.

On 2018 Jan 26, Tony Gardner-Medwin commented:

I think for most people with some knowledge of biophysics it will be fairly clear already that the paper Gomes et al. 2016 is quite inadequate to provide any sort of challenge to conventional electrophysiological modelling.

. I had an extensive and constructive correspondence with Destexhe last year. It was clear to me (and at least to some extent to Destexhe) that conventional theory can closely and quite simply fit the data of Figs 2,8 in Gomes et al.. At first Destexhe and colleagues argued that such a model was too simplistic, leaving out certain factors. When these were included and more complete fits could be made, there have been no clear suggestions from them that critical parameters were actually wrong or implausible (for example, over-compensated negative capacitance to explain phase data in Fig. 8). I had hoped to publish these fits jointly with Destexhe and colleagues, without getting involved in the more detailed disputes over Barbour's comments. Destexhe didn't agree to this, and I have not so far felt it worth publishing on my own what might be seen as a rather unnecessary attack on an already somewhat discredited paper.

. Since the issues seem still continuing in a manner reminiscent of tweets, I have put up the model that I developed in the correspondence with Destexhe at http://tmedwin.net/docs/Gomes_fits_v4.xlsx and encourage anyone interested to play around with it. I have a more sophisticated version (in Labview) that takes account of the distributed e-c field potentials generated by dendritic current in the model - but the differences are pretty negligible in their effect on what Gomes et al. measured. Comments and queries are of course welcome, either here or to me at ucgbarg@ucl.ac.uk .

. Tony Gardner-Medwin

On 2018 Jan 26, Alain Destexhe commented:

Not at all - this paper uses NEURON so we can't include any complex extracellular impedance. As we said previously, we are waiting for appropriate experiments to settle this issue of extracellular impedance, evaluate the importance of the short-cut and determine which model should be considered in which circumstance. The previous discussion has shown that each party has its own logic and supporting data, so there is no point of continuing the debate in the absence of these new experiments. So no, the discussion is not "closed" at all, but it is "on hold" waiting for new experiments.

On 2018 Jan 25, Boris Barbour commented:

Alain Destexhe is an author on a recently posted preprint using a low and resistive value for the extracellular impedance.

https://www.biorxiv.org/content/early/2018/01/05/243808

This is completely inconsistent with the position he puts forward here. If he has changed his opinion, it would be helpful to readers to close this discussion by making that clear.

On 2017 Oct 04, Boris Barbour commented:

My preprint has been published as a letter to the editor

http://www.cell.com/biophysj/fulltext/S0006-3495(17)30913-X

Bédard and Destexhe reply

http://www.cell.com/biophysj/fulltext/S0006-3495(17)30914-1

I have since found a metaphor that might offer a useful intuition to newcomers to the subject. Imagine that the extracellular impedance is represented by wallpaper and the membrane impedance by a castle wall. You wish to measure the thickness of the wallpaper (extracellular impedance). You must choose one of the following measurement methods. 1) Measure the wallpaper thickness directly, before sticking it to the wall. 2) Measure the thickness of the paper AND the castle wall to which it is stuck. Obviously it is much, much more difficult to extract an accurate estimate of the wallpaper thickness if it is measured together with that of the wall. Yet this is essentially the approach that Gomes et al have chosen by placing one of their electrodes in the intracellular compartment and measuring membrane and extracellular impedances in series. The paper contains no independent validation or justification of their ability to perform the separation of membrane and extracellular components of the impedance to the required accuracy.

On 2017 Mar 08, Alain Destexhe commented:

The discussion becomes interesting... we are very happy that our paper triggers so much comments. To the last Barbour's reply, it contains several simplifications and errors about the 1/f scaling, in particular the claim that cable filtering explains the 1/f scaling, while it only partially explains it. Barbour focuses on the evidence for non-resistive media from impedance measurements, and we agree that those are subject to controversy and to multiple interpretations (but all of them, not only ours...) A more detailed reply is obviously needed here - we are preparing this and it will take some time.

The evidence for non-resistive media goes well beyond impedance measurements, and because Barbour does not mention these evidences, while they are important for the discussion, we are summarizing them here. We hope that it will be apparent that our view is coherent, perhaps even more coherent than the traditional view.

(1) The first point is te observation that LFP and EEG can scale as 1/f. This 1/f is only seen in the so-called "desynchronized EEG" states, with no slow-waves (with slow-waves it scales as 1/f2). In 2006, in a paper in PRL, by relating LFPs with unit activity, we suggested for the first time that there is a 1/f filter somewhere. Three explanations were proposed for this: first, a random arrangement of capacitive and resistive elements (like in extracellular space) is known to create a 1/f filter; second, the cable filtering (Pettersen and Einevoll, 2008), and third, the influence of ionic diffusion (Bedard et al. Biophys J, 2009). All generate 1/f, but cable filtering generates 1/f only at high frequencies (the kernel is flat at low frequencies), and this is also true for the very recent measurements discussed by Barbour. On the other hand, ionic diffusion predicts 1/f over the whole frequency spectrum, and thus accounts better for the LFP and EEG, which also scale as 1/f at low frequencies (the cable filtering is unable to explain this). This is already a first indication that cable filtering is not entirely satisfactory.

(2) A second point is that if one relates the power spectra of intracellular and LFP recordings in vivo, one cannot fit the transfer function obtained using a resistive medium, but it better fits the prediction from ionic diffusion (Bedard et al., JCNS 2010). In the same paper, we showed that the cable filtering only works in a silent neuron (in vitro conditions), but this effect vanishes in the presence of synaptic bombardment (in vivo conditions), so cable filtering is unlikely to provide a satisfactory explanation for these in vivo data as well. The fact that ionic diffusion fits better is of course not any kind of proof, but only an indication that the spectral structure of these signals is consistent with it.

(3) A third evidence comes from the scaling exponent of EEG and MEG signals. If the media traversed by the fields are resistive, electric potential and magnetic field should scale the same, and they are not (Dehghani et al., 2010). This is true for all locations on the scalp, and when the exponents were similar, it is when the SNR was low, so there seems not to be a single location in the brain which behaves as a resistive medium according to that analysis.

(4) The inhomogeneity of the impedances is also important. In 2004, we made a theoretical study showing that if there are impedance inhomogeneities (like a succession of fluids and membranes), then the electric potential is strongly filtered (Bedard et al., Biophys J. 2004). Note that this model was resistive, but with spatial variations in resistivity (which is actually known to exist in cortex; see conductivity measurements of Herreras lab). Later, a study by Nelson et al. (J Neurosci 2013) showed that the neuropil in cerebral cortex is also inhomogeneous at smaller scales. This does not show anything in favor or disfavor of a resistive medium, but it shows that the inhomogeneous electric structure of the medium necessarily predicts a filtering effect on the extracellular potential.

(5) The Gomes et al. measurements (Biophys J 2016, discussed here) also show a filtering filtering consistent with ionic diffusion. However, the present discussion is about whether the same result can also be explained by cable filtering rather than an effect of the extracellular medium. It remains to be shown (1) if the match of cable filtering is as good as claimed for biophysically realistic conditions; (2) whether it also works in vivo, where we see the same effect, while cable filtering is supposed to be much attenuated. This is the discussion we have at the moment also with Tony Gardner-Medwin, and I hope we can reach an agreement at least on that one.

(6) Finally, we suggested a framework where all these data can be explained, in a recent review paper (Bedard et al., J Integrative Neurosci, 2017). We showed that all the above data can be explained by a diffusive medium, although we agree that this is a theory, nothing has been demonstrated about diffusion, there may be something else scaling as 1/sqrt(omega). We also suggested that there is a current shunt in the water column that surrounds electrodes, which could explain measurements of resistivity. We also sketched an experiment to test it.

On the other hand, if we understand well, Barbour's "theory" postulates that 1,2,3,4,5,6 are all wrong. Of course this is also a possibility, but frankly, we find it not really satisfying and not constructive, since no experiment is proposed to test it. This looks like a tentative to close the discussion, while our approach is the opposite, our paper tries to open the debate.

Moreover, as theoreticians, we are more satisfied with the diffusive theory because it builds on a much wider set of experimental observations and analyses. Building only on impedance measures is dangerous, because we do not know at 100% the accuracy of these measures (and indeed they are controverted, the proof is all this discussion we have here...) In any case, we made efforts to find a framework where all data can be explained. Of course this framework may be incomplete and probably needs to be improved, but at least it provides a solid basis to make further experiments.

So in the future, one should examine the respective contributions of cable filtering, impedance inhomogeneity, ionic diffusion (also recently investigated by the group of Einevoll), and possibly other unknown factors, to yield a precise biophysical picture of the genesis of extracellular potentials and magnetic fields. In our mind, it is clear that all these factors contribute, and considering the medium as just a resistance is an dangerous oversimplification.

On 2017 Mar 05, Boris Barbour commented:

See also this recent paper measuring brain extracellular impedance in humans and finding no evidence for a frequency dependence.

Ranta R, 2017

On 2017 Feb 18, Boris Barbour commented:

Tony Gardner-Medwin shows how even a simple cable model with a low-resistance extracellular space comes remarkably close to generating the somatic impedance spectra reported in Gomes et al. This cable property was described no later than 1973.

Destexhe calls for more experiments, but both both prior and recent work on pyramidal cells have clearly demonstrated that the ~1/sqrt(f) impedance can be fully accounted for by the cellular impedance without any need to invoke a high or reactive extracellular impedance, eliminating the only supporting (and very indirect) argument Destexhe has so far advanced. A prior paper was

Yaron-Jakoubovitch, Jacobson, Koch, Segev and Yarom (2008) A paradoxical isopotentiality: a spatially uniform noise spectrum in neocortical pyramidal cells Front. Cell. Neurosci., https://doi.org/10.3389/neuro.03.003.2008

It shows that the somatic impedance (i.e. the impedance measured at the soma) of juvenile rat pyramidal cells exhibits a slightly steeper than 1/sqrt(f) decrease with frequency, just like in Gomes et al (although the curves are shifted somewhat): see the red somatic impedance trace in Fig. 2A of Yaron-Jakoubovitch et al. A very similar impedance spectrum emerges from a simulation with a reconstructed pyramidal cell: see red simulated somatic impedance in Fig. 4A of Yaron-Jakoubovitch et al. Thus, impedance spectra of the form observed by Gomes et al. can be quite precisely accounted for by the electrical morphology of the pyramidal cell, without invoking an implausible reactive and elevated extracellular impedance. This has been known for at least 9 years.

A recent paper that directly addresses the results of Gomes et al.:

Miceli, Ness, Einevoll and Schubert (2017) Impedance spectrum in cortical tissue: Implications for propagation of LFP signals on the microscopic level. eNeuro, https://doi.org/10.1523/ENEURO.0291-16.2016

The authors reproduce a ~1/sqrt(f) impedance in the presence of a low and resistive extracellular space (see their Fig. 4D). Furthermore, that low, resistive impedance was verified directly, yet again. Miceli et al conclude

"... the overall evidence points to an essentially real (Ohmic) extracellular conductivity with negligible effects from ionic diffusion in the frequency range between 5 and 500Hz."

Destexhe questions my suggestion that his proposed high extracellular impedance would be associated with gigantic extracellular action potential signals. My argument does contain several implicit approximations. However, because the proposed extracellular impedance is of the same order of magnitude as the membrane impedance, I still believe that membrane and extracellular voltage responses to a given current would be predicted to have quite comparable amplitudes. In other words, those in the extracellular space would indeed be gigantic.

The shunt-current mechanism proposed by Destexhe in the recent ArXiv was already addressed and ruled out in my preprint (the tissue fraction occupied by the electrode is too small to make a big difference).

The majority of the points I raised in my preprint regarding the experimental design and analysis strategy of Gomes et al. have not been addressed at all, except by appeal to authority. In particular, the assertion by Destexhe to have measured the extracellular impedance is precisely the point in question. I maintain they have simply measured the intracellular impedance and are unable to draw from it any conclusions regarding the extracellular impedance. This point of view is in full agreement with the results of the Segev/Yarom and Einevoll/Schubert groups, as well as the arguments of Gardner-Medwin drawing on the work of Rall and Rinzel. In summary, Gomes et al. provide no good reason to prefer their conclusions over those of the many researchers who have previously measured the extracellular impedance directly, including Ranck, Nicholson and Logothetis.

On 2017 Feb 08, Alain Destexhe commented:

Dr Barbour casts doubts on our analysis, but makes several confusions: first he confuses measurements in Fourier frequency space, which cannot be extrapolated so simply to the temporal domain (for example translate mV/Hz into a LFP in mV is not so straightforward). Consequently, he obtains an aberrant LFP amplitude of 20 mV, which our measurements do not predict at all. Barbour makes a second confusion by making an analysis that assumes that the medium is resistive, while our measurements did not make this assumption, so his analysis also predicts aberrant values for this reason.

We have to say that it is very harmful to allow such non peer-reviewed criticisms, which spread wrong statements and cause harm to published papers, because uninformed readers will believe we were not careful in our analysis. Our papers, measurements and analyses were all peer reviewed, in journals such as Physical Review or The Biophysical Journal. It was thus seen by reviewers (mostly physicists) specialists in electromagnetism theory, electrophysiology or biophysics. We suggest that, instead of spreading non-reviewed and wrong critisms, it is more scientific to make himself biophysical measurements and gets his work published in peer-reviewed journals (ie, not just words), and in journals of the same standard as Physical Review or Biophysical Journal (ie, not just arXiv).

Finally, we fully understand that our measurements are against the current belief, and it is of course much easier and reassuring to try find arguments against them. In our recent review paper https://arxiv.org/abs/1611.10047 , we suggested an experiment which will determine if the evidence for resistive medium was contaminated by shunt currents. So instead of exchanging non peer reviewed statements, we suggest to make this experiment, which should definitively solve the issue.

On 2016 Dec 28, Boris Barbour commented:

In this and previous papers, the authors report that the extracellular impedance is high and non-resistive, compared to many previous measurements that have found it to be much lower and essentially resistive. I argue in this arXiv preprint

https://arxiv.org/abs/1612.08457

that the authors' estimate was probably confounded by an inaccurate representation and extraction of the series neuronal impedance in their measurement. In consequence, there is no compelling evidence to abandon the well established consensus that the extracellular impedance is low and essentially resistive in the frequency range of interest for biological signals.

On 2016 May 09, KEVIN BLACK commented:

If you get to this page, click on "Other versions," above, to see the corrected version 2.

On 2016 Mar 18, Shin-ichiro Hiraga commented:

I wonder if the MRE11 SIM2 mutant shows hypersensitivity to camptothecin.

On 2016 Nov 12, Tom Yates commented:

Pretorius and colleagues are to be congratulated for undertaking perhaps the largest case control study to date exploring the viral aetiology of severe acute respiratory illness (SARI) (Pretorius MA, 2016). The study is remarkable for two reasons other than its size.

First, large numbers of HIV positive cases and controls were enrolled. Second, unlike other studies of acute respiratory tract infection or pneumonia undertaken in Sub Saharan Africa (Hammitt LL, 2012, Bénet T, 2015, Breiman RF, 2015), human rhinovirus was isolated more frequently in cases than in controls. The investigators estimated that the population fraction of SARI attributable to rhinovirus (an entity they call ‘adjusted prevalence’) was approximately twenty percent.

One potential reason for an association between rhinovirus infection and SARI being observed in this study but not in other studies would be if rhinovirus were only a cause of SARI in the setting of HIV-related immunocompromise. It would therefore be very interesting to see these data presented separately by HIV status.

Tom A. Yates ^a ^b ^*

Patrick K. Munywoki ^a ^c

D. James Nokes ^a ^d

a) Virus Epidemiology and Control Research Group, Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya b) Institute for Global Health, University College London, London, UK c) School of Health and Human Sciences, Pwani University, Kilifi, Kenya d) School of Life Sciences and WIDER, University of Warwick, Coventry, UK

* Dr Tom Yates, t.yates@ucl.ac.uk

On 2017 Jun 21, Randi Pechacek commented:

Elisabeth Bik references this paper on a microbe.net blog post, discussing Roman culture.

On 2016 Apr 28, Clive Bates commented:

Please note this comment is replicated on the PubMed entry for the Pediatrics version of this paper. See Singh T, 2016.

There are several weaknesses in the reasoning in this paper.

1. Singh et al assert: “exposure to e-cigarette advertisements might contribute to increased use of e-cigarettes among youths.” The study is cross-sectional and does not (and cannot) establish that advertising causes e-cigarette use. Even if the authors acknowledge that their study does not establish a causal relationship, that has not stopped them drawing conclusions as if it does.

2. The finding that higher advertising exposure would be associated with greater e-cigarette use is quite likely, but there are many possible explanations. It could be that e-cigarette users see more advertising because of the way they live and their interests direct them to where such advertising is visible. Alternatively, teenagers already using the products may just be more interested and have better recall of advertising they have seen, even if exposure is no different.

3. Marijuana is not advertised but its prevalence among high school students is higher (23.4%) than tobacco (22.4%) on the basis generally used by CDC (used at least once in the last 30 days) - see CDC Youth Risk Behavior Surveillance — United States, 2013. It may be that better explanatory variables than advertising exposure are needed to interrogate prevalence of youth risk behaviours.

4. Even if we allow that e-cigarette advertising may be increasing youth e-cigarette uptake, something that is far from established, the authors need to consider the likelihood that this is displacing cigarette smoking. Given that independent risk factors for teenage vaping and smoking are likely to be similar, it would be surprising if vaping was not adopted as an alternative to smoking, at least in some cases. In this event, the health effect of e-cigarette use is positive, and, therefore, so is any role that advertising plays in it.

5. The observed sharp decline in teenage cigarette smoking that has coincided with the sharp rise in teenage e-cigarette use does not establish a causal relationship between these trends, but it does suggest that it is a plausible hypothesis that vaping is reducing smoking and therefore that great care should be taken when designing policies that may attenuate this effect. See data: CDC Tobacco Use Among Middle and High School Students — United States, 2011–2014.

6. The authors jump to a policy conclusion that goes far beyond the limitations of their study: "Multiple approaches are warranted to reduce youth e-cigarette use and exposure to e-cigarette advertisements”.

7. Before making such policy proposals, the authors should consider several issues and potential unintended consequences beyond the scope of this paper: that young people might smoke instead of using e-cigarettes; that e-cigarette advertising might be an effective form of anti-smoking advertising; that such restrictions may reduce adult switching from smoking to vaping and thus create damage to adult health; that excessive restrictions on advertising protect incumbent industries (cigarettes) and reduce the returns to innovation in the disruptive entrants (e-cigarettes).

8. The assertive and unqualified nature of the policy proposal raises concerns of an unacknowledged investigator bias. This would not be that surprising. The authors are from CDC, and the media release that accompanied this survey abandoned all caution about causality or unintended consequences. It reflected the CDC’s adversarial prior policy stance on these issues, none of which are supported by the survey itself:

“The same advertising tactics the tobacco industry used years ago to get kids addicted to nicotine are now being used to entice a new generation of young people to use e-cigarettes,” said CDC Director Tom Frieden, M.D., M.P.H. “I hope all can agree that kids should not use e-cigarettes.”

Conclusions: CDC should adopt a more dispassionate and careful approach to both reporting and communicating survey findings. In publishing for peer-reviewed journals, CDC staff should disclose relevant CDC policy and advocacy positions as non-financial competing interests.

On 2016 Apr 18, Gwangseong Kim commented:

In two recent articles [1, 2] two techniques for removing or inactivating blood borne pathogens were introduced. The initial experiments were performed in vitro under simplified conditions. First, the primary achievement of the PDT work deserves clarification [1]. PDT is a powerful therapeutic modality, but its clinical application has been hampered by the inability of light to penetrate deep layers of the tissue, which is mainly due to hemoglobins in the blood readily absorbing photons. Utilizing a millimeter- diameter transparent tube for extracorporeal blood circulation allows PDT to function well despite the presence of hemoglobins in blood. Another point that deserves clarification is that the tube capturing device is not a microfluidic device [2]. This technique can be adapted using existing medical tubing without the need for complicated microfluidics and micro-fabrication. The device is a medical tube that has been chemically modified using simple steps to adapt the internal surface for cell capturing. We would like to take this opportunity to respond to concerns brought up in [3]. We start off by addressing concern (1), which speculates about the possibility of overheating during the use of near IR light. Our control data (Fig.3 and Fig.4 of [1]), confirmed that controls illuminated without photosensitizer-antibody conjugates did not undergo cell death, whereas those with photosensitizer-antibody conjugates underwent significant cell death under identical conditions. Thus it is clear from our data that temperature did not affect the outcome. It has been shown that 660 nm irradiation is safe and effective [4-6]. Moving on to concern (2) part (a) that brings up the problem of using the CD-44 antigen as a target. Limitations of antibody specificity are common knowledge and not unique to CD-44, but to all antibodies. To our knowledge, a targeting method that exclusively binds only to cancer cells does not yet exist, making the use of such a compound an unreasonable standard for publication. We used CD-44 antibody to demonstrate feasibility. As targeting methodologies advance and better selectivity to target cells becomes available, this technique will have improved selectivity. Our experiments were designed to avoid non-specific damage to other cells by pre-staining pure cancer cells with the photosensitizer-antibody conjugates and subsequently removing extra free conjugates before spiking into blood (described in detail in [1]). This elimination of the possibility of side effects due to undesired binding to other blood cells and excess free photosensitizer-antibody conjugates precluded the need for a toxicity study, particularly because we were at the proof-of-principle stage. Part (b) of concern (2) suggests that we may have caused non-specific damage to non-cancerous cells by ROS' convection in the blood stream. We believe that this is highly unlikely. One of the authors has been conducting research focusing on ROS and PDT for years, in collaboration with other researchers [7-15]. This research demonstrated that PDT is extremely selective to targeted cells [13]. Part (c) of concern (2) states that we should have used additional cytotoxicity assays, such as Annexin V, TUNEL, and MTT. However, because none of these techniques are cell-type specific, they would be useless for the particular objective they were suggested. Once our line of investigation reaches a more mature stage, we plan to undertake more useful studies, such as applying separate fluorescent tags, or radio labels, in addition to a cell viability assay and analyzing cell death with a cell sorting technology, such as FACS, MACS, density gradient centrifugation, etc. Concern (3) is that the capturing work [2] lacked purity confirmation concerning non-specific capturing of blood cells. Though purity confirmation is critical in diagnostic testing, our work was strictly limited to in vitro conditions, using spiked pure PC-3 cells as a model. To visualize and quantify PC-3 cells in the presence of whole blood, PC-3 cells were pre-labeled using a fluorescence tag (Calcein AM) and the extra free dye was subsequently removed before spiking PC-3 cells into blood. Because only PC-3 cells can have fluorescence in the blood mixture, and because quantification was based on fluorescing cells, false-positive results from other blood cells can be reasonably excluded. Furthermore, if other blood cells were captured but not identified by our detection method our data would then indicate that the simple tube captured cancer cells despite being blocked by other blood cells. If our technique were applied to CTC diagnosis, independent isolation procedures could be used to ensure the purity of captured cells. In contrast, if used for removal or killing, the purity of captured cells would not be as critical, provided that CTCs are effectively removed. If, by chance, capturing is hampered by accumulation of non-specific binding in filtering the entire blood volume, this issue can be addressed with strategies such as scaling up the tube and carefully determining the tube dimensions, flow rate, frequency of tube replacements, etc. Finally, concern (4), points out that the experimental conditions were not translatable to clinical applications. Part (a) regards scaling up the system to show high throughput. The concept of extracorporeal blood processing of the entire blood volume has been used for years in cases such as hemodialysis. We already are working on optimizing the technique for larger blood volume processing. Part (b) of concern (4) discusses the static no-flow condition as being unrealistic. This issue was brought up during the review process, and we provided with our results showing data under constant flow conditions by peristaltic pump (to be published in future publication). The reviewers agreed that the use of a no-flow condition as a conservative approach during a proof-of-concept stage was appropriate. Despite its preliminary nature, we believe that our work communicates novel ideas, an important objective of research and publication. Given the number of research articles dealing with diagnostics and microfluidics, perhaps a further point of confusion came about by thinking of our work in those terms. We want to clarify that diagnostics were not the primary objective in our work. Furthermore, as it becomes evident by this response our experimental design was carefully devised to minimized unnecessary interferences. We hope that this response mitigates any confusion and addresses the concerns raised. The entire response appears in the PLOS1 comment section under response: http://www.plosone.org/article/comments/info:doi/10.1371/journal.pone.0127219. Feel free to contact us for further clarifications.

1. Kim G, Gaitas A. PloS One. 2014;10(5):e0127219-e.
2. Gaitas A, Kim G. PLoS One. 2015;10(7):e0133194. doi: 0.1371/journal.pone.0133194.
3. Marshall JR, King MR. DOI: 101007/s12195-015-0418-3. 2015;First online.
4. Ferraresi C, et al. Photonics and Lasers in Medicine. 2012;1(4):267-86.
5. Avci P, et al. Seminars in cutaneous medicine and surgery; 2013.
6. Jalian HR, Sakamoto FH. Lasers and Light Source Treatment for the Skin. 2014:43.
7. Ross B, et al. Biomedical Optics, 2004
8. Kim G, et al. Journal of biomedical optics. 2007;12(4):044020--8.
9. Kim G, et al Analytical chemistry. 2010;82(6):2165-9.
10. Hah HJ, et al. Macromolecular bioscience. 2011;11(1):90-9.
11. Qin M, et al. Photochemical & Photobiological Sciences. 2011;10(5):832-41.
12. Wang S, et al. et al. Lasers in surgery and medicine. 2011;43(7):686-95.
13. Avula UMR, et al.Heart Rhythm. 2012;9(9):1504-9.
14. Kim G, et al. R. Oxidative Stress and Nanotechnology, 2013. p. 101-14.
15. Lou X, et al. E. Lab on a Chip. 2014;14(5):892-901.

On 2016 Mar 24, Melissa Garrido commented:

Thank you for the feedback on the paper. I wanted to respond to the comment about exclusion of post-discharge survival time from the propensity score model.Covariates chosen for inclusion in a propensity score should be those thought to influence both the treatment (here, palliative care consultation) and outcome (hospitalization costs). Because post-discharge survival occurs after both receipt of palliative care and after the period in which the outcome was measured (and thus could not be on any potential causal pathway between palliative care receipt and hospitalization costs), it was not considered as a potential covariate.

On 2016 Mar 22, Cicely Saunders Institute Journal Club commented:

The Cicely Saunders Institute journal club discussed this paper on Wednesday 2nd March 2016. We agreed that this is an important study that adds to the growing body of evidence on the cost saving effects of palliative care, which has the potential to influence policy and commissioners.

We enjoyed discussing the prospective cohort design of the study and the use of propensity score matching to address problems of selection bias. We commended the large number of variables that were included in the propensity matching; however we also questioned the impact of omitting some important potential confounders, such as post-discharge survival time. We noted that those with a diagnosis of dementia were excluded from the study. Whilst we acknowledged there may be practical reasons for this, such patients may have higher numbers of comorbidities, higher associated costs and possibly be more likely to benefit from palliative care. We agreed that enabling participation of those who lack capacity by gaining assent via a consultee and obtaining proxy responses would strengthen future studies of this design.

The study examines the impact of palliative care consultation on hospital costs only without assessing its concurrent impact on patients and carer outcomes, which limits the impact and relevance of the findings. Authors acknowledge this limitation and state that further analyses will assess the effect of palliative care on patient and carer outcomes. We look forward to seeing these findings presented in future publications to strengthen the evidence regarding hospital palliative care consultations.

Commentary by Nilay Hepgul and Anna Bone

On 2016 Aug 24, Ben Goldacre commented:

This trial has the wrong trial registry ID associated with it on PubMed: both in the XML on PubMed, and in the originating journal article. The ID given is NCT0247317. We believe the correct ID, which we have found by hand searching, is NCT02473172.

This comment is being posted as part of the OpenTrials.net project^[1] , an open database threading together all publicly accessible documents and data on each trial, globally. In the course of creating the database, and matching documents and data sources about trials from different locations, we have identified various anomalies in datasets such as PubMed, and in published papers. Alongside documenting the prevalence of problems, we are also attempting to correct these errors and anomalies wherever possible, by feeding back to the originators. We have corrected this data in the OpenTrials.net database; we hope that this trial’s text and metadata can also be corrected at source, in PubMed and in the accompanying paper.

Many thanks,

Jessica Fleminger, Ben Goldacre*

[1] Goldacre, B., Gray, J., 2016. OpenTrials: towards a collaborative open database of all available information on all clinical trials. Trials 17. doi:10.1186/s13063-016-1290-8 PMID: 27056367

* Dr Ben Goldacre BA MA MSc MBBS MRCPsych<br> Senior Clinical Research Fellow<br> ben.goldacre@phc.ox.ac.uk<br> www.ebmDataLab.net<br> Centre for Evidence Based Medicine<br> Department of Primary Care Health Sciences<br> University of Oxford<br> Radcliffe Observatory Quarter<br> Woodstock Road<br> Oxford OX2 6GG

On 2016 Sep 19, Melissa Rethlefsen commented:

I applaud the authors' reporting of all of the search strategies behind this Cochrane review. There is, however, one area with a minor error. The MEDLINE search strategy for this review update is not reproducible, due to two causes: 1) no PRISMA-style flow chart to indicate the number of references found in either all or individual databases or in-text reporting of the complete number of references identified by searches before and after deduplication, and 2) a major Boolean error in the MEDLINE search strategy. For the second point, the MEDLINE search strategy is missing one or more lines that would combine the gynecological cancer terms together with the obstruction terms. It can be somewhat extrapolated from more complete search strategies reported for EMBASE and other databases, but because there is no flow chart, it is not clear if the extrapolated search is indeed what the authors performed. It appears as though the correct Boolean logic addition would be to combine lines 15 and 23, plus add the additional date limitation.

On 2016 Jun 24, Lydia Maniatis commented:

The authors do two things in this study:

First, they point out that past studies on “constancy” have been hopelessly confounded due a. to condition-sensitivity of and ambiguity in what is actually percieved and b. questions that are confusing to observers because they are vague, ambiguous, unintelligible or unanswerable on the basis of the percept, thus forcing respondents to try to guess at the right answer. As a result, the designers of these studies have generated often incoherent data and proferred vague speculations as to the reasons for the randomness of the results.

Second, as though teaching (what to avoid) by example, they produce yet another study embodying all of the problems they describe. Using arbitrary sets of stimuli, they ask an arbitrary set of questions of varying clarity/answerability-on-the-basis-of-the-percept, and generate the typically heterogeneous, highly variable set of outcomes, accompanied by the usual vague and non-committal discussion. (The conditions and questions are arbitrary in the sense that we could easily produce a very different set of outcomes by (especially) changing the colors of the stimuli or (less importantly) changing the questions asked.) Thus, the only possible value of these experiments would be to show the condition-dependence of the outcomes. But this was an already established fact, and it is, furthermore, a fact that any experimenter in any field should be aware of. It's the reason that planning an experiment requires careful, theory-guided control of conditions.

The authors make no attempt to hide the fact that some of the questions they ask participants cannot be anwered by referring to the percept. For example,, they are asked about some physical characteristic of the simulus, which, of course, is inaccessible to either the human visual system and unavailable in the conscious percept. In these cases, we are not studying perception of the color of surfaces, but a different kind of problem-solving. The authors refer to answers “based on reasoning.” If we're interested in studying color perception, then the simple answer would be not to use this type of question. The authors seem to agree: “Although we believe that the question of how subjects can reason from their percepts is interesting in its own right, we think it is a different question from how objects appear. Our view is that instructional effects are telling us about the former, and that to get at the latter neutral instructions are the most likely to succeed...In summary, our results suggest that certain types of instructions cause subjects to employ strategies based on explicit reasoning— which are grounded in their perceptions and developed using the information provided in the instructions and training—to achieve the response they believe is requested by the experimenter.” This was all clearly known on the basis of prior experimence, as described in the introduction.

So, at any rate, the investigators express an interest in what is actually perceived by observers. But what is the question they're interested in answering? This is the real problem. The question, or goal, seems to be, “How do we measure color constancy?” But we don't measure things for measurement's sake. The natural follow-up is “Why do we want to measure color constancy?” What is the theoretical goal, or question we want to answer? This question matters because we can never, ever, arrive at some kind of universal, general, number for this phenomenon, which is totally condition-dependent. But I'm not able to discern, in these authors' work, any indication of their purpose in making these highly unreliable measurements.

Color constancy refers to the fact that sometimes, a surface “x” will continue to appear the same color even as the kind and intensity of the light it is projecting to the eye changes. On the other hand, it is equally possible for that same surface to appear to change color, even as the kind and intensity of the light it is reflecting to the eye remains the same. In both cases – constancy and inconstancy – the outcome depends on the total light projecting to the eye, and the way the visual system organizes it. In both cases – constancy and inconstancy – the visual principles mediating the outcome are the same.

The authors, in this and in previous studies, “measure constancy.” Sometimes it's higher, sometimes it's lower. It's condition-dependent. Even if they were actually measuring “constancy” in the sense of testing how an actually stable surface behaves under varying conditions, what would be the value of this data? We already know that constancy is condition-dependent, that it is often good or good enough, and that it can fail under certain well-understood conditions. (That these conditions are fairly well-understood is the reason the authors possess a graphics program for simulating “constancy” effects). How does simply measuring this rise and fall under random conditions (random because not guided by theory, meaning that the results won't help clarify any particular theoretical question) provide any useful information? What is, in short, the point?

Yet another twist in the plot is that in their experiments, the authors aren't actually measuring constancy. Because we are talking about simulations, in order to exhibit “constancy,” observes need (often) to actually judge two surface with different spectral characteristics as being the same. This criterion is based on assumptions made by the investigators as to what surfaces should look the same under different conditions/spectral properties. But this doesn't make sense. What does it mean, for example, if an observer returns “low constancy” results? It means that the conditions required for two actually spectrally different surfaces to appear the same simply didn't hold, in other words, that the investigators' assumptions as to the conditions that should produce this “constancy” result didn't hold. If the different stimuli were designed to actually test original assumptions about the specific conditions that do or do not produce constancy, fine. But this is not the case. The stimuli are simply and crudely labelled “simplified” and “more realistic.” This means nothing with respect to constancy-inducing conditions. Both of these kinds of stimuli can produce any degree of “constancy” or “inconstancy” you want.

In short, we know that color perception is condition-sensitive, and that some questions may fail to tap percepts; illustrating this this yet again is the most that this experiment can be said to have accomplished.

On 2016 Jan 10, Shashi Seshia commented:

I regret there is an error in the formatting of the abstract that may cause some confusion. Readers are requested to look at the abstract in the review. Briefly, the key points are: 1.SUMMARY OF THE APPRAISAL: should be BOLDED the 3rd main heading, equivalent to results.Subheadings under this would include: (i) Strengths: Clinical pearls...including the examples (which should not be bolded), (ii) Weaknesses, (iii) Notable Omissions, and (iv) Additional issues. Shashi Seshia January 10, 2016

On 2016 Jan 09, David Keller commented:

Without a placebo control group, double-blinding or randomization, the results are difficult to interpret

Without a randomized, double-blinded, placebo-controlled trial, it is not possible to determine how much of the decrease in motor seizures was due to cannabidiol, nor how cannabidiol affected the frequency of serious adverse events, such as status epilepticus and "convulsions". Cannabidiol is a component of cannabis, the persistent use of which has been shown to be associated with neuropsychological decline in childhood through midlife [1].

Reference:

1: Meier MH, et al. Persistent cannabis users show neuropsychological decline from childhood to midlife. Proc Natl Acad Sci U S A. 2012 Oct 2;109(40):E2657-64. PubMed PMID: 22927402

On 2016 May 15, Felix Scholkmann commented:

We read with interest the article by Rizzo et al. [1] about the alleged ability for diagnosing “cardiovascular disease through mitochondria respiration as depicted through biophotonic emission”. As researchers in the field of ultra-weak photon emission (UPE) from biological systems (e.g. [2-12]) (also termed “biophotonic emission”) we were surprised to notice that some important statements made in the publication of Rizzo et al. are not correct or unsubstantiated, unfortunately. In the following we will point out these issues in detail.

(1) The “ClearView System” is neither able to detect UPE, nor is the measurement principle related to UPE.

The authors claim that the measurement device used, i.e., the ClearView System, “can detect cardiovascular disease through the measurement of mitochondria dysfunction through biophoton emission.” Concerning the measurement principle of the ClearView System the authors wrote that the “system measures electromagnetic energy at a smaller scale through amplification of biophotons.” Furthermore, it is stated that through “measuring mitochondrial respiration via biophoton detection, the ClearView system has the ability to quantify electrophysiological biophoton activity.”

Unfortunately, the statements are technically not correct. As described in section “1.3 ClearView System” of the paper, and also on the companies’ website (http://epicdiagnostics.com/clearview), the ClearView System is a corona discharge photography (CDP) device (for a detailed description of the technique see [13, 14]), i.e., a device performing contact print photographs of the coronal discharge (of the finger tip) by a high-frequency and high voltage pulse exposure (sinusoidal, 1 KHz, according to the patent for the device [15]). A CCD camera under a transparent electrode is capturing then this discharge pattern. The obtained image is due to the electrical discharge causing air-ionization and subsequently electromagnetic radiation in the optical spectrum when the excited electrons of molecules in the air return to the energetic ground state. This measured light by the device is neither “biophoton emission” nor is it due to an “amplification of biophotons”. The detection of UPE is only possible using high-sensitive photodetectors (i.e., photomultipliers or specific CCD cameras [16-19]). The optical radiation detected using CDP is a stimulated emission, whereas the UPE is a spontaneous emission. Furthermore, the authors state that the “ClearView System is a non-invasive, electrophysiological measurement tool”. And the sentence “[u]nlike other bio-impedance devices, … the ClearView System is ...” is misleading since it links the ClearView system to “bio-impedance devices”. However, this is erroneous and introduces further confusion.

(2) The assignment of the measured corona discharge patters to mitochondria respiration is unsubstantiated.

The authors state that the used measurement device (ClearView) is able of “measuring mitochondrial respiration” indirectly, and “can detect cardiovascular disease through the measurement of mitochondria dysfunction”. Even if we assume that the device would be able to measure UPE (which we showed is not justified), the detected UPE from the skin (i.e., finger tips) is a result of many different biochemical reactions that are not necessarily linked to mitochondrial function/respiration only. A detailed description of the UPE sources in biological systems can be found in the recent reviews [20, 21].

(3) Further questionable statements.

According to the authors, the “ClearView system taps into the global electromagnetic holographic communication system via the fingertips.” Neither give the authors an explanation what they mean with the term “global electromagnetic holographic communication system” nor do they refer to scientific literature that supports their statement.

Also the authors state that it “has been scientifically proven that every cell in the body emits more than 100,000 light impulses or photons per second.” This statement is inconsistent with the earlier statement that “biophoton emission is described to be less than 1000 photons per second per cm”. Additionally that statement contains incorrect units (it should be “per cm²”).In addition the authors state that the “biophotons”, they are allegedly measuring, “have been found to be the steering mechanism behind all biochemical reactions.” Whereas there are indeed theories linking UPE to physiological functions (i.e., delivering activation energy for biochemical reactions and coordinating them) these concepts are based on theoretical work (e.g., [22]) and there exist no scientific consensus regarding this issue at present.

(4) Flaws in the studies experimental design and statistical analysis.

Although the results presented by the authors are interesting, according to our view they should be regarded with caution because of the following reasons:

(a) A case-control study must ensure that the characteristics of the investigated populations (cases and controls) are similar, i.e. the populations should be age-matched and the number of subjects should be approximately the same [23]. Both conditions seem to be not fulfilled in the study of Rizzo et al. According to the authors the “age of cardiovascular subjects was 64.22 (95%CI: 62.44, 65.99) and the mean age of controls was 44.14 (95% CI: 40.73, 47.55).” That the age is a confounder was even found by the authors using the statistical analysis (i.e., OR for cardiovascular disease without considering age: 4.03 (2.71, 6.00), OR with age as a confounder: OR: 3.44 (2.13-5.55)). Additionally, the sample sizes were different (n = 195 vs. n = 64).

(b) The authors state the studies aim was to “indicate the presence or absence of cardiovascular disease”. For such an assessment the calculation of the odds ratios are not sufficient since they give only information about the prevalence, whereas the sensitivity and specificity are important factors to determine if a biomarker is useful for diagnostic purposes [24]. Such an analysis is classically performed by calculating the receiver operating characteristic (ROC) curves and quantifying them. Unfortunately, this kind of analysis is not reported by the authors in the manuscript. However, in the patent application (from which the results of the study were taken), ROC curves were given [25].

(c) Another important factor in showing the usefulness of the proposed novel diagnostic approach is to show the reproducibility of the measurement. The authors report that “a second measurement session was done 3-5 minutes after the first one was completed” in order to “assess the reproducibility and variability of the measurements”. However, we cannot find the results of this assessment in the published paper.

Felix Scholkmann^1, ^2, Michal Cifra³

¹ Biomedical Optics Research Laboratory, Division of Neonatology, University Hospital Zurich, 8091 Zurich, Switzerland

² Research Office of Complex Physical and Biological Systems (ROCoS), 8038 Zurich, Switzerland

³ Institute of Photonics and Electronics, The Czech Academy of Sciences, 18200 Prague, Czech Republic

On 2016 May 15, Felix Scholkmann commented:

References

[1] Rizzo, N.R., N.C. Hank, and J. Zhang, Detecting Presence of Cardiovascular Disease through Mitochondria Respiration as Depicted through Biophotonic Emission. Redox Biologx, 2016. 8: p. 11-17

[2] Cifra, M. and P. Pospisil, Ultra-weak photon emission from biological samples: definition, mechanisms, properties, detection and applications. J Photochem Photobiol B, 2014. 139: p. 2-10.

[3] Kucera, O. and M. Cifra, Cell-to-cell signaling through light: just a ghost of chance? Cell Commun Signal, 2013. 11: p. 87.

[4] Scholkmann, F., D. Fels, and M. Cifra, Non-chemical and non-contact cell-to-cell communication: a short review. Am J Transl Res, 2013. 5(6): p. 586-93.

[5] Rahnama, M., et al., Emission of mitochondrial biophotons and their effect on electrical activity of membrane via microtubules. J Integr Neurosci, 2011. 10(1): p. 65-88.

[6] Cifra, M., J.Z. Fields, and A. Farhadi, Electromagnetic cellular interactions. Prog Biophys Mol Biol, 2011. 105(3): p. 223-46.

[7] Kucera, O., M. Cifra, and J. Pokorny, Technical aspects of measurement of cellular electromagnetic activity. Eur Biophys J, 2010. 39(10): p. 1465-70.

[8] Scholkmann, F., et al., The effect of venous and arterial occlusion of the arm on changes in tissue hemodynamics, oxygenation, and ultra-weak photon emission. Adv Exp Med Biol, 2013. 765: p. 257-64.

[9] Fels, D., M. Cifra, and F. Scholkmann, eds. Fields of the cell. 2015, Research Signpost: Trivandrum.

[10] Scholkmann, F., et al., Using multifractal analysis of ultra-weak photon emission from germinating wheat seedlings to differentiate between two grades of intoxication with potassium dichromate. Journal of Physics: Conference Series, 2011. 329: p. 012020.

[11] Cifra, M., et al., Spontaneous ultra-weak photon emission from human hands is time dependent. Radioengineering, 2007. 16(2): p. 15-19.

[12] Cifra, M., et al., Biophotons, coherence and photocount statistics: A critical review. Journal of Luminescence, 2015. 164: p. 38–51.

[13] Boyers, D.G. and W.A. Tiller, Corona discharge photography. Journal of Applied Physics, 1973. 44(3102).

[14] Kwark, C. and C.W. Lee, Experimental study of a real-time corona discharge imaging system as a future biomedical imaging device. Med Biol Eng Comput, 1994. 32(3): p. 283-8.

[15] Rizzo, N.R., Localized physiologic status from luminosity around fingertip or toe, I. Epic Research And Diagnostics, Editor. 2013.

[16] Van Wijk, R., M. Kobayashi, and E.P. Van Wijk, Anatomic characterization of human ultra-weak photon emission with a moveable photomultiplier and CCD imaging. J Photochem Photobiol B, 2006. 83(1): p. 69-76.

[17] Kobayashi, M., et al., Two-dimensional photon counting imaging and spatiotemporal characterization of ultraweak photon emission from a rat's brain in vivo. J Neurosci Methods, 1999. 93(2): p. 163-8.

[18] Kobayashi, M., Highly sensitive imaging for ultra-weak photon emission from living organisms. J Photochem Photobiol B, 2014. 139: p. 34-8.

[19] Yang, M., et al., Spectral discrimination between healthy people and cold patients using spontaneous photon emission. Biomed Opt Express, 2015. 6(4): p. 1331-9.

[20] Prasad, A., Pospisil, P., The photon source within the cell, in Field of the cell, D. Fels, M. Cifra, and F. Scholkmann, Editors. 2015, Research Signpost: Trivandrum. p. 113-129.

[21] Pospisil, P., A. Prasad, and M. Rac, Role of reactive oxygen species in ultra-weak photon emission in biological systems. J Photochem Photobiol B, 2014. 139: p. 11-23.

[22] Popp, F.A. and J.J. Chang, The Physical Background and the Informational Character of Biophoton Emission, in Biophotons, J.-J. Chang, J. Fisch, and F.-A. Popp, Editors. 1998, Springer Netherlands. p. 239-250.

[23] Bland, M., An Introduction to Medical Statistics. 4th ed. 2015: Oxford University Press.

[24] Grund, B. and C. Sabin, Analysis of biomarker data: logs, odds ratios, and receiver operating characteristic curves. Curr Opin HIV AIDS, 2010. 5(6): p. 473-9.

[25] Rizzo, N.R., Isolated physiological state of brightness by fingertip or toe, I. Epic Research And Diagnostics, Editor. 2014.

On 2016 Feb 03, Jos Verbeek commented:

It is interesting to see that the conclusions of this review are at odds with a Cochrane Review on the same topic that concluded that there was no evidence of an effect for safety engeneered devices. The reason is that the authors of this review included uncontrolled before-after studies. They took the reduction of sharps injuries at one point in time after the introduction as the control condition. Of course, this carries a very high risk of bias because many things change over time and it is difficult to ascribe the change to the intervention. Using the GRADE qualification moderate quality evidence for evidence based on uncontrolled before-after studies is therefore misleading. I rather believe the results of the Cochrane Review

On 2016 Apr 22, Emily Ferenczi commented:

Here we expand upon the influence of medial prefrontal cortex (mPFC) stimulation in different hedonic behaviors. As documented in several previous studies, behaviorally relevant sucrose preference changes (for example those induced by stress) are often modulated similarly to the extent we observed (for example: Chaudhury et al., Nature 2013, 493: 532-536; Lim et al., Nature 2012, 487: 183-189; Covington et al., J Neurosci 2010, 30: 16082-16090). Indeed, sucrose has powerful motivational influences (as noted in the earlier commenter’s numerous Pubmed comments and postings relevant to his prior findings, e.g. http://www.ncbi.nlm.nih.gov/pubmed/25120076, http://www.ncbi.nlm.nih.gov/pubmed/23542690) and it would be surprising to achieve complete indifference to sucrose with a mild and distant mPFC modulation, nor is anhedonia absolute in the clinical setting. With respect to the influence of increased excitability of mPFC via SSFO stimulation, we did not claim (or use the word) “indifference” to sucrose (which would presumably mean a sucrose preference of 50%) but rather noted a significant reduction in preference. In line with previous literature, we in fact expected this reduction to be modest and characterized the reduction as a “mild but consistent and reversible reduction in sucrose preference only during days when light-stimulation was delivered”. The decrease in sucrose preference that we observed was in fact not only consistent across days and reversible, but also significantly differed to the behavior of YFP controls (Figure 4J) and accompanied suppressed engagement in another naturally rewarding activity (social interaction), as well. Finally, further support for the neurobiological relevance of this manipulation comes from the observation that it induced differences in fMRI functional connectivity between the medial prefrontal cortex and striatum, which in turn tracked the magnitude of the decrease in sucrose preference at the individual subject level (Fig. 6I). It is interesting to note that recent clinical trials have demonstrated suppression of cocaine use (Terraneo et al., Eur Neuropsychopharmacol 2016, 26: 37-44) and heroin cravings (Shen et al., Biol Psychiatry 2016, doi: 10.1016/j.biopsych.2016.02.006) in patients with addiction following transcranial magnetic stimulation of the prefrontal cortex, perhaps pointing towards a similar principle of cortical regulation of hedonic processing.

In the dual stimulation place preference experiments, rats were allowed to explore three chambers freely for 30 minutes total, and one chamber was paired with stimulation of ventral tegmental area dopamine (VTA-DA) neurons. The rats were exposed to chamber-paired VTA-DA stimulation for the first 10 minutes of the test and quickly began to show a preference for the VTA-DA stimulation side. When SSFO was switched on for the middle 10 minutes of the test, rats no longer preferred the VTA-DA stimulation side (consistent with approximately 50% preference). Once SSFO was switched off, the rats spent another 10 minutes with chamber-paired VTA-DA stimulation only, again preferring the VTA-DA stimulated side. Crucially, in the second 10 minute section of the test when mPFC was concurrently stimulated, it was in a non-chamber paired fashion. Specifically, SSFO stimulation was constantly present throughout the 10 minutes regardless of which chamber rats occupied (as reported in the paper, “10 min of superimposed mPFC activation by SSFO (single 5-s pulse of blue light in mPFC at the start, 10-s pulse of yellow light at the end)”). Thus, the chamber not paired with VTA-DA stimulation acted as an internal control for concurrent SSFO stimulation, and any possible SSFO-mediated aversion would therefore occur in both chambers. Both before and after mPFC stimulation, rats significantly preferred the VTA-DA stimulation chamber (mean percent time spent on stimulation side = 65.1%, 95% CI = 55.0 to 75.1%, p = 0.007) but did not prefer this chamber during mPFC stimulation (mean = 45.1%, 95% CI = 26.7 to 63.4%, p = 0.54). It is possible that a sufficiently aversive condition in which rats are no longer responsive to environmental stimuli could lead to anhedonic behavior, which we would consider to be one of several interesting mechanisms for this effect and would have some clinical relevance, though we note that the mPFC intervention did not alter baseline locomotion, water consumption, initial social interaction, or novel object investigation. While mPFC stimulation reduced the positive hedonic impact of VTA-DA stimulation, we note that the behavioral paradigm can also detect aversive effects, since inhibition of VTA-DA dopamine neurons with eNpHR elicited behavioral avoidance instead (see place preference test in Figure S7).

In summary, the behavioral effects related to mPFC stimulation are significant and coherent across studies, with changes in elicited ofMRI activity linked to individual-subject differences in targeted hedonic behavioral phenotypes. Although much more experimental ground was covered in the article (as noted by the commenter), no claims were made regarding identification of direct top-down anatomical connectivity -- a topic that remains of great future interest. We would be happy to provide any additional clarifications, so if questions remain please directly contact us for more detailed, extensive, or even hands-on productive exchange.

On 2016 Apr 05, Serge Ahmed commented:

There are many different types of data in this ambitious Research Article. I will only comment on the behavioral effects of medial prefrontal (mPFC) activation. Though those manipulations induced large-scale reorganization of both cortical and subcortical brain activities, as measured by fMRI, they had only marginal behavioral repercussions.

Notably, contrary to what the authors seem to imply, there is little or no evidence for anhedonia during mPFC activation (see Figure 4 of the paper). At best, there is a small reduction in preference for a low concentration of sucrose (i.e., from 90 to about 85%) but rats still continued to largely prefer sucrose over water. The behavioral effects of mPFC activation are simply magnified by setting the origin of the Y-axis at 70% - a value well above indifference. The behavioral significance of this tiny decrease in preference, if any, is largely unclear. In addition, there is no direct evidence that it results from a prefrontal top-down control over dopamine-dependent reward signaling in the striatum, as suggested by the authors. Finally, there is no evidence in Figure 5 that rats seek to spend more time in a place associated with stimulation of midbrain DA neurons. Rats are initially globally indifferent. The small, albeit significant, effect of mPFC activation likely reflects a direct aversive effect that might also be observed alone with no concurrent stimulation of midbrain DA neurons – an important control experiment that the authors apparently failed to conduct. It would have been more relevant to test whether and to what extent mPFC activation directly modulates the self-stimulation behavior of midbrain DA neurons reported in Figure 2.

Overall, the behavioral effects reported in this Research Article are too marginal and too disparate to offer a clear picture of the role of mPFC activation in regulating dopamine-dependent reward-seeking behavior.

On 2018 Jan 06, DAVID LUDWIG commented:

A recent NY Times investigative article raised questions about the interpretation of this study, and possible harms to public health in developing nations from consumption of sugary beverages such as the ones examined here. However, the NY Times article did not provide a detailed critique of the scientific methods.

The authors of this study conclude, "These findings suggest that malted drinks are a micronutrient-rich beverage which are unlikely to promote excess energy intake and obesity risk, at the consumption pattern in the population assessed." I believe that this conclusion is overstated, for the following reasons:

First: The study design, a cross-sectional survey, is weak and especially susceptible to confounding.

Second: The final participation rate was only about 1/5 the total invited sample, potentially leading to major selection bias (thus, undermining intent to obtain a nationally representative sample).

Third: The validity of the method to measure diet, (e.g., 10 to 12 year olds responded on their own) was not demonstrated.

Fourth: Malt beverage consumers were more physically active and watched less screen time: thus, they likely came from families with greater health consciousness. Therefore, the associations with higher intakes of a few micronutrients may simply reflect confounding. That is, they may have gotten the extra nutrients from other components of the diet. Unfortunately, this point was not examined in the study.

Fifth: Concerningly, the statistical models were not adjusted for physical activity and screen time. Doing so could have unmasked higher body weight among the malt beverage consumers. That is, perhaps the increased PAL and less screen time counteracted the adverse effects of beverage consumption.

Indeed, the true associations between sugar-sweetened beverages and body weight shown in higher quality prospective studies Schulze MB, 2004 are often not seen in cross-sectional surveys Forshee RA, 2004 – demonstrating the weak nature of this study type.

On 2016 Jan 07, Luis Querol commented:

The authors raise an important and intriguing finding that is the extraordinary response to Rituximab of some diseases. This fact is becoming an inteersting topic of research in the neuroimmunology field because several diseases show this type of response (Huijbers MG, 2015). Although the authors do not mention it, this finding may be related to the IgG4 nature of the pathogenic autoantibodies. This type of extraordinary and long-lasting response happens in several other diseases with very different target organs: myasthenia with anit-Musk antibodies (Díaz-Manera J, 2012), anti-contactin and anti-NF155 chronic inflammatory polyradiculoneuropathy (Querol L, 2015), anti-PLA2R nephropathy (Beck LH Jr, 2011)... Uncovering the differences that IgG4 plasma cells show with respect the more typical Ig1-3 would be key to understand the amazing response to rituximab in these diseases.

On 2016 Mar 09, Melissa Greenwald commented:

The United States Health Resources and Services Administration (HRSA) is the federal agency that awarded the grant funding for this research proposal. Grant awards were based on ranking after applications were reviewed by an external Technical Review Committee. “Delayed graft function” (DGF) was clearly stated as one of the goals of this research study as noted in the original grant application submitted in March 2011: “The goals of the this intervention are to demonstrate that TH [Therapeutic Hypothermia]: 1) better preserves deceased donor renal function while awaiting organ recovery when compared to normothermia; 2) increases the number of suitable organs for transplantation; and 3) improves recipient renal function after transplantation as measured by a reduction in DGF [Delayed Graft Function] and SGF [Slow Graft Function].” The grant application listed “Initial graft function” one of four variables to be measured for assessment of the first of two specific objectives of this research study. This is further specified in the Methods section of the grant application as: “The primary outcome measure will be number of patients in each group showing DGF/ SGF.” The parameters for information about research grants that is included and displayed on the Clinical Trials.gov website is under oversight of the U.S. National Institutes of Health.

Melissa Greenwald MD, Acting Director, Division of Transplantation, Health Resources and Services Administration, Rockville, Maryland, USA

On 2016 Mar 21, Oliver E Blacque commented:

You are right about the name. HGNC has now approved KATNIP (katanin interacting protein) as an alternative name, and JBTS26 as an alias. Appreciate your comment.

On 2016 Jan 22, Christopher Southan commented:

Exellent paper, but why didnt the authors engage with the HGNC to give this a useful name rather than a decades-old Japanese clone ID?

On 2016 Aug 08, Andrew Leifer commented:

I am the senior author of this work. There is a small error in the supplement regarding which frame grabbers were used with which camera. In Table S6, the row "Frame Grabbers" should read "Active Silicon Firebird PCIe GEN II 8x" in the left column, and "BitFlow Karbon PCIe x16 10-tap" in the right column. This error has no impact on the results, but may have caused confusion for those seeking to exactly replicate our setup. I apologies for the inconvenience.

On 2016 Jan 06, Carl L von Baeyer commented:

Spoofs and hoaxes are sometimes fun to read, but not if they look so much like real studies that many readers would be fooled -- particularly people whose first language is not English.

This article is amusing but it is a hoax and it should not have been indexed by NCBI (and perhaps should not have been published without a clear disclaimer in the title). It does a disservice to the field of research on pain relief in young children.

See http://ethicsalarms.com/2016/01/01/whats-more-unethical-than-a-web-hoax-how-about-a-scientific-journal-hoax/

On 2016 May 03, Jaime A. Teixeira da Silva commented:

There are public concerns at PubPeer about a figure in this paper: https://pubpeer.com/publications/F2D03946483D4C86569CD34751C4C7

Despite a formal request to the senior author, Prof. Suprasanna Penna, to address this, the request has been met with silence.

On 2016 Sep 21, Servi Stevens commented:

While consulting the Exome Aggregation Consortium Database (ExAC) I noticed that the identified variant at position chrX:153,173,202 has a frequency of >1% in the East Asian population (see http://exac.broadinstitute.org/variant/X-153173202-G-A). This frequency may be too high to fully explain the clinical phenotype in this family. Furthermore, the variant is referred to as "T491M" in the Abstract, but is "T941M" in the rest of the manuscript.

On 2016 Jan 04, Avital Rodal commented:

First, we would like to clarify that our FCHSD1 and FCHSD2 constructs, which generate protrusions in cultured cells, are not >500 aa as Dr. Gould suggested in her comment on 12/31. As described in Becalska AN, 2013, we quantitatively determined robust cellular activities for FCHSD1[1-417] (41 amino acids longer than the construct in McDonald NA, 2015 and for FCHSD2[1-414] (only 18 amino acids longer than the construct in McDonald NA, 2015). While we have not yet further characterized these two mammalian proteins in vitro, the same purified fragment of their Drosophila homolog, Nwk, generates ridges and scallops on liposomes and flattens, pinches, or crumples GUVs of the appropriate lipid composition Becalska AN, 2013, Kelley CF, 2015. These in vitro activities occur in the absence of the cytoskeleton or additional cellular factors. Further, when actin polymerization is inhibited in cells, the Nwk F-BAR still generates small buds, analogous to its scalloping activity in vitro Becalska AN, 2013. The cellular activity of Nwk requires both the concave surface and the tips of the canonical F-BAR, suggesting that the short additional C-terminal alpha-helical segment in our constructs is critical for F-BAR-dependent membrane bending activity, similar to SrGAPs Guerrier S, 2009. With this information, readers can make their own assessment about how the lack of activity reported by McDonald NA, 2015 from slightly shorter fragments of FCHSD1 and FCHSD2 could be related to the robust activity we have previously reported.

Second, our interpretation that the mutants generated in McDonald NA, 2015 do not uncouple membrane binding and oligomerization arises from their data showing no biochemical difference in membrane binding affinity between mutants in the basic oligomerization interface (K163E) compared to the acidic oligomerization interface (E30K, E152K) (Fig. 5D,E). Their assumption was that the acidic patch mutants would not affect electrostatic membrane binding. However, these mutants impair binding to charged membranes to the same extent as the basic patch mutants, instead of the expected intermediate membrane binding affinity if only oligomerization (and thus avidity) was affected. Since the mutants behave identically, it suggests either that membrane binding affinity and oligomerization are intrinsically coupled, or at least that these specific mutations do not uncouple them.

On 2015 Dec 31, Kathleen L Gould commented:

We appreciate the productive comments by Dr. Rodal regarding the important biological function of F-BAR proteins. We completely agree that deciphering the nature of the “non-canonical” function of various F-BAR domain proteins is an important area of future research.

Dr. Rodal takes issue with two aspects of our study: first with a lack of discussion of srGAP and Nwk literature, and second with the experimental methods used to detect membrane bending.

First, we agree that additional F-BAR proteins have been identified with “non-canonical” membrane remodeling abilities in vitro including srGAPs and Drosophila Nwk proteins. Due to space constraints we could not extensively discuss this previous work, but cited and summarized it in Table S1. We utilized the same assays which originally discovered the activities of srGAP and Nwk to conclude Cdc15 and 6 other human F-BAR domains do not bend membranes. We tested a wide range of additional binding conditions (Figure S1), including testing diverse lipid compositions (unpublished data), which resulted in identical results. Indeed, we believe these examples of non-canonical F-BAR membrane assemblies further support the idea that F-BAR domains utilize diverse modes of oligomerization for functions upon the membrane.

Second, Dr. Rodal indicates her group “published in 2013 that the F-BAR domains of FCHSD1 and FCHSD2 generate extensive membrane protrusions (to which the protein localizes) in both S2 cells and HEK cells, similar to Drosophila Nwk”. Indeed, these experiments and those with Gas7 were performed in vivo, with a full complement of cellular machinery. The results of such an in vivo experiment cannot substantiate the conclusion that these F-BAR domains physically deform the membrane. To directly test for membrane deformation, an in vitro experiment with the isolated domain is required, as we have performed (Figure 3 and S1). Dr. Rodal correctly points out the protrusions observed for FCHSD1/2 and Gas7 in vivo were actin dependent, indicating these proteins are organizing the actin cytoskeleton to generate protrusions, not necessarily directly remodeling of the membrane on their own. Furthermore, additional portions of FCHSD1/2 and Gas7 were present in the constructs used in these experiments. F-BAR domains comprise ~300-350 aa that fold into banana-shaped molecules as evidenced by >10 crystal structures. Large constructs were used in Dr. Rodal's experiments and these additional elements may confer unknown interactions and/or activities to the proteins in vivo.

In sum, though our specific interpretations may differ, we appreciate the interest in our work and encourage all researchers in this area as we together pursue this exciting area.

On 2015 Dec 27, Avital Rodal commented:

F-BAR domains: diversity in oligomerization and membrane bending activities

Avital Rodal, Brandeis University

McDonald et al. report that several oligomerizing yeast and mammalian F-BAR proteins do not form membrane tubules in vitro or in heterologous cells. They go on to show that surfaces required for oligomerization in vitro are required for the in vivo functions of several of these proteins. They conclude that oligomerization, but not membrane bending, underlies the in vivo roles of these F-BAR proteins, and that their main function is to recruit and organize other proteins at the membrane. However, their conclusion that these proteins do not bend membranes is only supported by negative results (i.e. the authors did not observe deformation in vitro or in heterologous cells), and in some cases contradict published results. Further, the authors do not discuss a previous body of literature that shows that several F-BAR proteins, including SRGAPs and FCHSD proteins, generate non-canonical (i.e. non-tubular) membrane deformations that would not have been detected in their assays.

Several groups have shown that the SRGAP family of F-BAR proteins generate negative membrane curvature (i.e. away from the protein-decorated face of the membrane) in multiple contexts: in purified systems in vitro, in heterologous cells upon overexpression, and in vivo during neuronal protrusion formation (Guerrier S, 2009; Carlson BR, 2011; Coutinho-Budd J, 2012). This activity is not consistent with tubular arrays observed for canonical F-BAR proteins (Frost A, 2008). Further, our group found that the FCHSD family of F-BAR proteins, which includes Drosophila Nervous Wreck (Nwk), exhibit an unusual higher order assembly that leads to non-tubule membrane remodeling. Using single particle EM, we showed that Nwk assembles into zig-zags on membranes instead of linear filaments typical of canonical F-BARs, and that this resulted in membrane ridges (Becalska AN, 2013). These deformations led to actin-dependent protrusions in heterologous cells, similar to a previous model for formation of cellular microspikes by the F-BAR protein syndapin (Becalska AN, 2013; Kelley CF, 2015; Shimada A, 2010). This activity does not require a novel membrane binding surface for any of these F-BAR domains. Instead these proteins use a conventional concave membrane binding surface, and appear to oligomerize into non-canonical arrays to deform membranes. This is not likely to be a special case for these specific F-BAR proteins, but rather suggests that different members of this protein family oligomerize into variable types of higher order arrays to generate and/or sense different types of membrane curvatures, which are neither tubules (the "dogma" for F-BAR domains (Traub LM, 2015)) or flat membranes (as proposed by McDonald et al.).

McDonald et al. report that the Nwk homologues FCHSD1 and FCHSD2 do not bend membranes in vitro or in cells, and state that theirs is the first study to report their activities. In fact, we published in 2013 that the F-BAR domains of FCHSD1 and FCHSD2 generate extensive membrane protrusions (to which the protein localizes) in both S2 cells and HEK cells, similar to Drosophila Nwk (Becalska AN, 2013). They may have failed to detect membrane remodeling activity for FCHSD1 and FCHSD2 in cells because their constructs omitted part of a C terminal alpha-helical extension to the F-BAR domain that is essential for function in SRGAPs (Guerrier S, 2009). Indeed, another of their non-membrane bending mammalian proteins, Gas7, has been reported to generate cellular protrusions upon full-length protein overexpression (She BR, 2002). It remains to be tested if Cdc15 or the other apparently non-membrane remodeling mammalian F-BAR proteins in their study also show activity in vivo or in vitro when a more extended region of the protein is studied.

In addition to the issue of potentially using inactive protein fragments, the specific in vitro and in vivo assays used by McDonald et al. could easily have missed non-canonical membrane bending activities. Several types of deformations are subtle on giant unilamellar vesicles (e.g. flattening, ridging, or any deformation that occurs on a ~100-200 nm scale rather than the micron scale of tubules), or are not detectable by negative stain (e.g. ridged, negatively curved, or flattened liposomes appear very similar to dried undecorated liposomes), or are unresolvable by light microscopy in cells. Cryo-EM of liposomes or thin sectioning and EM of cells is necessary to detect smaller scale deformation. Indeed, only large scale deformations like tubulation would have been detectable in the assays they used. Further, BAR domain membrane remodeling depends on a large set of parameters (Simunovic M, 2015), many of which were not tested by McDonald et al. For example, we recently showed that membrane binding and membrane deformation are not correlated, and that Nwk only deforms membranes within a limited "sweet spot" of membrane charge. This is likely dependent on F-BAR domain assembly and orientation on the membrane, which favors concave side-down under stringent binding conditions (Kelley CF, 2015). The activities of F-BAR proteins like Nwk/FCHSD1/FCHSD2 are not likely to have been detected by McDonald et al at 5% PI(4)P, the only lipid composition they tested for GUV and liposome deformation assays. Indeed, two more members of their set of six “non-deforming” F-BAR proteins, Fer and Fes, were previously shown to generate membrane tubules in vitro at 10% PI(4,5)P2 (Tsujita K, 2006; McPherson VA, 2009).

Thus, though McDonald et al. may be able to make a case against tubulation for a few of these six human F-BAR proteins (as has previously been demonstrated for both SRGAPs and Nwks), they do not test other types of membrane bending or enough parameters to conclude that these proteins do not have membrane remodeling activities. Instead, the most compelling conclusion from our work, the SRGAP work, and McDonald et al. is that F-BAR domains oligomerize on membranes into diverse higher order assemblies, and that tubular scaffolds (for which there is indeed little in vivo evidence) are just one potential way to deploy F-BAR oligomers. A non-membrane-deforming assembly, as they suggest for Cdc15, is a plausible variation on this theme for some subset of F-BAR proteins, but the limited negative data they provide are not convincing enough at this point to rule out other models, nor do they indicate that this is the rule for non-tubulating F-BAR proteins. In addition, we note that since the mutants generated in McDonald et al. do not fully uncouple membrane binding affinity from oligomerization (because the tips are part of the membrane-binding surface), an alternative model that remains consistent with all of their data is that some F-BAR domains, including Cdc15, may function as individual, non-oligomerized dimers on the membrane.

On 2016 May 17, Marcus Munafò commented:

Price and colleagues rightly celebrate the success of genomewide association studies (GWAS) in identifying genetic loci associated with a range of physical and mental health outcomes [1]. We agree that the GWAS approach continues to prove extraordinarily successful, in stark contrast to the candidate gene approach that preceded it [2]. However, what they do not emphasise is that in many cases these genetic loci can tell us as much about modifiable behavioural risk factors as they can about underlying biology.

Perhaps the clearest example of this comes from GWAS of lung cancer, which identified an association with a nicotinic receptor gene cluster CHRNA5-A3-B4 on chromosome 15 (at 15q25) [3]. This cluster encodes three nicotinic acetylcholine receptor subunit proteins: alpha-5, alpha-3 and beta-4. The same locus was shown, in the same GWAS, to be associated with peripheral arterial disease, and has also been shown to be associated with chronic obstructive pulmonary disease [4]. What is critical to interpreting these results is the knowledge that the same CHRNA5-A3-B4 locus has been consistently associated with heaviness of cigarette smoking [3,5]. Functional studies have demonstrated that the minor allele at rs16969968 (i.e., the risk variant for heavier smoking) is associated with a decreased maximal response to a nicotine agonist in vitro [6], while animal studies using alpha-5 knock-out mice have clarified the behavioural effects on nicotine self-administration: knock-out mice respond far more vigorously for nicotine infusions at high doses and do not self-titrate nicotine delivery [7].

There was initially some debate as to whether there is an independent effect of this locus on lung cancer risk (based on evidence of residual association after adjustment for self-reported smoking quantity). However, it is likely this residual association is due to the imprecision of self-report measures of heaviness of smoking, and misclassification of smoking status. For example, the locus accounts for a far greater proportion of variance in nicotine metabolite levels relative to self-report measures of daily tobacco consumption, and this is sufficient to fully account for the association with lung cancer risk [8]. In other words, smoking causes lung cancer, peripheral arterial disease and chronic obstructive pulmonary disease (as well as many other diseases), and this is confirmed by GWAS.

The implication is clear – GWAS can tell us about modifiable behavioural risk factors that contribute to disease [9], and the results of GWAS should therefore be interpreted with this in mind. For example, a recent GWAS of schizophrenia identified the same CHRNA5-A3-B4 locus [10], raising the intriguing possibility that smoking may be a risk factor for schizophrenia [11]. With this in mind, Figure 3 in the commentary by Price and colleagues is striking – one gene associated with a range of different outcomes is ALDH2. The genes in this figure are described as pleiotropic, but here the distinction between biological (or horizontal) and mediated (or vertical) pleiotropy is critical. The former refers to a genetic variant influencing multiple separate biological pathways, while the latter refers to the effects of a genetic variant on multiple outcomes via a single biological pathway. In the case of ALDH2, which encodes the aldehyde dehydrogenase enzyme involved in the metabolism of alcohol and acetalydehyde, it is well established that a variant in this gene influences alcohol consumption [12]. Individuals with one or two copies of the inactive variant experience unpleasant symptoms following alcohol consumption, due to slow metabolism of acetaldehyde and its subsequent transient accumulation [12]. For example, ALDH2 was not identified in GWAS of blood pressure that recruited predominantly European samples [13], where the variant is rare, but was identified in studies that recruited East Asian samples [14,15], where the variant is common. A parsimonious explanation for the associations shown in Figure 3 of Price and colleagues, therefore, is that alcohol consumption causes these outcomes – a results of mediated (rather than biological) pleiotropy.

Behavioural traits such as tobacco and alcohol use can be regarded as intermediate traits, which are under a degree of genetic influence, but which are themselves direct causal agents influencing various health outcomes. This logic also applies to intermediate phenotypes that may lie on the causal pathway, and may be amenable to behavioural or pharmacological intervention, such as LDL cholesterol. While GWAS have been extraordinarily successful in identifying genetic loci associated with disease outcomes, making full use of this knowledge will require an appreciation that GWAS can tell us as much about modifiable – including behavioural – risk factors as it can about underlying biology.

Marcus Munafò and George Davey Smith

1. Price, A.L., et al. Progress and promise in understanding the genetic basis of common diseases. Proc Biol Sci, 2015. 282: 20151684.
2. Flint, J. and, Munafò, M.R. Candidate and non-candidate genes in behavior genetics. Curr Opin Neurobiol, 2013. 23: p. 57-61.
3. Thorgeirsson, T.E., et al. A variant associated with nicotine dependence, lung cancer and peripheral arterial disease. Nature, 2008. 452: p. 638-642.
4. Pillai, S.G., et al. A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci. PLoS Genet, 2009. 5: e1000421.
5. Ware, J.J., et al. Association of the CHRNA5-A3-B4 gene cluster with heaviness of smoking: a meta-analysis. Nicotine Tob Res, 2011. 13: 1167-1175.
6. Bierut, L.J., et al. Variants in nicotinic receptors and risk for nicotine dependence. Am J Psychiatry, 2008. 165: p. 1163-1171.
7. Fowler, C.D., et al. Habenular alpha5 nicotinic receptor subunit signalling controls nicotine intake. Nature, 2011. 471: p. 597-601.
8. Munafò, M.R., et al. Association between genetic variants on chromosome 15q25 locus and objective measures of tobacco exposure. J Natl Cancer Inst, 2012. 104: p. 740-748.
9. Gage, S.H., et al. G = E: What GWAS Can Tell Us about the Environment. PLoS Genet, 2016. 12: e1005765.
10. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature, 2014. 511: p. 421-427.
11. Gage, S.H. and Munafò M.R. Smoking as a causal risk factor for schizophrenia. Lancet Psychiatry, 2015. 2: p. 778-779.
12. Quertemont E. Genetic polymorphism in ethanol metabolism: acetaldehyde contribution to alcohol abuse and alcoholism. Mol Psychiatry, 2004. 9: p. 570-581.
13. International Consortium for Blood Pressure Genome Wide Association Studies, et al. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature, 2011. 478: p. 103-109.
14. Kato, N., et al. Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians. Nat Genet, 2011. 43: p. 531-538.
15. Lu, X., et al. Genome-wide association study in Chinese identifies novel loci for blood pressure and hypertension. Hum Mol Genet, 2015. 24: p. 865-874.

On 2016 Mar 01, C Lopez-Molina commented:

Code for this research, as well as for similar projects, can be found in: http://kermitimagetoolkit.com/

On 2016 Mar 01, C Lopez-Molina commented:

Too bad, you're right, that's a terrible typo. It was formulated differently in [24], we rewrote it wrong ever since the earlier versions, and it got totally under our radar in every single revision. We hope it's understandable from the text and the previous formulae. Thanks for noticing.

On 2016 Feb 12, Michael McCann commented:

It seems that the inequality in P5 is reversed.

On 2017 Oct 21, Anju Anand commented:

Mohan Sindu, Anand A, Stanbrook M. Neuromuscular electrical stimulation to improve exercise capacity in patients with severe COPD. The Lancet Respiratory Medicine. 2016 Apr;4(4):e14-e16.

This is a summary from our twitter journal club @respandsleepjc on this article

On 2016 Dec 15, Victoria MacBean commented:

Plain English summary:

Patients with severe COPD often have weak legs as breathlessness can limit their ability to be active. Normally, to combat this and other symptoms of COPD, exercise classes called Pulmonary Rehabilitation (PR) are carried out. However, more severely affected patients may struggle to do PR.

An alternative therapy was introduced, neuromuscular electrical stimulation (NMES), to COPD patients with more severe symptoms. NMES is when electricity is used to create muscle contractions, in this case in the thigh muscles. While NMES has been used to strengthen muscles in previous research, this trial is the first to explore the impact on daily activities and the first to investigate the longer-term impact of the treatment.

52 participants with very severe COPD took part in this trial over two years. Participants received 30 minutes of NMES to both sets of thigh muscles daily for 6 weeks; 27 were placebo (‘sham’ stimulation) and 25 received active NMES. The aim: to assess the effectiveness of NMES, as a therapy to be conducted unsupervised at home, and at aiding daily activities. The main measure of effectiveness in this trial was a test of how far participants could walk in 6 minutes.

The results of the walk tests strongly support the use of NMES for severe COPD patients, with the patients who received the active NMES being able to walk substantially further. During interviews active NMES participants expressed a greater ease in everyday tasks (such as climbing the stairs) and stated that they could carry out physical activities for longer. No participants reported any negative views. Unfortunately, the improvement provided by NMES quickly waned after the treatment had stopped. Therefore, all existing evidence suggests that NMES should not be considered a replacement for PR. NMES can be used as an extension to PR, and could be used when patients are unable to take part in PR programmes. In addition, the short duration of effect suggests that longer programmes need to be investigated. Nonetheless, this trial has shown that NMES is a practical home-based therapy, suited to patients with more severe symptoms and has gives suggestions for future research.

This summary was produced by Reef Ronel, Year 12 student from JFS School, London as part of the investigators' departmental outreach programme.

On 2016 Sep 08, Morten Oksvold commented:

Please note that this article contains falsified data presentations, which was concluded after an investigation by ORI:

http://ori.hhs.gov/content/case-summary-forbes-meredyth-m

On 2016 Apr 05, Marko Premzl commented:

The third party data gene data set of eutherian growth hormone genes LM644135-LM644234 was deposited in European Nucleotide Archive under research project "Comparative genomic analysis of eutherian genes" (https://www.ebi.ac.uk/ena/data/view/LM644135-LM644234). The 100 complete coding sequences were curated using tests of reliability of eutherian public genomic sequences included in eutherian comparative genomic analysis protocol including gene annotations, phylogenetic analysis and protein molecular evolution analysis (RRID:SCR_014401).

Project leader: Marko Premzl PhD, ANU Alumni, 4 Kninski trg Sq., Zagreb, Croatia

E-mail address: Marko.Premzl@alumni.anu.edu.au

Internet: https://www.ncbi.nlm.nih.gov/myncbi/mpremzl/cv/130205/

On 2017 Jun 10, Akihiro Umezawa commented:

Thank you so much, Alistair. I also received the same comment from a chinese scientist. The authors totally agree with your comment. We will investigate phenotypes of the iPSC from the viewpoint of your comment 'Compound heterozygous mutations of the ERCC2 gene'. Some of the phenotypes could be linked to the gene functions.

On 2017 Jun 05, Alistair Pagnamenta commented:

Very interesting study and great that VCFs were freely available to review. Although my primary interest was to look at iPS induced artefacts (incl. UPD9), as the study “failed to find causal mutations in the XP-related genes”, I also searched for variants that might be responsible for the XP phenotype. Amongst the 300+ high-confidence, rare variants that were predicted potentially deleterious (https://variants.ingenuity.com/XP40OS), there were two in ERCC2, a gene which encodes a subunit of the TFIIH core complex helicase and which is linked to xeroderma pigmentosum complementation group D, XPD (OMIM *126340):

• a c.2048G>A; p.(Arg683Gln) in exon 22 which is listed in HGMD and ClinVar as a disease causing mutation (CM970443; RCV000248679.1). The variant is in gnomAD database present on 4/246,000 chromosomes.

• a 23bp deletion (c.2025_2046+1delCCTCATGGTCTTTGCCGACAAGG) which removes the end of the preceding exon. As indels aren’t robustly called from exome data, we are typically wary about reporting such variants without having viewed read alignments and/or having validated them with another method. However in this case, the deletion passes a number of confidence filters and is present in gnomAD on 1/246,108 chromosomes in an E Asian sample.

As these variants are both heterozygous, it remains to be confirmed that they are found in trans. However, given the loci are 153bp apart, the alleles can likely be phased by using Illumina read-pair information. Assuming compound-heterozygosity can be demonstrated, these variants represent plausible candidates to explain the condition.

The fibroblast cell line (XP40OS) was originally obtained from the JCRB cell bank catalogue which lists it as belonging to complementation group C and not group D. The stock cell line should be retested, either by the original polyethylene glycol-induced cell fusion based method (Sato K, 1982), or by molecular analysis of the above loci. Based on a review of submissions to major cell repositories, it has been estimated that 18-36% of cell lines are misidentified or contaminated (Hughes P, 2007). While in Okamura K, 2015, the mislabelling was relatively minor and doesn’t affect the overall conclusions, in other situations misidentified cell lines can lead to the inability to replicate scientific results and is a drain on scientific funding.

On 2016 Dec 15, Victoria MacBean commented:

Plain English summary:

Sickle Cell Disease (SCD) is amongst the most prevalent genetic conditions worldwide. Only being inherited if both one’s parents carry a ‘faulty’ gene in their DNA, SCD affects the Haemoglobin molecules that carry Oxygen in the blood, changing the shape of the red blood cells into so-called crescent shaped ‘sickles’. Despite its commonness, with over 300,000 babies being born with SCD worldwide every year, a clear and consistent picture of how SCD affects the lungs of children with SCD had not yet been researched. This study aimed to research the lung function of children affected by the disorder over time, observing how this changed in early and later childhood, and how this was affected by episodes of ACS (Acute Chest Syndrome) in early childhood, when the sickle-shaped red blood cells can block blood vessels and lead to various different injuries.

Two groups of children were tested. The first, who were slightly younger on average, were measured twice for their lung function over an average of 2 years, while the second group were measured twice over approximately 10 years. A number of methods were used to test each person’s lung function, including ‘spirometry’ in which the quantity of air one can force out the lungs is measured, among other values like lung capacity. These measurements were then compared to a ‘control’ group of healthy children without SCD at a similar age, to give a normal level of lung function to compare against the SCD patients’.

In both groups of children with SCD, a reduction in lung function over time was seen when compared to the groups of children without SCD. However, the lung function of those in the first, younger, group decreased at a faster rate.

The results suggest that the fastest period of deterioration in lung function takes place in early childhood. Indeed, having an episode of ACS in young childhood was the only factor found that increased the likelihood of worse overall lung function later on. This could explain the faster decline of the younger group, as ACS is more common in younger children. This would seem to conclude that a focus should be placed on preventing ACS in young children as a strategy to improve the general lung function later on of those with SCD.

This summary was produced by David Launer, Year 12 student from JFS School, London, as part of the investigators' departmental outreach programme.

On 2016 Feb 03, Pedro Silva commented:

I am glad that Kosak et al. were able to improve the description of this reaction mechanism, and to find a superior pathway vs. the bimolecular mechanism I proposed with Carla Sousa (http://dx.doi.org/10.1002/ejoc.201300337 , with erratum at http://dx.doi.org/10.1002/ejoc.201301647).

The following text would be most relevant in an entry for http://dx.doi.org/10.1002/ejoc.201300337, which is unfortunately unavailable in PubMed. It may nonetheless be useful for readers of the present paper.

Upon reading this paper, I realized that I had not been completely clear regarding the reaction barrier of the bimolecular pathway. Our computations of that barrier were performed as:

Gº(TS) -Gº(anisole:anisole prereaction complex )

rather than :

Gº(TS) - 2* Gº(anisole)

The barrier we depicted did not therefore include the translational entropy component of ca. 10 kcal.mol-1 . We performed the computation in that way because the computation of entropy changes upon binding in solution (reviewed by Zhou and Gilson, Chem.Rev. 2009,109,4092-4107 DOI: 10.1021/cr800551w) is still somewhat contentious, and can be argued to depend on the relative magnitude of the volume of the complex vs. the expected volume available to a molecule in solution at a standard concentration of 1 mol.L-1 (1661 cubic angstrom). I feared that including the entropy values "as provided" by the program in gas phase would unreasonably inflate that estimate, especially because of the relatively large dimensions of the anisole:anisole complex (vs. the "theoretical cubic cage" of length 11.8 angstrom and 1661 angstrom3 volume).

In case any readers find it useful for additional investigations, I have placed all my results (ca. 11 GB) in figshare.

http://figshare.com/articles/Supporting_info_for_DOI_10_1002_ejoc_201300337/1541140

On 2016 Jan 14, Michelle Lin commented:

For more discussion about the study and Team Based Learning, read more in the JGME-ALiEM Hot Topics in Medical Education discussion (medical education virtual journal club) featuring this article. This site also includes a Google Hangout on Air discussion with the authors (Balwan, Fornari), a TBL expert (Jalali), and education scholar (Sherbino).

http://www.aliem.com/team-based-learning-2016-jgme-aliem-hot-topics-in-medical-education/

On 2016 Jan 04, Michael Green commented:

ATP6AP1 and ATP6V1B2 mutations were described about 1 year ago in a paper that the authors did not cite. PMID: 25713363.

On 2016 Apr 07, Stephen L. Black commented:

Update: BMJ has now belatedly but effectively responded to my complaint, and a version of my original comment has been posted on the Open Diabetes website as I had initially intended.

On 2016 Jan 27, Valentine Njike commented:

The reviewer is right to suggest this point it getting excessive attention. It was a secondary outcome measure, and a significant within-group change only, when primary measures were between-group changes. This is indicated explicitly in the paper...

On 2016 Jan 22, Stephen L. Black commented:

This study claims to demonstrate that eating walnuts lowers cholesterol level, a claim enthusiastically and uncritically repeated in the media. Unfortunately, the claim is spurious, as the published data show no such effect. Instead the results do not show a statistically significant difference in cholesterol level between the experimental group which ate walnuts and the control group which did not. This is evident in Table 2 and is admitted by the authors in their discussion. In a puzzling comment, they attribute this negative outcome as “probably due to the placebo effect”. They instead focus on a significant decline in cholesterol level from baseline in the experimental group, ignoring the fact that a similar decline was evident in the control group which did not ingest walnuts. Thus, by the conventional logic of a placebo-controlled experiment, they failed to demonstrate that eating walnuts lowers cholesterol level. I find it inexplicable that a study with such an obviously-flawed conclusion should have been allowed to be published.

As the journal web page invites on-line comments, I submitted one, pointing this out. I was astonished to be told by the editor that my comment would not be published, not because it lacked merit, but because the journal does not publish comments. As a last resort, I protested to the BMJ itself this pointless practice of inviting on-line comments while refusing to publish them. Alas, the BMJ, which proudly states that it “welcomes complaints” and will acknowledge them “within three working days” instead ignored me. All-in-all, my failed attempt to merely correct a scientific error leaves me discouraged concerning the current practices of this once-respected journal.

On 2017 Apr 02, Katherine Flegal commented:

Kim et al Kim SH, 2016 provide a valuable review of the complexities surrounding issues of obesity and cardiovascular disease. They describe the AARP 10-year follow-up study of 527,265 respondents (Adams et al NEJM 2006 Adams KF, 2006) as showing that overweight was associated with higher mortality than normal weight. They then contrast these findings to those of the meta-analysis by Flegal et al (JAMA 2013 Flegal KM, 2013), attributing the apparent differences to a difference in the normal weight BMI category used in the two studies. However, the findings of these two studies are not as different as they may appear. The AARP article used the high normal BMI of 23-24.9 as the reference category and divided overweight into low (BMI 25-26.4), medium (BMI 26.5-27.9), and high (BMI 28.0-29.9) overweight. For men, the multivariate-adjusted HRs were 0.95 (95% CI 0.91–0.98) for low overweight. 0.95 (95% CI 0.92–0.98) for medium overweight and 1.00 (95% CI 0.96–1.04) for high overweight. The corresponding values for women were 1.00 (95% CI 0.94–1.07), 1.06 (95% CI 0.99–1.12) and 1.07 (95% CI 1.01–1.14). Thus even with a narrower reference BMI category, these findings from the full sample in the AARP study do not suggest excess mortality in the full overweight category (BMI 25-<30). Similarly, the ALLHAT study (Shah et al 2014, J Clin Hypertens Shah RV, 2014) cited by Kim et al found an HR of 0.96 (0.76–1.23) for overweight relative to BMI 22-24.9), again suggesting that a narrower reference category is not the explanation for findings of lower risk in overweight than in normal weight. The finding of higher mortality in overweight categories in the AARP study is only seen after the authors switched to a subgroup of 111,181 respondents and used reported past weight at age 50 instead of baseline weight. This special analysis with reported past weight rather than baseline weight, rather than the use of a narrower reference category, is the source of the apparent disagreement between the AARP study and the Flegal meta-analysis. Results from selective analyses of subgroups should be interpreted with caution.

On 2016 Jan 15, RAMON VILALLONGA commented:

PLEASE CHECK THE COMMENT ON THE ARTICLE.

Comment on “Panniculectomy Combined with Bariatric Surgery by Laparotomy: An Analysis of 325 Cases” R Vilallonga - Surgery Research and Practice, 2016 - hindawi.com

We would be happy to comment on the study by Dr. Colabianchi et al. on the role of synchronic panniculectomy and bariatric surgery when performed by laparotomy. (...)

On 2015 Dec 26, Miguel Lopez-Lazaro commented:

Most cancer risk is unavoidable, but most cancer cases are preventable.

Tomasetti and Vogelstein recently reported in Science a highly positive correlation between the lifetime number of stem cell divisions in a tissue and the risk of cancer in that tissue. Based on this correlation, they proposed that most cancers are unpreventable ('the bad luck of cancer'), and that early detection may be more effective than prevention to reduce cancer mortality [1]. Fortunately, 'the bad luck hypothesis' does not seem to be correct. It was based on the assumption that the parameters 'stem cell divisions' and 'DNA replication mutations' are interchangeable. These parameters cannot be interchanged, mainly because the mutations arising during DNA replication are random and unavoidable, while the division of stem cells is not a random and unavoidable process (the division of stem cells is highly influenced by external factors and physiological signals that can be controlled). A second important reason is that the parameters 'cancer risk' and 'cancer incidence' cannot be interchanged either [2].

In this Nature article, Wu et al. use several modeling approaches to propose that most cancer risk is avoidable. They conclude that unavoidable intrinsic factors contribute only less than 10-30% of the lifetime cancer risk. However, cancer statistics make this conclusion very difficult to accept. Age (an 'unavoidable' intrinsic factor) is by large the most important risk factor for the development of most cancers. For example, according to SEER Cancer Statistics Review 1975–2012, the risk of being diagnosed with prostate cancer is over 2800 times higher in men over 60 years old than in men under 30. For lung cancer, the risk is over 600 times higher in people over 60 than in people under 30. Extrinsic factors do not increase cancer risk that much; for example, smoking increases lung cancer risk by approximately 20 times. Therefore, the proposal that extrinsic factors contribute more than 70-90% to the development of these and other common cancers (see e.g. Figure 3b) does not seem to be correct. The second assumption present in the Science article also seems to be present in this article (see e.g. Extended Data Table 2).

The fact that most cancer risk is unavoidable does not mean that most cancer cases are unpreventable. Preventing a small percentage of cancer risk may be sufficient to prevent a high percentage of cancer cases. For example, although age is by large the most important risk factor for lung cancer, avoiding smoking prevents a high percentage of lung cancer cases. Extrinsic factors can be seen as the “the straw that breaks the camel’s back”; they are not the major contributors in most cases, but they can be decisive [2].

[1] http://www.ncbi.nlm.nih.gov/pubmed/25554788

[2] http://www.ncbi.nlm.nih.gov/pubmed/26682276

On 2015 Dec 23, Song Wu commented:

We appreciate the thoughtful comment, which raises a very interesting point that tumor microenviroment may also affect tissue-specific cancer incidences. We agree with that. However, it is important to note that we adopted a very specific definition of intrinsic cancer risk factors as defined in this article, as well as in the previous study in Science. In this formulation intrinsic risk refers only to the internal mutation rate in those dividing cells (stem or otherwise). As such, this factor is most susceptible to randomness. In our further analyses including all our four distinct approaches, we remained agnostic as to the nature of extrinsic factors. These would include not only environmental factors but also factors in the organism that are extrinsic to the tumor including inflammatory mediators, immune responses, hormones, and tissue microenviroment. These are all potentially modifiable conditions, and should belong to the domain of extrinsic factors.

We also agree that external factors may act through avenues other than stem cell, which is the reason that we specifically did not say that external factors (or even internal factors) act exclusively through stem cells. Additionally, in some components of our analyses, such as evidence from epidemiological data and mutational signatures, the results are independent of whether external factors act through stem cells or not. In this regards, our initial approaches were primarily directed at the question of whether the strong correlation between stem cell division and cancer risk can distinguish the effects of intrinsic from extrinsic factors, and our results show that it does not.

Overall, our main message is to promote further research into the causes of cancer and how they could be prevented.

-The Authors

On 2015 Dec 20, James Degregori commented:

The article by Wu et al argues that extrinsic risk factors contribute far more to cancer risk than calculated by Tomasetti and Vogelstein (1). While I share their critique of the deficiencies in the assumptions and conclusions made by Tomasetti and Vogelstein (2), I would argue that they make a major error in solely regarding extrinsic factors as mutagens; i.e. they calculate the added risk of cancer caused by these factors (such as smoking) as solely coming from increases in mutation frequency. In fact, their modeling (see Fig 4) requires very large numbers of lifetime stem cell divisions, in part because they do not consider any selective impact of mutations. The accumulation of multiple mutations in a single cell lineage would be extremely improbable without clonal expansion (to increase the target size) following each mutation. Since Nowell (1976) (3), the cancer field has largely considered these mutational events to be inherently advantageous. Thus, most cancer models have been primarily focused on the occurrence of mutations, assuming that each oncogenic mutation immediately and inevitably leads to clonal proliferation and is thus rate-limiting for cancer progression. But this understanding of the fitness effect of mutations is discrepant with evolutionary theory, whereby the fitness value of a mutation is entirely dependent on context (genetic, environmental, etc.).

Extrinsic risk factors like smoking, as well as intrinsic risk factors like aging, will do much more than affect mutation load – they will drastically alter tissue landscapes and thus influence the selective value of mutations (4). The major driver of organismal evolution is environmental change, largely by impacting selection and drift. To give just one example, the hominid lineage leading to modern humans has undergone drastic phenotypic change in the last 5+ million years, and yet I doubt that any evolutionary biologist would argue that this was due primarily to mutation accumulation. Instead, changing environments and selective pressures drove human evolution. Our ape and chimp cousins took a different path, due to different environmental pressures, not due to differences in mutation rates. At the organismal level, it is environmental perturbations that lead to evolutionary change as organisms adapt to new environments. So why do cancer biologists so often ignore the role of altered selection driven by environmental (i.e. tissue microenvironment) changes when considering links between cancer incidence and factors such as aging, smoking, obesity, etc.?

When the dynamic evolutionary concept of fitness is incorporated into our understanding of cancer, then cancer progression, as a type of somatic evolution, can primarily be understood as a microenvironment-dependent process. While the natural selection driven maintenance of tissues through periods of likely reproduction promote stabilizing selection in stem and progenitor cell pools (limiting somatic evolution), alterations in tissue landscapes (whether from aging, smoking or other insults) will change adaptive landscapes, promoting selection for mutations that are adaptive to this new microenvironment. Some of these mutations can be oncogenic, and thus contexts that promote tissue change like aging promote selection for adaptive oncogenic mutations. Of course, mutations are still necessary (and thus cell divisions are necessary), but mutations without the other evolutionary forces of selection and drift would be insufficient to account for increased rates of cancer in old age, in smokers, and for other cancer-promoting contexts. Hopefully, the impact of etiologic factors on cancer risk will be more frequently considered in terms of how they impact tissue microenvironments and selection, in addition to how they impact mutation frequency.

This comment was also posted on the Nature website linked to this same paper.

James DeGregori Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine james.degregori@ucdenver.edu

1 Tomasetti, C. & Vogelstein, B. Cancer etiology. Variation in cancer risk among tissues can be explained by the number of stem cell divisions. Science 347, 78-81, doi:10.1126/science.1260825 (2015).

2 Rozhok, A. I., Wahl, G. M. & DeGregori, J. A Critical Examination of the “Bad Luck” Explanation of Cancer Risk. Cancer Prevention Research 8, 762-764, doi:10.1158/1940-6207.capr-15-0229 (2015).

3 Nowell, P. C. The clonal evolution of tumor cell populations. Science 194, 23-28 (1976).

4 Rozhok, A. I. & DeGregori, J. Toward an evolutionary model of cancer: Considering the mechanisms that govern the fate of somatic mutations. Proceedings of the National Academy of Sciences of the United States of America 112, 8914-8921, doi:10.1073/pnas.1501713112 (2015).

On 2017 Jun 24, Randi Pechacek commented:

Jonathan Eisen wrote a blog post on microbe.net praising this paper for its careful accuracy.

On 2016 Feb 11, Todd Lowe commented:

We thank Isidore Rigoutsos and co-authors for the helpful, detailed comments. We have addressed all the issues in their commentary.

In brief:

1) The legacy names have been fixed and updated.

2) For now, we have put the pseudogene designations back into the database — this will likely change in the future as we develop a more objective, less arbitrary cutoff for what is called a tRNA pseudogene. We will post release notes when we do make these types of changes in the future, and welcome feedback from users.

3) The name mismatches between the GtRNAdb, NCBI, and HGNC for human tRNAs is due to an incomplete update of HGNC records requested previously, but we are coordinating with them to get these updated quickly.

4) We have put a disclaimer on the front page of the GtRNAdb letting users know that this database is a reflection of what we believe is the state of the art in tRNA detection and annotation. Our own understanding of tRNAs has been greatly enhanced by the use of the new isotype-specific models and increased sensitivity from tRNAscan-SE 2.0 (manuscript in preparation), so the criteria that we previously applied are, in some cases, clearly outdated and can be improved. A number of manuscripts are in preparation detailing these new insights based on our improved tRNA detection methods.

5) If users prefer a static, historical view of tRNAscan-SE gene calls, the prior GtRNAdb will still be available for reference at http://gtrnadb2009.ucsc.edu/ for the foreseeable future.

6) Some endpoints have indeed changed slightly (generally by 3-10 nucleotides total, for just 15 of 600+ total genes) because low-scoring tRNAs are aligned & scored slightly differently by Infernal 1.1 and the new tRNA covariance models, compared to the older software. We have over 60 new isotype-specific covariance models that we are still improving and refining, so small adjustments are expected over the next few months.

7) Of the "new" tRNAs in the GtRNAdb from the human genome, the vast majority are either very low scoring (i.e., they were just below the 20.0 bit covariance model score reporting cutoff used by the old version of tRNAscan-SE; with Infernal and new models, those scores may shift by 2-5 bits, bringing some above the reporting threshold, and some dropping below it). Because these differences are only affecting very low-scoring tRNAs, they appear to have little to no effect on the high-scoring tRNAs used in translation. Also, a fair number appear to be mitochondrial-derived tRNA genes, which tRNAscan-SE 2.0 is now able to detect with high sensitivity. These nuclear-encoded mitochondrial tRNA genes are now recognized to be commonly found in nuclear genomes, just as many mitochondrial proteins have migrated to the nuclear genome.

We regret any inconvenience these issues have caused users in the first few weeks since the database went live in December 2015. We encourage users to email us directly if they have questions or issues we can address. We are working hard to make this a useful, powerful resource to support the rapidly growing field of tRNA research.

Todd M. Lowe, Biomolecular Engineering, University of California, Santa Cruz

On 2016 Jan 21, Isidore Rigoutsos commented:

Comments on the contents of release v2.0 of gtRNAdb

The gtRNAdb repository is a great resource for researchers studying transfer RNAs (tRNAs). With the increasing interest in the roles tRNAs and tRNA fragments play outside the confines of codon translation into amino acids, databases such as gtRNAdb are expected to provide invaluable reference information.

We focused on the Homo sapiens portion of gtRNAdb v2.0 and found the following:

Sweeping, undocumented changes in v2.0. In the above article, the authors state that they populated gtRNAdb v2.0 using a method that underwent major development but has not yet been peer-reviewed (the method is cited as “Chan et al., in preparation”). Specifically, for Homo sapiens the new method resulted in changes affecting 28% of the human tRNA records; the changes comprise

• the deletion of 74 tRNA records originally in v1.0

• the “elevation” of 41 pseudo-tRNAs of v1.0 to tRNAs in v2.0

• the modification of endpoints in v2.0 compared to v1.0 for 20 tRNAs

• changes in the claimed anticodon for 6 tRNAs

• the addition of 60 new human tRNAs in v2.0

Many new/modified human tRNAs have secondary structures that deviate substantially from the tRNA cloverleaf. We inspected manually the secondary structures of those human tRNA entries that are new to or have been corrected in v2.0 and found that

• at least 9 of the 41 elevated pseudo-tRNAs,

• at least 15 of the 20 entries whose endpoints changed in v2.0, and

• at least 18 of the 60 newly added tRNAs

(i.e. nearly 35% of the new/corrected entries) have abnormal secondary structures that deviate greatly from the tRNA cloverleaf.

Many v2.0 tRNA records are linked to incorrect legacy identifiers. 66% of the human tRNA records (405 of the 606) contained in gtRNAdb v2.0 have been linked to incorrect legacy identifiers. Specifically:

• legacy identifiers were given to the 60 new tRNAs of v2.0 even though they did not exist in v1.0

• 331 tRNAs whose coordinates did not change between v1.0 and v2.0 have been associated with a legacy identifier in v2.0 that does not match the original identifier in v1.0

• 14 entries that had their endpoints modified in v2.0 have been assigned legacy identifiers that do not match the entries’ original v1.0 identifier

Many v2.0 tRNA records contain data that are in conflict with their counterpart NCBI Gene and HGNC records. For 116 of the 606 human tRNAs, their gtRNAdb v2.0 records list different chromosome, strand, and endpoint information than the respective NCBI Gene record. These chromosomal location incompatibilities also extend to HGNC (HUGO Gene Nomenclature Committee) records that are linked to directly from within gtRNAdb records.

Competing interests: The above observations were compiled by Phillipe Loher, Venetia Pliatsika, Aristeidis G. Telonis, Yohei Kirino and Isidore Rigoutsos all of whom are with the Computational Medicine Center of Thomas Jefferson University and are actively involved in tRNA research or have published previously in this area. PL, VP, AGT, YK and IR declare no competing financial interests.

More information: a more detailed description on the above together with accompanying Figures and Tables can be found here.

On 2016 Jan 28, Atanas G. Atanasov commented:

Whereby known or predicted usefulness of the synthesized molecules is lately a major driving factor dictating whether chemical synthesis projects are financed or not by funding bodies, it is still important to consider that generation of new chemical molecules might also lead to a following discovery of physical, chemical, or biological properties that are not possible to be predicted in advance. Therefore, new structure synthesis could also be seen as a tool for “exploring the unknown”, which might later lead to unpredictable but very beneficial expansion of existing knowledge. In the context of drug discovery, for example, screening approaches can lead to the discovery of new pharmacological activities of chemical structures that were previously generated without knowledge for possible effects on the biological target molecules that are later found to be affected (e.g., a recent example from this journal: Huang et al. Allosteric ligands for the pharmacologically dark receptors GPR68 and GPR65. Nature. 2015 Nov 26;527(7579):477-83. doi: 10.1038/nature15699).

Atanas G. Atanasov http://pharmakognosie.univie.ac.at/people/atanasov-atanas-g/ http://homepage.univie.ac.at/atanas.atanasov/ http://about.me/Atanas_At

On 2016 Mar 25, Egon Willighagen commented:

I was wondering earlier today if a possible cause if this could be a change in research funding, which has become more project-based and often more focusing on societal impact (or so is my perception) [0]. Chris Evelo argued [1] that if that to be true, one would expect words like important, valuable, and beneficial. Have you considered including words that could hint at societal impact? Do you even have data on such words too? Does that show different patterns than the positive words you measured?

0.https://twitter.com/egonwillighagen/status/713341316244107265 1.https://twitter.com/Chris_Evelo/status/713361254941908992

On 2016 Oct 24, Sean Ekins commented:

infographic for Sanfilippo syndrome http://www.slideshare.net/ekinssean/infographic-for-sanfilippo-syndrome-iiic-and-iiid

On 2016 Oct 24, Sean Ekins commented:

examples of the golden ticket slide http://www.slideshare.net/ekinssean/the-value-of-the-pediatric-and-tropical-disease-voucher-the-golden-ticket http://www.slideshare.net/ekinssean/rare-pediatric-and-neglected-tropical-diseases-priority-review-voucher-and-transaction-values

On 2016 Feb 11, thomas samaras commented:

The paper provides excellent information on the body fat differences in different ethnic groups. Heymsfield et al. also provide convincing evidence that contemporary cohorts usually follow the height squared law [Quetelet Index (QI)] instead of the height cubed law [Ponderal Index (PI)]. However, there are significant exceptions such as data from the HES and HANEs findings (Advancedata Nov. 1976, p 8.). Based on about 6500 individuals, these findings show increasing weight follows or exceeds the PI.

Men 18-74 years: Actual weight: 172 lb vs. Predicted height cubed 
weight (PI): 171.2 lb

Women 18-74 years: Actual weight: 143 lb vs. PI: 140 lb

While there was a 10 year difference in the two populations, the QI did not apply. The increase in weight with height followed the PI (wt/ht3).

Another study (Heymsfield, et al. 2007) showed taller and shorter contemporary cohorts of men followed the PI as shown below:

Height 177cm vs. 174 cm: Actual weight of taller males = 80.6 kg vs.predicted height cubed weight
    (PI) = 80.8 kg 

Data from Cameron and Demerath (2002) showed the PI applied to contemporary 9-year old children as well. See below:

Heights: 135.8 cm vs. 132.1 cm: Actual weight of taller cohort = 32.4 kg vs.31.1 kg predicted by
    the PI.

Data from Heude et al. (2003) also found that 10-11 year old French children experienced a weight increase that was slightly higher than the PI between 1992 and 2000.

Over 80 populations worldwide follow or exceed the PI when different generations are compared. A few are reported in Medical Hypotheses 2002, vol 58 (Table 1): The actual weight for the taller group is compared to the predicted weight based on the assumption that weight increases as the cube of the increase in height or PI and not the square of height as in the Quetelet Index):

Harvard entrants (males)in 1930s vs. 1958-9: Actual wt: 73.7 kg vs. PI prediction: 71.5 kg                  

Wellesley entrants (females)in 1930s vs. 1958-59: Actual wt: 57.9 kg vs. PI prediction: 58.2 kg                         

Male school children in 1934-35 vs. 1958-59: Actual wt: 51.0 kg vs. PI prediction: 51.3 kg

Swedish males in 1971 vs. 1995 (n = 488,732): Actual wt: 72.1 kg vs. PI prediction: 68.0 kg                     

The reasons for taller people having the same or lower BMI/QI compared to contemporary shorter people may be that food portions are standardized so that taller people consume fewer calories per day and shorter people get relatively more. For example, independent of height, most people drink or eat one glass of milk, one hamburger, and the same size meal when dining out. Another factor is socioeconomic status (SES). Taller people are more often from higher SES compared to shorter people, and we know that in the West, poorer people tend to be more overweight or obese than higher SES people. The most likely explanation for this condition is that higher SES people follow healthier eating habits and are more attentive to weight gain. However, the BMI of taller people appears to be increasing. For example, Cohen and Sturm (2008) reported that shorter Americans had significantly higher BMIs than taller people in the past. However, in recent years, they found that taller people have been gaining in BMI at a faster rate than shorter individuals.

In conclusion, as the world population increases in height, weight increases at a rate that matches the Ponderal Index. That’s why the average US male in 1900 had a BMI of 21-23 compared to 26-28 today. Height since the 1900s has increased by 3 to 4 inches. Of course, much of weight increase is related to fat mass.

On 2016 Jan 25, Andrea Messori commented:

Application of the budget-threshold pricing model to PCSK9 inhibitors: detailed description of the the pharmacoeconomic calculations

By Andrea Messori, HTA Unit, Regional Health Service, 50100 Firenze (Italy)

                                                                                                        .

Table 1 of this Comment describes in detail the calculation steps that, in the budget-threshold pricing model developed by the Institute for Clinical and Economic Review (ICER), lead to the estimation of the annual treatment cost of $2,177 per patient.

                                                                                                        .

Table 1. Price estimation method proposed by ICER for PCSK9 inhibitors: steps involved in the estimation of the annual treatment cost of $2,177 per patient

        Parameter                                                             Estimate  

A) Total drug spending …………………. : $410 billion (estimated as 13.3% of $3.08 trillion, which is the total health care spending).

B) Annual threshold for net health care

cost growth for ALL new drugs.............…: $ 15.4 billion (3.75% of $410 billion, where 3.75% is the growth in US GDP, 2015-2016+1%).

C) Annual threshold for

average cost growth per

individual new molecular

entity....................................................... : $452 million (estimated as $15.4 billion/34, where 34 is the average annual FDA entity

                                                                    approvals, 2013-2014). 

D) Annual threshold for estimated potential

budget impact for each individual new

molecular entity…………………….....……: $904 million (estimated as 2 x $452 million).*

E) Five-year annual budget impact

threshold per new moldecular entity........… : $4.52 trillion (calculated as 5 x $904 million).

F) Total five-year health-care savings for<br> each PCSK9 inhibitor……....................…… : $1.22 trillion (estimated by ICER).

G) Five-year annual budget impact

threshold per each PCSK inhibitor

corrected according to health-care

savings…..............…………................….… : $5.74 trillion [sum of (E)+(F)]

H) Annual treatment cost per patient for

each PCSK9 inhibitor………………………… $2,177 (estimated as $5.74 trillion / 2,636,179 (assuming that 2,636,179 patients are treated).

*This step is not perfectly clear. |It seems that the maximum absolute budget allowed to a new molecular entity is the double of the budget expected on average for a new molecular entity.

On 2016 Jan 25, Andrea Messori commented:

None

On 2016 Jan 25, Andrea Messori commented:

None

On 2016 Jan 25, Andrea Messori commented:

None

On 2016 Jan 25, Andrea Messori commented:

None

On 2016 Jan 25, Andrea Messori commented:

None

On 2016 Apr 28, Stuart RAY commented:

Ten genomic sequences reported in this publication (which should be linked to this PubMed entry) are: KT427414.1 KT427413.1 KT427412.1 KT427411.1 KT427410.1 KT427409.1 KT427408.1 KT427407.1 KU159665.1 KU159664.1 Note that NC_027998.2, the reference genome for HPgV-2, is a duplicate of KT427414.1 on which it's based.

Metagenomic reads are in the NCBI Sequence read archive with accession SRP066211

On 2016 Jul 28, Michael Bunce commented:

Thank you for your comments from the 5th June 2016 we welcome the chance to respond.

The main point to be taken from this paper is that there is an urgent need for an accurate testing method including DNA, toxicological and heavy metal screening of complementary medicines. It is clear from the results of this paper that some products that are available for over the counter sale to the general public, whether or not they have been correctly listed with the TGA, could pose a health risk to consumers or contain ingredients that are not declared on the packaging. The authors agree with the comment that the ‘actions of a few have the potential to tarnish the reputation of the majority whose behaviour is professional’, and this is precisely why we believe that stronger regulation and pre and post-market auditing of products should occur. Consumers of TCM and other complementary medicines should be made aware that some products do not conform to TGA regulations, and consumers are encouraged to contact the TGA for more information about particular products if they have a concern.

A few more replies to your specific queries:

1) These 26 TCM were purchased across a number of retailers as a consumer would purchase them (they were not sold as ‘food’). The fact that they are not randomised does not compromise the study as we simply report on the results of the 26 TCM tested here – noting the results warrant concern. We welcome future efforts to expand sampling to determine a more holistic overview of compliance or lack thereof. The salient point here is perhaps auditing should occur before market?

2) We fully concede (and refer to it in the paper) that salicylic acid can be naturally derived from many plant species.

3) The blue/red colour coding in Figure 1 refers to TCM that are listed and unlisted – as such the data is clearly portrayed.

4) With regard to ‘measurement error’ and ‘false positives’ – we document fully the clean room precautions, replication and controls implemented in the DNA workflows. Our lab specialises in trace DNA analyses on a variety of biological substrates. As noted in the paper assignments based on DNA metabarcoding data (publically available – see link in paper) are conservative.

5) In response to your query regarding Supplemental Table 1, the allocation of TCM8 and TCM11 to the TGA unlisted category of products was an error in the Supplemental Table and we can confirm that these two products do have AUSTL numbers and are formally listed with the TGA, as correctly reported in the published manuscript (Tables 1, 2 and 3). We will correct this minor error in the supplemental table with the publishers – many thanks for making us aware of it.

6) Finally, we would have been happy to write a reply to the ‘Journal of Chinese Medicine and Science’ but the journal has no content online and is not formally listed as a journal, the link at www.fcma.org.au (as of July 2016) lists no content. Can you please provide a formal link to the Journal so readers at PubMed can assess the legitimacy of the publication.

On 2016 Jun 05, Sherman Gu commented:

We are writing to express our concerns about some reporting errors and therefore conclusions reached in this paper. Firstly, there is a discrepancy in the reporting of which group, the Therapeutic Goods Administration (TGA) unlisted or listed products, a few of the products belong to. For example, according to the Supplementary Table (S1) of the report, TCM8 and TCM11 belong to the TGA unlisted product group, yet the results for these products appear in the TGA listed group in Tables 1, 2 and 3. It would thus appear from Table S1 that there are nine listed TCM products and 17 unlisted products, not 12 listed products as is stated in the Discussion Section of the report. Secondly, with respect to Table 2 which reports adulterants or undeclared products, trace amounts of salicylic acid were found in five listed TCMs including TCM22. TCM22 contains Panax ginseng, and one of components of this herb is known to be salicylic acid. This might explain the trace amounts found in this TCM sample. Nonetheless, it is of concern that three (excluding TCM8 and TCM11 which are apparently unlisted TCMs according to Table S1) of the nine listed TCM products were adulterated with either pseudo/ephedrine, methylephedrine (TCM2, TCM7) or sildenafil (TCM23). Thirdly, it should also be noted that five of the TCM samples were herbal tea bags (TCM11, TCM13, TCM24, TCM25, TCM26) and one was ‘flakes’ (TCM10), all of which are unlisted, according to Table S1. In our opinion, these would not be considered conventional TCM herbal medicines that a registered Chinese medicine practitioner would prescribe. Without any information as to where these six products were purchased, it is difficult to form any conclusions as to whether these are potentially prescribed by any practitioner or whether they were sold as food in a shop. These findings potentially skew the summary set out in Figure 1 (i.e. if TCM8, TCM11 do not belong in the listed group and if the salicylic acid found in TCM22 were to be consistent with that expected in a TCM containing Panax ginseng, and if the six herbal tea bags and flake samples were deleted). The percentages of contaminated/adulterated products may well be different between the unlisted and listed products. Fourth, by reporting the results of all the products sampled together (92%) in the Abstract, rather than separating them out into percentages relating to the listed group of products and the unlisted group of products, important information and an important distinction is missed. Those TCMs that are considered safe for use are those that are listed (or registered) under the TGA. Those that have not been listed (or registered) on the Australian Register of Therapeutic Goods have not been assessed by the TGA for safety, quality and in the case of registered products, efficacy. The use of unlisted (or unregistered) proprietary TCMs by a registered Chinese medicine practitioner is against the Chinese Medicine Board of Australia (CMBA)’s Code of conduct and Guidelines for safe Chinese herbal medicine practice. Fifth, the sample collection method is somewhat vague and there is no evidence of any randomisation of the process of selecting the products. There is no information about whether the Chinese medicine practitioners were registered with the CMBA and how many practices the products were purchased from, nor how many nor what kind of retail stores were targeted for the selection of products. These factors are important to consider in any discussion of the ramifications of findings, in particular in relation to the unlisted products. Finally most measurement instruments have a level of error. The possibility of false positives with respect to, for example, the DNA testing has not been mentioned. These details are important in the analysis of findings and also constitute some of the limitations of the study. Unfortunately limitations of the study do not appear to have been discussed at all, as would be expected of a scientific study. Whilst there may be valid reasons for not divulging the names of the TCM products (i.e. the potential for litigation), non-disclosure makes this investigation impossible to replicate by other researchers and therefore verify the results. The results will be of concern to responsible Chinese medicine practitioners who need to know which products should be avoided. These criticisms of the paper are not meant to detract from some of the findings of the paper. The fact that unlisted products are available, albeit possibly from only a small number of sources, is unfortunate since the actions of a few have the potential to tarnish the reputation of the majority whose behavior is professional. It is commendable that the authors of the above-named paper have conducted an independent analysis of several proprietary TCMs. However, greater care and tighter reporting of results would have gone a long way to improving the quality of this report. The popular press will always pick up what makes for a sensational headline. The consequences of reporting the combined result of 92%, the figure itself open to debate, has been to cause alarm. The general public is unlikely to read the research paper nor be able to interpret the research findings and may be left feeling concerned. We look forward to reading the results of future research which investigates such an important issue, conducted in a large and more representative sample of TCM products.

Re-printed with permission from “Gu, S., O' Brien, K., & Cheung, T. (2016). Reporting Errors in the Coghlan et al report 2015. Australian Journal of Chinese Medicine and Science, 3(1), 66-67.”

On 2017 Oct 05, ROBERT HURST commented:

Unfortunately, KU-7 is not bladder cancer but is, instead, HeLa cells. PMC3805942

On 2015 Dec 17, Peng Chen commented:

Excellent work, very impressive!

On 2016 Feb 25, Kristina Hanspers commented:

Figures EV6b and EV7j are available as a pathway in the WikiPathways Open Access Collection: http://www.wikipathways.org/index.php/Pathway:WP3596 and http://www.wikipathways.org/index.php/Pathway:WP3595. This pathway can be downloaded in gpml format and used for analysis and visualization in applications like PathVisio and Cytoscape.

On 2016 Aug 17, Kirk O'Reilly commented:

McIntyre et al. have published a series of papers evaluating the use of soil bioretention systems to reduce the toxicity of stormwater and highway runoff (McIntyre et al. 2014, 2016, 2016b). Their recent paper (McIntyre et al. 2016) investigates the use of soil bioretention to treat artificial runoff from a test plot treated with a refined tar sealant (RTS). What readers may not know is that there is an on-going controversy concerning the environmental implications of RTS use (LeHuray 2015; USGS 2016). According to McIntyre’s acknowledgement, U.S. Geological Survey personnel responsible for the agency’s effort to ban RTS assisted in project planning. The goal of this comment is not to criticize McIntyre’s research on the use of soil bioretention systems but to discuss the results in the context of other studies so that the paper is not misused by those advocating for RTS product bans. The technical basis for these comments are summarized in Exponent (2016).

Key Points:

The title overstates the toxicity of RTS runoff.

The title suggests that sealant runoff causes “severe” toxicity. But severe is neither defined nor used in the text of the article. Severe toxicity is not a commonly used term in aquatic toxicology. Use of “acute toxicity” or just “toxicity” in the title would be less inflammatory and more consistent with the study results.

As noted by the authors in a prior publication (McIntyre et al. 2014), “Developing fish embryos are particularly vulnerable to the harmful effects of chemical contaminants and have long been a focus for toxicity screening. More recently, model species such as the zebrafish have provided an increasingly sophisticated experimental context for evaluating the developmental toxicity of individual chemical constituents in stormwater.” McIntyre et al. (2016b) says that their tests measure subtle biological effects. A positive bioassay result with a particularly vulnerable fish embryo test system is insufficient to support the suggestion of severe toxicity.

While the survival of another test species, juvenile Coho salmon, was less in runoff from a sealant test plot than the control, only the runoff collected within a few hours of sealant application killed all the organisms. Mortality decreased substantially for subsequent samples and remained significantly different from controls with runoff collected two weeks but not three weeks after application.

The toxicity of sealant runoff is consistent with the toxicity of runoff from unsealed surfaces.

McIntyre et al. (2014, 2016b) describe tests conducted on highway runoff collected during six storm events. Two of the six stormwater samples killed all Zebrafish embryos, and a third sample resulted in a significant reduction in survival. All six of the stormwater samples caused sublethal effects similar to those discussed in the RTS paper.

Greenstein et al (2004) tested the toxicity of artificial runoff from an operating asphalt parking lot in Southern California. There was no evidence that RTS was ever applied on the lot. Using a sensitive marine aquatic bioassay, sea urchin egg fertilization, toxicity was noted in all runoff samples.

Soil Bioretention treatment of RTS and highway runoff can eliminate toxicity and significantly reduced the response of sensitive molecular indicators.

Soil bioretention is a sustainable approach in which runoff is filtered by soil. It mimics natural processes that can reduce the toxicity of runoff from urban surfaces including sealed parking lots.

Acknowledgment

The author of this comment has conducted research funded by the Pavement Coating Technology Council.

References

McIntyre JK, Edmunds RC, Anulacion BF, Davis JW, Incardona JP, Stark JD, Scholz NL. 2016. Severe coal tar sealcoat runoff toxicity to fish and reversal by bioretention filtration. Environmental Science & Technology 50(3): 1570–1578.

LeHuray, A. 2015. In response to Bales (2014). Integrated Environmental Assessment and Management, 11(2), 185–187.

USGS. 2016. Information Quality - Information Correction Request. At: https://www2.usgs.gov/info_qual/archives/coal_tar_sealants.html

Exponent 2016. Summary of McIntyre et al. 2016. “Severe Coal Tar Sealcoat Runoff Toxicity to Fish Is Prevented by Bioretention Filtration” Environ. Sci. Technol. 50:1570−1578. Pavement Coatings Technology Council. 2016-08-14. URL:http://www.pavementcouncil.org/wp-content/uploads/2016/08/Tech-Memo-McIntyre-2016-review-Final.pdf. Accessed: 2016-08-14. (Archived by WebCite® at http://www.webcitation.org/6jlOpIS8t)

McIntyre JK, Davis J, Incardona J, Stark J, Anulacion B, Scholz N. 2014. Zebrafish and clean water technology: Assessing soil bioretention as a protective treatment for toxic urban runoff. Science of the Total Environment 500:173–178. Open Access: http://www.sciencedirect.com/science/article/pii/S0048969714012455

McIntyre JK, Edmunds RC, Redig MG, Mudrock EM, Davis JW, Incardona JP, Stark JD, Scholz NL. 2016b. Confirmation of stormwater bioretention treatment effectiveness using molecular indicators of cardiovascular toxicity in developing fish. Environmental Science & Technology 50(3): 1561–1569.

Greenstein D, Tiefenthaler L, and Bay S. 2004. Toxicity of parking lot runoff after simulated rainfall Arch Environ Contam Toxicol. 47:199–206.

On 2017 Apr 21, EDUARDO FRANCO commented:

PLease note that this seems to be a duplicate of PMID: 28417802. I posted a similar note in the latter.

On 2015 Dec 22, Christopher Southan commented:

The GtoPdb release used to compile this series is described in the 2016 NAR Database issue http://www.ncbi.nlm.nih.gov/pubmed/26464438

On 2017 Oct 07, Ruth Gabizon commented:

Definitely agree. Indeed the utility of EAE as an MS model has always been questioned. Many treatment strategies that were usefull for EAE had no effects on humans, which is the case for many reagents in all animal models of diseases. However, it is important to acknowledge that all MS treatments used today were first shown to be active in EAE models

On 2017 Sep 30, Alessandro Rasman commented:

Very interesting study. It is important now to test it on humans because there are doubts about the utility of the EAE model in the MS (1). References: 1. Behan, Peter O., and Abhijit Chaudhuri. "EAE is not a useful model for demyelinating disease." Multiple Sclerosis and Related Disorders 3.5 (2014): 565-574.

On 2016 Aug 19, Stephanie Sivell commented:

Dear H Benalia and N Novell,

Thank you for the comments from your team. Like you and your colleagues in the Cicely Saunders Institute, we also felt this to be an important and underrepresented area of the literature. A key remit of the Marie Curie Palliative Care Research Centre (MCPCRC), Cardiff is to advance the research methodology within the field of palliative and end of life care. Our discussion, and the resulting paper, was an opportunity to explore the issues our colleagues were regularly facing and reflecting upon. As methodologists within each of our varying disciplines in the MCPCRC (also co-authors of our paper), we thought that it was timely to come together as a team to discuss these issues and document them. We hoped that our paper would resonate with our colleagues in the wider academic community both within the world of palliative and supportive care and more generally in health and social care. We were therefore delighted that you and your team not only took the time to read and critique our paper in your journal club, but also shared your thoughts to widen up the debate.

By ‘consensus’ we were referring to the definition of a general agreement; we were not aiming to undertake a ‘rigorous’ piece of work, collecting primary data etc., and/or undertaking some kind of adapted Delphi or similar. This was simply beyond the parameters of this discussion. Rather, and as our paper describes, this was a discussion which we felt was something important for our team to reflect upon and potentially benefit from. We also felt that if we were having these thoughts and concerns within the MCPCRC, then the wider academic community are likely to encounter similar issues and conversations. Ethical approval therefore, was not required but we sought consent for the recording of the discussion; furthermore, and as required by the governance of the journal, we documented the roles of all co-authors who were also part of the discussion which stimulated the resulting paper. We were also interested in your thoughts on comparing interview settings. Again, this was not possible within the parameters of our discussions and our paper, but we would be interested in any papers which specifically focus on such issues in their work.

As is often the case, we were limited by the house style of the journal we submitted our manuscript to, not least of all the word limits. That being said, we did attempt to summarise the key issues to at least give the reader a flavour of each aspect we have discussed in the paper and addressing all issues raised by the peer reviewers, including practical and safety issues. We did offer quite a detailed account of such issues, within the boundaries of the journal’s requirements; that being said we also did not feel that reviewers and readers would be interested in minutia of how to develop a protocol per se. However, we would be more than happy to extend this discussion should there be any specific queries concerning health and safety issues and practice amongst our researchers.

We look forward to extending the discussion and debate; we welcome and encourage our colleagues undertaking qualitative palliative and end of life care, and beyond, to discuss and reflect upon their own experiences of undertaking qualitative research interviews.

Regards,

Dr Stephanie Sivell, Dr Emily J Harrop and Dr Annmarie Nelson on behalf of the Marie Curie Palliative Care Research Centre, Division of Population Medicine, Cardiff University.

On 2016 Aug 03, Cicely Saunders Institute Journal Club commented:

The Cicely Saunders Institute journal club discussed this paper on 03/08/2016

Considerations around conducting qualitative interviews with palliative and end of life care patients, particularly in the home setting, is an important and underrepresented area of the literature.

We enjoyed discussing this paper and felt it raised some important questions. We were particularly interested in the methods, and felt that more information would have been valuable. For example how were participants for the consensus meeting chosen, what topics were selected for discussion and how these were selected/ shortlisted, levels of agreement and consensus, and area of discordance during the discussion, ethical approval and consent processes prior to the meeting, and at what point consensus was reached (was this during or after the meeting)? A section detailing limitations of this research would be helpful when interpreting the results.

We had an interesting discussion around potential conflicts of interest that might arise when all participants of a consensus group are authors of a subsequent publication, and we are not aware of any evidence around this? During our journal club we discussed many of the benefits of conducting interviews in participant’s home setting, which might have been interesting to emphasise more in the paper. Practical issues and the importance of safety are areas that require consideration when planning and conducting research in home settings, and we would have been interested to see more discussion of this. We thought it might also be helpful to compare interviews settings (hospital, hospice, home, etc) and highlight key differences.

Commentary by H Benalia & N Lovell

On 2016 Apr 05, Marko Premzl commented:

The third party data gene data set of eutherian tumor necrosis factor ligand genes LN874312-LN874522 was deposited in European Nucleotide Archive under research project "Comparative genomic analysis of eutherian genes" (https://www.ebi.ac.uk/ena/data/view/LN874312-LN874522). The 211 complete coding sequences were curated using tests of reliability of eutherian public genomic sequences included in eutherian comparative genomic analysis protocol including gene annotations, phylogenetic analysis and protein molecular evolution analysis (RRID:SCR_014401).

Project leader: Marko Premzl PhD, ANU Alumni, 4 Kninski trg Sq., Zagreb, Croatia

E-mail address: Marko.Premzl@alumni.anu.edu.au

Internet: https://www.ncbi.nlm.nih.gov/myncbi/mpremzl/cv/130205/

On 2016 Apr 07, Angelo Calderone commented:

The paper by Tamura and colleagues has provided the interesting observation that a subpopulation of cardiac resident neural crest-derived stem cells differentiated to an adrenergic phenotype following heterotopic transplantation of the mouse heart. Previous work from this lab (JBC 2005) reported that cardiac resident neural-crest derived stem cells grew as spheres in the presence of EGF and FGF2, expressed nestin, musashi-1 and differentiated to a neuronal phenotype in vitro. Work from our lab has likewise revealed the presence of neural crest-derived stem cells in the rodent heart and expressed nestin (El-Helou et al, 2008, J Molecular Cellular Cardiology). Furthermore, nestin(+)-cells isolated from the scar of the infarcted heart grew as spheres when cultured in EGF/FGF2 and differentiated to a neuronal phenotype in vitro (El-Helou et al, 2008, J Molecular Cellular Cardiology). Furthermore, work from our lab has reported that a subpopulation of nestin(+)-cells in the infarct region expressed neurofilament-M and contributed in part to the reported innervation of the scar (Beguin et al, 2011, J Cellular Physiology; Chabot et al, 2013 Cardiovascular Diabetology). Moreover, we further demonstrated that following isogenic heterotopic transplantation of the rat heart, the superimposition of an ischemic injury to the transplanted heart led to de novo cardiac innervation mediated by the expression of neurofilament-M by nestin(+)-cells (Beguin et al, 2011, J Cellular Physiology). However, we did not further assess whether these nestin(+)-cells that expressed neurofilament-M in the ischemically damaged transplanted heart acquired an adrenergic phenotype. Thus, in the true spirit of scientific research, the paper by Tamura and colleagues should have cited previous work from our lab that recapitulated in part the findings provided in their recent paper published in Cardiovascular Research.

On 2016 Jan 03, Peter Gøtzsche commented:

Antidepressants are addictive and increase the risk of relapse

In their systematic review, Amick et al. write that reasons for preferring psychotherapy over drugs for depression include concerns about side effects and ‘perceived “addictiveness”’ of drugs (1). This addictiveness is not hypothetical, it is very real (2,3) and affects about half of those treated with antidepressants (3,4).

The authors do not discuss what might be their most important finding, that psychotherapy leads to fewer relapses than drug therapy, which was expected, as it is related to the drugs’ addictiveness. It is tricky that withdrawal symptoms and disease symptoms can be the same, but there are clear differences. Withdrawal-induced, depression-like symptoms usually come rather quickly and disappear within hours when the full dose is resumed, whereas it takes weeks before the patients get better if they have a true depression (3).

A large trial of patients with remitted depression illustrates this (5). After the patients had become well, they continued with open maintenance drug therapy for 4-24 months. They then suddenly had their therapy changed to a double-blind placebo for 5-8 days at a time that was unknown to the patients and clinicians. Forty of 122 patients (33 %) on sertraline or paroxetine had an increase in their Hamilton depression score of at least eight, which is a clinically relevant increase. This study illustrates why most doctors get it wrong when they think the disease has come back upon lowering or stopping the dose. In a group of 122 patients whose depression has been in remission for 4-24 months, likely only one or none would get a true relapse of the depression during 5-8 random days.

Antidepressants trap people into what often becomes life-long treatment. Of 260,322 persons in Finland who were on such a drug in 2008, 45 % were on an antidepressant drug five years later (3).

1 Amick HR, Gartlehner G, Gaynes BN, et al. Comparative benefits and harms of second generation antidepressants and cognitive behavioral therapies in initial treatment of major depressive disorder: systematic review and meta-analysis. BMJ 2015;351:h6019. 2 Nielsen M, Hansen EH, Gøtzsche PC. What is the difference between dependence and withdrawal reactions? A comparison of benzodiazepines and selective serotonin re-uptake inhibitors. Addiction 2012;107:900–8. 3 Gøtzsche PC. Deadly psychiatry and organised denial. Copenhagen: People’s Press; 2015. 4 Kessing L, Hansen HV, Demyttenaere K, et al. Depressive and bipolar disorders: patients’ attitudes and beliefs towards depression and antidepressants. Psychological Medicine 2005;35:1205-13. 5 Rosenbaum JF, Fava M, Hoog SL, et al. Selective serotonin reuptake inhibitor discontinuation syndrome: a randomised clincial trial. Biol Psychiatry 1998;44:77-87.

On 2017 Feb 09, Karsten Suhre commented:

Very interesting paper - The TXNIP cg19693031 association with Type 2 Diabetes clearly replicates everywhere. The authors write "While finalizing this manuscript,three studies were published and observed an association of DNA methylation at cg19693031 in TXNIP, and type 2 diabetes (36–38)." Actually, there is a fourth paper that came out in Jan 2016: "Epigenetic associations of type 2 diabetes and BMI in an Arab population" by Al Muftah et al. (Clin Epigenetics. 2016 Jan 28;8:13. doi: 10.1186/s13148-016-0177-6, PMID: 26823690). You may be interested to take a look at Table 4 of the Al Muftah paper - it puts the recent Petersen et al. metabolomics findings (ref 35 in the present Soriano-Tárraga et al. paper) into the context of the TXNIP association: The associated metabolic phenotype (metabotype) of the TXNIP CpG association is characteristic of a diabetes state. What is more, the obesity (BMI) associated CpG loci cg06500161 (ABCG1) and cg00574958 (CPT1A) also display the same diabetes metabotype. This suggests that the methylation of all of these sites could be a regulatory response to obesity induced deregulated metabolism. It would be interesting to test whether the TXNIP CpG association holds in a cohort of non-obese diabetics.

On 2016 Aug 22, Anthony Jorm commented:

The Royal Australian and New Zealand College of Psychiatrists (RANZCP) has recently published clinical practice guidelines on eating disorders Hay P, 2014, mood disorders Malhi GS, 2015 and schizophrenia Galletly C, 2016. These guidelines contain a mixture of evidence-based recommendations where there were relevant intervention studies, and consensus-based recommendations where relevant studies did not exist. The consensus-based recommendations comprised a substantial proportion of the guidelines for mood disorders (59%) and schizophrenia (46%), but less so for eating disorders (10%), indicating that expert consensus is an important source of guidance on best practice in psychiatry.

Given the substantial contribution of expert consensus to these guidelines, it is important that the methods for establishing this consensus are adequate. The Australian National Health and Medical Research Council (NHMRC) has published requirements for development of clinical practice guidelines, but these do not give much guidance on how this should be done, simply mandating that “The method used to arrive at consensus-based recommendations or points (e.g. voting or formal methods, such as Delphi) is documented”. (National Health and Medical Research Council. Procedures and requirements for meeting the 2011 NHMRC standard for clinical practice guidelines. Melbourne: National Health and Medical Research Council; 2011.)

Another potential source of criteria for evaluating the quality of methods for developing consensus-based recommendations comes from research on ‘wisdom of crowds’ Lorenz J, 2011 Kattan MW, 2016 Baumeister RF, 2016. Based on such research, Surowiecki has proposed four conditions necessary for a group to make good decisions (Surowiecki J. The wisdom of crowds: why the many are smarter than the few. London: Abacus; 2004.): 1. Diversity of expertise. A heterogeneous group of experts will produce better quality decisions than a homogeneous one. For guidelines developers, this may mean that the experts should come from a range of relevant disciplines, including consumer experts where appropriate. 2. Independence. The experts must be able to make their decisions independently, so that they are not influenced by others. For guidelines developers, this means that voting on consensus-based recommendations is carried out privately so that strong individuals cannot dominate the group. 3. Decentralization. Expertise is held by autonomous individuals working in a decentralized way. For guidelines developers, it is important to specify what sources of information the experts had available to them. 4. Aggregation. There is a mechanism for coordinating and aggregating the group’s expertise. For guideline developers, this could involve an independent person who runs the voting and gives feedback to the group.

If we take these four conditions as appropriate for judging the quality of methods for developing consensus-based recommendations, how well do the RANZCP guidelines meet them?

An indication of diversity of expertise is the disciplinary composition of the guideline working groups. There was limited diversity for all working groups, with non-psychiatrists comprising 3 of the 8 members for eating disorders, 4 out of the 12 members for mood disorders and 2 out of the 10 members for schizophrenia working group. There were no consumer or carer members of any of the working groups. While the mood disorder and schizophrenia guidelines included consensus-based recommendations s for indigenous peoples, it is not stated whether any of the working groups included indigenous members.

The mood disorders and schizophrenia working groups did not appear to involve independent decision making. Both groups had discussions until consensus was reached. The eating disorders guidelines did not give relevant information about whether there was independence.

All three guidelines state that consensus-based recommendations were based on collective clinical and research knowledge and experience. The eating disorder guidelines additionally state that level IV articles were considered where higher-level evidence was lacking and this informed the consensus-based recommendations.

After drafting, all guidelines had input from a broader group of expert advisers with a wide diversity of expertise. However, it is not clear whether these advisers had the potential to persuade working group members to change consensus-based recommendations.

Where the guidelines included consensus-based recommendations relevant to indigenous peoples, it is not clear what sources of cultural expertise these were based on.

None of the guidelines state how judgements were aggregated to determine consensus. The mood disorders guidelines state that agreement on consensus-based recommendations was “in most cases unanimous but allowed one committee member to abstain”. The other guidelines did not define what constituted consensus.

In conclusion, there are major weaknesses in the procedures used to determine consensus-based recommendations for all three guidelines. These are lack of independence in decision making by experts, a lack of a formal mechanism for aggregating judgments, and a lack of diversity of expertise, particular in areas where consumers and carers could contribute and where cultural expertise is relevant.

While NHMRC gives quite detailed guidance on how to develop evidence-based recommendations, there is little guidance on best practice for developing consensus-based recommendations. While many of these weaknesses would be overcome by using formal consensus methods such as the Delphi process, there is a need for NHMRC and similar agencies to produce more rigorous quality standards for development of consensus-based recommendations.

On 2015 Dec 21, Christopher Southan commented:

Please could the authors open the Dryad link (still closed 21 Dec) to what I assume includes specification of the 50 structures - now open 28 Dec, thanks. See molecular mapping efforts at http://cdsouthan.blogspot.se/2015/12/resolving-tb-actives-shouldnt-be-this.html

On 2016 Feb 05, Lydia Maniatis commented:

Some additional examples of the casual approach to theory and method that's exhibited here and seems to have become the norm in the vision literature:

1. A tolerance for extremely ad hoc suggestions: "Meese (personal communication) has suggested an alternative explanation for why β declines with signal area that does not preclude the possibility that the maximum, i.e., whole-area signal condition is detected by a global linear integrator. He suggests that the visual system might employ linear filters matched in shape to the various signal-shape conditions. Thus for the single pie-wedge and windmill conditions these would be pie-wedge and windmill-shaped filters matched to the signal area, culminating in full-circle global linear integrators for the 100% signal area conditions."

There is no rationale for the suggestion that there are special mechanisms for "wedge and windmill -shaped" areas; they just happen to be the shapes of the stimuli the authors chose (also without a rationale). If they had used square or heart-shaped stimuli, the existence of the corresponding "filters" would apparently have been conceivable.

1. In their introduction the authors indicate they are studying basic visual perception. However, their definition of "external noise" is completely contingent, not on the spontaneous appearance of stimuli, but on the instructions given to observers to attempt to locate in the spontaneously-arising percept. They are instructed to detect a particular "texture" in a surface that contains more than one such, and in which the different textures tend to blend perceptually. The non-target texture is labelled "external noise" for the purpose of creating the noise terms demanded by the "model." If the task had been to estimate the presence or proportion of vertical bars in the entire stimulus, the noise term would presumably have been all the non-vertical bars. The definition of the term is completely arbitrary, designated without consulting the visual system, so to speak, as to functionally relevant concepts. In a recent article, Solomon, May and Tyler (2016) defined "external noise" in terms of the standard deviations from which they draw their stimuli; this standard deviation is given two different values simply because the model they choose to fit calls for two "external noise" terms.

2. The title itself (as well as the text) indicates that the vague conclusions are to be applied to the particular stimuli used, stimuli contained in a round envelope (with wedge or windmill-shaped targets areas).

On 2016 Jan 27, Lydia Maniatis commented:

A little way into their introduction, the authors of this article make the following clear and unequivocal assertion:

“These findings underscore the idea that the encoding of objects and shapes is accomplished by a hierarchical feedforward process along the ventral pathway (Cadieu et al., 2007; Serre, Kouh, Cadieu, Knoblich, & Krei- man, 2005; Serre, Oliva, & Poggio, 2007; Van Essen, Anderson, & Felleman, 1992). The question that arises is how local information detected in the early visual areas is integrated to encode more complex stimuli at subsequent stages.”

As all vision scientists are aware, the processes involved at every level of vision are both hierarchical and parallel, feedforward and feedback. These processes do not consist of summing “local information” to produce more complex percepts; a small local stimulus change can reconfigure the entire percept, even if the remaining “local information” is unchanged. This has been solidly established, on a perceptual and neural level, on the basis of experiment and logical argument, for many decades. (The authors' use of the term “complex stimuli,” rather than “complex percepts” is also misjudged, as all stimuli are simple in the sense that they stimulate individual, retinal photoreceptors in the same, simple way. Complexity arises as a result of processing - it is not a feature of the retinal (i.e. proximal) stimulus).

The inaccurate description of the visual process aligns with the authors' attempt to frame the problem of vision as a “summation” problem (using assumptions of signal detection theory), which, again, it decidedly is not. If the theoretical relevance of this study hinges on this inaccurate description, then it has no relevance. Even on its own terms, methodological problems render it without merit.

In order to apply their paradigm, the authors have constructed an unnatural task, highly challenging because of unnatural conditions - very brief exposures resulting in high levels of uncertainty by design, resulting in many errors, and employing unnaturally ambiguous stimuli. The task demands cut across detection, form perception, attention, and cognition (at the limit, where the subjects are instructed to guess, it is purely cognitive). (Such procedures may be common and old (“popular” according to the authors), but this on its own doesn't lend them theoretical merit).

On this basis, the investigators generate a dataset reflecting declining performance in the evermore difficult task. The prediction of their particular model seems to be generic: In terms of the type of models the authors are comparing, the probability of success appears to be 50/50; either a particular exponent (“beta”) in their psychometric function will decline, or it will be flat. (In a personal communication, one of the authors notes that no alternative model would predict a rising beta). The fitting is highly motivated and the criteria for success permissive. Half of the conditions produced non-significant results. Muscular and theory-neutral attempts to fit the data couldn't discover a value of “Q” to fit the model, so the authors “have chosen different values for each experiment,” ranging from 75 to 1,500. The data of one of five subjects were “extreme.” In addition, the results were “approximately half as strong as some previous reports, but “It ...remains somewhat of a mystery as to why the threshold versus signal area slopes found here are shallower than in previous studies, and why there is no difference in our study between the thresholds for Glass patterns and Gabor textures.” In other words, it is not known whether such results are replicable, and what mysterious forces are responsible for this lack of replicability.

It is not clear (to me) how a rough fit to a particular dataset, generated from an unnaturally challenging task implicating multiple, complex, methodologically/theoretically undifferentiated visual processes, of a model that makes such general, low-risk predictions (such as can be virtually assured by a-theoretical methodological choices) can elucidate questions of physiology or principle of the visual, or any, system.

Finally, although the authors state as their goal to decide whether their model “could be rejected as a model of signal integration in Glass pattern and Glass-pattern-like textures” (does this mean they think there are special mechanisms for such patterns?)” they do not claim to reject the only alternative that they compare (“linear summation”), only that “probability and not linear summation is the most likely basis for the detection of circular, orientation-defined textures.”

It is not clear what the “most likely” term means here. Most likely that their hypothesis about the visual system is true (what is the hypothesis)? Most likely to have fit their data better than the alternative? (If we take their analysis at face value, then this is 100% true). Is there a critical experiment that could allow us to reject one or the other? If no alternatives can be rejected, then what is the point of such exercises? If some can be, what would be the theoretical implications? Is there a value in simply knowing that a particular method can produce datasets that can be fit (more or less) to a particular algorithm?

The "summation" approach seen here is typical of an active and productive (in a manner of speaking) subdiscipline (e.g. Kingdom, F. A. A., Baldwin, A. S., & Schmidtmann, G. (2015). Modeling probability and additive summation for detection across multiple mecha- nisms under the assumptions of signal detection theory. Journal of Vision, 15(5):1, 1–16; Meese, T. S., & Summers, R. J. (2012). Theory and data for area summation of contrast with and without uncertainty: Evidence for a noisy energy model. Journal of Vision, 12(11):9, 1–28; Tyler, C. W., & Chen, C.-C. (2000). Signal detection theory in the 2AFC paradigm: Attention, channel uncertainty and probability summation. Vision Research, 40, 3121–3144.)

On 2016 Apr 13, Judith Finlay commented:

This article is not free even with an ASH account set up. It appears membership/subscription is required.