On 2014 Jan 09, Tom Kindlon commented:

Further comments on the outcome measures being used and suggestions for other outcome measures that could be useful in such trials

(This was originally posted here http://www.biomedcentral.com/1741-7015/4/9/comments in 2009)

In the protocol, the authors say the following: "A 2001 systematic review of all treatments for CFS/ME concluded that cognitive behaviour therapy (CBT) and graded exercise therapy (GET) were the most promising treatments for CFS/ME, but that owing to the small number of studies available for review, the generalisability of these results could not be assured [1]*. The authors recommended that further studies be carried out using standardised outcome measures."

They authors neglect to say that the authors of that review also recommended the use of more objective outcome measures: e.g. "Outcomes such as 'improvement,' in which participants were asked to rate themselves as better or worse than they were before the intervention began, were frequently reported. However, the person may feel better able to cope with daily activities because they have reduced their expectations of what they should achieve, rather than because they have made any recovery as a result of the intervention. A more objective measure of the effect of any intervention would be whether participants have increased their working hours, returned to work or school, or increased their physical activities."

It is very disappointing that the organisers of this trial have not taken this on board with this study. Given the cost of the trial (over £1m), the cost of some actometers (for example) would have virtually neglible.

Existing research has some interesting findings on the issue. For example, one study (on a single patient)[2] found "using a 26-session graded activity intervention involved gradual increases in physical activity" that "from baseline to treatment termination, the patient’s self-reported increase in walk time from 0 to 155 min a week contrasted with a surprising 10.6% decrease in mean weekly step counts."The authors of the current trial refer to the Prins (2001) study[3] as an example of a study which supposedly found that hospital-based hospital-based CBT was an "effective treatment" for CFS. Judging by some of the questionnaire data, it does look like CBT has had an effect. However the actometer data from this study subsequently became available[4) and the increases in activity were minimal. For instance, the baseline average for the group which received CBT was 67.9, which increased to 68.8 after treatment and to 72.2 at follow-up. About 4 points. Not unlike the medical care controls, who went from 64.9 to 68.7 in the same period.

One of the aims of CBT (for CFS) has been said to be "increased confidence in exercise and physical activity"[5]. Thus it may be the case that when asked questions about one's ability to do things, such as in the physical functioning subscale of SF-36 (one of the three primary outcome measures in the FINE Trial), the patients might say that they are "Limited A Little" or "Not Limited At All" but may be just as limited as patients in other arms of study who say "limited a lot".

The physical functioning subscale is the primary outcome measure that is also being used to measure "clinically significant improvement" ("An improvement of 50% or more on the SF-36 physical functioning scale, or a score of 75% or more on that scale, will be considered a clinically significant improvement"). It is not an objective instrument, particularly in a psychosocial trial.

In my two previous comments, I have criticised the use of the bimodal Chalder Fatigue Scale as an outcome measure in a trial of patients with "CFS/ME". Recently another trial[6] was published involving CFS patients in the UK. The mean score was not given but the median mark was 11. That is to say, at least 50% of the people scored the maximum mark before the intervention. These people can not "get worse" on the scale using the scale even if they feel worse.

The third and final primary outcome measure being used is a quality of life measure. Although it may be useful to measure the quality of life, the findings of a recent study[7] make for interesting reading. It used 73 patients, also with a diagnosis of CFS according to the Oxford criteria, from UK clinics. It involved using principal-component analysis to analyse various bits of questionnaire. The Principal-component analysis of all scale scores revealed 2 distinct components, explaining 53% of the total variance. The results are summarised in the following extract: "The perceived incapacity in fulfilling social and physical roles may be best captured by the subscales of the SF-36 on social and physical functioning. The scores on these subscales are associated with vitality and inversely with one of the defining symptoms of CFS, i.e. fatigue (Chalder Fatigue Scale, Fatigue Visual Analogue Scale). They are also associated with other physical symptoms (SDQ, SCL-90-R subscale ‘somatization’), but not with psychological symptoms such as depression (Beck Hopelessness Scale, SCL-90-R subscale ‘depression’) and anxiety (Spielberger Trait Anxiety Questionnaire, SCL-90-R subscale ‘anxiety’). These psychological symptoms are linked to a generic measure of quality of life (MANSA), reflecting satisfaction with life in general and life domains, and to emotional role functioning and mental health (SF-36, subscale)."

Of course, the instrument to measure quality of life is different in this study so the relevance of this study is unclear at this time. But like the other two outcome measures (Chalder Fatigue Scale and SF-36 PF), the Euroqol is subjective.

It is disappointing that there apart from checking for the presence or absence of the CDC criteria, there appears to be no measurement of other symptoms apart from fatigue. (And of course I've already pointed out the problems with using the bimodal Chalder Fatigue Scale e.g. it's hard for some patients to score "worse" scores using the scale). But most researchers do not think CFS = fatigue. Even if some patients have few other symptoms because the Oxford criteria is being used, this should not have mattered.

(contd.)

On 2014 Jan 09, Tom Kindlon commented:

Study confirms problems of using the 11-item bimodal Chalder Fatigue Scale as an outcome measure

(This was originally posted here http://www.biomedcentral.com/1741-7015/4/9/comments in 2008)

A study[1] has recently been published which confirms the problems 11-item bimodal Chalder Fatigue Scale I highlighted in my first comment[2].

In a group of 26 people with ME recruited from a local support group in England, it found a mean bimodal score of 9.81 (SD 2.04). Fifty per cent of the patients recorded the maximum score using the bimodal method and 77% recorded the two highest scores. The two questions which attracted the lowest scores and which were responsible for most of the variance were ‘do you feel sleepy or drowsy’ and ‘do you have problems starting things’. These are hardly crucial elements of CFS/ME.

References:

[1] Goudsmit EM, Stouten B, Howes S: Fatigue in Myalgic Encephalomyelitis. Bulletin of the IACFS/ME - Volume 16, Issue 3. http://tinyurl.com/3zcgw8 i.e. http://www.iacfsme.org/BULLETINFALL2008/Fall08GoudsmitFatigueinMyalgicEnceph/tabid/292/Default.aspx

[2] Kindlon Tom: Why is the 11-item bimodal Chalder Fatigue Scale being used as a primary outcome measure? http://www.biomedcentral.com/1741-7015/4/9/comments

On 2014 Jan 09, Tom Kindlon commented:

References:

[1] Stouten B: Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution. BMC Health Serv Res. 2005 May 13;5:37. http://www.biomedcentral.com/1472-6963/5/37

[2] Powell P, Bentall RP, Nye FJ, Edwards RHT: Randomised controlled trial of patient education to encourage graded exercise in chronic fatigue syndrome. BMJ 2001, 322:387-390.http://www.bmj.com/cgi/content/full/322/7283/387

[3] Jenkins M, Rayman M. Nutrient intake is unrelated to nutrient status in patients with chronic fatigue syndrome. Journal of Nutritional & Environmental Medicine, 2005, 15, 4, 177-189.

[4] Independent Working Group: A Report of the CFS/ME working group. Report to the Chief Medical Officer of an Independent Working Group. London: Department of Health; 2002.

[5] Action for ME & Association of Youth with ME Survey 2008. http://afme.wordpress.com/ (Accessed 31st May 2008)

[6] Action for ME Survey 2003.www.afme.org.uk/res/img/resources/AfME members survey.PDF (Accessed 31st May 2008)

On 2014 Jan 09, Tom Kindlon commented:

Why is the 11-item bimodal Chalder Fatigue Scale being used as a primary outcome measure?

(This was originally posted here http://www.biomedcentral.com/1741-7015/4/9/comments in 2008)

Stouten [1] has analysed some commonly used fatigue scales in the CFS area: the Chalder Fatigue Scale, the Checklist Individual Strength and the Krupp Fatigue Severity. He calculated the lower bound for the number and percentage of items with the maximum score for several studies and found that "extreme scoring" was common in studies in the field using these instruments. What is clear from this analysis is that the bimodal Chalder Fatigue Scale comes out worst in this regard.

Two of the authors of the current study should have been "intimately" aware of this problem as they were involved in one [2] of the two studies examined by Stouten [1] that used the 11-item bimodal Chalder Fatigue Scale. Here is the data from that study[2]: Baseline assessment for four intervention groups: Mean (95% Confidence Interval): 10.6 (10.4 to 10.9); 10.4 (10.0 to 10.7); 9.9 (9.2 to 10.6); 10.2 (9.9 to 10.6).

In percentage terms, this means that the lower bounds for the number of items with the maximum score for intervention groups were: 96%;95%;90%;93%. One can also calculate a lower bound for the percentage of patients who scored a maximum of 11 out of 11 for the items in the four intervention groups: 60%; 40%; 0%; 20%.

It should be remembered that these are lower bounds and the actual figure is likely to be higher (unless the authors give this data one can't calculate it from the mean). This can be illustrated by calculating the lower bound for the percentage of maximum (11 out of 11) scores for one study of an outpatient clinic in London[3] and comparing it to the actually percentage with the maximum score that was given. The Mean Score on the 11-item bimodal Chalder Fatigue Scale was 9.9. This translates to a lower bound for the percentage of patients who scored a maximum of 11 out of 11 of 0% (this could be achieved, for example, by 90% of the patients scoring 10/11 and 10% scoring 9/11). However the actual percentage of patients who scored the maximum (11/11) was 58%.

This shows that the 11-item bimodal Chalder Fatigue Scale doesn't just have a low ceiling for each individual question but also for the total score when applied to Chronic Fatigue Syndrome patients. Why is this important? Well, as the authors point out, some surveys of patient groups have found patients reporting being made worse by interventions such as Graded Exercise Therapy and Cognitive Behavioural Therapy (CBT).

For example, the results of a large survey with 2338 respondents were published in a report for the Chief Medical Officer[4]: it found that, of 285 who had done Cognitive Behavioural Therapy, 26% reported being made worse by the program, compared to 7% who said they were helped and 67% who said it made no difference. Of 1214 people who had done a graded exercise program, 50% had been been made worse by it (compared to 34% who said it helped and 16% who said it made no difference).These are not once-off results. For example, a recently published report of 2763 patients with ME or CFS in the UK[5] which asked about people's experiences of treatments over the last three years, found that of 699 who said they'd tried Graded Exercise Therapy, 34% said they'd been made worse by it compared to 45% who said they'd been helped and 21% who said it made no difference. The contention that people would not have being made worse by a treatment if they had done the treatment under specialist supervision, is not backed up by the data from this study[5]. Patients were asked who provided the GET treatment. Of the 567 who answered this question, 181 (31.92%) said it had made them worse compared to 276 (48.68%) who said it helped and 110 (19.40%) who said it made no difference; these are very similar percentages to the subgroup of 335 patients who had done the management strategy under an "NHS specialist": 111 (31.27%) of this group said they'd been made worse compared to 162 (45.63%) who said they'd been helped and 82 (23.10%) who said it made no difference. Again these don't appear to be once-off figures. In 2003, Action for ME did a smaller survey of 550 members asking about their experiences of Treatments[6]. 354 (64%) replied. The numbers for this study were small but if you combined the data from those who had done GET under a Physiotherapist, Occupational Therapist, Doctor or Behavioural Therapist, the results are: Negative 22 (56.41%) Neutral 2 (5.13%) Positive 15 (38.46%). [These don't compare favorably to the small group who did GET under no professional: Negative 1 (8.33%), Neutral 4 (33%) and Positive 7 (58%)]. A large percentage of the patients also reported being made by made worse by CBT in this study. Of 55 who had done CBT under a CBT Therapist/psychologist, Doctor/Psychiatrist, CPN/Other Mental Health, Counsellor/Psychotherapist, OT or Nurse specialist, 19 (34.55%) said it had made them worse compared to 24 (43.64%) who had been helped and 12 (21.82%) who said it made no difference.

The reason this is important is that if somebody already has a score of 11/11, they can't come up on the 11-item bimodal Chalder Fatigue Scale as being made worse on the treatment. Indeed, once they improved on one item, it would be marked as an improvement overall even if they actually felt worse on one or more of the other 10 items. Of course, this doesn't just apply to patients who score 11 out of 11; a patient could score 10/11 (say), feel worse on several items they'd already scored the maximum but come out as an improver once they improved on one idea. Saying all that, it would be good if the authors reported how many patients in each branch of the study scored the maximum.

Some of the items on the 11-item Chalder Fatigue Scale may also not be good as a measure of severity of CFS or ME. For example, somebody could be severe but not answer positively to the question, 'do you feel sleepy or drowsy'. Similarly a patient could disimprove and still not answer positively to this question. So a patient who scores 11 may not necessarily be more severely affected on a patient scoring 10. Saying all this, the generally very high scores (i.e. close to 11 on average) found in previous studies in the field suggest that the Likert method (0,1,2,3) of scoring does appear preferable. However it too also suffers from a ceiling effect although not to the same extent[1]. Also as previously pointed out, because of questions such as 'do you feel sleepy or drowsy', (which many if not most would feel are not intrinsic to Chronic Fatigue Syndrome or ME), even the likert version of the Chalder Fatigue Scale is not ideal for measuring severity of the condition.

On 2013 Nov 18, Lior Pachter commented:

The GeneMapper software is no longer supported or maintained.

On 2014 Nov 23, Harri Hemila commented:

A manuscript version is available at HDL

On 2016 Feb 18, Kristina Hanspers commented:

A version of the pathway in figure 6a is available in the "Open Access Publication" collection at WikiPathways: http://www.wikipathways.org/index.php/Pathway:WP2293. This pathway can be downloaded for use in network analysis tools such as Cytoscape and PathVisio.

On 2016 Oct 19, Richard Kunert commented:

The central claim of this paper is not supported by the numbers reported in the paper.

p. 142:

Participants exhibited the core personality features of psychopathy (Factor 1) to a greater extent than the core behavioral features of psychopathy (Factor 2).

In contradiction to this central claim of the paper, Factor 2 scores at 7.1 (the behavioural features of psychopathy) are actually higher than the Factor 1 scores at 5.2 (the personality features of psychopathy). The numbers tell the exactly opposite story to the words.

The numbers are given twice in the paper making a typo unlikely (p. 138 and p. 139). Adjusting the scores for the maxima of the scales that they are from (factor 1 x/xmax = 0.352 < factor 2 x/xmax=0.394) or the sample maximum (factor 1 x/xmaxobtained = 0.433 < factor 2 x/xmaxobtained = 0.44375) makes no difference. No outlier rejection is mentioned in the paper.

In sum, it appears as if DeMatteo and his co-authors interpret their numbers in a way which makes intuitive sense but which is in direct contradiction to their own data.

This issue was first raised publicly on Brain's Idea. The first author (DeMatteo) and the editor of the journal (Ewing) have been invited to respond via e-mail on 12/8/2016. Now, more than two months later, there is still no response.

On 2016 Nov 20, Morten Oksvold commented:

An investigation committee at Wayne State University (WSU) recommends that 42 articles from Fazlul Sarkar to be retracted (report finished August 31, 2015). This article represents one of them.

This information was published by Retraction Watch (November 17, 2016) and you can find a link to the full report here:

http://retractionwatch.com/2016/11/17/details-of-investigative-report-into-sarkar-released-by-aclu/

This article should therefore no longer be cited.

On 2014 Sep 15, Dr Yasmin Momin commented:

a rare event --intresting

On 2016 Nov 20, Morten Oksvold commented:

An investigation committee at Wayne State University (WSU) recommends that 42 articles from Fazlul Sarkar to be retracted (report finished August 31, 2015). This article represents one of them.

This information was published by Retraction Watch (November 17, 2016) and you can find a link to the full report here:

http://retractionwatch.com/2016/11/17/details-of-investigative-report-into-sarkar-released-by-aclu/

This article should therefore no longer be cited.

On 2015 Oct 29, Vinodh Srinivasasainagendra commented:

PowerAtlas web-application has a new URL http://poweratlas.ssg.uab.edu , which replaces our previous homepage http://www.poweratlas.org.

Thanks, PowerAtlas Team

On 2016 Jul 29, Noel O'Boyle commented:

I believe that the description of the structure as cyclo-(D-NMePhe-L-Leu-L-Ile-L-NMeTyr-L-Phe-NMeGly-L-Pro) is incorrect, as the convention is to write the residues from the N terminus to the C terminus. This is a cyclic peptide, and thus missing the terminii, but there is still a directionality from the N of a residue towards its carbonyl.

In short, to be consistent with the X-ray and structural depiction, I believe that it should be written instead as cyclo-(L-Pro-NMeGly-L-Phe-L-NMeTyr-L-Ile-L-Leu-D-NMePhe).

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2016 Aug 21, Morten Oksvold commented:

Please note that this article represents one of eleven publications which were found to contain false data, after an investigation led by ORI in 2015:

https://ori.hhs.gov/content/case-summary-dasmahapatra-girija

This article should therefor not be cited.

On 2014 Apr 24, Stuart RAY commented:

NOTE: Sequence features reported prominently in this report have been found in a subsequent report (http://www.ncbi.nlm.nih.gov/pubmed/21702696) to have been erroneous, due to alignment error and other issues.

On 2014 Nov 14, Robert Eibl commented:

This was the very first report on VLA-1 / VCAM-1 interactions measured at the single-molecule level with AFM and at the same time between two living mammalian cells. Two later AFM reports on VLA-4/VCAM-1 lack citation and discussion of my original work, although they were clearly induced or even initiated by myself; interestingly, my years of initiating and pioniering such AFM experiments as independent and unpaid guest PI and exclusive sharing of know-how was neither acknowledged, nor cited in related reviews.

On 2016 Jul 14, Pedro Reche commented:

This tool is now maintained at the Facultad de Medicina of the University Complutense of Madrid (http://imed.med.ucm.es/dachis/)

On 2013 Nov 24, John Sotos commented:

The death of “Mr. Abbott” (*) whose overlooked aortic dissection was misdiagnosed as an acute coronary syndrome, illuminates more than just the demise of the physical examination. It also illustrates Goethe`s precept “What one knows, one sees” (1).

A patient writhing because of chest pain should immediately be suspected to have aortic dissection (2)(3). Patients with chest discomfort due to coronary events more characteristically lie motionless (3), as noted in older (4), but not newer (5) cardiology textbooks.

Today`s highly specific imaging and biochemical tests have changed the role of physical examination from hypothesis confirmation to hypothesis generation. However, these tests have not, in the words of Dr. Joseph Bell (the model for Sherlock Holmes), changed the obligation of each physician to know “the features of disease… as precisely as you know the features, the gait, the tricks of manner of your most intimate friend” (3).

(*) Jauhar S. The demise of the physical exam. N Engl J Med. 2006; 354: 548-551.

(1) DeGowin RL. DeGowin & DeGowin`s Bedside Diagnostic Examination. 5th ed. New York: Macmillan, 1987; 37.

(2) Slater EE. Aortic dissection: presentation and diagnosis. In: Doroghazi RM, Slater EE, Aortic Dissection. New York: McGraw-Hill, 1983; 62.

(3) Sotos JG. Zebra Cards. Philadelphia: American College of Physicians, 1989; page 19 and card HE-011.

(4) Pasternak RC, Braunwald E, Sobel BE. Acute myocardial infarction. In: Heart Disease. 3rd ed. Braunwald E (ed.). Philadelphia: WB Saunders, 1988; 1235.

(5) Antman EM, Braunwald E. Acute myocardial infarction. In: Heart Disease. 5th ed. Braunwald E (ed.). Philadelphia: WB Saunders, 1997; 1198.

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2014 Nov 23, Harri Hemila commented:

A comment on the study is available at: http://hdl.handle.net/10250/8081

On 2016 Feb 01, Raphael Levy commented:

I have written a blog post where I identify this influential article (cited 5000 times) as one that introduces the (misleading) idea that nanoparticles can "penetrate cell membrane". Comments very much welcome, here or at the blog:

NANOPARTICLES & CELL MEMBRANES: HISTORY OF A (SCIENCE) FICTION? https://raphazlab.wordpress.com/2016/02/01/nanoparticles-cell-membranes-history-of-a-science-fiction/

On 2016 Jan 05, Morten Oksvold commented:

Please note that this article contains fraudulent data, which was concluded from an investigation by the University of Alabama at Birmingham in 2009 (!):

http://www.uab.edu/reporterarchive/71570-uab-statement-on-protein-data-bank-issues

The case was recently discussed at Retraction Watch: http://retractionwatch.com/2016/01/04/nature-retracts-paper-six-years-after-it-was-flagged-for-fraud/

PNAS was informed about this case in 2009, but as far as I can see there has still not been published any retraction. In light of the fact that this single article has been cited more than 40 times since 2009, and all the wasted work and resources, correction of the literature is highly important.

On 2016 Feb 12, Daniel Schwartz commented:

This tool can be used online and in mobile apps here:

https://qxmd.com/calculate/mayo-early-screen-for-discharge-planning

Conflict of interest: Medical Director, QxMD

On 2015 Oct 27, Peter Gøtzsche commented:

This review concludes that, “The three cholinesterase inhibitors are efficacious for mild to moderate Alzheimer’s disease.” I believe these drugs don’t work. The improvement in cognitive function was 2.7 points, in the midrange of a 70-point scale. This is less than the 4 points the FDA considers the minimally relevant clinical chan¬ge (1). We can also compare with the smallest effect that can be per¬ceived on the Hamilton scale for depression, which is 5-6 (2), although the maximum on this scale is only 52.

The placebo controlled trials have not been effectively blinded, as cholinesterase inhibitors have conspicuous side effect. This lack of blinding can in itself easily have caused the very minor effect that was noted in the trials (3).

A long-term trial of 565 patients with mild to moderate Alz¬heimer’s disease that compared donepezil with placebo found no meaningful effects whatsoever, and the authors concluded that do¬nepezil isn’t cost-effective, with benefits below minimally relevant thresholds (4). In contrast to other trials, it was publicly funded. This trial was excluded from the Cochrane review, for no good reason, as far as I can see. The outcomes after three years were similar on drug and placebo with respect to institutionalisation, progression of disability, and behavioural and psychological symptoms.

The author of the Cochrane review wrote that “donepezil appears to have no serious or common side effects.” This sentence is highly misleading. The harms are both common and serious, and she documents in her review that 29% of the patients left the drug group on account of adverse events, as compared to only 18% in the placebo groups. The most common side effects of donepezil are nausea, diarrhoea, not sleeping well, vomiting, muscle cramps, feeling tired, and not wanting to eat. I believe this is not what we would want for an old person who might already have problems with not sleeping well, feeling tired, and not wanting to eat.

The list of frequent side effects in Pfizer’s product information for Aricept (donepezil) is very long (5). Hypotension and syncope occurs in more than 1% and when old people fall, there is a considerable risk that they break their hip and die. A large Canadian cohort study showed that people who took anti-dementia drugs had almost a doubled risk of hospitalisation for syncope compared to demented people who didn’t take these drugs, and they had more pacemakers inserted and more hip fractures (6). Most astonishingly, more than half the patients who were admitted to hospital for bradycardia were retreated with the drug.

There are many good reasons not to use anti-dementia drugs.

1 Molnar FJ, Man-Son-Hing M, Fergusson D. Systematic review of measures of clinical significance employed in randomized controlled trials of drugs for de¬mentia. J Am Geriatr Soc 2009;57:536-46.

2 Leucht S, Fennema H, Engel R, et al. What does the HAMD mean? J Affect Disord 2013;148:243-8.

3 Gøtzsche PC. Deadly psychiatry and organised denial. Copenhagen: People’s Press; 2015.

4 Courtney C, Farrell D, Gray R, et al. Long-term donepezil treatment in 565 patients with Alzheimer’s disease (AD2000): randomised double-blind trial. Lancet 2004;363:2105-15.

5 ARICEPT ® (donepezil hydrochloride) tablets. http://labeling.pfizer.com/ShowLabeling.aspx?id=510.

6 Syncope with cholinesterase inhibitors. Rev Prescrire 2011;31:434.

On 2014 Jan 09, Andrew Brown commented:

This article was corrected in 2006, but does not appear to be linked in PubMed. Correction: Are fast food restaurants an environmental risk factor for obesity? http://www.ijbnpa.org/content/pdf/1479-5868-3-35.pdf

On 2016 Nov 20, Morten Oksvold commented:

An investigation committee at Wayne State University (WSU) recommends that 42 articles from Fazlul Sarkar to be retracted (report finished August 31, 2015). This article represents one of them.

This information was published by Retraction Watch (November 17, 2016) and you can find a link to the full report here:

http://retractionwatch.com/2016/11/17/details-of-investigative-report-into-sarkar-released-by-aclu/

This article should therefore no longer be cited.

On 2015 Jan 21, Anders von Heijne commented:

We have just seen a case (young woman;in Stockholm, Sweden) with the exakt same type of vascular malformation and no obvious etiology, but with episodes of left sided pleuritic pain.

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2018 Jan 08, Alexander Kraev commented:

Please note that this is a peculiar case of retraction, since while there are indeed problems with certain images, the authors stated the following in the retraction notice: "Nevertheless, although we feel that the scientific conclusions of the paper (that loss of NNT impairs insulin secretion and impairs glucose tolerance in C57BL/6J mice) still stand, given the conclusion of scientific misconduct against the first author, the authors think the most responsible course is to retract the paper." It is important to understand that nuance especially in view that thousands of publications state that they used "C57BL6" without making a crucial distinction between C57BL/6J and C57BL/6N.

On 2016 Dec 15, Jim Stewart commented:

Please note, this article has been retracted. The "full text" link will take you to the retraction notice.

On 2016 Mar 29, Jonathan Wren commented:

URL relocated: http://www.genenames.org/

On 2017 Dec 23, Adriano Aguzzi commented:

If anything, it should read "E uno plures".

On 2014 May 06, John Roger Andersen commented:

Green Open Access to the authors final version: click here.

On 2014 Oct 12, EDWARD BERRY commented:

The structure of the 3NPA-Arg adduct proposed here has been confirmed in the case of E. coli fumarate reductase, and a mechanism for its formation has been proposed, by Tomasiak et al. (J Biol Chem. 2011 286:3047-56) Pubmed ID 21098488 . Correction: The heterocyclic ring of carboxin is modeled with the wrong orientation in 2fbw, shown in Figure 6 here. Ruprecht et al.(J Biol Chem. 2009 284:29836-46) PMID 19710024. have deposited a corrected structure as 2wqy. The original authors agree with this correction as indicated here. Edward A. Berry 21:52, 21 May 2014 (IDT)

On 2015 Aug 27, Bernard Friedenson commented:

For more information please see the article entitled "Mutations in Breast Cancer Exome Sequences Predict Susceptibility to Infection and Converge on the Same Signaling Pathways" This article is available at http://la-press.com/article.php?article_id=5029

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2014 Jun 01, Ivan Oransky commented:

This paper has been retracted: http://retractionwatch.com/2014/05/27/oncology-researcher-getzenberg-notches-seventh-retraction/

On 2016 Jul 21, Tom Kindlon commented:

Another study raises serious questions about the use of the role emotional subscale of the SF-36 in the diagnosis of CFS

A CDC group (Reeves et al (2005)) proposed a way to operationalise chronic fatigue syndrome (CFS) criteria including subscales of the SF-36[1,2]: "We defined substantial reduction in occupational, educational, social, or recreational activities as scores lower than the 25th percentile of published US population [] on the physical function (≤ 70), or role physical (≤ 50), or social function (≤ 75), or role emotional (≤ 66.7) subscales of the SF-36." This method has been used in numerous subsequent CDC CFS studies but not by external groups, apart from Leonard Jason and colleagues who have examined the effect of this operationalisation of the criteria.

A newly published study looked at using the SF 36 subscales to define reduced activity in CFS (and ME)[3]. Six of the 8 subscales (Physical Functioning, Role-Physical, Bodily Pain, General Health, Vitality and Social Functioning) correlated with the sum of current hours of activity. Two subscales did not correlate (Role-Emotional and Mental Health).

The same 6 subscales (negatively) correlated with percentage reduction in the total hours of activity. Again, two subscales did not correlate (Role-Emotional and Mental Health).

Also, a "ROC analysis was used to assess which of the SF-36 subscales best discriminated between patients with ME and CFS and healthy controls. The ROC analysis used a plot of sensitivity versus 1-specificity for scores on the SF-36. The area under the curve (AUC) assessed the degree to which each subscale was able to discriminate between patients and controls. The closer the AUC is to 1, the better discriminatory power that SF-36 subscale has." The same 6 subscales (Physical Functioning, Role-Physical, Bodily Pain, General Health, Vitality and Social Functioning) had AUCs of 0.89 or better. By comparison, the Mental Health Functioning subscale had a AUC of 0.59. The AUC for the Role Emotional subscale was even worse at 0.47.

Each of these results demonstrates that the Role Emotional subscale is not suitable to be used to operationalise criteria for CFS.

References:

[1] Reeves WC, Wagner D, Risenbaum R, et al. Chronic fatigue syndrome – a clinically empirical approach to its definition and study. BMC Med. 2005;3(19):1–9.

[2] Ware JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36): conceptual framework and item selection. Med Care. 1992;30:473–483

[3] Thorpe T, McManimen S, Gleason K, Stoothoff J, Newton J, Strand EB, Jason LA (2016). Assessing current functioning as a measure of significant reduction in activity level. Fatigue: Biomedicine, Health & Behavior. Published online: 19 Jul 2016 doi: 10.1080/21641846.2016.1206176

On 2014 Feb 28, Tom Kindlon commented:

Using two MFI scales ("General Fatigue" or "Reduced Activity") to ensure patients satisfying the definition have "severe fatigue"

(This was originally posted here http://www.biomedcentral.com/1741-7015/3/19/comments#304567 but the formatting has gone from that page)

Initially when I read this paper, where it says "we defined severe fatigue as >= medians of the MFI general fatigue (>=13) or reduced activity (>=10) scales", I thought this referred to medians of the general population.Hearing other people commenting on it, that's how some other people have been interpreting it also. It is probably somewhat natural to do this as the sentence before reads: "We defined substantial reduction in occupational, educational, social, or recreational activities as scores lower than the 25th percentile of published US population [11] on the physical function (<=70), or role physical (<=50), or social function (<=75), or role emotional (<=66.7) subscales of the SF-36."

However from looking at the scores for controls in other papers, these MFI scores do not look like medians for the whole US population but in fact are medians for this particular group of patients. This seems a strange way to set cut-off points for a CFS definition that is used for numerous studies into the illness, given the cohort that is being used as a basis: "This population-based case control study enrolled 227 adults identified from the population of Wichita with: (1) CFS (n = 58); (2) non-fatigued controls matched to CFS on sex, race, age and body mass index (n = 55); (3) persons with medically unexplained fatigue not CFS, which we term ISF (n = 59); (4) CFS accompanied by melancholic depression (n = 27); and (5) ISF plus melancholic depression (n= 28)." i.e. this is not a random sample of the US population but a group of people selected for a specific purpose (or purposes) (not necessarily to design a definition, but as a follow-up study of people previously diagnosed with CFS or given some other label).

Some of the groups are of different sizes - if the relative size of these groups had been changed, with relatively more people taken from some classification groups and less people taken from other groups, the median scores would likely have been different.

It should also be remembered that in this context the categories listed in the last paragraph refer to their classification when they evaluated years before (from 1997 to 2000), and not necessarily at the time when they were evaluated in this study (December 2002 to July 2003) (as is clear from the tables in this paper).

I thought it would be interesting to look at MFI scores in some other papers on CFS that did not use the "empirical definition".

I don't claim this is a definitive list but, at the same time, mean MFI scores with standard deviations only seem to be listed in a small percentage of papers. The papers use cohorts from a variety of locations: England [3], The Netherlands [4], Germany [5] and the USA (New Jersey) [6]. I did not see any ranges given which would be useful given the task at hand (selecting cut-off points for a definition).Unfortunately not all of the papers I found used the Fukuda [1] definition for CFS; some also used the Sharpe [2] definition for CFS. I indicate which definition is used in each case.

MFI: General Fatigue (i) Sample/(ii) Sample Size/(iii) Mean/(iv) SD/ (v) (Mean - 13)/SD/ (vi) Definition

Weatherley-Jones [3] 53 18.4 1.7 3.176470588 Sharpe (1991)

Vermeulen (Group 1) [4] 30 18.6 1.9 2.947368421 Fukuda (1994)

Vermeulen (Group 2) [4] 30 18.4 1.8 3 Fukuda (1994)

Vermeulen (Group 3) [4] 30 19.1 1.4 4.357142857 Fukuda (1994)

Gaab [5] 21 17.7 0.5 9.4 Sharpe (1991) and Fukuda (1994)

Brimacombe [6] 65 18.41 2.02 2.678217822 Fukuda (1994)Combining these give a sample of 229 patients with a mean "General Fatigue" score of 18.45655022.

This data suggests that a threshold of >=13 will have a very very high sensitivity. This would suggest that another measure would not be necessary (unless it was being used as an extra criterion to increase the specificity, which isn't done with this definition).

However for completeness, I'm including the "Reduced Activity" data from the same papers:Reduced activity (MFI) (i) Sample / (ii) Sample Size / (iii) Mean Score / (iv) SE (v) (Mean-10)/SD (vi) Definition

Weatherley-Jones [3] 53 16.1 3.1 1.967741935 Sharpe(1991)

Gaab [5] 21 15 0.7 8.714285714 Sharpe (1991) and Fukuda(1994)

Brimacombe [6] 65 15.93 4.55 1.340659341 Fukuda 1994

Combining these give a sample of 139 patients with a mean Reduced Activity score of 15.85431655.

Note: the Vermeulen paper[4] did not collect the MFI scores for Reduced Activity, just "the fatigue axes of the Multidimensional Fatigue Inventory" (which they defined as the MFI scores for General fatigue, Physical fatigue, Mental fatigue).

It seems strange in the definition of Chronic Fatigue Syndrome defined in this paper (i.e. Reeves et al) that the "severe fatigue" criterion can be satisfied by a patient having a low score on a subscale of the MFI testing activity levels (as opposed to one of the 3 subscales measuring fatigue), especially when the function of the SF-36 is to "measure functional impairment". Just because someone is inactive doesn't mean they have severe fatigue. Allowing patients to be included if they simply have a "Reduced Activity" score of 10 or more (without necessarily having a low score on one of the fatigue axes of the MFI) risks reducing the specificity of the definition.

References:

[1] Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. The chronic fatigue syndrome; a comprehensive approach to its definition and study. Ann Int Med 1994, 121:953-959.

[2] Sharpe MC, Archard LC, Banatvala JE, Borysiewicz LK, Clare AW, David A, Edwards RH, Hawton KE, Lambert HP, Lane RJ, et al. A report--chronic fatigue syndrome: guidelines for research. J R Soc Med. 1991 Feb;84(2):118-21.

[3] Weatherley-Jones, E., Nicholl, JP., Thomas, KJ., Parry, GJ., McKendrick, MW., Green, ST., Stanley, PJ and Lynch, SPJ. A randomised, controlled, triple-blind trial of the efficacy of homeopathic treatment for chronic fatigue syndrome. Journal of Psychosomatic Research, 2004, 56, 2, 189-197.

[4] Vermeulen, RCW and Scholte, HR. Exploratory open label, randomized study of acetyl- and propionylcarnitine in chronic fatigue syndrome. Psychosomatic Medicine, 2004, 66, 276-282.

[5] Gaab J, Hüster D, Peisen R, Engert V, Heitz V, Schad T, Schürmeyer TH, Ehlert U. Hypothalamic-pituitary-adrenal axis reactivity in chronic fatigue syndrome and health under psychological, physiological, and pharmacological stimulation.Psychosom Med. 2002 Nov-Dec;64(6):951-62.

[6] Brimacombe, Michael; Lange, Gudrun; Bisuchio, Kim; Ciccone, Donald S.; Natelson, Benjamin. Cognitive Function Index for Patients with Chronic Fatigue Syndrome Journal of Chronic Fatigue Syndrome, 2004, vol 12; number 4, pages 3-24

On 2014 Feb 28, Tom Kindlon commented:

Why is this definition being referred to as an "empirical definition"?

(This was originally posted here http://www.biomedcentral.com/1741-7015/3/19/comments#301566 but the formatting has gone from that page)

I believe most people's understanding of "empirical criteria" or an "empirical definition" would be that the data would speak for itself; it "would decide" the cut-off points through methods such as cluster analysis (for example).

Indeed this would seem to have been William Reeves' understanding of an empirical definition. For example, in a presentation on the CDC's CFS research program (to a Task Force Meeting on the Epidemiology of Interstitial Cystitis)[1], he said: "The problem with the CFS criteria was that they were not specific enough and not empiric-based. For example, one of the criteria stated that the research subject must have at least four of eight symptoms, among them, impaired concentration or memory and postexertional worsening of physical or mental fatigue. "The accompanying symptoms need to be defined in and of themselves," Dr. Reeves said.

The 1994 International Study Group also hypothesized that fatigue led to patients' symptoms rather than the reverse. The CDC is currently conducting population studies to develop an empiric definition of CFS that is based on statistical modeling."At the inaugural meeting of the US Department of Health and Human Services' Chronic Fatigue Syndrome Advisory Committee (CFSAC), Dr Reeves said the CDC team of research would "derive an empirical case definition based on data".[2]

The definition presented here does not seem to have been based either on "statistical modeling" or "data". It seems to involve relatively arbitrary cut-off points; for example, of the 8 subscales of the SF-36, four are chosen and, for each of these, the 25th percentile of the published US population is chosen as a cut-off point. A patient is required to be in the bottom quartile for just one of these subscales to satisfy the criteria. Where did this cut-off point come from? There is no mention of it in the paper that suggested the use of the SF-36[3]; nor is there any mention that these particular subscales should be chosen or that one would be sufficient. One of the authors of the paper[3] has confirmed that cut-off points were never chosen nor was it decided which sub-scales would be used.

Given that the CDC's definition of CFS tends to go on to be used in numerous studies, would it not be better to investigate which thresholds give a "better" definition e.g. with a higher specificity and sensitivity - for example, for some of the SF-36 subscales, perhaps (say) the 13th, 15th, 20th or even 30th percentiles may be more appropriate.

The cut-off points suggested in this paper may or may not be useful. But is it really accurate to suggest that they are "empirically" derived?

References:

[1] Epidemiology of Interstitial Cystitis - Executive Committee Summary and Task Force Meeting Report October 29th, 2003. http://www.niddk.nih.gov/fund/reports/ic/task_force_summary.pdf

[2] US Department of Health and Human Services - Chronic Fatigue Syndrome Advisory Committee (CFSAC). Inaugural Meeting. September 29th, 2003Meeting Summary. http://www.hhs.gov/advcomcfs/CSFAC_mins_2003.09.29R.pdf

[3] Reeves WC, Lloyd A, Vernon SD, Klimas N, Jason LA, Bleijenberg G, Evengard B, White PD, Nisenbaum R, Unger ER, International Chronic Fatigue Syndrome Study Group: Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution. BMC Health Services Research 2003, 3:25

On 2014 Feb 28, Tom Kindlon commented:

This may not be a representative group of those who would be diagnosed in a random sample using the "standardized clinically empirical criteria"

(This was originally posted here http://www.biomedcentral.com/1741-7015/3/19/comments#290587 but the formatting has gone from that page)

This "empirical" method of operationalizing the CDC 1994 CFS criteria[1] has subsequently been used in a population study[2]. It found a prevalence rate for CFS of 2540 per 100,000 persons 18 to 59 years of age[2].

This is considerably higher than the prevalence rates found in earlier studies.

For example, a previous study using this cohort using a "previous" method of operationalizing the CDC 1994 CFS criteria[1] found a prevalence rate of 235 per 100,000[3]. Given the way the cohort in this current study was drawn up, using 58 people who had previously been diagnosed using a "previous" method of operationalizing the CDC 1994 CFS criteria, the group satisfying the new method of operationalizing the CDC 1994 CFS criteria, the "empirical" criteria, in this study may well not be the same sort of people that would show up if the method was used on a random sample of the population. So for example the results in Table 6 may not be similar to the results one can get in a random sample.

Unfortunately the paper giving the prevalence rate for Georgia[2] does not give the same pieces of information as is in Table 6 in this study. However we do have a paper which uses a group from the Georgia cohort[4]. Table 1 of this study[4] includes similar data. Some of the numbers are somewhat similar. However one that particularly stands out is the Role Emotional score. It was 35.6 (95% CI: 26.3-44.8). That compares to the value in this paper of 55.8+/-42.2.

Perhaps other data will be published in time. The main point of this comment is to point out or remind people that the data presented in this paper may not be representative of those that would be diagnosed using the empirical criteria.

References:

[1] Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, & Komaroff A. (1994). The chronic fatigue syndrome: A comprehensive approach to its definition and study. Annals of Internal Medicine, 121 (12):953-959. http://www.annals.org/cgi/content/full/121/12/953

[2] Reeves WC, Jones JF, Maloney E, Heim C, Hoaglin DC, Boneva RS, Morrissey M, Devlin R. Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia. Population Health Metrics 2007, 5:5 doi:10.1186/1478-7954-5-5http://www.pophealthmetrics.com/content/5/1/5

[3] Reyes M, Nisenbaum R, Hoaglin DC, Unger ER, Emmons C, Randall B, Stewart JA, Abbey S, Jones JF, Gantz N, Minden S, Reeves WC: Prevalence and incidence of chronic fatigue syndrome in Wichita, Kansas. Arch Int Med 2003, 163:1530-1536.

[4] Nater UM, Maloney E, Boneva RS, Gurbaxani BM, Lin JM, Jones JF, Reeves WC, Heim C. Attenuated Morning Salivary Cortisol Concentrations in a Population-based Study of Persons with Chronic Fatigue Syndrome and Well Controls. J Clin Endocrinol Metab. 2007 Dec 26

On 2014 Feb 21, Tom Kindlon commented:

Data from another population study found scores on the RE subscale are similar in CFS patients to those found in healthy controls

(This was originally posted here http://www.biomedcentral.com/1741-7015/3/19/comments#285575 but the formatting has gone from that page)

I previously said that I questioned the value of using the Role Emotional (RE) subscale to satisfy functional impairment criteria (http://www.biomedcentral.com/1741-7015/3/19/comments#284561). Researchers deciding whether to follow the method of operationalizing the Fukuda [1] used in this study, might be interested at looking at Table 2 in Jason et al [2].

The subjects were also obtained from a random-digit population study. Here is what the authors said in the text on this part of the results: "A MANCOVA for the Medical Outcomes Study SF-36 Health Survey (controlling for the effects of work status) revealed significant differences in gradations of disability across the diagnostic categories of CFS only, MCS only, FM only, more than one diagnosis, and no diagnosis on seven of the eight subscales (F(4,208) = 1.82, p < .05). The role-emotional scale was the only scale that did not reveal significant differences between the groups (see Table 2). Significant post hoc tests revealed that individuals with CFS demonstrated greater disability than those with no diagnosis on the role-physical; bodily pain; vitality; and social functioning scales. Individuals with MCS demonstrated greater disability than the no diagnosis group on the physical functioning; role-physical; bodily pain; general health; vitality; social functioning; and mental health scales. Individuals with FM demonstrated greater disability than the no diagnosis group on the physical functioning; role-physical; bodily pain; and social functioning scales. In addition, individuals with more than one diagnosis demonstrated greater disability than those in the no diagnosis group on the physical functioning; role-physical; bodily pain; vitality; and social functioning scales. Means for each of the Medical Outcomes Study subscales are reported in Table 2."

This issue of how the Fukuda criteria [1] are operationalized is not a trivial matter. Using the previous method of operationalizing the criteria, a CDC team found a prevalence for CFS of 235 per 100,000 [3]. Using the method of operationalizing the criteria outlined in this study, the prevalence rate for CFS was found to be 2.54% or 2540 per 100,000 [4] or 10.81 times the previous prevalence rate!

References

[1] Fukuda, K., Straus, S.E., Hickie, I., Sharpe, M.C., Dobbins, J.G., & Komaroff, A. (1994). The chronic fatigue syndrome: A comprehensive approach to its definition and study. Annals of Internal Medicine, 121 (12):953-959. http://www.annals.org/cgi/content/full/121/12/953

[2] Jason, L.E., Taylor, R.R., & Kennedy, C.L. "Chronic Fatigue Syndrome, Fibromyalgia, and Multiple Chemical Sensitivities in a Community-Based Sample of Persons With Chronic Fatigue Syndrome-Like Symptoms." Psychosomatic Medicine 62:655-663 (2000). http://www.psychosomaticmedicine.org/cgi/reprint/62/5/655

[3] Reyes M, Nisenbaum R, Hoaglin DC, Unger ER, Emmons C, Randall B, Stewart JA, Abbey S, Jones JF, Gantz N. Prevalence and incidence of chronic fatigue syndrome in Wichita, Kansas. Arch Intern Med. 2003;163:1530–1536. doi: 10.1001/archinte.163.13.1530.

[4] Reeves WC, Jones JF, Maloney E, Heim C, Hoaglin DC, Boneva RS, Morrissey M, Devlin R. Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia. Population Health Metrics 2007, 5:5 doi:10.1186/1478-7954-5-5

On 2014 Feb 21, Tom Kindlon commented:

MDDm should be resolved for more than 5 years before a CFS diagnosis can be given

(This was originally posted here http://www.biomedcentral.com/1741-7015/3/19/comments#285572 but the formatting has gone from that page)

In this paper, it says: "Following recommendations of the International CFS Study Group, only current MDDm was considered exclusionary for CFS." However, part of the specific recommendations of the International CFS Study Group [1] was that MDDm had to have been resolved for more than 5 years: "The 1994 case definition stated that any past or current diagnosis of major depressive disorder with psychotic or melancholic features, anorexia nervosa, or bulimia permanently excluded a subject from the classification of CFS ... we now recommend that if these conditions have been resolved for more than 5 years before the onset of the current chronically fatiguing illness, they should not be considered exclusionary." It might not be important to point this out for definitions for some illnesses: however if one looks at table 2, 6 of the 16 who are said to have CFS using the "current classification" of CFS, had been diagnosed with MDDm at a previous assessment which suggests it is important in this context.

Reference:

[1] Reeves WC, Lloyd A, Vernon SD, Klimas N, Jason LA, Bleijenberg G, Evengard B, White PD, Nisenbaum R, Unger ER, International Chronic Fatigue Syndrome Study Group: Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution.BMC Health Services Research 2003, 3:25. http://dx.doi.org/10.1186/1472-6963-3-25

On 2015 Feb 23, Ivan Oransky commented:

Although this paper has been retracted, it has been cited 52 times since, with only two of those citations mentioning the retraction: http://retractionwatch.com/2015/02/18/evidence-scientists-continue-cite-retracted-papers/

(Deleted first of these comments as they posted twice.)

On 2015 Feb 23, Ivan Oransky commented:

None

On 2013 Nov 15, George McNamara commented:

The direct link to the supplemental files is http://bloodjournal.hematologylibrary.org/content/107/7/2643/suppl/DC1 The supplemental files includes two movies. My rule of thumb is you should make popcorn before watching movies.

An additional movie from this project is available at http://works.bepress.com/gmcnamara/21/ Shows a triplet cell division. That is, a cell that divided three ways. I have discussed this with other researchers, a few of whom have observed triplet cell divisions as well.

Several of the authors have moved from City of Hope - Mike Jensen is in Seattle. I am with Laurence Cooper at M.D. Anderson Cancer Center in Houston.

On 2014 Oct 14, GEORGE ANDERSON commented:

The paper that Dr. Carter comments on should have been retracted 9 years ago. The urinary oxytocin (and AVP) data that provide the foundation of the research are fundamentally flawed, with the reported values being approximately one million times higher than prior (and subsequent) reports (see Anderson GM. Report of altered urinary oxytocin and AVP excretion in neglected orphans should be reconsidered. Journal of Autism and Developmental Disorders, 36:829-30, 2006). This was NOT due to a simple error in calculation or a misplaced decimal points. Rather, the analytical method used was non-specific. At the time, the authors defended their results as accurate and even provided some mass spectral data purporting to show that they were indeed measuring correct amounts of urinary oxytocin. In more recent research they have used a more specific method and now obtain results consistent with all other published work. However, they continue to reference this paper without mentioning the huge discrepancy. The paper and any of its conclusions should be disregarded. Just as regretable as the continued presence in the literature and continued citing of this misleading research is the fact that the editiorial board of PNAS has not seen fit to perform the retraction which is a necessary part of self-correcting science. This latter fact reflects very poorly on all papers published in PNAS as there does not seem to be any standard or threshold for retraction; the low quality of review that the paper received in the first place is also not reassuring when considering how much credence to give PNAS papers.

On 2015 Mar 12, Ivan Oransky commented:

This paper has been retracted, the second retraction from the group: http://retractionwatch.com/2015/03/12/second-cell-bio-retraction-from-upitt-investigation-of-tweaked-images/

On 2014 Feb 25, Jim Woodgett commented:

[This entry is incorrectly cited by PubMed. The correct page numbers are 10992-11000.]

Nevermind - It's the correct shortening/abbreviation 10992-1000. Looks odd but is correct. My mistake. Thanks @clathrin @michaelhoffman

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2014 Oct 13, Ivan Oransky commented:

This paper has been subjected to a significant correction for duplicate publication: http://retractionwatch.com/2014/10/09/u-illinois-chancellor-earns-mega-correction-for-duplicate-publication/

On 2013 Dec 30, Mike KLYMKOWSKY commented:

the "text" link points to a completely unrelated paper

On 2015 Dec 11, Harri Hemila commented:

Available at http://dx.doi.org/10.1016/0378-1119(92)90625-Y

On 2016 Aug 19, Morten Oksvold commented:

Please note that this article has been retracted and should therefore not be cited in the future:

"The above article and associated erratum, published online on 11 November 2005 and 6 February 2014, respectively, in Wiley Online Library (wileyonlinelibrary.com), have been retracted by agreement between the authors, the journal Editor-in-Chief, Professor Peter Lichter, and Wiley Periodicals, Inc. In addition to what was corrected in the erratum, a university investigation involving the first and the corresponding author determined that several figures in this paper were re-used, mislabeled, manipulated, or duplicated while processing/compiling the final figures assembled from the original data sources. Therefore, the authors are retracting the paper in its entirety although they maintain that these issues did not affect the major conclusions. They apologize for any inconvenience this may have caused".

Link: http://onlinelibrary.wiley.com/doi/10.1002/ijc.30267/full

On 2015 Jul 16, Bill Cayley commented:

A good example of when a "less-medical" approach is better: https://lessismoreebm.wordpress.com/2015/07/16/nonsurgical-management-of-partial-adhesive-small-bowel-obstruction-with-oral-therapy-a-randomized-controlled-trial/

On 2015 Nov 18, Diana Petitti commented:

Reviewing articles about vitamin D and falls, I discovered that, while the abstract states that this was a randomized, placebo-controlled trials of vitamin D to prevent falls, all subjects were prescribed 600 mg of elemental calcium in the form of calcium carbonate (p. 1182). Thus, the trial was a randomized trial of vitamin D plus calcium versus calcium alone.

On 2013 Oct 28, DAVID SANDERS commented:

See the earlier articles "Sulfhydryl involvement in fusion mechanisms" [2000]Sanders DA, 2000 and "Ancient viruses in the fight against HIV" [2003] Sanders DA, 2003 for the prediction of the results published here.

On 2014 Aug 18, Nicholas J L Brown commented:

cf. http://www.ncbi.nlm.nih.gov/pubmed/23855896

On 2016 Aug 21, Morten Oksvold commented:

Please note that this article represents one of eleven publications which were found to contain false data, after an investigation led by ORI in 2015:

https://ori.hhs.gov/content/case-summary-dasmahapatra-girija

This article should therefor not be cited.

On 2017 Jan 05, Pablo Tamayo commented:

A key aspect of the Gene Set Enrichment Analysis (GSEA) approach is the preservation of gene-gene dependency in estimating the significance of enrichment (i.e., coordinate expression) of a set of genes. Because we know that genes are not independent variables, modeling dependencies as done by GSEA better mirrors the underlying biology of the systems we seek to study. While simpler statistical tests may reduce computational complexity, they do so at the expense of making unrealistic assumptions not supported by the data. In our response (http://www.ncbi.nlm.nih.gov/pubmed/23070592) to the claims in http://www.ncbi.nlm.nih.gov/pubmed/20048385 we carefully considered the assumptions of the proposed “simplified” SEA method and its results. This included a comparative analysis on a large collection of 50 benchmarks. By randomizing phenotypes, we showed that gene-gene correlations produce significant variance inflation in SEA results, which in turn produce very high false positive rates and inflated p- and q-values, while GSEA does not. These results provide strong empirical evidence that gene-gene correlations cannot be ignored and agree with the extensive literature providing theoretical or empirical evidence against the gene independence assumption. See, e.g., https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3091509/ https://www.ncbi.nlm.nih.gov/pubmed/16646853 https://www.ncbi.nlm.nih.gov/pubmed/17303618

On 2013 Nov 12, James Hadfield commented:

Who would run a differential gene expression experiment today and NOT look at gene set enrichment analysis? It is difficult to remember the impact this paper had on the field and what we were doing just five years earlier with the first microarrays!

On 2013 Jun 28, Rafael Irizarry commented:

I agree with Rob that this is an important paper. The idea of analyzing differential expression for groups of genes, as opposed to individual genes, was an important step forward in the analysis of gene expression data. In one of the papers Rob links to we point out that the method would have worked just as well (or perhaps better) using simple (existing) statistical tests rather than the novel versions of the KS-test presented in the paper. Examples of some of these simpler tests are implemented in the Bioconductor limma package. The critique is not just about power, but about interpretability and ease of implementation. But these critiques should not take away from the important contribution made by this paper.

On 2013 Jun 16, Robert Tibshirani commented:

This is an important paper, one that introduced the idea of analyzing the differential expression of groups of genes, rather than individual genes. The advantage is both in power and interpretability. Importantly, this group has also created and curated an impressive collection of gene sets for this purpose. See http://www.broadinstitute.org/gsea/index.jsp

The particular test here- the KS statistic- has been criticized for lack of power and alternatives have been suggested (see eg http://arxiv.org/pdf/math/0610667.pdf and http://www.ncbi.nlm.nih.gov/pubmed/20048385.

A response to the latter is in http://www.ncbi.nlm.nih.gov/pubmed/23070592

On 2014 Jan 09, Tom Kindlon commented:

Will the CDC CFS Research team (and other teams) please now look at enteroviruses in CFS

(This was originally accepted as a comment here: http://www.biomedcentral.com/1471-2334/5/78/comments in 2007. However, the formatting has been removed meaning few may read it there. Also, many people may not read the paper on the biomedcentral site and thus not see the comment there)

Not for the first time [1-2], a CDC-funded research team produces a paper on CFS which has a title which mentions a lack of an association with a particular infection[3]. It would be good if some of the CDC's (not inconsiderable) CFS research budget could be used to investigate enteroviruses in CFS.

Earlier this year a study involving enteroviruses[4] resulted in much excitement in the media on the subject. It found, in a sample of CFS patients who had gastrointestinal symptoms, that 135/165 (82%) biopsies stained positive for VP1 within parietal cells, whereas 7/34 (20%) of the controls stained positive (p=<0.001). Earlier studies have demonstrated circulating antigen of enterovirus, raised antibody titres and viral RNA in the blood and muscle biopsy specimens of patients with CFS[4-8].

John Chia does recognize that other infections could be playing a part in some CFS cases but enteroviruses are by far the most common infection he is finding in his clinic in California[9].

References:

[1] Gelman JH, Unger ER, Mawle AC, Nisenbaum R, Reeves WC: Chronic fatigue syndrome is not associated with expression of endogenous retroviral p15E. Molec Diagnosis 2000, 5:155-156.

[2] Vernon SD, Shukla S, Reeves WC: Absence of Mycoplasma species DNA in chronic fatigue syndrome. J Med Microbiol 2003, 52:1027-1028.

[3] Jones JF, Kulkarni PS, Butera ST, Reeves WC: GB virus-C--a virus without a disease: we cannot give it chronic fatigue syndrome. Jones JF, Kulkarni PS, Butera ST, Reeves WC. BMC Infect Dis 2005, 5:78

[4] Yousef GE, Mann GF, Smith DF, et al: Chronic enterovirus infection in patients with postviral fatigue syndrome. Lancet 1988;1:146-7.

[5] Cunningham L, Bowles NE, Lane RJM, et al: Persistence of enteroviral RNA in chronic fatigue syndrome is associated with abnormal production of equal amounts of positive and negative strands of enteroviral RNA. J Gen Virol 1990;71:1399-402.

[6] Galbraith DN, Nairn C, Clements GB: Phylogenetic analysis of short enteroviral sequences from patients with chronic fatigue syndrome. J Gen Virol 1995;76:1701-7.

[7] Lane RJ, Soteriou BA, Zhang H, et al: Enterovirus related metabolic myopathy: a postviral fatigue syndrome. J Neurol Neurosurg Psychiatry 2003;74:1382-6.

[8] Douche-Aourik F, Berlier W, Fe´asson L, et al: Detection of enterovirus to human skeletal muscle from patients with chronic inflammatory muscle disease or fibromyalgia and healthy subjects. J Med Virol 2003;71:540-7.

[9] Chia JK, Chia A: Diverse etiologies for the chronic fatigue syndrome. Clin Infect Dis 2003;36:671-2.

On 2014 Jun 01, Ivan Oransky commented:

This paper has been corrected: http://retractionwatch.com/2014/05/28/failure-to-cite-leads-to-ignoble-end-for-xenon-paper-and-a-correction/

On 2016 Aug 21, Morten Oksvold commented:

Please note that this article represents one of eleven publications which were found to contain false data, after an investigation led by ORI in 2015:

https://ori.hhs.gov/content/case-summary-dasmahapatra-girija

This article should therefor not be cited.

On 2015 Mar 16, Donald Forsdyke commented:

Concluding that this paper showed, if anything, the very opposite of what was claimed, a commentary on this paper was submitted to Bioinformatics in 2005, but was declined for publication. The paper and correspondence with the authors was placed online (2006) at: http://post.queensu.ca/~forsdyke/bioinfo9.htm, and various updates have since been added.

On 2016 May 13, Richard E Harris commented:

The sample size in this study was based on a power calculation using results from the Deluze et al. 1992 study as an estimate of effect size. This was the only publication using acupuncture in fibromyalgia at that time. Our power analysis indicated that we would need 30 participants (per group) to detect a 30% difference between groups at a significance level of 0.05. We enrolled from 27 to 30 per arm suggesting we had significant power to test our hypotheses.

Regarding the drop out rate of 33%, we performed an Intention To Treat analysis which controls for some effects of drop outs. Also there was no significant difference in drop outs (or treatments received) between study arms. These make it unlikely that our results were influenced by dropouts.

On 2016 May 04, Arthur Yin Fan commented:

This study has a significant flaw--the sample size is over small, and could not make sure the acupuncture's efficacy--the design of four groups, should have 800 patients.

The second, the drop out rate 33%, makes the result is not trust-able.

On 2015 Aug 19, Bill Cayley commented:

An example of when less is better: https://lessismoreebm.wordpress.com/2015/06/30/acetaminophen-aspirin-and-caffeine-versus-sumatriptan-succinate-in-the-early-treatment-of-migraine-results-from-the-asset-trial/

On 2014 Aug 07, Randy Blakely commented:

In this paper, the authors report an inability of an hDAT E602G mutant to transport DA or to reach the cell surface. The findings are at odds with a study from my lab (Expression studies of naturally occurring human dopamine transporter variants identifies a novel state of transporter inactivation associated with Val382Ala. Mazei-Robison MS, Blakely RD. Neuropharmacology. 2005 Nov;49(6):737-49). Although the impact of the E602G mutation warrants further analysis, discussions with Drs. Horschitz and Schloss lead to retraction of the Horschitz et al paper As the authors note in their retraction (S Horschitz, R Hummerich, T Lau, M Rietschel & P Schloss Molecular Psychiatry 11, 704-704, 27 June 2006):

"Mazei-Robison and Blakely have published in Neuropharmacology (2005) 49, 737–749, a characterization of several naturally occurring mutants of hDAT. In contrast to our data, in their study the E602G mutant was fully active and comparable to wild-type hDAT. In order to elucidate these contradictory results, both our labs exchanged the mutant cDNAs and re-analysed the properties of the E602G mutant. Uptake experiments in both labs with HEK 293 transiently transfected with both cDNA plasmids revealed transport activity of the E602G mutant comparable to wild-type hDAT. Thus, our conclusion published in Molecular Psychiatry (2005) 10, 1104–1109 is wrong and has to be withdrawn at this point of time."

Since the original Horschitz et al report continues to be cited inappropriately as support for a role for altered DAT (or DA signaling) in BPD, I am hoping the PubMed Commons forum will provide a suitable opportunity to redirect readers attention to the, as yet, unknown properties of the E602G mutation that may include alterations in roles of the hDAT C-terminus (membrane trafficking, interactions with regulatory proteins, DA efflux, e.g. Calmodulin kinase II interacts with the dopamine transporter C terminus to regulate amphetamine-induced reverse transport. Fog JU, Khoshbouei H, Holy M, Owens WA, Vaegter CB, Sen N, Nikandrova Y, Bowton E, McMahon DG, Colbran RJ, Daws LC, Sitte HH, Javitch JA, Galli A, Gether U. Neuron. 2006 Aug 17;51(4):417-29; Attention deficit/hyperactivity disorder-derived coding variation in the dopamine transporter disrupts microdomain targeting and trafficking regulation. Sakrikar D, Mazei-Robison MS, Mergy MA, Richtand NW, Han Q, Hamilton PJ, Bowton E, Galli A, Veenstra-Vanderweele J, Gill M, Blakely RD. J Neurosci. 2012 Apr 18;32(16):5385-97. doi: 10.1523/JNEUROSCI.6033-11.2012. Erratum in: J Neurosci. 2012 Oct 31;32(44):15643).

On 2014 Jul 27, DATTATRAY PAWAR commented:

What is the use of guidelines if no one has free access to them?

On 2016 Jan 05, Morten Oksvold commented:

Please not that this article contains fraudulent data, which was concluded from an investigation by the University of Alabama at Birmingham in 2009 (!):

http://www.uab.edu/reporterarchive/71570-uab-statement-on-protein-data-bank-issues

The case was recently discussed at Retraction Watch: http://retractionwatch.com/2016/01/04/nature-retracts-paper-six-years-after-it-was-flagged-for-fraud/

Biochemistry was informed about this case in 2009, but as far as I can see there has still not been published any retraction.

On 2014 Mar 07, Preben Berthelsen commented:

A foregone conclusion.

The result of this investigation was a dead certainty even before it was conducted. The authors initiating PAC guided therapy 18 hours after the critically ill patients were admitted to intensive care units. This delay in the deployment of the PAC makes it extremely unlikely that PAC guided therapy would influence the mortality rate; it is like shutting the stable door after the horse has bolted. This study does not inform on the timely use of the pulmonary artery catheter.

The primary sample size calculation stipulated that 5673 patients were needed to demonstrate a 5% reduction in mortality. Due to slow recruitment, the primary endpoint was changed to a 10% reduction - 1281 patients were then required. In the end, the authors report the results from 1014 patients.

The principal clinical investigator/corresponding author M. Singer “does consultancy work for, and receives research funds from Deltex Medical, manufacturers of the CardioQ oesophageal Doppler device.”

Preben G. Berthelsen MD

Charlottenlund, Denmark

On 2014 Mar 07, Preben Berthelsen commented:

None

On 2016 Feb 19, E M Martínez-Cáceres commented:

In the light of the recent PubMed comment by Morten Oksvold, the referenced research study was performed entirely in our research centre by the research team led by Dr. Martínez-Cáceres at the time with Dr. Espejo as predoctoral researcher. Hence, the EAE in vivo experiments were performed in Barcelona with no involvement from Dr. Penkowa, who was engaged as an expert histopathologist. Dr. Penkowa received processed and encoded samples with which she performed some of the histopathological studies. The results were returned to us for overall analysis and submission for publication. It was agreed that Dr. Penkowa would be co-author of the published work.

On 2016 Feb 01, Morten Oksvold commented:

Please note that this article is 1 out of 15 publications for which an independent investigation initiated by the University of Copenhagen has found suspicion of scientific dishonesty. The conclusion from the report was published July 23, 2012:

http://news.ku.dk/all_news/2012/2012.8/indications_of_fraud_in_penkowas_early_research/

This articles should therefore not be cited.

On 2017 Aug 29, David Mage commented:

In the introduction the authors write: "the peak incidence of SIDS coincides with the nadir in the physiologic anaemia of infancy (PAI)." This nadir is defined as the minimum in total (T) hemoglobin (Hb)(g/dL) vs age as the infant's fetal hemoglobin (HbF) is replaced by adult hemoglobin (HbA). This gives the relation as follows: THb = HbA + HbF, where HbF decreases with age and HbA increases with age. Differentiating the equation with respect to time t since birth we obtain the relation d(THb)/dt = d(HbA)/dt + d(HbF)/dt. That is, the nadir is the point in time when the increase in HbA plus the decrease in HbF equals 0.

However, because HbF holds oxygen more tightly than HbA does, the available oxygen (AO2) to the tissues from the blood will also have a minimum during the period between birth and the nadir in PAI. This can be seen because when the increase in HbA is equal and opposite to the decrease in HbF, d(AO2)/dt is greater than zero so the nadir in AO2 must occur earlier than the nadir in PAI.

Of course this time differential between the nadirs will be a function of gestational age and the time interval between birth and cord clamping, that relates to the placental transfusion from mother to infant that increases the infant THb.

On 2016 Nov 20, Morten Oksvold commented:

An investigation committee at Wayne State University (WSU) recommends that 42 articles from Fazlul Sarkar to be retracted (report finished August 31, 2015). This article represents one of them.

This information was published by Retraction Watch (November 17, 2016) and you can find a link to the full report here:

http://retractionwatch.com/2016/11/17/details-of-investigative-report-into-sarkar-released-by-aclu/

This article should therefore no longer be cited.

On 2013 Nov 08, Mark Gijzen commented:

New results published by others (PMCID: PMC3718677 and Morais JK, 2010) have led us to revise our hypothesis regarding the cross-reactivity of the SC24 antibody. Instead of cross-reactivity with the seed coat peroxidase, it is more likely that the antibody simply cross-reacts with the newly discovered soybean toxin SBTX, since SC24 and SBTX share sequence similarity. Our purified sample of peroxidase enzyme likely contained SBTX, since these two proteins are of the same size, 44 kD.

On 2013 Nov 09, Subhash Thakre commented:

This article is an effort to assess the quality and strengths of study findings. it has also addressed the issue in various corollary. I liked it very much.

On 2013 Oct 23, Hilda Bastian commented:

The conclusions of this paper (Ioannidis JP, 2005) were challenged by Goodman and Greenfield in 2007 (and responded to by Ioannidis JP, 2007). They were also challenged by Jager and Leek (Jager LR, 2014). Those authors conclude, using a different analytical approach (false discovery rate), that the literature reliably charts scientific progress. Ioannidis then responds to this discussion, challenging the data and analytical approach here: (Ioannidis JP, 2014). (I discuss this debate in a blog post.)

On 2016 Jul 11, Pedro Reche commented:

This tool isnow available at http://imed.med.ucm.es/Methylator

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2016 Mar 29, Jonathan Wren commented:

Apparently relocated to: http://www.lbgi.fr/balibase/

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2014 Feb 02, Tom Kindlon commented:

Observations on apparent changes in methods of assessing symptoms

(This was originally posted here: http://www.pophealthmetrics.com/content/3/1/8/comments but the formatting has been removed and some people may not read the paper there either).

I notice that the "Symptom Inventory collects information about the presence, frequency, and intensity of .. symptoms during the month preceding the interview". However the Fukuda et al '94 definition [1] is supposed to look for "the concurrent occurrence of four or more of the following symptoms, all of which must have persisted or recurred during 6 or more consecutive months of illness and must not have predated the fatigue".

Was there a particular reason why a time frame of one month was chosen? This would suggest that relatively short-lived symptoms would be counted. If the reasoning was that asking people detailed questions about symptom severity and frequency over a longer period would might not be as accurate, perhaps a two-stage question could be asked: firstly asking whether symptoms "have persisted or recurred during 6 or more consecutive months of illness" and then asking a more detailed question about frequency and intensity.

I also see no mention of the requirement, that was in the initial definition [1], that the symptoms didn't predate the fatigue. Again, if this is a change, it would seem to risk reducing the specificity of the symptom criteria (i.e. increasing the chances that symptoms from other causes are counted) so perhaps again a yes/no question would be good.

References:

[1] Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A: The chronic fatigue syndrome; a comprehensive approach to its definition and study. Ann Int Med 1994, 121:953-959.

On 2014 Feb 02, Tom Kindlon commented:

More symptoms could be added to a CFS Symptom Inventory

(This was originally posted here: http://www.pophealthmetrics.com/content/3/1/8/comments but the formatting has been removed and some people may not read the paper there either).

Many would feel that the 8 symptoms used in the CDC '94 definition [1] were chosen in a somewhat arbitrary fashion; so it is to be welcomed that the CDC itself has started to look beyond these symptoms with the CDC CFS Symptom Inventory. The idea of a Short Form of the CDC Symptom Inventory is also interesting.

However, it is not clear to me where the extra symptoms that are on the CDC CFS Symptom Inventory came from. For example, I didn't see some of the symptoms listed in Reeves et al [2].

In 2001, De Becker et al [3] published data on the symptoms found in over 2500 patients. They tried to improve on the 1988 [4] and 1994 CDC criteria. They suggested a list of symptoms that could be used to strengthen the ability to select ME/CFS patients. Many of the symptoms they mentioned are not in the CDC CFS Symptom Inventory.

So to claim that the "CDC Symptom Inventory assesses the full range of CFS associated symptoms" seems questionable. It would be interesting if in future these symptoms (that De Becker et al were suggesting) were added before statistical analyses are performed. The fatigue criteria and functional impairment criteria have become much less restrictive [5]. For example, to satisfy the fatigue criteria, the fatigue is required to be greater than or equal to the medians of the MFI general fatigue (≥ 13) or reduced activity (≥ 10) scales. So it now seems particularly important that the symptom criteria have good sensitivity and specificity or one is going to end up with a definition that leads to very heterogeneous samples.

References:

[1] Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A: The chronic fatigue syndrome; a comprehensive approach to its definition and study.Ann Int Med 1994, 121:953-959.

[2] Reeves WC, Lloyd A, Vernon SD, Klimas N, Jason LA, Bleijenberg G, Evengard B, White PD, Nisenbaum R, Unger ER, International Chronic Fatigue Syndrome Study Group: Identification of ambiguities in the 1994 chronic fatigue syndrome research case definition and recommendations for resolution.BMC Health Services Research 2003, 3:25.http://dx.doi.org/10.1186/1472-6963-3-25

[3] A definition-based analysis of symptoms in a large cohort of patients withchronic fatigue syndrome, P. De Becker, N. McGregor, and K. De Meirleir.Journal of Internal Medicine 2001;250:234-240

[4] Holmes GP, Kaplan JE, Gantz NM, Komaroff AL, Schonberger LB, Straus SE, et al.: Chronic fatigue syndrome: a working case definition. Ann Intern Med 1988, 108:387-389.

[5] Reeves WC, Wagner D, Nisenbaum R, Jones JF, Gurbaxani B, Solomon L, Papanicolaou DA,Unger ER, Vernon SD, Heim C: Chronic fatigue syndrome — a clinically empirical approachto its definition and study. BMC Medicine 2005, 3:16.

On 2016 Aug 21, Morten Oksvold commented:

Please note that this article represents one of eleven publications which were found to contain false data, after an investigation led by ORI in 2015:

https://ori.hhs.gov/content/case-summary-dasmahapatra-girija

This article should therefor not be cited.

On 2017 Apr 27, Mante S Nieuwland commented:

For more in-depth discussion on why this effect may be hard to replicate, and the problems with the original study, see our newest paper in LCN https://osf.io/preprints/psyarxiv/ayd3t

On 2017 Apr 05, Katherine A DeLong commented:

There are a number of concerns regarding Nieuwland et al.'s (2017) multi-lab effort. We here highlight features of their project that undermine confidence in their purported non-replication of the DeLong et al. (2005) findings: http://kutaslab.ucsd.edu/FinalDUK17Comment9LabStudy.pdf

On 2017 Mar 01, Mante S Nieuwland commented:

We've failed to replicate the results of this paper in a recent multi-lab effort. Biorxiv pre-print of our paper is available on http://www.biorxiv.org/content/early/2017/02/25/111807

On 2015 Jun 04, thomas samaras commented:

Additional information on height, CHD and longevity is available from these publications.

Samaras TT. Shorter height is related to lower cardiovascular disease risk—A narrative review. Indian Heart Journal 2013; 65: 66-71.

Samaras TT. Evidence from eight different types of studies showing that smaller body size is related to greater longevity. Journal of Scientific Research & Reports. 2014: 3 (16): 2150-2160, 2014; article no. JSRR.2014.16.003.

Samaras TT. Human Scaling and Body Mass Index. In: Samaras TT (ed): Human Body Size and the Laws of Scaling: Physiological Performance, Growth, Longevity and Ecological Ramifications. New York: Nova Science Pub; 2007: pp 17-32.

He Q, Morris BJ, Grove JS, Petrovitch H, Ross W, Masaki KH, et al. Shorter men live longer: Association of height with longevity and FOXO3 genotype in American men of Japanese ancestry. Plos ONE 9(5): e94385. doi:10.1371/journal.pone.0094385.

Salaris L, Poulain M, Samaras TT. Height and survival at older ages among men born in an inland village in Sardinia (Italy), 1866-2006. Biodemography and Social Biology, 58:1, 1-13.

Bartke A. Healthy Aging: Is Smaller better? A mini-review. Gerontology 2012; 58:337-43.

On 2015 Jun 02, thomas samaras commented:

Additional information on height, CHD, and longevity is available from these recent publications.

Samaras TT. Shorter height is related to lower cardiovascular disease risk—A narrative review. Indian Heart Journal 2013; 65: 66-71.

Samaras, TT. Is short height really a risk factor for coronary heart disease and stroke mortality? A review. Med Sci Monit 2004; 10(4): RA63-76.

Samaras TT. Evidence from eight different types of studies showing that smaller body size is related to greater longevity. Journal of Scientific Research & Reports. 2014: 3 (16): 2150-2160, 2014; article no. JSRR.2014.16.003.

Samaras TT. Human Scaling and Body Mass Index. In: Samaras TT (ed): Human Body Size and the Laws of Scaling: Physiological Performance, Growth, Longevity and Ecological Ramifications. New York: Nova Science Pub; 2007: pp 17-32.

He Q, Morris BJ, Grove JS, Petrovitch H, Ross W, Masaki KH, et al. Shorter men live longer: Association of height with longevity and FOXO3 genotype in American men of Japanese ancestry. Plos ONE 9(5): e94385. doi:10.1371/journal.pone.0094385.

Salaris L, Poulain M, Samaras TT. Height and survival at older ages among men born in an inland village in Sardinia (Italy), 1866-2006. Biodemography and Social Biology, 58:1, 1-13.

Bartke A. Healthy Aging: Is Smaller better? A mini-review. Gerontology 2012; 58:337-43.

On 2014 Nov 24, Ivan Oransky commented:

The second author of this paper has agreed to retract it and five others following a finding of misconduct by the Office of Research Integrity: http://retractionwatch.com/2014/11/20/former-vanderbilt-scientist-faked-nearly-70-images-will-retract-6-papers-ori/

On 2016 Jan 07, Gwinyai Masukume commented:

Did anabolic steroids contribute to Mike Webster’s death?

During Mike Webster’s autopsy documented in this case report, dilated cardiomyopathy was found. Mike Webster admitted to trying anabolic steroids during his sporting career: Use of anabolic steroids has been associated with the development of dilated cardiomyopathy Ahlgrim C, 2009, Kalmanovich, 2014 and cardiac dysfunction Baggish AL, 2010 that can eventually be fatal. Although the focus of this excellent case report by Omalu and colleagues was the neuropathology aspect, exploring the dilated cardiomyopathy in someone with a history of anabolic steroid use can have important public health lessons.

On 2013 Oct 29, Michael Eisen commented:

According to recent Frontline documentary "League of Denial" http://www.pbs.org/wgbh/pages/frontline/league-of-denial/ this paper was the first step in a chain of events that has finally led to the NFL acknowledging that repeated head trauma can potentially cause long term problems for professional football players, and to a series of changes in the game designed to reduce head injuries.

Note that, according to Frontline, the NFL originally disputed the finding and attacked the work and its author - see Casson IR, 2006.

On 2014 Jun 02, Pedro Reche commented:

PEPVAC is now available at http://imed.med.ucm.es/PEPVAC/.

On 2016 Jan 02, Prashant Sharma, MD, DM commented:

This highly unusual case was a diagnostic challenge wherein filarial infection diagnosed in a lymph node sample provided clues to the patient's non-healing fistula. Wuchereria bancrofti filariasis is commonly diagnosed in parts of India, and parasitic infections must be considered in the differential diagnosis of non-healing chronic discharging ulcers/fistulae. Please feel free to write to me for the full article.

On 2014 Nov 23, Harri Hemila commented:

A manuscript version of the comment is available at the University of Helsinki institutional repository: http://hdl.handle.net/10250/7981

On 2015 Jun 26, Bill Cayley commented:

a good example of when "less" is "more": https://lessismoreebm.wordpress.com/2015/06/27/how-little-is-enough-the-evidence-for-post-vasectomy-testing/

On 2017 Mar 26, Misha Koksharov commented:

1) It is really sad to see that almost everyone is still using IPTG even after all these years.

2) Full-text (DOI) link is missing from Pubmed for some reason: Final manuscript, NIH-PA author manuscript.

3) If someone wonders: it doesn't matter if it is exactly alpha-form of lactose - it will equilibrate to about 40:60 ratio of both forms in solution anyway, especially in an autoclave and this works fine.

On 2016 Feb 18, Kristina Hanspers commented:

The pathway in figure 1a is available in the "Open Access Publication" collection at WikiPathways: http://www.wikipathways.org/index.php/Pathway:WP2566. This pathway can be downloaded for use in network analysis tools such as Cytoscape and PathVisio.

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2015 Apr 18, Dorothy V M Bishop commented:

As a psychologist interested in the genetics of lateralization, I frequently come across this paper, which is cited as evidence for early genetic influences on brain asymmetry. As of today, 160 citations are shown in Web of Science.

When I read the paper a couple of years ago, I found some details that did not seem to support the conclusions of the authors. These are described in a blogpost: http://deevybee.blogspot.co.uk/2012/12/genes-brains-and-lateralisation-how.html

I will summarise the main issue below, but I was interested to note that, since that time, other papers have appeared, using larger datasets, which have stressed the remarkable symmetry of early gene expression, notably:

Johnson, M. B., et al (2009). Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron, 62(4), 494-509. doi: 10.1016/j.neuron.2009.03.027

and

Pletikos, M., Sousa, A. M. M., Sedmak, G., Meyer, K. A., Zhu, Y., Cheng, F., . . . Sestan, N. (2014). Temporal specification and bilaterality of human neocortical topographic gene expression. Neuron, 81(2), 321-332. doi: 10.1016/j.neuron.2013.11.018

Here is a brief account of the main issue I raised about the study. Please see the blogpost for more details.

Sun et al used a method called Serial Analysis of Gene Expression (SAGE) which compares gene expression in different tissues or – as in this case – in corresponding left and right regions of the embryonic brain. The analysis looks for specific sequences of 10 DNA base-pairs, or tags, which index particular genes. SAGE output consists of simple tables, giving the identity of each tag, its count (a measure of cellular gene expression) and an identifier and more detailed description of the corresponding gene. These tables are available for left and right sides for three brain regions (frontal, perisylvian and occipital) for 12- and 14-week old brains, and for perisylvian only for a 19-week-old brain. The perisylvian region is of particular interest because it is the brain region that will develop into the planum temporale, which has been linked with language development. One brain at each age was used to create the set of SAGE tags.

To verify asymmetrically expressed genes the authors performed chi square tests. The chi square involves testing whether the distribution of expression on left and right is significantly different from the distribution of left vs. right expression across all tags in this brain region – which is close to 50%. In the left-right perisylvian region of a 12-week-old embryonic human brain, there were 49 genes with chi square greater than 6.63 (p < .01): 21 were more highly expressed on the left and 28 more highly expressed on the right. But for each region the authors considered several thousand tags. My analysis indicated that the number of asymmetrically expressed genes appeared to be lower than you would expect by chance – entirely consistent with the conclusions of Pletikos et al.

Unless my analysis is mistaken, it would seem this paper should not be cited as evidence for asymmetric fetal gene expression, as it actually shows the opposite.

On 2014 Dec 10, Kath Wright commented:

None

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2015 Oct 07, Bill Cayley commented:

One of several examples showing that sometimes in obstetric care "less" is "more": https://lessismoreebm.wordpress.com/tag/obstetric-gynegologic/

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home

On 2014 Dec 10, Kath Wright commented:

Other search filters are available from the InterTASC Information Specialists' Sub-Group Search Filter Resource at https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home