6,062 Matching Annotations
  1. May 2026
    1. On 2026-03-26 15:44:14, user Peter J. Wolf wrote:

      As both a researcher and community cat caregiver, I’m very pleased to see this work being conducted!

      I was rather surprised to see the relatively low instances of secondary traumatic stress (i.e., 47% moderate, 10% high) reported in this study. I imagine this is the result of using the thresholds proposed by Stamm (2010). You might consider repeating your analysis using the revised thresholds proposed by De La Rosa et al. (2018).

      Literature cited<br /> De La Rosa, G. M., Webb-Murphy, J. A., Fesperman, S. F., & Johnston, S. L. (2018). Professional quality of life normative benchmarks. Psychological Trauma: Theory, Research, Practice, and Policy, 10, 225–228. https://doi.org/10.1037/tra0000263

      Stamm, B. H. (2010). The Concise ProQOL Manual (2nd ed.). https://proqol.org/proqol-manual

    1. On 2026-03-27 14:32:15, user Peter Ellis wrote:

      If you can validate this finding by some other method then this would be a truly remarkable finding. The Y chromosome contains numerous genes that are essential for spermatogenesis - it should not be possible for any cell lineage lacking the Y to give rise to mature sperm. The only possible point at which the Y could be lost (or Y-bearing cells could be lost) would be post-meiotic.

      Is it possible instead that there is some alteration in chromatin packaging which somehow selectively affects the extraction efficiency of Y chromosomal DNA sequences?

      Alternatively, how exactly is the calculation of Y content being done? If this is an aggregate measurement from bulk DNA, is it possible that rather than there being cells that have fully lost the Y, there is a mix of cell lineages present, each of which has a range of different Y microdeletions present?

      Given the known essentiality of the Y for sperm production, I think you will find it challenging to get this past peer review without some kind of per-cell analysis, which could be FISH-based or single-cell genotyping. In either case you'd need very high throughput to have statistical power to detect 1% of cells with LOY

    1. On 2026-01-12 13:02:28, user Ryan wrote:

      The plot in figure 2 is great. However, providing a supplemental with the actual HR of testing would be helpful for others to do a tipping point analysis of your results and confirm the testing effect is or is not strong enough to nullify your results. This would greatly enhance the reproducibility of your research.

    2. On 2026-01-12 13:11:20, user Ryan wrote:

      I recommend leaving an HR for testing positivity or adding the positivity rate as adjusted variable, this will allow testing level to be compared and not just testing timing on the results. From the look of it hin the log ratios over time, it does not look like it will completely wash out the signal, however, it is hard to tell with giving the actual values.

    3. On 2025-12-12 17:45:56, user Ceejay wrote:

      Line 293: "This study’s inability to find a protective influence of influenza..." I think what is meant is protective influence *of vaccination* on influenza

    1. On 2026-03-30 13:27:10, user Sverre wrote:

      This is a very cool article, thanks for sharing it! Currently planning a kinda similar analysis. I just want to point out that Norwegian middle school GPA is not a 10-year cumulative measure: it just contains grades from year 10 (and a few from year 9).

    1. On 2026-03-29 15:01:54, user Ian Buller wrote:

      Quick note that your citation of the abstract by Brown & Vo et al. (2022; DOI: 10.1158/1538-7755.DISP21-PO-192) is now published as a manuscript in JNCI by Vo & Brown et al. (2025; DOI: 10.1093/jnci/djaf066). I am a co-author on both.

    1. On 2026-03-25 06:58:19, user Eugenio Forbes wrote:

      As part of the methodology, did anyone diagnose equipment and cables, plot the recordings to verify that it's not mostly noise?

    1. On 2026-03-25 02:47:47, user Tin Pham wrote:

      This paper could have been ameliorated by specifying the target trial specifications (eg. eligibility criteria, treatment and outcome, follow-up, causal contrasts) and the emulated analogues, according to the TARGET guideline (Cashin et al, 2025). Also, I suggest some sensitivity analyses be done (e.g. varying the lag time, different model specifications for calculating the propensity score, ITT vs PP treatment estimates) to verify the robustness of the findings.<br /> _____<br /> References: <br /> Cashin AG, Hansford HJ, Hernán MA, et al. Transparent Reporting of Observational Studies Emulating a Target Trial—The TARGET Statement. JAMA. 2025;334(12):1084–1093. doi:10.1001/jama.2025.13350

    1. On 2026-03-23 19:50:14, user Neville Calleja wrote:

      There is clearly a number of confounders here and the way it is written and summarised in the abstract does not give enough credit to this. The link with pre-existing EBV infection, potential infection before the vaccine took full effect etc has not been well described. A number of subset analyses have been carried out, which may border on data dredging, rather than formal multivariate analyses. Also clearly the involvement of a major antivax advocate has meant that the study has been highjacked.

    1. On 2026-03-23 18:21:15, user Evolutionary Health Group wrote:

      We at the Evolutionary Health Group ( https://evoheal.github.io/ ) enjoyed this paper. Here are our highlights:

      The saliva-based work presented here shows convincing equivalence to blood tests across multiple pathogens, cohorts, and age groups. The attention to real-world validation shows that the method is platform-level, opening the possibility of applying this type of assay in other contexts.

      Because saliva samples are self-collected, non-invasive, and stable, the authors demonstrate that it's possible to capture the daily resolution of important pathogens, addressing a major limitation in epidemiology where true dynamics can't be captured due to infrequent sampling.

      Blood-based studies frequently under-sample children, older adults, rural populations, and low-resource populations. Saliva testing removes many of the cost, commute, and invasiveness barriers and helps create more representative datasets for use in epidemiological inference and public health policy.

      Professionally collected blood samples benefit from consistent quality. Self-collected samples are more likely to suffer a loss of quality due to improper collection techniques. We would be interested to know how sample quality compares when collections are truly independent of any professional guidance.

    1. On 2026-03-14 00:41:31, user Lisa DeTora wrote:

      What an interesting study! I'd be curious about your views on more open-ended questions users might ask of LLMs about specific vaccines. I also wonder if you have advice for public health agencies or healthcare providers on using LLMs in this setting

      One small point: the vaccine hesitancy reference is pre-COVID. My understanding is that this problem has been somewhat worse since the pandemic, making the problems you seek to address even more critical.

    1. On 2026-03-13 17:56:20, user NomosLogic wrote:

      Important preprint out of Johns Hopkins — LLMs evaluated as a diagnostic safety net for correcting physician errors.<br /> The right question to ask alongside it: for which clinical decisions is "better probabilistic reasoning" the correct architectural answer, and for which decisions is determinism required?<br /> Drug-gene interactions have correct answers. They are computable. An LLM that reasons well about a CYP2C19 finding is still approximating what a deterministic rules engine computes exactly — every time, auditably, without session-level variance.<br /> The safety net shouldn't be a better guesser. It should be a system that cannot get the answer wrong.

    1. On 2026-03-10 21:27:15, user Abdul Harif wrote:

      Training a 160-input multilayer perceptron on a cohort of only 35 unique participants is highly prone to overfitting, even with the inclusion of dropout layers and early stopping. Also, the control group only provided a single breath specimen at one time point, whereas the patient group provided breath specimens before treatment and again 6 to 8 weeks later. This introduces unmitigated temporal confounding variables, such as seasonal changes or device drift over the 8-week period, which the control group does not account for.

    1. On 2026-03-09 13:24:18, user David Glasser, MD wrote:

      All authors are equity owners of the system studied. Were these the same experts that reviewed discordant cases and sided with the system they owned almost 4 times as often as the board certified clinicians who made the initial assessments?

      Ethical review was by the company that markets the system studied.

      MAJOR sources of bias and conflicts of interest here. I give them credit for being forthright about disclosing them.

    2. On 2026-02-20 13:58:16, user Peer Reviewer wrote:

      We requested the materials needed to reproduce the main results in this preprint. Although the manuscript states that “all data produced in the present study are available upon reasonable request,” a request from our group did not receive a response, and the requested materials have not been made available for independent replication.

    1. On 2026-02-27 17:03:20, user Deepak Modi wrote:

      The NGS dataset in this study is available with IBDC Study Accession: INRP000591 and INSDC (SRA) Project Accession: PRJEB108860

    1. On 2026-02-22 17:29:44, user Sue Hewitt wrote:

      How is it possible to review the supplementary tables, which do not seem to be included in the preprint? Will this research be submitted for peer review?

    1. On 2026-02-21 03:18:58, user Naoki Watanabe wrote:

      We are pleased to announce that this preprint has undergone peer review and has been published in a formal journal. Please refer to the final version of the article.

      Watanabe N, Watari T, Otsuka Y. Desulfovibrio Bacteremia in Patients with Abdominal Infections, Japan, 2020–2025. Emerg Infect Dis. 2026 Feb [cited 2026 Feb 21];32(2). Available from: http://dx.doi.org/10.3201/eid3202.251581

    1. On 2026-02-02 05:15:23, user S. Miyamoto wrote:

      Now published in Commun Med.

      Miyamoto S, Numakura K, Kinoshita R, Arashiro T, Takahashi H, Hibino H, Hayakawa M, Kanno T, Sataka A, Sakamoto R, Ainai A, Arai S, Suzuki M, Yoneoka D, Wakita T, Suzuki T. Serum anti-nucleocapsid antibody correlates of protection from SARS-CoV-2 re-infection regardless of symptoms or immune history. Commun Med (Lond). 2025 May 15;5(1):172. doi: 10.1038/s43856-025-00894-8. PMID: 40374831; PMCID: PMC12081900.

    1. On 2026-01-31 09:06:49, user Chris Morgan wrote:

      I understand from the Methods that the background population were required to have at least 12 months registration prior to each observation year and that PD events prior to 2007 were excluded. I am therefore assuming PD patients had to have the first diagnosis after this 12 months as a wash-in to ascertain true incident cases. As this is not explicit in the text and noting the higher incidence in the early years of the study, could the author just confirm this please

    1. On 2026-01-29 02:57:44, user Vanessa Haase wrote:

      Correction to my previous comment: The HQ calculations for heart rate increase are scientifically invalid. Heart rate increase from nicotinic agonists is the intended pharmacological effect, not an adverse outcome. The authors use an ARfD based on heart rate increases, but HQ methodology is designed to assess adverse health effects. Pharmacological receptor activation that produces the desired stimulant effect cannot be characterized as a toxicological hazard. By this logic, caffeine would have unacceptable HQs for increased alertness.<br /> Valid cardiovascular risk assessment requires identifying doses causing actual adverse outcomes like sustained tachycardia leading to arrhythmias, hypertensive crises, or cardiovascular events in vulnerable populations. The physiological response that constitutes the purpose of product use is not a safety threshold exceedance.<br /> The conclusions about exceeding safety thresholds rest on this fundamental mischaracterization of pharmacology as toxicity. This undermines legitimate regulatory concerns about unregulated nicotine analogues. Meaningful risk assessment requires identification of true adverse cardiovascular outcomes, not normal receptor-mediated responses.

    1. On 2026-01-26 18:38:43, user Johanna Karla Lehmann wrote:

      No single factor that could be associated with a deterioration in post-COVID-19 symptoms after a SARS-CoV2 vaccine dose was investigated (objectives, title, primary outcome). Factors that could have been considered include quantitative changes in spike production, ACE2 expression, Ang II and Ang 1-7 levels, immunological/ inflammatory markers or changes in the severity/extent of comorbidity (blood pressure behaviour, changes in blood circulation, glucose/lipid metabolism, blood clotting, etc.) and smoking habits.<br /> A deterioration and/or increase in symptoms comes as no surprise. Both the infection and the desired acquired immunity through a COVID-19 vaccination (vaccine indication) require SARS-CoV2 spike antigens (RBD of the spike S1 subunit). These are known to react with ACE2 and trigger pathophysiologically undesirable specific organ dysfunctions and symptoms via an Ang II increase and other reactions (bradykinin increase, etc.). For long Covid, an influence of spikes on nicotinic acetylcholine receptor reactions in the periphery and in the CNS is also being discussed. This was evident in the symptoms of coughing (probably dry cough!) and concentration problems, both of which increased significantly after vaccination.<br /> Vaccination (inclusion criterion) and coughing (a symptom!) were named as the ‘identified only factors’ for a worsening of post-COVID-19 symptoms. Neither of these can be described as factors underlying the worsening. The different risks associated with specific vaccines (mRNA, adenovirus, protein-based, attenuated) should be carefully examined in a representative, controlled, comprehensive clinical study.

    1. On 2026-01-26 15:25:00, user Veronica Ruiz wrote:

      In response to the question Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection? I believe that use of fourth-generation rapid tests should continue and be encouraged simply because reduce the window period, and it always should be incorporated into a complete diagnostic and confirmatory algorithm. Like other HIV diagnostic tools, its true usefulness lies in the interpretation framed within an algorithm, and I believe that the vast majority of people who work in the field of diagnosis understand this, and it is clearly outlined in all the guides or recommendations on the subject. In other words, fourth-generation rapid tests alone do not guarantee the detection of acute infection, but in combination of counseling applied to high-risk populations including continuous monitoring and application of other tests including NAT and Ac/Agp24 combo for the detection of the acute viremia phase and the information provided to users can considerably improve the chance of early detection.<br /> As has already been expressed in other comments, there is a huge bias in comparing studies that use different tests, including some that were not approved for use and whose sensitivity increased in updated versions, as well as including mixed populations of very different types in which the percentage of incidence of HIV infection is not comparable.<br /> However, I believe that the greatest bias in the sensitivity calculation is the failure to take into account the appearance of different markers throughout the evolution of the infection, a topic already described by Fiebig in Fiebig EW, Wright DJ, Rawal BD, et al. Dynamics of HIV viremia and antibody seroconversion in plasma donors: implications for diagnosis and staging of primary HIV infection. AIDS 2003; 17(13):1871–1879. <br /> This review conflates detection methods using tests that detect different markers (Table I) related to the time of infection. For example when compared to a NAT test, which has a shorter window period, a fourth-rate rapid test won't have the same diagnostic scope, just like tests that exclusively detect the p24 antigen, whose detection threshold is well-proven to be much lower than any rapid test.<br /> Is also a well-known and reported fact that fourth-generation rapid tests do not perform as well as instrumental methods, but is an inherent limitation of method. Therefore, comparisons should be made using methods with at least a similar detection threshold and window period.The discussion is always interesting and enriching, and I will seek to contact the authors to continue it.

    2. On 2026-01-23 13:21:44, user Dr Ali Johnson Onoja wrote:

      The analysis aggregates performance data from a heterogeneous mix of fourth-generation HIV rapid tests, including research-use-only products (e.g., SD Bioline HIV Ag/Ab Combo), discontinued devices (Combo RT, D4G, E4G, Geenius HIV-1/2, Bio-Rad GS HIV Combo), the FDA-approved U.S. version of Determine HIV-1/2 Ag/Ab Combo, and the WHO-prequalified Alere HIV Combo/Determine HIV Early Detect. In the Nigerian context, where national HIV testing algorithms approved by the Federal Ministry of Health (FMoH) and NACA restrict use to WHO-prequalified assays, pooling data from obsolete or non-programmatic tests without stratification by brand, version, or regulatory status may misrepresent the true performance of diagnostics currently available or deployable in Nigeria.<br /> Assumption of Class-Dependent Performance and Its Programmatic Implications in Nigeria<br /> The review assumes that diagnostic performance is determined primarily by test class (i.e., fourth-generation Ag/Ab RDTs), without sufficient consideration of infection kinetics, targeted biomarkers, assay technology, or specimen type. In Nigeria—where HIV testing is predominantly conducted using finger-prick whole blood in community, primary healthcare, and outreach settings—test performance during acute HIV infection (AHI) is heavily influenced by the timing of presentation and the biological stage of infection. Failure to account for Fiebig stage–specific detectability risks overgeneralizing performance expectations and may undermine rational decisions about where and how fourth-generation RDTs could add value within Nigerian testing strategies.<br /> Non-Standard Definitions of Acute HIV Infection and Relevance to Nigerian Epidemiology<br /> Definitions of AHI vary widely across included studies, spanning multiple Fiebig stages (I–III or I–IV), each characterised by distinct biomarker kinetics (HIV RNA -> p24 antigen -> antibody). In the Nigerian epidemic—where individuals often present late for testing but key populations and high-incidence sub-groups may test during early infection—averaging sensitivity across biologically heterogeneous stages obscures the specific window (notably p24-positive Fiebig II–III) in which Ag/Ab RDTs are theoretically expected to improve case detection. This limits the applicability of pooled sensitivity estimates for informing targeted AHI screening strategies in Nigeria, including among key populations, STI clinics, and PrEP entry points.<br /> Influence of Older Devices and Study Design on Applicability to Nigeria<br /> Lower pooled sensitivity estimates are largely driven by evaluations of older diagnostic devices and laboratory-based case–control studies. Approximately two-thirds of included studies rely on non-consecutive sampling, small AHI sample sizes (<100), and archived specimens—designs known to introduce spectrum and selection bias. For Nigeria, where HIV testing occurs primarily in real-world service delivery settings with operational constraints, such estimates may understate the potential performance of newer WHO-prequalified fourth-generation RDTs when integrated appropriately into national algorithms. Consequently, these findings should be interpreted cautiously when informing policy decisions, guideline updates, or pilot implementation of AHI screening in Nigeria.

    3. On 2025-12-24 04:25:36, user Dr Micah Matiang'i wrote:

      If the role of Ag/ab RDTs is not well understood in resource limited settings , then there is need to do more population based studies before WHO reaches a conclusion

    4. On 2025-12-19 17:14:16, user Cesar Ugarte wrote:

      The preprint by Fajardo et al. addresses an important evidence gap regarding the utility of combined antigen–antibody tests for detecting acute HIV infection. Although the authors adopt a valuable global perspective, the interpretation and synthesis of the data would benefit from greater nuance to enhance clinical relevance. The authors' QUADAS-2 assessment shows High Risk of Bias regarding patient selection and Unclear Risk regarding the conduct of the index test. In diagnostic epidemiology, such findings are not just descriptive but also signal a huge spectrum effect and possible threshold bias. Therefore, the summary estimates presented in Figures 3 and 4 may reflect a statistical average of disparate clinical realities rather than a reliable indicator of test performance (for example in Figure 3 there are 10 studies with a sensitivity less than 10%, including some with 0%, so the evaluation in detail of these studies should be done to see if these studies can be combined with the other ones). Another issue is the inclusion of "obsolete" diagnostic platforms that have been withdrawn due to suboptimal performance. A sensitivity analysis or subgroup stratification should be restricted to tests currently on the market. This would enable the reader to distinguish between the historical evolution of the technology and the expected performance in contemporary clinical practice.

      The interpretation of diagnostic performance also should be addressed in detail. Whereas sensitivity and specificity have usually been considered "intrinsic" to a test (so doesn´t depends on disease prevalence), evidence suggests significant variation across clinical settings. The underlying epidemiological status and operator expertise can affect the test’s accuracy. Finally, I agree with the authors that real-world evidence on cost-effectiveness and implementation barriers is lacking. However, we should be very careful to avoid having a biased meta-analytic estimate that leads to the premature abandonment of "imperfect" but viable diagnostic solutions. In the case of acute HIV infection, for which early detection is critical to ART initiation and reduction of secondary transmission, interpretation of this evidence needs to balance statistical rigor against the urgent public health need for early diagnosis.

    5. On 2025-12-17 21:30:43, user Norman Moore wrote:

      We have contacted the authors of the article Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection? A systematic review and meta-analysis of diagnostic performance by Fajardo et al. ( https://doi.org/10.1101/2025.10.14.25338004) . The primary limitation of this article is that it conflates the performance of 4th generation HIV tests that (1) were never launched, (2) that were earlier versions of tests that are no longer available in most parts of the world, and (3) tests that have received WHO pre-qualification (PQ), in a single analysis despite the known and significant differences in performance among them. This has resulted in lower performance representation of certain products over others. It would be more beneficial to the medical community to have a meta-analysis that includes HIV diagnostic tests that are both CE marked and have WHO PQ to maximize the real-world applicability of this systematic review.

    6. On 2025-12-13 03:02:23, user Missiani wrote:

      Title: Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection? A systematic review and meta-analysis of diagnostic performance<br /> Authors: Emmanuel Fajardo, Céline Lastrucci1, Pascal Jolivet1, Magdalena DiChiara1, Carlota Baptista da Silva1, Busi Msimanga1, Anita Sands2, Cheryl Johnson1

      The authors systematically searched six databases for studies evaluating Ag/Ab RDTs vs laboratory reference standards in individuals aged >=18 months. Out of 53 studies from 24 countries, they documented a pooled sensitivity of Ag/Ab RDTs for AHI to be 48% (95% CI: 34–62) with specificity of 97% (95% CI: 84–100). They concluded that Ag/Ab RDTs appear to have limited ability to detect AHI, missing more than half of AHI cases<br /> They also documented analytical sensitivity (detection of p24 antigen) at 31%, and antibody detection at 15% which was too low.

      I have three main comments that can improve the programmatic application of this manuscript <br /> 1. The study is presented negatively and concludes “Detection of AHI using Ag/Ab RDTs remains a challenge” despite the effort made and resources used. The study oversimplifies highly variable diagnostic data and assumes similarity between the studies, ignoring that a sensitivity of 48% and a specificity of 97% means that half of the kits performed better and almost all were specific. In Table 2, the authors examined region, study settings, and design, population, specimen, etc., but did not examine the group of kits whose sensitivity and specificity exceeded the pooled values. By examining this group of kits, they will successfully address the title of the article (Should antigen-antibody rapid diagnostic tests be used to detect acute HIV infection). Omitting this subgroup analysis presents one dimension of the data. We recommend they include this analysis as a way to address the gaps.<br /> 2. The authors present the p24 and Ag/Ab as a standalone approach rather than a combined or multiplex kit to address early diagnosis during AHI, which will provide an opportunity in low-income countries to reduce transmission, improve linkage to care and clinical outcome. Based on their sensitivity of 48%, multiplexing the test would improve diagnosis by the same margin, which is a substantial gain. We recommend adding a paragraph on the impact of incorporating p24 into a multiplex platform. Because many diagnostic tests are now packaged as multiplex platforms, incorporating this perspective will give the title greater depth and better reflect current testing practices<br /> 3. Some test kits reviewed in the study are either obsolete, recalled, or never progressed beyond early pre-evaluation stages. This raises significant concerns about the validity and current use of the findings. Manufacturers may have already recognized the kits’ poor sensitivity and, as a result, chose not to move forward with full production. Without acknowledging the discontinued or preliminary status of these kits, the study’s conclusions risk being misleading since the kits are not on the market. Recognizing the actual status of these products is essential, as it directly affects how their findings should be interpreted and whether they can responsibly inform policy or implementation decisions.

    1. On 2026-01-26 09:10:28, user Gail Davey wrote:

      The Neglected Tropical Diseases considered by the 2021-25 Ethiopian National Strategic Plan ( https://espen.afro.who.int/sites/default/files/content/document/Third%20NTD%20national%20Strategic%20Plan%202021-2025_0.pdf ) include podoconiosis. This is also considered among the skin-NTDs by WHO. Extensive information is available on the distribution and impact of podoconiosis, which has a greater burden than LF in Ethiopia. It would be helpful to include mention of this conditon within the manuscript.

    1. On 2026-01-23 19:44:39, user David Laursen wrote:

      Thanks for an interesting preprint, which I hope to read more carefully soon. I am not particularly well versed within causal inference so apologies if the question is unclear.

      I noticed your warning against conditioning on post-treatment belief (since it is a collider). Just wondering, does this reservation extend more generally to cautioning against testing for success of blinding at all, regardless of doing a stratified analysis of treatment effects by belief (in an estimation setting, this would probably be estimating differences in beliefs between arms, either with conventional 2x2 measures, or blinding indices). This appears to be a central discussion in many fields, so would appreciate your reflections.

    1. On 2026-01-19 13:00:58, user Gene C Koh wrote:

      Gene Ching Chiek Koh, Serena Nik-Zainal

      Department of Genomic Medicine, University of Cambridge, CB2 0QQ, UK.

      We commend Kanwal et al. for their timely evaluation of the in vivo mutagenic potential of CX-5461. This follows our report that CX-5461 induces substantial mutagenesis in cultured mammalian cells1. The authors analysed samples from four patients treated with CX-5461, including marrow aspirates, trephine biopsies, PBMCs, and skin lesions collected at early treatment timepoints (baseline; days 1, 2, or 9; and end-of-treatment of a 21-/28-day cycle), and used error-corrected duplex sequencing to detect low-frequency mutations. They concluded that CX-5461 exposure did not increase single-/ double-base substitution or indel burdens, nor reproduced the mutational signatures reported in our in vitro study. While we welcome their contribution, several methodological and interpretive shortcomings limit the conclusions that can be drawn.

      1. Data presentation<br /> Figures 1–3 present absolute mutation counts instead of frequencies normalized to total informative duplex bases per sample. In duplex sequencing, normalization is a basic requirement to account for variability in sequencing depth and library complexity; without it, true mutation accrual or fold-change differences versus controls (if any) cannot be assessed reliably.

      2. Experimental controls, assay sensitivity, and performance<br /> The study lacks essential positive and negative controls making it impossible to evaluate whether the sequencing and analytical processes used by the authors have worked. Clinical samples with known mutational signatures detectable through this approach should have been included to confirm assay sensitivity and substantiate a true negative finding. This is fundamental. Samples from patients unexposed to CX-5461 were also required as negative controls to establish background variability, affording confidence intervals and statistical robustness.<br /> Moreover, the authors have not shown awareness of the assay’s limit of detection (LOD). What is the smallest measurable fold-change at the reported sequencing depth? Without this, one cannot determine the smallest mutational differences that could have been missed. The authors have not disclosed quality-control metrics required to understand whether sufficient data quality was achieved for detecting differential mutagenesis. P/S: TwinStrand kit has an error rate ~0.5e-7 to 1e-7 depending on the protocols, and this can be considerably higher if DNA quality is low or from fixed biopsies.

      3. Lack of curation, comparisons to literature<br /> The reported mutation counts did not make sense (baseline values exceeding treated samples, patient samples sometimes lower than kit control). The authors should perform some ‘sanity check’ comparisons with published mutation frequencies of respective normal adult tissues from other duplex-sequencing studies2,3. Analytical rigour would include, for example, examining whether detected variants represent driver mutations from clonal haematopoiesis or occurred in genes under post-treatment selection. Such analyses would have demonstrated critical evaluation of data quality and biological relevance.

      4. Cell-type considerations, sampling window<br /> Most analysed compartments—PBMCs, MACS-sorted marrow fractions—are dominated by mature, non-dividing cells that rarely fix new mutations. A more relevant population for assessing mutagenicity is the haematopoietic stem and progenitor cells (HSPCs), typically <0.5% of marrow cells. A null result in the analysed compartments could just mean no widespread mutation fixation in mature immune cells; it does not exclude the possibility of mutagenesis in progenitors below the detection threshold of the current assay.<br /> In addition, samples were taken at very early timepoints (days 1, 2, 9, or EOT) of the first treatment cycle. At such intervals, mutagenic events are unlikely to have become fixed, as mutagen-induced DNA damage will need time to become embedded through DNA repair and replication. Exposure in terminally-differentiated cells might yield no detectable mutations. If exposure occurs on dividing cells, mutational footprints may only become detectable months or years after exposure. The current dataset lacks the temporal window necessary to assess cumulative in vivo mutagenicity.

      5. Expected evidence of prior treatments <br /> All four patients reportedly had “measurable, relapsed, or refractory advanced haematologic malignancies without any standard therapeutic options available”4. Although treatment histories were not provided, these patients likely received multiple prior therapies (e.g., doxorubicin, cyclophosphamide, etc) that could induce characteristic mutational signatures in normal haematopoietic cells5. Were signatures of prior therapy detected by the authors? Their absence raises concerns regarding the overall assay sensitivity and/or suggests that sampling strategy was suboptimal for detecting mutagenic exposures.

      6. Interpretation of model data<br /> While critical of our findings in cultured human cells as “not adequately representative of physiological human tissue” – a limitation we explicitly acknowledged in our manuscript’s title and discussion – the authors cited a C. elegans study6 in support of their argument of “low non-selective mutagenic potential of CX-5461”. This interpretation is incorrect: the worm study reported high copy-number aberrations, high SNV burdens, and a distinct A>T/T>A-rich signature after CX-5461 exposure, with survival requiring multiple repair pathways (homology-directed repair, microhomology-mediated end joining, nucleotide excision repair, and translesion synthesis). If anything, these cross-species findings reinforce rather than contradict our observations that CX-5461 is highly mutagenic. The concentrations used in that study were chosen to promote viability in the worms, not to minimise mutagenicity. Selective viability does not equate to selective mutagenicity.

      7. Clinical mutagenicity testing<br /> We agree that clinical safety assessments must be rigorous and physiologically relevant. The authors dismissed our experiments as not rivalling the “GLP-compliant, non-mutagenic” results of the CX-5461 drug development pathway. However, those mutagenicity data are not available in the public domain and have neither been shared by the authors nor the company that distributes CX-5461.

      We urge the authors to reconsider and not simply dismiss our findings. First, the primary clinical quality mutagenicity assay (required by agencies such as the US Food and Drug Administration (FDA), European Medicines Agency, and UK Medicines and Healthcare Regulatory Agency (MHRA)) referred to by the authors comprises the Ames test – a reverse gene mutation test performed in prokaryotes (e.g., E.coli, Salmonella).

      Second, according to the FDA’s ICH S2(R1) guidance for a standard battery of mutagenicity assays (Safety Implementation Working Group of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use), additional genotoxic assays should be performed in mammalian cells in vitro (where some of the more common assays include metaphase chromosome aberration assays, the micronucleus assay, and the mouse lymphoma L5178Y cell Tk (thymidine kinase) gene mutation assay (MLA)) or in in vivo studies as necessary.

      Third, the FDA guidance acknowledges that “no single test is capable of detecting all genotoxic mechanisms relevant in tumorigenesis” and that the standard battery serves primarily for hazard identification rather than comprehensive assessment of mutagenic potential. For negative in vivo results, the ICH S2(R1) guidance requires evidence of adequate target-tissue exposure (e.g., toxicity in the tissue, TK/PK data, or direct tissue concentrations) to validate interpretability. Without such data, negative findings have limited meaning, especially where in vitro systems demonstrate strong mutagenicity.

      Fourth, while the Ames test served its purpose for decades, there are well-described problems including false positives, false negatives and critically, a lack of human metabolism that even supplementation with rodent S9 mix cannot always overcome.

      Finally, a point also raised by the accompanying commentary to our publication is that perhaps the time has come to re-evaluate how mutagenicity assays are performed. Current assays cannot capture the genome-wide mutation patterns revealed by whole-genome sequencing in human cells, and as a community we should consider using unbiased, agnostic, modern genomic approaches capable of detecting all classes of mutational changes in human cells. This is not an attack on CX-5461; rather, it is a call to the community to consider re-evaluation of mutagenicity assays in drug development.

      8. Unsubstantiated claims<br /> The claim of potential contaminants accounting for the mutagenic outcomes we and others have observed is speculative and unsupported. The fact that multiple studies1,6 observed the same mutagenic outcomes using CX-5461 from independent sources suggests that this is unlikely. The authors showed no analytic chemistry (LC-MS/MS) and/or spiking experiments to substantiate this claim.

      9. Inadequate supporting material throughout <br /> There were many gaps in the methods/supporting information, including adequate clinical annotation, precise sampling times/total treatment cycle, and basic quality-control metrics. Experimental details (e.g., antibodies used for MACS sorting, essential for interpreting analysed subpopulations) were not provided. These omissions limit transparency, reproducibility, and the interpretability of the findings.

      10. Beneficence, non-maleficence, autonomy, justice<br /> First, in academia and medicine, we are guided by the principle of doing no harm. In identifying mutagenesis in experimental systems (an incidental finding), we acted in the best interest of the community – reporting an observation that could have an impact on patients and acknowledging the limitations of our system. We have no role in the (dis)continuation of clinical trials; we simply presented our data transparently and highlighted potential risk. <br /> Second, while the authors chose to discontinue their trial, several others remained active (e.g., NCT04890613, NCT06606990, NCT07069699, NCT07147231, NCT07137416). Their decision was conservative, and in our view, scientifically prudent. We commend their caution. However, it does not justify criticism of those of us reporting safety concerns in good faith.<br /> Third, as a community, we serve society better by being aware of issues, addressing the problems with robust experiments rather than polarising into groups “for” or “against” a compound, so that truly beneficial compounds can get to patients as quickly as possible. <br /> Finally, safety concerns may extend beyond mutagenesis and include tumour promotion effects. CX-5461’s interaction with TOP2B, for example, has been linked to serious, late-emerging toxicities, including therapy-induced leukaemia and cardiotoxicity7-10.

      Concluding remarks<br /> Given the experimental and analytical shortcomings outlined above, definitive conclusions regarding CX-5461’s in vivo mutagenicity cannot yet be drawn. The absence of evidence should not be taken as evidence of absence. Rigorous, longitudinal studies with appropriate controls and independent oversight are required to assess true medium- to long-term risks.

      We share the authors’ view that thorough, transparent evaluation of anticancer agents is essential. Given the authors’ vested interest in finding a negative result, we suggest independent individuals be involved in performing the analysis/interpretation of their studies to negate potential conflicts of interest. We remain open to collaboration in this effort, in the shared interest of patient safety and scientific integrity.

      1. Koh, G.C.C., Boushaki, S., Zhao, S.J., Pregnall, A.M., Sadiyah, F., Badja, C., Memari, Y., Georgakopoulos-Soares, I., and Nik-Zainal, S. (2024). The chemotherapeutic drug CX-5461 is a potent mutagen in cultured human cells. Nat Genet 56, 23-26. 10.1038/s41588-023-01602-9.
      2. Abascal, F., Harvey, L.M.R., Mitchell, E., Lawson, A.R.J., Lensing, S.V., Ellis, P., Russell, A.J.C., Alcantara, R.E., Baez-Ortega, A., Wang, Y., et al. (2021). Somatic mutation landscapes at single-molecule resolution. Nature 593, 405-410. 10.1038/s41586-021-03477-4.
      3. Machado, H.E., Mitchell, E., Obro, N.F., Kubler, K., Davies, M., Leongamornlert, D., Cull, A., Maura, F., Sanders, M.A., Cagan, A.T.J., et al. (2022). Diverse mutational landscapes in human lymphocytes. Nature 608, 724-732. 10.1038/s41586-022-05072-7.
      4. Khot, A., Brajanovski, N., Cameron, D.P., Hein, N., Maclachlan, K.H., Sanij, E., Lim, J., Soong, J., Link, E., Blombery, P., et al. (2019). First-in-Human RNA Polymerase I Transcription Inhibitor CX-5461 in Patients with Advanced Hematologic Cancers: Results of a Phase I Dose-Escalation Study. Cancer Discov 9, 1036-1049. 10.1158/2159-8290.CD-18-1455.
      5. Mitchell, E., Pham, M.H., Clay, A., Sanghvi, R., Williams, N., Pietsch, S., Hsu, J.I., Obro, N.F., Jung, H., Vedi, A., et al. (2025). The long-term effects of chemotherapy on normal blood cells. Nat Genet 57, 1684-1694. 10.1038/s41588-025-02234-x.
      6. Ye, F.B., Hamza, A., Singh, T., Flibotte, S., Hieter, P., and O'Neil, N.J. (2020). A Multimodal Genotoxic Anticancer Drug Characterized by Pharmacogenetic Analysis in Caenorhabditis elegans. Genetics 215, 609-621. 10.1534/genetics.120.303169.
      7. Pan, M., Wright, W.C., Chapple, R.H., Zubair, A., Sandhu, M., Batchelder, J.E., Huddle, B.C., Low, J., Blankenship, K.B., Wang, Y., et al. (2021). The chemotherapeutic CX-5461 primarily targets TOP2B and exhibits selective activity in high-risk neuroblastoma. Nat Commun 12, 6468. 10.1038/s41467-021-26640-x.
      8. Zhang, W., Gou, P., Dupret, J.M., Chomienne, C., and Rodrigues-Lima, F. (2021). Etoposide, an anticancer drug involved in therapy-related secondary leukemia: Enzymes at play. Transl Oncol 14, 101169. 10.1016/j.tranon.2021.101169.
      9. Cowell, I.G., Sondka, Z., Smith, K., Lee, K.C., Manville, C.M., Sidorczuk-Lesthuruge, M., Rance, H.A., Padget, K., Jackson, G.H., Adachi, N., and Austin, C.A. (2012). Model for MLL translocations in therapy-related leukemia involving topoisomerase IIbeta-mediated DNA strand breaks and gene proximity. Proc Natl Acad Sci U S A 109, 8989-8994. 10.1073/pnas.1204406109.
      10. Zhang, S., Liu, X., Bawa-Khalfe, T., Lu, L.S., Lyu, Y.L., Liu, L.F., and Yeh, E.T. (2012). Identification of the molecular basis of doxorubicin-induced cardiotoxicity. Nat Med 18, 1639-1642. 10.1038/nm.2919.
    1. On 2026-01-14 16:06:13, user Charles Tritt wrote:

      This is interesting and important work. However, the flaw I see in this study is that it included only 40 episodes of hypoxia (defined as a SpO2 of < 90%) out of 1760 measurements. Arterial saturation measurements are only clinically significant when they are significantly low, so the approach used doesn’t seem to answer the important question – are there systematic pulse ox errors that make a clinical difference?

      The linked protocols show induced hypoxia (I assume by subjects breathing air diluted with nitrogen). Of course, this couldn’t be done with critically ill patients. But I don’t see that the state of the patients being particularly important to the question of systematic pulse ox errors. Would it not be a better approach to test healthy individuals an induce hypoxia so their data set contains the clinically important information.

    1. On 2026-01-13 16:13:38, user Christine Stabell Benn wrote:

      Comment on “Non-specific effects of vaccines on all-cause mortality: a meta-analysis of randomized controlled trials (RCTs) 2012–2025”<br /> Christine Stabell Benn, Frederik Schaltz-Buchholzer, Sebastian Nielsen, Peter Aaby<br /> We commend the authors for addressing the important and contentious question of non-specific effects (NSEs) of vaccines on all-cause mortality. However, we have several major concerns regarding the framing, completeness, methodology, and interpretation of the preprint. Collectively, these issues undermine the conclusions drawn.

      1. Restricted research question and dismissal of large parts of the evidence baseThe authors explicitly restrict their review to randomized controlled trials (RCTs) published after the WHO review of non-specific effects(1). If the stated objective is to assess the evidence for NSEs on all-cause mortality in randomized trials, an updated meta-analysis incorporating all relevant RCTs, rather than an arbitrarily time-limited subset, would be more informative. The decision to exclude pre-2012 RCTs from the main analysis appears methodological rather than substantive and risks answering a narrow procedural question rather than addressing the broader scientific question.

      More importantly, NSEs represent a research area in which randomized trials are inherently difficult or impossible to conduct at scale, because the vaccines in question are already part of routine immunization schedules. As in other areas of public health - such as smoking, breastfeeding, or nutrition - causal inference therefore relies on triangulation across multiple study designs, including observational studies and natural experiments, supported by biological and immunological evidence.<br /> If the intention is to provide a meaningful update on the state of the evidence for NSEs, a comprehensive synthesis that acknowledges the strengths and limitations of all relevant study designs - or at minimum a clear and balanced justification for excluding them - is required.

      2. Incomplete identification of relevant randomized trialsDespite claiming a comprehensive search, the review misses several important randomized controlled trials that are directly relevant to NSEs, including recent RCTs published well within the stated search window (e.g. PubMed IDs: 39357573, 38350670, 33893799, 30256314). The omission of these trials raises concerns about the sensitivity of the search strategy and undermines confidence in the completeness of the evidence base.

      3. Extreme clinical and methodological heterogeneity invalidates the pooled meta-analysis<br /> The meta-analysis combines trials of three different vaccines (BCG, measles vaccine, and OPV) administered at vastly different ages (birth to 59 months), with follow-up periods ranging from days to five years, and using different randomization schemes and outcomes structures. This is not merely “heterogeneity,” but fundamentally different interventions addressing different biological hypotheses.

      Pooling these studies is not equivalent to combining “apples and bananas,” but rather apples and cars. The resulting pooled estimate does not correspond to a coherent causal treatment effect and is therefore not interpretable.

      4. Non-adherence with the WHO meta-analysis methodologyBy pooling all vaccines together, and furthermore by not focusing on the time window where a given vaccine is the most recent, the authors of the new meta-analysis violates the principles set out in the WHO meta-analysis, which emphasized vaccine-specific analyses and the importance of the most recent vaccine exposure.

      5. Overreliance on conservative confidence interval methods without adequate justificationThe authors emphasize the use of the Hartung-Knapp-Sidik-Jonkman (HKSJ) method as providing “more reliable and conservative control of type I error.” While HKSJ can be appropriate when few studies estimate the same underlying effect, its application here - given the very marked heterogeneity and conceptual incoherence of the pooled treatment effect - adds statistical conservatism without resolving the more fundamental problem of model misspecification. The resulting wide confidence intervals should not be interpreted as robust evidence against NSEs.

      6. Misinterpretation of heterogeneity statistics (I²)The statement that an I² of ~44% indicates that “approximately half the differences in the results are due to actual variations between studies” is misleading in this context. I² is meaningful only when studies estimate the same underlying causal association. When fundamentally different interventions are pooled, I² no longer has the interpretation implied by the authors.

      7. Speculation that early BCG effects are due to bias is unsubstantiatedThe manuscript repeatedly suggests that observed mortality reductions within the first 1–3 days after BCG vaccination may reflect bias due to lack of blinding. This speculation appears inconsistent with the design and reporting of the original trials. In Guinea-Bissau randomization occurred at discharge, and post-randomization care was not provided by study staff(2). In the Indian trial, the authors explicitly state that it is unlikely that the lack of blinding influenced the result. In previous open label randomized trials of BCG Russian strain in the same sites, no difference in neonatal mortality was found, which suggests that the lack of blinding did not bias the findings(3).

      Given these safeguards, attributing early effects to bias is unsupported by trial evidence and suggests that the original studies were not carefully read or adequately considered.

      8. Ignoring extensive mechanistic evidence for rapid BCG effectsThe authors further imply that effects within days are biologically implausible. This overlooks a substantial body of experimental and clinical evidence demonstrating that BCG induces trained innate immunity, including rapid functional reprogramming of myeloid cells and emergency granulopoiesis, which can occur within days and protect against severe infections such as sepsis(4, 5). These mechanisms provide a biologically coherent explanation for early effects and should have been discussed as plausible alternatives to bias.

      9. Failure to engage with established explanations for heterogeneous measles vaccine effectsThe manuscript notes heterogeneity across measles vaccine trials but does not engage with recent work offering compelling explanations for these differences, including interactions with OPV campaigns and vaccination sequence effects(6). Ignoring this literature leads to an oversimplified interpretation in which heterogeneity is treated primarily as noise rather than as potentially informative signal.

      10. Introduction of an a posteriori unifying hypothesisLate in the discussion, the authors invoke a new hypothesis that all live-attenuated vaccines should yield similar NSEs on all-cause mortality. This hypothesis appears post hoc and is not clearly justified biologically. It has never been a hypothesis within the NSE field and is biologically implausible, not least because baseline mortality differs substantially by age. Introducing this assumption only after the pooled analysis further weakens the inferential logic of the paper.

      Overall assessmentThe manuscript raises an important question, but its conclusions are undermined by:<br /> • an artificially restricted scope,<br /> • incomplete inclusion of relevant RCTs,<br /> • inappropriate pooling across fundamentally different interventions,<br /> • speculative dismissal of biologically plausible findings,<br /> • and inconsistent use of hypotheses introduced after the analysis.<br /> As currently written, the preprint does not provide a reliable basis for concluding that NSEs of vaccines on all-cause mortality are absent or unimportant. A substantially revised analysis - grounded in a comprehensive evidence base, clearer causal questions, and vaccine-specific syntheses - would be required to support such claims.

      References1. Higgins JP, Soares-Weiser K, Lopez-Lopez JA, Kakourou A, Chaplin K, Christensen H, et al. Association of BCG, DTP, and measles containing vaccines with childhood mortality: systematic review. BMJ. 2016;355:i5170.<br /> 2. Biering-Sorensen S, Aaby P, Lund N, Monteiro I, Jensen KJ, Eriksen HB, et al. Early BCG-Denmark and Neonatal Mortality Among Infants Weighing <2500 g: A Randomized Controlled Trial. Clin Infect Dis. 2017;65(7):1183-90.<br /> 3. Adhisivam B, Kamalarathnam C, Bhat BV, Jayaraman K, Namachivayam SP, Shann F, et al. Effect of BCG Danish and oral polio vaccine on neonatal mortality in newborn babies weighing less than 2000 g in India: multicentre open label randomised controlled trial (BLOW2). BMJ. 2025;390:e084745.<br /> 4. Kleinnijenhuis J, Quintin J, Preijers F, Joosten LA, Ifrim DC, Saeed S, et al. Bacille Calmette-Guerin induces NOD2-dependent nonspecific protection from reinfection via epigenetic reprogramming of monocytes. Proc Natl Acad Sci U S A. 2012;109(43):17537-42.<br /> 5. Brook B, Harbeson DJ, Shannon CP, Cai B, He D, Ben-Othman R, et al. BCG vaccination-induced emergency granulopoiesis provides rapid protection from neonatal sepsis. Sci Transl Med. 2020;12(542):eaax4517.<br /> 6. Nielsen S, Fisker AB, da Silva I, Byberg S, Biering-Sørensen S, Balé C, et al. Effect of early two-dose measles vaccination on childhood mortality and modification by maternal measles antibody in Guinea-Bissau, West Africa: A single-centre open-label randomised controlled trial. EClinicalMedicine. 2022;49:101467.

    1. On 2026-01-10 20:05:34, user Sequoia wrote:

      I'm interested in seeing if replacing the UPFs near the checkout with non-UPFs would result in an increase in non-UPFs consumption, especially if they were easy to eat with no preparation required (e.g. an apple or energy balls), and if so, by how much.<br /> I am delighted to know that research is being done on this critical subject.

    1. On 2026-01-09 08:47:36, user Janne Ruotsalainen wrote:

      The MVA vector is highly immunogenic as it has been used as a small pox vaccine. The ex vivo ELISPOT responses against MVA are pretty high raising the question whether the anti-vector T cell responses became immunodominant and thus suppressed some neoantigen specific T cell responses?

    1. On 2025-12-30 06:02:44, user James P wrote:

      Really nice, timely methods paper. It puts clear names and concrete examples on two ways biomarker studies can look better than they truly are in practice: (1) enrichment/range restriction, where you study a highly selected group and results don’t transport to typical patients, and (2) “double dipping,” where the same biomarker data influence who gets included and how performance is judged, which can inflate accuracy.

      I also appreciated how the audit plus the simple simulation experiments make the problems intuitive rather than abstract. The recommendations are practical (be explicit about the intended target population/estimand, and separate discovery from confirmation or prespecify analyses) and feel immediately useful for trial-ready cohorts and clinical workflows.

    1. On 2025-12-27 04:25:05, user Anjum wrote:

      Hi <br /> This manuscript has been published at <br /> John A, V R Reshma, El-Hazimy K. Bridging the Nutrition Education Gap: From Theory to Practice- A Scalable Model for Nutrition Practicums in Medical Training. Journal of Teaching Innovation and Reform. 2025;1:11-25.

    1. On 2026-03-25 16:26:02, user Kristina Jakobsson wrote:

      The outcome of this interesting study was the absolute change in eGFR from the start of the work shift to the end of the work shift.

      Cross-shift fluctuations of biomarkers are valuable for group-level evaluation of work-related kidney strain. S-Cr and S Cystatin C can rise significantly during a hot, labor-intensive shift and normalize overnight (1,2)

      However, eGFR should not be used for cross-shift comparisons, since eGFR assumes a stable level of creatinine over days (i.e., steady-state) (3) Hence, conventional eGFR calculations are not valid if creatinine is rapidly changing. S-Cr change is the preferred metric for cross-shift evaluations.

      An alternative for estimation of rapid functional changes during clinical AKI has also been suggested; the “Kinetic eGFR” (4).

      REFERENCES: <br /> 1. Lucas RAI, Hansson E, Skinner BD, Arias-Monge E, Wesseling C, Ekström U, Weiss I, Castellón ZE, Poveda S, Cerda-Granados FI, Martinez-Cuadra WJ, Glaser J, Wegman DH, Jakobsson K. The work-recovery cycle of kidney strain and inflammation in sugarcane workers following repeat heat exposure at work and at home. Eur J Appl Physiol. 2025 Mar;125(3):639-652. doi:10.1007/s00421-024-05610-3. Epub 2024 Oct 5. PMID: 39369140; PMCID: PMC11889006<br /> 2. Hansson E, Lucas RAI, Glaser JR, Weiss U, Ekström U, Abrahamson M, Wesseling C, Wegman DH, Jakobsson K. Understanding changes in serum creatinine during work in heat. Kidn Int Report vol 10 issue 8, p2860-63, Aug 2025. <br /> 3. Waikar SS, Bonventre JV. Creatinine kinetics and the definition of acute kidney injury. J Am Soc Nephrol. 2009;20: 672–679. doi: 10.1681/ASN.2008070669<br /> 4. Chen S (2013). Retooling the creatinine clearance equation to estimate kinetic GFR when the plasma creatinine is changing acutely. Journal of the American Society of Nephrology DOI: 10.1681/ASN.2012070653

    1. On 2025-12-05 05:35:16, user Evolutionary Health Group wrote:

      We at Evolutionary Health Group ( https://evoheal.github.io/ ) really enjoyed this paper.

      Here are our highlights:

      One of the strongest contributions is the introduction of a nonlinear null model of covariates that outputs a single scaler, which can be inserted into existing linear frameworks while adding the power of nonlinear modeling.

      The authors demonstrate that nonlinear covariate modeling consistently helps more than it harms: adding the null prediction rarely interferes with genetic inference and the gains are substantial for many traits, giving the method an encouraging risk-benefit profile.

      Instead of attempting to model exposures explicitly, the authors show that spatiotemporal information can capture complex environmental influences. Even though these features are non-causal, researchers can use such data to hypothesize environmental drivers without having to specify them individually in models.

      Using TreeSHAP-IQ, the authors show that nonlinear models find age-sex, seasonality-sex, and birth-home location interactions. These patterns are biologically credible and validated by external literature but cannot be captured by standard linear covariate adjustments. This shows that nonlinear covariate modeling doesn't just improve predictions, it produces interpretable biological insights.

    1. On 2020-04-03 17:14:59, user Paula Thompson wrote:

      OK. While I do like to look at data, I don't understand comments abt this being too simplistic. Are the data too simple, and not fitting reality well, or are they good? Thanks for help.

    1. On 2022-12-15 21:37:06, user Yiwen Zhu wrote:

      This paper has now been published in Neuroscience & Biobehavioral Reviews Volume 143, December 2022, 104954 (doi: 10.1016/j.neubiorev.2022.104954). Please update the link if possible, thank you! <br /> - Yiwen Zhu

    1. On 2020-04-06 01:21:26, user iggy wrote:

      TLDR; Does Coronavirus lower the testosterone of those who survived it, long term? <br /> What percentage of men who had Covid-19 is affected by lowered testosterone? <br /> How much is it lowered?

    1. On 2020-04-23 17:59:14, user El Ray wrote:

      You can only measure what makes it into a sample. Comparing different assays on the same samples is the most informative approach.

    1. On 2020-07-23 11:59:38, user Mr C S Mence wrote:

      All the researchers seem to be north of the equator. Is there any data from countries south of the equator who have experience of the pandemic through their winter months

    1. On 2020-04-21 23:43:04, user docmeehan wrote:

      I'm not sure VA database born retrospective cohort analysis that declines to reveal drug dosing protocols contributes much to the science. Let's have those drug dosing protocols.

    1. On 2020-06-08 21:08:42, user Paul Gordon wrote:

      Hi, nice work. I notice that NRW-11 is reported in the supplementary tables, but is the only genome missing in GISAID. Was it withdrawn due to quality or was there an oversight in the submission? Thanks!

    1. On 2021-12-27 21:14:28, user Danes wrote:

      Any comment on the huge discrepancy in pre-risk between vaccine and COVID groups in Table 1? Does not seem to be appropriate for this type of comparison.

    1. On 2022-01-01 14:56:50, user Jeffrey_S_Morris wrote:

      Nice study! For completeness, it would be nice if table 3 included the transmissibility odds ratios for vaccination statuses stratified by variant

    1. On 2020-06-15 02:32:20, user Sinai Immunol Review Project wrote:

      Main findings<br /> Sex-based differences in the immune response have been reported for various types of infections. There is a growing body of epidemiological evidence that supports the finding that men experience more severe COVID-19 disease than women do, but the immune mechanisms underscoring such a difference remain unknown.

      Here, Takahashi et al. analyze PBMCs, plasma, and nasopharyngeal swabs or saliva from 93 mild-to-moderate COVID-19 patients (n=93), comprised of 48 women (n=48) and 45 men (n=45), to characterize potential sex-based differences in the immune response to SARS-CoV-2 infection. It is important to note that patients on hydroxychloroquine and Remdesivir were not excluded from a sub-cohort of patients (n=39) evaluated as baseline measures for untampered immune responses to SARS-CoV-2 (these patients were not treated prior to first sample collection). In a second sub-cohort, 54 patients were assessed longitudinally for an undisclosed amount of time. Samples from uninfected healthcare workers were used as controls.

      Viral Load (nasopharyngeal or saliva samples)<br /> No significant differences were identified between male and female patients. Still, median viral RNA was higher in male patients at first sample collection and generally throughout disease course.

      Antibody production (plasma samples)<br /> Anti-SARS-CoV-2 S1 protein-specific IgG and IgM antibodies were measured in the plasma of male and female patients. Though anti-S1-IgG antibodies were higher in female patients, compared to male patients, no significant differences could be identified either in the baseline cohort or in longitudinal patients.

      Cytokine analysis (plasma samples)<br /> Among baseline patients, who had not received immunomodulatory therapy prior to sample collection (except hydroxychloroquine), type I/II/III IFN levels were not significantly different between male and female patients. However, IL-8 was significantly higher in male than in female patients. Of note, among longitudinally evaluated patients, CCL5 levels were significantly higher in male than in female patients. CXCL10 levels show a similar trend, though this was not significant.

      Immune cell landscape (PBMCs)<br /> Both male and female patients exhibited a reduction among T cells and an increase in B cells. No significant differences in T cell subtypes (naïve, central/effector memory, follicular, regulatory) were observed between male and female patients. Of note, however, female patients showed (1) a significantly greater proportion of CD38+HLA-DR+ activated CD8+ T cells and (2) a concomitant enrichment of PD-1+TIM-3+ terminally differentiated T cells, compared to male patients. Otherwise, no other significant differences were identified between male and female patients.

      The authors subsequently interrogated the peripheral myeloid compartment. Female patients showed a greater increase in CD14+CD16+ intermediate monocytes than male patients, while both patients exhibited a marked increase in total monocytes, compared to the controls. However, male patients showed higher levels of CD14loCD16+ non-classical monocytes than female patients and their uninfected, healthy counterparts. The authors noted that this enrichment of non-classical monocytes was correlated with CCL5 levels only in male patients.

      Clinical comparison<br /> Clinical outcomes were tracked for both male and female patients. Clinical scoring was used to separate each group into two sub-groups: patients that had remained stable throughout hospital stay (stabilized) and patients that had worsened since the first sample collection (deteriorated). Deteriorated male patients were significantly older than stabilized male patients; there was no significant difference in age between stabilized and deteriorated female patients. In terms of BMI, both deteriorated male and female patients tended to be higher in BMI than their respective stabilized counterparts. Interestingly, anti-S1-IgG antibodies were higher in stabilized female patients than their deteriorated counterparts, though this trend was not seen with male patients. Otherwise, no other significant differences in clinical parameters were observed.

      Additional comparisons between deteriorated and stabilized patients of each sex revealed that certain innate cytokine mediators (TNFSF10 and IL-15) associated with worse outcome in female patients but not in male patients. In contrast, the proportion of CD38+HLA-DR+ activated CD8+ T cells was significantly reduced in deteriorated male patients compared to their stable counterparts, but this was not true for female patients. Indeed, poor CD8+ T cell activation and IFN? production were both negatively correlated with age in male patients, but not in female patients.

      Limitations<br /> • A significant number of patients were diagnosed with underlying chronic conditions that have been previously described to associate with poorer COVID-19 outcomes or with a compromised immune system. <br /> • Approximately two-thirds of each group (men and women) were treated with tocilizumab, and nearly a sixth of each group were treated with corticosteroids. While these patients were excluded from the baseline cohort, it is unclear whether or not these patients contributed to the second cohort that was longitudinally examined.<br /> • The mean age for patients is notably higher than the mean age for the HCW control group.<br /> • Duration of hospital stay was not considered, so it is unclear how quickly certain subsets of male and female patients deteriorated. This may be a confounding variable, or at the very least, the kinetics of disease course in male and female patients is a parameter that warrants investigation.

      Significance<br /> In summary, Takahashi et al. provide the first report-to-date that delineates immunological differences between male and female patients with mild-to-moderate COVID-19 disease during the initial stages of infection. For example, male patients deteriorate due to less robust T cell-mediated antiviral immunity, compared to their female counterparts. Several of the other findings substantiate previous reports, such as those of significant neutrophil chemotaxis in the lung of COVID-19 patients (and its association with poorer prognosis). This study, therefore, provides an important platform for additional inquiries into key signaling pathways and transcriptional programs that are differentially regulated between male and female COVID-19 patients by specific cell types (i.e. intermediate and non-classical monocytes, CD38+HLA-DR+ CD8+ T cells) identified in this report. These studies, alongside others, are warranted to better tailor therapies for male and female COVID-19 patients.

      This review was undertaken by Matthew D. Park as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

    1. On 2020-07-11 04:42:51, user Tom Jarman wrote:

      the authors reached the conclusion that masks do not have a significant difference in person-to-person transmission for influenza-like illnesses, yet they still recommend use of masks. What am I missing here?

    1. On 2022-01-06 23:28:48, user Greg Nelson wrote:

      This is encouraging, would love to see another paper comparing to the PCR negative population (2346 respondees - 951 with PCR positive (study population) = 1395 people) to see baseline frequency of symptoms

    1. On 2020-08-24 05:59:23, user Jala Painter wrote:

      If hydroxychloroquine is dangerous as a treatment for COVID19 will a lupus patient have to go off his Plaquenil medication if he contracts COVID19?

    1. On 2020-08-24 17:50:51, user Puvvada Rahul krishna wrote:

      We would like to withdraw the article from MedRxiv. The reason for withdrawal was plagiarism issue while publishing to other journal's

    1. On 2020-08-25 20:28:59, user Jean Sanders wrote:

      this is very valuable information; I am trying to process the data so I will be informed when we have meetings this week on school re-opening... Thank you for this fine work and the many references

    1. On 2020-09-05 11:35:05, user Tricia Young wrote:

      Thank you for providing statistics that are more consistent with what is really happening. Will this article be published?

    1. On 2020-05-13 03:36:31, user Annalisse Mayer wrote:

      But what about the people who died suddenly at home and never made it to the hospital? How many of them were smokers? Maybe being able to get to the hospital means one is better at resisting the infection

    1. On 2022-02-12 20:26:12, user Jan Lakota wrote:

      This paper is in concert with the presented findings:<br /> New diagnosis of multiple sclerosis in the setting of mRNA COVID-19 vaccine exposure

      J Neuroimmunol. 2022 Jan 15;362:577785. doi: 10.1016/j.jneuroim.2021.577785.

    1. On 2020-03-25 22:19:11, user Sinai Immunol Review Project wrote:

      Title

      Detectable serum SARS-CoV-2 viral load (RNAaemia) is closely associated with drastically elevated interleukin 6 (IL-6) level in critically ill COVID-19 patients

      Keywords

      ARDS; interleukin-6 (IL-6); procalcitonin (PCT); pro-inflammatory cytokines; SARS-CoV-2 RNAaemia

      Key findings

      48 adult patients diagnosed with Covid19 according to Chinese guidelines for Covid19 diagnosis and treatment version 6 were included in this study. Patients were further sub-divided into three groups based on clinical symptoms and disease severity: (1) mild, positive Covid19 qPCR with no or mild clinical symptoms (fever; respiratory; radiological abnormalities); (2) severe, at least one of the following: shortness of breath/respiratory rate >30/min, oxygen saturation SaO2<93%, Horowitz index paO2/FiO2 < 300 mmHg (indicating moderate pulmonary damage); and (3) critically ill, at least one additional complicating factor: respiratory failure with need for mechanical ventilation; systemic shock; multi-organ failure and transfer to ICU. Serum samples and throat-swaps were collected from all 48 patients enrolled. SARS-CoV-2 RNA was assessed by qPCR with positive results being defined as Ct values < 40, and serum interleukin-6 (IL-6) was quantified using a commercially available detection kit. Briefly, patient characteristics in this study confirm previous reports suggesting that higher age and comorbidities are significant risk factors of clinical severity. Of note, 5 out of 48 of patients (10.41%), all in the critically ill category, were found to have detectable serum SARS-CoV-2 RNA levels, so-called RNAaemia. Moreover, serum IL-6 levels in these patients were found to be substantially higher and this correlated with the presence of detectable SARS-CoV-2 RNA levels. The authors hypothesize that viral RNA might be released from acutely damages tissues in moribund patients during the course of Covid19 and that RNaemia along with IL-6 could potentially be used as a prognostic marker.

      Potential limitations

      While this group’s report generally confirms some of the major findings of a more extensive study, published in early February 2020, (Huang C et al, Lancet 2020; 395:497-506; https://www.thelancet.com/a... "https://www.thelancet.com/action/showPdf?pii=S0140-6736%2820%2930183-5)"), there are limitations that should be taken into account. First, the number of patients enrolled is relatively small; second, interpretation of these data would benefit from inclusion of information about study specifics as well as providing relevant data on the clinical course of these patients other than the fact that some were admitted to ICU (i.e. demographics on how many patients needed respiratory support, dialysis, APACHE Ii/III or other standard ICU scores as robust prognostic markers for mortality etc). It also remains unclear at which time point the serum samples were taken, i.e. whether at admission, when the diagnosis was made or during the course of the hospital stay (and potentially after onset of therapy, which could have affected both IL-6 and RNA levels). The methods section lacks important information on the qPCR protocol employed, including primers and cycling conditions used. From a technical point of view, Ct values >35 seem somewhat non-specific (although Ct <40 was defined as the CDC cutoff as well) indicating that serum RNA levels are probably very low, therefore stressing the need for highly specific primers and high qPCR efficiency. In addition, the statistical tests used (t-tests, according to the methods section) do not seem appropriate as the organ-specific data such as BUN and troponin T values seem to be not normally distributed across groups (n= 5 RNAaemia+ vs. n= 43 RNAaemia-). Given the range of standard deviations and the differences in patient sample size, it is difficult to believe that these data are statistically significantly different.

      Overall relevance for the field

      This study is very rudimentary and lacks a lot of relevant clinical details. However, it corroborates some previously published observations regarding RNAemia and IL-6 by another group. Generally, regarding future studies, it would be important to address the question of IL-6 and other inflammatory cytokine dynamics in relation to Covid19 disease kinetics (high levels of IL-6, IL-8 and plasma leukotriene were shown to have prognostic value at the onset of ARDS ; serum IL-2 and IL-15 have been associated with mortality; reviewed by Chen W & Ware L, Clin Transl Med. 2015).

      Reviewed as part of a project by students, postdoctoral fellows and faculty at the Immunology Institute of the Icahn School of Medicine at Mount Sinai

    1. On 2020-10-22 15:04:33, user BB_Aragon wrote:

      Table 6 in the supplementary material appears to be another copy of the text. Could the author please replace this with the actual Table 6?

    1. On 2022-05-03 19:26:37, user Carol Taccetta, MD, FCAP wrote:

      The MMIA assay used here comes from the same institution as the authors--the reference states it is under a provisional patent.

    1. On 2022-10-23 23:35:14, user Aditya Awasare wrote:

      I really enjoyed reading the paper and it is amazing to see what the future of diagnosis and disease modelling could one day be. I was really curious about the criteria used for the definition and classification of signs and symptoms but could not find the attached supplemental tables. Also, since one of the factors that makes the diagnosis of neurological diseases so hard is the presence of comorbidities, can this model be extended to detect their presence? What would the training data look like for this or how would the signs and symptoms classification be modified to accommodate this?

    1. On 2022-11-10 09:21:51, user Clive Bates wrote:

      Please see our post-publication peer review of this pre-print published at Qeios.

      Bates, C., Youdan, B., Bonita, R., Laking, G., Sweanor, D., & Beaglehole, R. (2022). Review of: “Tobacco endgame intervention impacts on health gains and Maori:non-Maori health inequity: a simulation study of the Aotearoa-New Zealand Tobacco Action Plan.” Qeios DOI 10.32388/8WXH0J

      The paper, Ouakrim et al., refers to modelling of proposed New Zealand legislation that would make deep reductions in the nicotine in cigarettes. The review notes that the authors have assumed this will lead to an 85% reduction in smoking over five years, with almost one-third of smokers quitting in each year. Our Qeios review examines the origins and credibility of that assumption.

      We identify ten flaws in the modelling and stress that the smoking cessation trial on which its assumptions are largely based is not a viable proxy for assessing the impact of a market-wide regulatory intervention. The modelling does not simulate the most likely behavioural responses that would follow from such an intervention and does not address plausible unintended consequences such as illicit trade, hoarding or workarounds..

      I should stress that this review of the modelling is not intended as a decisive argument against the proposed denicotinisation policy. It is, however, an argument against relying on this modelling to justify the policy. There are other considerations both for and against the policy.

      Our review should be seen as a constructive contribution to sound policy-making. Decision makers should should proceed without over-reliance on modelling, knowing its limitations, possible risks and likely unintended consequences. The reveiw authors have not explicitly opposed the measure but suggested it needs to be re-evaluated: <br /> (1) with a deeper assessment of the risks of unintended consequences; <br /> (2) against a maximalist approach to voluntary tobacco harm reduction as the counterfactual (not just business as usual); <br /> (3) a better understanding of how it will work for the most disadvantaged people and communities.

    1. On 2022-11-11 09:33:21, user S Venkata Mohan wrote:

      This article was published with the following citation

      Surveillance of SARS-CoV-2 genome fragment in urban, peri-urban and rural water bodies: a temporal and comparative analysis<br /> p. 0987 | Hemalatha, Manupati; Tharak, Athmakuri; Kopperi, Harishankar; Kiran, Uday; Gokulan, C. G.; Mishra, Rakesh K.; Mohan, S. Venkata doi: 10.18520/cs/v123/i8/987-994.

      Due to DOI issue we are not able to link

    1. On 2022-11-26 16:52:14, user Miles Markus wrote:

      This analysis by expert mathematicians is very welcome because as they state: "Understanding the cause of recurrent vivax malaria is critical for disease control efforts …".

      Homology in relation to Plasmodium vivax malarial recurrences is a core concept in this interesting paper. A complication as regards interpreting the origin of recurrences caused by homologous parasites has recently arisen because there has been a paradigm shift in our understanding of P. vivax biology. The bulk of the P. vivax parasite biomass in chronic infections is now known to be located outside the peripheral bloodstream and liver; and more recurrences might be recrudescences (as opposed to relapses – there being comparatively few hepatic hypnozoites present) than meets the eye [1].

      Light should soon be shed upon the matter. This is when it becomes apparent, from experiments using humanized mice, whether or not primaquine kills non-circulating asexual stages in bone marrow [2]. The prevailing idea in the literature is that most recurrences of P. vivax malaria are relapses, which is not necessarily correct (although it could be). That conclusion has been drawn mainly from recurrence patterns following treatment of patients that included primaquine.

      It is hoped that once the forthcoming new information related to parasite homology has become available via drug testing, the authors of this medRxiv article will be able to further extend their important analyses to take account thereof.

      REFERENCES:<br /> 1. Markus MB. 2022. Theoretical origin of genetically homologous Plasmodium vivax malarial recurrences. Southern African Journal of Infectious Diseases 37 (1): 369. https://doi.org/10.4102/saj...<br /> 2. Markus MB. 2022. How does primaquine prevent Plasmodium vivax malarial recurrences? Trends in Parasitology 38 (11): 924–925. https://doi.org/10.1016/j.p...

    1. On 2023-01-03 01:06:03, user Myssi Graves wrote:

      How can they say it was unexpected that increased doses would increase risk when there’s decades of evidence of this with flu vax. It was an obvious outcome to anyone educated on the topic. Sadly anyone who mentioned this possibility was vilified.

    2. On 2023-01-07 03:30:19, user loki4loki wrote:

      The authors have a new definition of effectiveness. I thought a vaccine was effective if it prevented hospitalization and death. Now they have changed the goal posts. No wonder the Browns are having a bad year.

    1. On 2023-02-02 06:20:07, user Dr. Albert wrote:

      Thank you for such an amazing paper! Your paper provides novel insight into non-invasive COVID-19 detection method, which has the potential to be implanted worldwide. To strengthen this paper even more, I would suggest some edits for your introduction/discussion section. It would be great to incorporate the advantage and disadvantage of recently used detection methods followed by how your model overcomes the caveats of pre-existing detection methods. Also, a very recent preliminary paper from University of Toronto hypothesized the application of Raman scattering along with fluorescence resonance energy transfer to detect COVID-19 using the breath! It might be worthful for you to mention about it in the paper as one of the emerging technique along with its pros and cons relating to your detection method.

      Here is the link to that paper: https://www.tmrjournals.com...

    1. On 2023-02-27 14:29:13, user Katka2507 wrote:

      Thank you for sharing your data. I have a few questions. <br /> When did the patients start to complain about the symptoms indicating endophthalmitis? I could only read the information about the post catarct surgery period when you started a treatment. We also have to think of TASS.<br /> Did you counted as endophthalmitis only patients with positive cultures or all with symptoms? It is often difficult to take a vitreous sample but all of the symptoms indicate the endopthalmitis.

    1. On 2023-03-07 04:37:46, user Ted Gunderson wrote:

      July 2021 had more covid19 deaths than any other month in Rwanda.

      This was after 80% of the population was injected with the covid19 vaccines.

      African countries with significantly lower vaccination rates had significantly lower covid19 mortality rates.

      Why doesn't this paper address this?

    1. On 2023-04-02 19:09:38, user GL wrote:

      This systematic Review is lacking of protocol in PROSPERO. It says that follow PRISMA guidelines but it does not.

      Therefore the findings are biased.

      I would recommend the authors to follow more rigorously the PRISMA 2020 Guidelines or in case delete the term "systematic".

    1. On 2023-04-14 09:15:23, user Alexander Kastaniotis wrote:

      Very nice work! A comment on lipoic acid: <br /> lipoic acid does enter mitochondria, and it is used in standard mitochondrial disorder treatment cocktails, where it works as a potent antioxidant. However, in contrast to some prokaryotic lipoylation systems, mitochondria lack the machinery to activate free lipoic acid for attachment to pyruvate dehydrogenase, alpha-ketoglutarate dehydrogenase E2 subunits etc. When mitochondria are equipped with a lipoic acid activating enzyme, externally supplied lipic acid can be used for attachment. Please have a look at our work: <br /> Pietikäinen et al 2021: Genetic dissection of the mitochondrial lipoylation pathway in yeast. doi: 10.1186/s12915-021-00951-3<br /> It may also be worth noting that the complete KO of Mecr in mice causes embryonic lethality (Nair RR et al 2017; doi: 10.1093/hmg/ddx105)

    1. On 2023-04-19 11:20:18, user Jonas Reinold wrote:

      Page 6: "Current management of BD consists largely of pharmacological interventions, and the use of highly anticholinergic drugs has increased over the past 25 years (Reinold et al., 2021; Sumukadas et al., 2014)" The paper from Reinold et al is a cross-sectional study that reports prevalences of anticholinergic burden in Germany for a single year, it does not report any changes over time. The paper from Sumukadas is based on two cross-sectional analyses in 1995 and 2010 and does not say anything about an increase "over the past 25 years". Please revise the citations.

    1. On 2023-04-27 15:33:25, user Anshu Varma wrote:

      Dear Vincent Auvigne

      I hope this e-mail finds you well.

      My colleagues and I at the World Health Organization are<br /> intrigued by your study in France on the vaccine effectiveness of bivalent boosters compared to monovalent boosters against symptomatic SARS-coV-2 disease, among adults aged >60 years. Your work is timely, so we would be highly appreciative if you could help us improve our understanding of the study.

      We acknowledge that baseline characteristics did not differ<br /> between groups, but we wonder if the recommendation for bivalent boosters and<br /> monovalent boosters may have been different and would like to know your<br /> thoughts on that.

      Do you know why the bivalent booster was offered concurrently with the monovalent booster between 03/10/2022 and 06/11/2022 in the study area?

      Do you know who the bivalent booster was recommended to<br /> between 03/10/2022 and 06/11/2022 in the study area?

      Do you know who the monovalent booster was recommended<br /> to between 03/10/2022 and 06/11/2022 in the study area?

      Thank you very much in advance and looking forward to hearing from you.

      All the best

      Anshu Varma

      Technical Officer,<br /> COVID-19 Vaccine Effectiveness, Impact<br /> Department of Immunization, Vaccines & Biologicals (IVB)<br /> Universal Health Coverage/Lifecourse Division<br /> World Health Organization, Geneva, Switzerland<br /> varmaa@who.int

    1. On 2023-05-18 18:59:30, user Dave Fuller wrote:

      Please add peer-reviewed citation as:

      Wahid KA, Lin D, Sahin O, Cislo M, Nelms BE, He R, Naser MA, Duke S, Sherer MV, Christodouleas JP, Mohamed ASR, Murphy JD, Fuller CD, Gillespie EF. Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites. Sci Data. 2023 Mar 22;10(1):161. doi: 10.1038/s41597-023-02062-w. PMID: 36949088; PMCID: PMC10033824.

      Thanks!

    1. On 2023-06-14 10:46:05, user Sayomporn Sirinavin wrote:

      The title of the published version was changed by adding a word "nonimmune". <br /> The revised title is:

      Effect of Andrographis paniculata treatment for nonimmune patients with early-stage COVID-19 on the prevention of pneumonia: A retrospective cohort study.

    1. On 2023-06-15 06:08:48, user Ashok Palaniappan wrote:

      A peer-reviewed version of the preprint has now been published:<br /> Muthamilselvan S and Palaniappan A (2023) BrcaDx: precise identification of breast cancer from expression data using a minimal set of features. Front. Bioinform. 3:1103493. doi: 10.3389/fbinf.2023.1103493

    1. On 2023-07-01 05:57:09, user Zhaolong Adrian Li wrote:

      Published as Li ZA, Cai Y, Taylor RL, et al. Associations Between Socioeconomic Status, Obesity, Cognition, and White Matter Microstructure in Children. JAMA Netw Open. 2023;6(6):e2320276. doi:10.1001/jamanetworkopen.2023.20276

    1. On 2023-08-22 14:47:23, user SRamin wrote:

      I wonder if there is something different about individuals who get the bivalent vaccine versus individuals who do not that may explain the outcome observed in this study. <br /> 1) For example, perhaps individuals who received the bivalent vaccine work in a "higher risk" environment (ex. Doctors and nurses with direct patient contact) and those who did not get the bivalent vaccine worked in a "lower risk environment" (housekeeping/sanitation/cafeteria workers/laundry services). Perceived occupational risk would self-select for the exposure of interest and if perceived occupation risk matches actual risk then we would expect that bivalent vaccinated individuals would experience higher incident covid-19 rates because of higher risk of exposure. I see that one of the covariates of interest was "job location" which I presume refers to the physical location of employment in Ohio, but I think it is important to collect data on employee job type (direct patient contact vs indirect patient contact) and adjust for this in the multivariate models. <br /> 2) Another potential explanation for these results could be that individuals who received the bivalent vaccine versus those who did not had perceived an added protection and were more willing to place themselves in "riskier situations" for contracting COVID (perhaps bivalent vaccine recipients are more likely to eat out at restaurants or shop in public because of perceived added protection) or they may have felt less inclined to follow other COVID-19 infection prevention methods (less likely to wear masks or wash hands because of perceived protective benefit from the vaccine).

    1. On 2023-09-12 09:30:17, user Chris Iddon wrote:

      This paper conflates SARS-CoV-2 genome copies (ie RNA) with viable virions on page 14. Data from the human challenge studies suggests that there are between 100 to 10,000+ RNA copies to a viable virion and thus the authors are overestimating the transmission potential and infection risk. Please see Killingley et al doi 10.1038/s41591-022-01780-9 and Zhou et al doi 10.1016/S2666-5247(23)00101-5<br /> Also what is the limit of detection for the RT-PCR assay? How much of the total eluate was used in a single assay?

    1. On 2023-10-17 03:28:40, user CDSL JHSPH wrote:

      Dear Dr. Bi et. al., <br /> I would like to express my appreciation for your preprint. This preprint provides valuable insight into the phenomenon of declining effectiveness of repeated flu vaccinations. n this influenza pandemic season, it is important to have in-depth research on the issue of the effectiveness of the influenza vaccine. Your study provides timely insights. You used real-world data covering multiple seasons, which demonstrates a comprehensive understanding of vaccination and infection.

      However, I have some comments and questions that I hope will help improve the paper and deepen my understanding of the study. The discussion of potential causes of reduced vaccine effectiveness was insightful. However, it may be useful to discuss the practical implications of these findings for vaccination policies and recommendations. How might this research guide public health decision-making? Would age be one aspect that might influence the reduced effectiveness of repeat vaccination? As age often plays a role in immune responses. <br /> Furthermore, I encourage you to include a section on future directions, highlighting potential areas of research or specific questions that have emerged from this study. This could inspire further investigations in the field of influenza vaccine effectiveness. To enhance the clarity of your work, I also suggest incorporating a clear statement in the abstract or introduction section that succinctly outlines the problem your research aims to address. This would assist readers in swiftly understanding the primary focus of your study.<br /> Overall, your preprint is valuable and thought-provoking, and I look forward to seeing how it progresses in terms of publication and further research.

    2. On 2023-10-24 03:42:50, user Prasad Babar wrote:

      Dear Dr. Bi et al,<br /> This preprint provides valuable insights into the declining effectiveness of repeat flu vaccinations, addressing a critical issue in influenza vaccine effectiveness. The use of real-world data and the exploration of factors such as vaccination timing and prior clinical infections is commendable. The paper's significance lies in its contribution to understanding complex factors affecting vaccine efficacy.<br /> The robust methodology, including the use of observational data and logical theoretical modeling of subclinical infections, supports the paper's conclusions. However, the absence of data on subclinical infections is a notable limitation, and the paper should acknowledge this gap more explicitly and discuss its potential implications for the conclusions.<br /> While the paper is generally well-presented, a simple illustration of the modelling approach would enhance accessibility. <br /> The lessons regarding the influence of the immune system, the importance of monitoring subclinical infections, and the need for empirical studies on subclinical infection rates are valuable. Further research in these areas and the development of future research directions should be emphasized.<br /> Overall, this preprint makes a substantial contribution to the field, challenging conventional vaccine efficacy assessment and emphasizing the potential role of subclinical infections. It provides important insights while acknowledging the need for empirical data on subclinical infections and a more explicit discussion of limitations and practical implications.

    1. On 2024-01-03 10:54:03, user Andres Ceballos wrote:

      This paper has been publised on Frontiers. Cell. Infect. Microbiol journal:

      Emergence and circulation of azole-resistant C. albicans, C. auris and C. parapsilosis bloodstream isolates carrying Y132F, K143R or T220L Erg11p substitutions in Colombia https://doi.org/10.3389/fci...<br /> Front. Cell. Infect. Microbiol., 21 March 2023<br /> Sec. Fungal Pathogenesis<br /> Volume 13 - 2023

    1. On 2024-02-09 18:56:46, user Adriano Aguzzi wrote:

      It was brought to my attention that this manuscript contains an error. In Figure 2D, the band representing tau immunoreactivity is duplicated between the 2nd and the 10th lane. The raw data of the uncropped blot from which Figure 2D is derived (Supplemental Fig. S1) provides the correct images. The transposition error in Fig. 2D has no impact on the interpretation of the results and will be corrected in a future version of this manuscript. Adriano Aguzzi

    1. On 2024-02-26 17:16:20, user Ciarán McInerney wrote:

      Please, justify why<br /> you use a 1:4 ratio for matching. Is this representative of the true<br /> prevalence? Perturbing the true prevalence is only valid for control<br /> experimental studies, not for observational studies. Note that some of the<br /> statistics you use to evaluate your predictive model are affected by the<br /> prevalence of the outcome, so arbitrarily fixing it invalidates their<br /> interpretation as real-world evaluations (specifically, NPV and PPV, which are<br /> the canonical statistics for evaluating prediction).

    1. On 2024-03-05 20:40:49, user Calum Polwart wrote:

      An interesting approach to analysis, and good use of cross sector data.

      I'd be interested to know if the authors considered use the the WHO ATC defined daily doses for calculation of their prescription numbers. Ideally they should provide an explanation to the 5d course length.

      A couple of minor issues:

      1. The version of R is incorrect - it should presumably be R4.3.1 not 4.31

      2. The red line on the histograms are very difficult to read and perhaps the darkness of the histogram fill could be reduced?

    1. On 2024-04-24 21:14:09, user Austin Bessire wrote:

      I have personally suffered from TSW and this work is unimaginably valuable from a patient's perspective. Insight as to how there is increased expression of mitochondrial complex I helps legitimize my suffering and provide more understanding as to how I may be able to treat it. I also am grateful to see that abnormalities were induced by glucocorticoid exposure both in vitro and in a cohort of healthy controls to rule out it being solely environmentally caused.

    2. On 2024-04-27 20:26:14, user Sarah Simpson wrote:

      Thank you for this important study. I have been suffering with topical steroid withdrawal for over 20 months after 35+ years of use for my atopic dermatitis which only got worse. My skin is now finally healing after the cessation of all medication. We need more research and for doctors to know more about this iatrogenic condition

    3. On 2024-04-29 16:25:58, user Mandy wrote:

      I am a former research biochemist whose daughter suffered from this TSW. I am so profoundly grateful to see meaningful research being done in this area - this could be a first step to treatments to alleviate the symptoms of this debilitating condition, and of the ability to assess genetic or epigenetic risk factors so we can prevent it in the first place. It is particularly validating to see quantitative differences between steroid withdrawal/red skin syndrome and atopic eczema.

    1. On 2024-05-06 10:22:51, user Agustín Estrada Peña wrote:

      Dear author,<br /> At a first reading I could find three major gaps in this study, for which I advice a deep review:<br /> 1. If the mapping is based on human clinical cases, it ignores the reports on wild animals (serology), on questing and feeding ticks. An infection transmitted by vectors and reservoirs by wild vertebrates should be NEVER mapped using only human cases. It is simply underrated.<br /> 2. The pathogen is transmitted ONLY by Ixodes ricinus ticks (in Poland). Therefore, predicting the habitat of other tick species will dangerously bias your results, since they have quite different preferences regarding weather, vegetation, landscape, etc.<br /> 3. Several species of Borrelia burgdorferi circulate in Poland. They are reservoirs by different vertebrates, like birds, or Rodentia. If you do not account for the distribution of these reservoirs, you can not accurately map the "preferences" of each species of the pathogen to circulate. The community of vertebrates has an effect on these processes.<br /> Thank you.<br /> Agustín Estrada-Peña

    1. On 2024-08-06 18:36:26, user Cindy wrote:

      I would like to include some feedback regarding data analysis (full disclosure, I work for Olink), which I hope will be beneficial to both authors and others who are analyzing similar data from Olink:<br /> We recommend calculating Limit of Detection (LOD) according to manufacturer’s guidelines, specifically LOD for Explore HT should be calculated based on actual project data rather than use of estimates of LOD from unrelated validation data. <br /> The best practice is to use Olink Analyze functionality to determine the LOD for each project (available in the latest version!). <br /> Replacing values below LOD with LOD/2 is not recommended. It will artificially inflate coefficient of variation (CV) values. Instead, apply an LOD cutoff specific to the project data. Removing values below the project-specific LOD when calculating CVs ensures a more accurate representation of data variability.<br /> I am happy to coordinate any discussions with the Olink team to facilitate.

    1. On 2024-10-21 23:26:17, user CDSL JHSPH wrote:

      I think that the background behind your research is very important to the field of tuberculosis treatment. Treating the patients so that the bacteria is out of their body while also preventing antibiotic resistance and any toxicities that the medication may cause is an important balance when deciding duration and dosage of treatments. Utilizing the dose-finding methods, such as MCP-Mod, and applying it to studying duration-ranging of TB treatments seems like a very practical method to studying this topic.

      I am curious about what you plan to do with the results of this study moving forward? You have identified a method to use in duration-ranging studies for TB antibiotics, but are you planning on using this information in your own studies? Is this a topic that many researchers in the field were looking for? I am just wondering about the practicality of this study and how it will actually be used moving forward.

    1. On 2025-04-04 12:04:32, user Claire Brereton wrote:

      I would be very interested to know what value of R0 you derived. I cannot find the supplementary material you refer to.

    1. On 2022-07-27 11:02:06, user Karen wrote:

      The SARS-CoV-2 comparison is flawed.

      * You compare cases (testing and reporting-dependent, highly time-variable), not incidence rates (such as ONS estimates)<br /> * You compare cases in the general population, not the paediatric population<br /> * You plot cases on a log scale against hepatitis cases on a linear scale.

      This needs revision. Indeed, when you revise it, you find that the conclusion is literally reversed.

    1. On 2022-08-12 17:17:01, user Dr. Amy wrote:

      An updated version of this work is now accepted and in press. The primary differences are 1) we evaluated and did find a reduction in symptoms based on adherence to a 2/day regimen. 2) The most likely reduction in severity comes from the effect of NS high volume irrigation on the nasal biome. We have added this reference by Dr. Huijghebaert and recommend interested scientists use this as the rationale for why irrigation reduced COVID severity: https://pubmed.ncbi.nlm.nih... Finally, we would like to reiterate that Povidone Iodine did not provide any benefit over the other NS regimen, and of course vaccination is the best way to reduce severity.

    1. On 2022-09-13 08:47:26, user Gabriel Costa wrote:

      Here is Gabriel, the first author. Some updates:

      1 - There is an error in the prisma flowchart diagram (Fig 1), it is missing one observational study that was excluded. We had 81 RCTs, 7 phase one trials and 1 observational study (this last is missing in the figure). It was excluded due to the replication not having the same PICO components.

      2 - We are conducting the direct comparison meta-analyses via R and the results with simple coding are almost the same, using MH method for all. Network and IPD meta-analyses it was not possible for this to be done.

      3 - Since (2) = TRUE, we are excluding the highly cited article of the meta-analysis, making the meta-analysis a complete independent replication. We do not observe substantial differences in the effects, suggesting that the 50% cutoff was adequate and only if the trial weights 90% of the meta-analysis this dependency becomes a problem.

      4 - Since (2) and (3) = TRUE, we are calculating prediction intervals as well.

      5 - There is a typo in the abstract in the Methods section. "We... and potential predictors or replicability". The correct is predictors OF replicability.

      An overview of the project, datasets and analysis code can be found at https://osf.io/a8zug/. As well as these updates.

      Thanks for the interest,<br /> Gabriel Costa on behalf of all authors

    1. On 2022-10-04 16:28:04, user Thomas Arend wrote:

      Dear Venkata,

      I have some remarks to your study.

      The age bands in your tables are very big. We know elderly people were <br /> vaccinated first. Elderly people have a higher risk to die or get <br /> hospitalized from COVID-19.

      In the age band > 18 yo this would lead to a pattern as in figure 5b <br /> and 5c. The hospitalization and death rates rise with the start of the <br /> vaccination process in the vaccinated group, just because the members of <br /> the group are older.

      After a peak, the rates fall back to a lower level (right side of the figures).

      On the other hand the unvaccinated group consists of younger people<br /> as the older people leave the group by vaccination. The rates would <br /> fall with the beginning of the vaccination process and rise later to a <br /> higher level.

      This effect can be seen in the ONS data, even when you compare smaller age bands and take the start of the vaccination process into account.

      An equivalent argument would be valid for differences in sex.

      As I know from Germany, the vaccination rate rises with age. Older people<br /> are more likely to be vaccinated than younger people. Therefore, there <br /> is a bias between vaccinated and unvaccinated people by age and possible<br /> sex.

      For risk assessment, you are comparing a group of younger unvaccinated with older vaccinated people. This is misleading. And will probably be the reason for the negative vaccine effectiveness.

      The curves in figure 5b and 5c depend highly on the age and sex structure of the groups.

      In table 1 you are comparing all ages. The proportion of infected people in the differs largely by age over the time.

      In Germany, only ~ 20 % of the age group 60+ yo and 80+ yo got infected <br /> until now. In the age group 5 – 14 yo and 15 – 34 yo, nearly 60 % got infected until now. The incidence varied a lot during the <br /> pandemic. So different time frames differ in the age and sex structure <br /> of the infected people.

      Proposals

      You should report and discuss the mean and median ages of the groups with standard deviation and IQR.

      You should take at least the differences in age and sex into account and<br /> transfer the populations of the groups into a standard population and <br /> calculate the hospitalization and death rates for this standard <br /> population before comparing.

      Or:

      Even in the age bands 60+ yo the vaccination process produces a bias<br /> by age and sex because the risks rise almost with each age year and female have a lesser risk than male. Therefore, you should <br /> only compare small age bands with a width of five years or less.

      You should divide the group of unvaccinated into unvaccinated and still not infected and unvaccinated and at least one time infected. Because infection works similar to vaccination.

      Without these improvements, I can't see how you will come to a valid conclusion and result.

      Best regards

      Thomas Arend

    1. On 2020-05-26 20:56:26, user Sinai Immunol Review Project wrote:

      Main Findings<br /> In this study, Bouadma and authors longitudinally profiled multiple immune parameters of a fatal case of Covid-19 that quickly developed multiorgan failure. An 80-year old male patient presented with fever and diarrhea that developed into multiorgan failure and hemoptysis over the course of 24 days that resulted in death. During this time, he was treated with broad-spectrum antibacterial agents, Remdesivir, and interferon beta-1a. Peripheral naive CD4+ and CD8+ T cells remained stable throughout, but effector memory T cells continually increased. Exhausted and senescent CD4+ and CD8+ T cells, and gamma delta T cells increased following day 14. Activated and exhausted B cells peaked on day 20. After day 16, NK cells and monocytes generally declined possibly due to lung trafficking. These fluctuations in immune populations were accompanied by induction of pro-inflammatory cytokines and Th1/Th2 factors that increased on day 14. Although some cytokines decreased following day 14, cytokines associated with T cell activation, exhaustion, and apoptosis continued to increase.

      Limitations<br /> It is difficult to draw broad conclusions from one patient and this longitudinal study did not start at the onset of infection and symptoms. Furthermore, these observations were done on the peripheral blood without complementary analysis of the lung where they suspect NK cells and monocytes have trafficked to.

      Significance<br /> This shows that immune cells proportion, functional state, and soluble factors fluctuate throughout disease progression. This is a broad overview of potential blood biomarkers that can be used to assess progression and severity.

      Credit<br /> Reviewed by Dan Fu Ruan, Evan Cody and Venu Pothula as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai

    1. On 2020-05-28 16:49:42, user Ruth Cleary wrote:

      Wondering whether Metformin Instant Release and Extended release readings were different from each other and, if so, by how much.

    1. On 2020-05-28 22:26:40, user Andrew Cohen wrote:

      NOTE: On the Supplementary Material page, the file "Supplemental Material" goes with the currently posted preprint. (The file "Supplementary Appendix" belongs to an earlier version of the preprint that was posted on medRxiv.)

    1. On 2020-05-03 14:25:00, user Geoff Turner wrote:

      Comparing diagnostic tests like this is a classic signal detection problem. What is your d'? What's the d' for the nasopharyngeal test? What's the bias of each? This is the only way to know which test is most sensitive AND simultaneously least biased.

    1. On 2020-05-07 00:13:23, user mpeaton wrote:

      Layman question: What were the aerosols made of, and did they evaporate? I have yet to find a paper demonstrating that ANY virus is viable after being exhaled in a droplet containing NaCl, proteins etc. and then dehydrating. Though there are some that claim otherwise, such as this one: https://dx.doi.org/10.1098%...

    1. On 2020-05-07 15:07:58, user Thomas Meunier wrote:

      KEY TAKEAWAYS FROM STUDY:

      1. The research, which has not yet undergone standard peer review evaluation, does not question the efficiency of social distancing.

      2. The research looks specifically at the impact of police-enforced home containment policies in some European countries.

      3. The work suggests that social distancing may be just as effective as home containment.

      4.The results show that the epidemic was already in decline (that is, the number of cases was growing less and less rapidly for 2 to 3 weeks before the lockdown and kept declining at the same rate afterwards) before the full lockdown, possibly thanks to social distancing measures already in place.

    1. On 2020-05-07 20:20:44, user Gregory Kreiss wrote:

      6% positive cases for 5-19 years old versus 8.5% for 20-49 years does not look like similar but an increase of 40% for the middle ages adults!<br /> Also one of the major limitation of this study is that we do not know wether the infected children are part of household where one of the adult has been also infected (cluster effect) and if it is the case who has infected who. To be conclusive the children should have been selected randomly within the population and not part of the household members.

    1. On 2020-05-07 20:47:41, user Dan T.A. Eisenberg wrote:

      We are thinking of implementing this in my lab for research purposes and hopefully to expand testing capacity. Have you or anyone else you know of tested the stability of saliva samples for longer periods of time, adding in preservative, and/or keeping more of a cold chain (e.g. stored at +4 or -20 for some time)?

    1. On 2020-05-08 04:39:19, user Robin H wrote:

      This study is weird.

      First of all : why a daily dose of 600mg of HCQ?<br /> Raoult and his team use a dose of 200mg per day to treat Covid-19. The general dose for the treatment of rheumatoid arthritis or lupus is 200 to 400mg, max 600mg if there is no response.<br /> There is a high debate about the potential cardiac toxicity of HCQ... But with this dose, we can understand that "Eight patients receiving HCQ (9.5%) experienced electrocardiogram modifications requiring HCQ discontinuation." Of course...<br /> Did the authors intend to favor the cardiac toxicity of HCQ to invalidate this treatment?... I Wonder.

      Second point: when you display the characteristics of the observed populations in the first table, you should indicate the p-value concerning the comparisons. If I'm correct, the HCQ group tends to have a more severe condition BEFORE treatment, at admission. 14 HCQ-treated patients (21.9%) vs 8 control patients (12.1%) had >50% of lung affected in CT scan... There is a trend to a significant difference with a p-value of 0.08...

      Then, you can't be conclusive with such bias...

    1. On 2020-05-08 05:56:07, user Masfin Otta wrote:

      Obviously, the conclusion of the paper was dead wrong: the covid-19 outbreak in Okinawa had already been completely suppressed without stringent stay-home measures by 28 April and we are not seeing 20,000 deaths but only 5 so far. Perhaps, the total number of the cases was not on the exponential line, particularly after the middle of April, 2-3 weeks after the start of the outbreak as Professor Michael Levitt of Stanford observed from the outbreaks of China, Italy and Iran. Another discussion may be that Rt might have been much lower than assumed and the outbreak died out without many new cases imported from the mainland or perhaps Europe and North America where the epidemic is much much severe than the mainland.

    1. On 2020-05-09 23:51:12, user Sinai Immunol Review Project wrote:

      Main findings<br /> The humoral response to SARS-CoV-2 infection has been largely studied in the context of antibody distribution in the peripheral blood of COVID-19 patients. However, little has been explored that evaluates immunophenotyping of B cells in patients with different clinical courses of COVID-19. Here, Woodruff et al. investigated B cell populations by spectral flow cytometry to understand the protective and non-protective humoral responses using PBMCs from 9 critically ill and 8 mild patients with COVID-19.

      Comparing CD45+ hematopoietic cells from 22 healthy controls and 17 COVID-19 patients, the authors found an expansion of CD19+ B cells in COVID-19 patients with a significant increase in CD138+ antibody-secreting cells (ASCs) among other B cell subpopulations: transitional, naive, double-negative, and memory. Interestingly, a greater abundance of these mature, CD138+ ASCs, which are often associated with protection during a vaccine-induced response, was found in COVID-19 patients with worse outcomes. Previously, this group described, in flaring systemic lupus erythematosus (SLE), an activated IgD-CD27-double negative B cell population that they characterized as part of an extra-follicular (EF) response. The comparison of the PBMCs across COVID-19 samples revealed two clusters: one that strongly upregulated the EF response pathway (EF-CoV), and one with a low EF response but a high transitional B cell signal (Tr-CoV).

      Within the EF-CoV cluster, ASC expansion correlated with enriched ASC maturation and an increase in the active naïve (IgD+CD11c+) and a subset of the double-negative (DN2: IgMlo IgD- CD11c+ CD21-) cell compartments. The composition of the double-negative component with skewing to the ASC-associated DN2 group in the EF-CoV cluster appeared identical to the B cell landscape of patients with active SLE. Similar to the increase in IL-6 and IP-10 during active SLE, association with upregulated IL-6 and IP-10 and poor prognosis for COVID-19 was also found in this study. Higher serum IL-6 and IP-10, a CXCR3 ligand, and expression of CXCR3 by B cell subpopulations belonging to the EF-CoV cluster, supports the notion that peripheral homing of B cells to inflamed tissue sites, as described in both the lung and kidneys, takes place in COVID-19 patients.

      A minor subset of B cells in the EF-CoV cluster were CD21lo transitional B cells. These cells were enriched in the Tr-CoV cluster and associated with mild disease. They shared several B cell immaturity markers, such as high levels of CD10 and CD38, and expressed high levels of surface IgM and muted surface IgD, which indicate extrafollicular homing. A longitudinal comparison of two ICU patients in each cluster (two EF-CoV patients and two Tr-CoV patients) revealed that the paucity of CD21lo transitional B cells in the EF-CoV was associated with higher severity of disease and a decrease in PaO2/FiO2 ratio (a measure of gas exchange efficiency). EF-CoV patients had higher levels of CRP, which correlated with a low frequency of transitional B cells, a high number of DN2 B cells, and elevated serum IL-6. Importantly, these patients faced poorer outcomes.

      Limitations<br /> Aside from the small sample size in the primary study and in the longitudinal follow-up, this report relies on surface markers to assess B cell heterogeneity in COVID-19 patients and characterize potential autoimmune subpopulations that are also present in SLE patients. However, there are limitations to the scope of coverage that flow cytometric analyses can provide. Single-cell RNA sequencing (scRNAseq) can provide a broader expression profile to distinguish subsets based on transcriptomic expression, as opposed to relying on existing, classical categorizations as done in this study. Therefore, higher granularity in the evaluation of cell-type heterogeneity may yield more precise assessments of cell-type similarities and differences between COVID-19 and autoimmune disease.

      Importantly, the characterizations of B cell subpopulations in this study have largely been correlative. Trends with clinical outcome or existing prognostic markers are insufficient to define the roles that these cell types may play in the pathogenesis of COVID-19. Without additional studies (and accounting for the general lymphopenia already reported in COVID-19 patients), it is unclear whether these phenotypes are by-products of abnormal or absent T cell help or actual reactions to/consequences of SARS-CoV-2 infection.

      Lastly, since this report identified similar B cell subsets in both critically ill COVID-19 patients and SLE patients, additional serological studies exploring any evidence of autoreactivity in EF-CoV patients with high IL-6 are warranted.

      Significance<br /> Using a specialized flow cytometry panel for B cell analysis, the authors provide a description of the B cell landscape in COVID-19 patients. Understanding the role of potentially pathogenic B cell modules could be crucial for designing immuno-modulatory therapies that target pro-inflammatory or potentially autoimmune phenotypes seen with SARS-CoV-2 infections.

      Reviewed by Matthew D. Park and Miyo Ota as part of a project by students, postdocs, and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.

    1. On 2020-05-11 12:28:29, user Sinai Immunol Review Project wrote:

      The main finding of the article: <br /> This study analyzed the effects of the arterial hypertension and of the use of renin-angiotensin-aldosterone system (RAAS) inhibitors on mortality and recovery in patients with Covid-19. Through medical records, the authors performed a multicenter retrospective study of 3017 COVID-19 patients hospitalized within the Hackensack Meridian Health network in New Jersey. Among these patients, 52.5% presented a diagnosis of hypertension. The authors showed a significantly increase (2.7 times) of the mortality in patients with hypertension compared to Covid-19 patients without hypertension. However, when adjusted for age, the effect of hypertension in mortality decreased, as the incidence of hypertension was higher in older populations. In addition, when other clinical or demographic conditions were taken into account, no effect of hypertension on mortality was found. <br /> In relation to the RAAS inhibitors, angiotensin converting enzyme 1 (ACE1) inhibitors and angiotensin-receptor blockers (ARBs) were used in 22.8% and 18% of hypertensive patients. The use of ACE1 inhibitors and ARBs were found not to have detrimental effects and perhaps offer some protection to hypertensive patients in comparison with other anti-hypertensive agents. Hospital discharge rates were 9% higher for hypertensive patients prescribed RAAS inhibitors compared to other anti-hypertensive agents.

      Critical analysis of the study: <br /> The manuscript needs a better scientific writing, especially more in-depth details on the description of the patient population, clinical parameters, treatments used, other co-morbidities. The implications for COVID-19 disease of the upregulated cascade of vasoactive peptides belonging to RAAS on hypertensive patients, the relationship between the use of RAAS inhibitors on cytokine storm, plasma angiotensin II and ACE2 activity, could be better discussed. There is no information on which ARBs or other anti-hypertensive agents were used, despite being an important information given the different pharmacological characteristics of each one.

      The importance and implications for the current epidemics: <br /> While there is still uncertainty on the effect of RAAS inhibitors on Covid-19 severity in hypertensive patients, this manuscript demonstrates that ACE1 inhibitors and ARBs therapy are not detrimental, and can even be protective in hypertensive individuals. These results thus support the recommendations of the guidelines for maintaining therapy with these classes of drugs in hypertensive SARS-CoV-19 patients.

      Reviewed by Bruna Gazzi de Lima Seolin.

    1. On 2020-05-12 21:48:21, user Clive Bates wrote:

      I think the conclusions are radically overstated given the method. The authors summarise:

      ? Current e-cigarette use is positively associated with COVID-19 infections.<br /> ? Current e-cigarette use is positively associated with COVID-19 deaths.<br /> ? This study emphasizes the importance of studying the susceptibility of current e-cigarette users to COVID-19 infection and death.

      It would be more accurate to say "statewide prevalence of vaping is correlated with COVID-19 infections and deaths". The study did not discover if e-cigarette use is associated with COVID-19 because it did not actually measure this: "we did not have data on what proportion of those who actually contracted COVID-19 or died from COVID-19 were vapers".

      It is a "helicopter view" of the situation using variables covering millions of people in gigantic aggregations, and looking at the progression of the epidemic at different stages as it moves unevenly through the different states over time. There are so many factors that determine the progression of the epidemic, it is hard to imagine how any vaping signal could be detected among the roaring cacophony of confounders and noise.

      Luckily, we can also assess the usefulness of the method in the investigation of new associations that have not so far been established (e.g. vaping) by seeing how well it discovers associations that have been already well-established by other research. For example obesity and male sex have been found to be risk factors for COVID-19. But the big finding in this study (see Figure 1) is that obesity and, especially, being male appear to be protective, thus overturning the broad consensus. That would be the big news and should feature heavily in the conclusions if the authors were confident in the method. The trouble is that it could equally lead observers to dismiss the method used as self-evidently flawed. No such objection can be raised about vaping, however, because there is little other data available and therefore no reality-check is possible. So to act with integrity, the authors have a choice: stand by the method and challenge the consensus on male sex and obesity risk factors or accept that if the method does not reveal well-established associations then it should not be used to look for novel ones.

      Other than pure chance, the second most likely explanation for the result is that vaping is a marker for some larger scale confounding phenomenon (poverty, hospitality trade, housing density, urbanisation, cosmopolitan, early spread of the virus etc) that is contributory to COVID-19 susceptibility but that cannot be fully adjusted for by the variables available to the authors. It would require heroic assumptions to draw any conclusions about vaping from an analysis like this.

    1. On 2020-05-13 10:08:28, user Benjamin Hartley wrote:

      Hi, Can you clarify the meaning of the theta "infection" parameter in equation 1 (years 2015-2019) which multiplies the death rate? Is this a typo, or set to 1?