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Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, have demonstrated that: ( i ) more than 50% of all antibodies failed in one or more applications, ( ii ) yet, ~50–75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and ( iii ) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts. Commercially produced antibodies are essential research tools. Investigators at universities and pharmaceutical companies use them to study human proteins, which carry out all the functions of the cells. Scientists usually buy antibodies from commercial manufacturers who produce more than 6 million antibody products altogether. Yet many commercial antibodies do not work as advertised. They do not recognize their intended protein target or may flag untargeted proteins. Both can skew research results and make it challenging to reproduce scientific studies, which is vital to scientific integrity. Using ineffective commercial antibodies likely wastes$1 billion in research funding each year. Large-scale validation of commercial antibodies by an independent third party could reduce the waste and misinformation associated with using ineffective commercial antibodies. Previous research testing an antibody validation pipeline showed that a commercial antibody widely used in studies to detect a protein involved in amyotrophic lateral sclerosis did not work. Meanwhile, the best-performing commercial antibodies were not used in research. Testing commercial antibodies and making the resulting data available would help scientists identify the best study tools and improve research reliability. Ayoubi et al. collaborated with antibody manufacturers and organizations that produce genetic knock-out cell lines to develop a system validating the effectiveness of commercial antibodies. In the experiments, Ayoubi et al. tested 614 commercial antibodies intended to detect 65 proteins involved in neurologic diseases. An effective antibody was available for about two thirds of the 65 proteins. Yet, hundreds of the antibodies, including many used widely in studies, were ineffective. Manufacturers removed some underperforming antibodies from the market or altered their recommended uses based on these data. Ayoubi et al. shared the resulting data on Zenodo, a publicly available preprint database. The experiments suggest that 20-30% of protein studies use ineffective antibodies, indicating a substantial need for independent assessment of commercial antibodies. Ayoubi et al. demonstrated their side-by-side antibody comparison methods were an effective and efficient way of validating commercial antibodies. Using this approach to test commercial antibodies against all human proteins would cost about $ 50 million. But it could save much of the $1 billion wasted each year on research involving ineffective antibodies. Independent validation of commercial antibodies could also reduce wasted efforts by scientists using ineffective antibodies and improve the reliability of research results. It would also enable faster, more reliable research that may help scientists understand diseases and develop new therapies to improve patient’s lives.

Synaptotagmin-1 is a synaptic vesicle transmembrane protein that senses calcium influx via its tandem C2-domains, triggering synchronous neurotransmitter release. Disruption to SYT1 is associated with neurodevelopmental disorders, highlighting the importance of identifying high-quality research reagents to enhance understanding of Synaptotagmin-1 in health and disease. Here we have characterized thirteen Synaptotagmin-1 commercial antibodies for western blot, immunoprecipitation, immunofluorescence and flow cytometry using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. These studies are part of a larger, collaborative initiative seeking to address antibody reproducibility issues by characterizing commercially available antibodies for human proteins and publishing the results openly as a resource for the scientific community. While use of antibodies and protocols vary between laboratories, we encourage readers to use this report as a guide to select the most appropriate antibodies for their specific needs.

YCharOS is a collaborative initiative aimed at characterising antibodies against the entire human proteome. As of August 2023, they have presented comprehensive knockout characterisation data for 812 antibodies and 78 proteins using techniques such as Western blot, immunoprecipitation, and immunofluorescence. YCharOS consolidates its data into reports (one protein per report) available on Zenodo, a public repository controlled by CERN, to ensure open access. To enhance the visibility of their work, the group is progressively converting their Zenodo reports into F1000 articles, collected on the YCharOS Gateway, and indexed via PubMed. Their data is also accessible through searches on the Antibody Registry. The provided data is a valuable resource for researchers when selecting antibodies for specific applications, although certain limitations should be considered. The data accumulated thus far has illuminated the extent of the problem when poorly performing antibodies are employed in research. While the scientific community was already aware that this was likely a widespread issue, the establishment of a collaborative open science project with industry partners introduces an innovative solution that holds the potential to yield significant returns on investment in the public interest. This potential is substantiated by the number of antibodies that have either been withdrawn or had their recommended usage altered by the vendor. However, despite the discovery of high-performing renewable antibodies for most of the studied proteins, this accounts for a tiny fraction of the human proteome and the commercial antibody market. To realise the full potential of this work, end-users must adjust their antibody procurement and usage practises in line with the provided data. This editorial offers a guide on how individual scientists can utilise the YCharOS data, in addition to sharing the insights gained from the data thus far with the wider scientific community.

Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, have demonstrated that: ( i ) more than 50% of all antibodies failed in one or more applications, ( ii ) yet, ~50–75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and ( iii ) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts. Commercially produced antibodies are essential research tools. Investigators at universities and pharmaceutical companies use them to study human proteins, which carry out all the functions of the cells. Scientists usually buy antibodies from commercial manufacturers who produce more than 6 million antibody products altogether. Yet many commercial antibodies do not work as advertised. They do not recognize their intended protein target or may flag untargeted proteins. Both can skew research results and make it challenging to reproduce scientific studies, which is vital to scientific integrity. Using ineffective commercial antibodies likely wastes$1 billion in research funding each year. Large-scale validation of commercial antibodies by an independent third party could reduce the waste and misinformation associated with using ineffective commercial antibodies. Previous research testing an antibody validation pipeline showed that a commercial antibody widely used in studies to detect a protein involved in amyotrophic lateral sclerosis did not work. Meanwhile, the best-performing commercial antibodies were not used in research. Testing commercial antibodies and making the resulting data available would help scientists identify the best study tools and improve research reliability. Ayoubi et al. collaborated with antibody manufacturers and organizations that produce genetic knock-out cell lines to develop a system validating the effectiveness of commercial antibodies. In the experiments, Ayoubi et al. tested 614 commercial antibodies intended to detect 65 proteins involved in neurologic diseases. An effective antibody was available for about two thirds of the 65 proteins. Yet, hundreds of the antibodies, including many used widely in studies, were ineffective. Manufacturers removed some underperforming antibodies from the market or altered their recommended uses based on these data. Ayoubi et al. shared the resulting data on Zenodo, a publicly available preprint database. The experiments suggest that 20-30% of protein studies use ineffective antibodies, indicating a substantial need for independent assessment of commercial antibodies. Ayoubi et al. demonstrated their side-by-side antibody comparison methods were an effective and efficient way of validating commercial antibodies. Using this approach to test commercial antibodies against all human proteins would cost about $ 50 million. But it could save much of the $1 billion wasted each year on research involving ineffective antibodies. Independent validation of commercial antibodies could also reduce wasted efforts by scientists using ineffective antibodies and improve the reliability of research results. It would also enable faster, more reliable research that may help scientists understand diseases and develop new therapies to improve patient’s lives.

Genetic studies have identified hundreds of risk genes for neurodegenerative diseases, yet translating these variants into disease mechanisms remains limited by incomplete knowledge of the protein products. Here, we present the ALS-Reproducible Antibody Platform (ALS-RAP), a systematic effort to characterize 303 antibodies targeting 33 amyotrophic lateral sclerosis (ALS) risk genes: ACSL5, ALS2, ANG, ANXA11, ATXN2, C9orf72, CAV1, CCNF, CHCHD10, CHMP2B, FIG4, FUS, HNRNPA1, HNRNPA2B1, KIF5A, LGALS1, MATR3, NEK1, OPTN, PFN1, SETX, SIGMAR1, SOD1, SPG11, SQSTM1, TAF15, TARDBP, TBK1, TIA1, TUBA4A, UBQLN2, VAPB, and VCP using knockout-based characterization to identify high-quality reagents in common applications. Using these antibodies, we profiled protein expression across human iPSC-derived and primary neurological cell types. Protein-level analyses revealed diverse cell type-specific expression patterns, with subsets of ALS-associated proteins enriched in glial or neuronal populations. This work provides a validated antibody toolbox and ALS protein resource for translating genetic risk into mechanistic insights.Competing Interest StatementThe authors have declared no competing interest.Footnotes* This revised version refocuses the manuscript on tools for ALS research and introduces the Only Good Antibodies initiative, which curates and disseminates YCharOS antibody characterization data. The core findings and conclusions of the study remain unchanged.Funder Information DeclaredMotor Neurone Disease AssociationALS AssociationALS Society of CanadaGenome Canada, OGI-210Génome Québec, OGI-210Ontario Genomics, https://ror.org/00c68jz96, OGI-210Québec Consortium for Drug DiscoveryCanadian Institutes of Health Research, https://ror.org/01gavpb45, PJT-195804ALS FindingACureNational Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), NC/NAM0019/1MRC, MRC UKRI076

Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, demonstrates that: more than 50% of all antibodies failed in one or more tests, ) yet, ~50-75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and ) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first such study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts.

Background Evidence on current, national physical activity (PA) and sedentary behaviour (SB) policies is limited. We, therefore, analysed availability, comprehensiveness, implementation, and effectiveness of PA and SB policies internationally. Methods In this cross-sectional study, Global Observatory for Physical Activity (GoPA!) Country Contacts from 173 countries were asked to provide data on their national PA and SB policies by completing GoPA! Policy Inventory. Data were collected for 76 countries (response rate = 44%). Results Formal written policies for PA and SB were found in 92% (95% confidence interval [CI]: 86, 98) and 62% (95% CI: 50, 75) of countries, respectively. Sixty-two percent (95% CI: 51, 73) of countries have national PA guidelines, while 40% (95% CI: 29, 52) have SB guidelines. Fifty-two (95% CI: 40, 64) and 11% (95% CI: 3, 19) of countries have quantifiable national targets for PA and SB, respectively. The most represented ministries/departments involved in the promotion of more PA and/or less SB were in the sport (reported by 99% countries; 95% CI: 96, 100), health (97%; 95% CI: 94, 100), education (94%; 95% CI: 88, 100), and recreation and leisure (85%; 95% CI: 71, 99) sectors. The median score (0–10) for the comprehensiveness of PA and SB policies was 4 (95% CI: 4, 5) and 2 (95% CI: 2, 3), respectively. For PA and SB policy implementation it was 6 (95% CI: 5, 6). For the effectiveness of PA and SB policies it was 4 (95% CI: 3, 5) and 3 (95% CI: 2, 4), respectively. PA and SB policies were generally best developed in high-income countries and countries of European and Western-Pacific regions. Conclusions Most of the included countries have PA policies, but their comprehensiveness, implementation, and effectiveness are generally low-to-moderate. SB policies are less available, comprehensive, implemented, and effective than PA policies. PA and SB policies are better developed in high-income countries, compared with low- and lower-middle-income countries, and in countries of European and Western-Pacific regions, compared with other world regions. More investment is needed in development and implementation of comprehensive and effective PA and SB policies, particularly in low- and lower-middle-income countries.

Background In 2018, the World Health Organisation (WHO) commenced a program of work to update the 2010 Global Recommendations on Physical Activity for Health, for the first-time providing population-based guidelines on sedentary behaviour. This paper briefly summarizes and highlights the scientific evidence behind the new sedentary behaviour guidelines for all adults and discusses its strengths and limitations, including evidence gaps/research needs and potential implications for public health practice. Methods An overview of the scope and methods used to update the evidence is provided, along with quality assessment and grading methods for the eligible new systematic reviews. The literature search update was conducted for WHO by an external team and reviewers used the AMSTAR 2 (Assessment of Multiple Systematic Reviews) tool for critical appraisal of the systematic reviews under consideration for inclusion. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) method was used to rate the certainty (i.e. very low to high) of the evidence. Results The updated systematic review identified 22 new reviews published from 2017 up to August 2019, 14 of which were incorporated into the final evidence profiles. Overall, there was moderate certainty evidence that higher amounts of sedentary behaviour increase the risk for all-cause, cardiovascular disease (CVD) and cancer mortality, as well as incidence of CVD, cancer, and type 2 diabetes. However, evidence was deemed insufficient at present to set quantified (time-based) recommendations for sedentary time. Moderate certainty evidence also showed that associations between sedentary behaviour and all-cause, CVD and cancer mortality vary by level of moderate-to-vigorous physical activity (MVPA), which underpinned additional guidance around MVPA in the context of high sedentary time. Finally, there was insufficient or low-certainty systematic review evidence on the type or domain of sedentary behaviour, or the frequency and/or duration of bouts or breaks in sedentary behaviour, to make specific recommendations for the health outcomes examined. Conclusions The WHO 2020 guidelines are based on the latest evidence on sedentary behaviour and health, along with interactions between sedentary behaviour and MVPA, and support implementing public health programmes and policies aimed at increasing MVPA and limiting sedentary behaviour. Important evidence gaps and research opportunities are identified.

Background In July, 2019, the World Health Organization (WHO) commenced work to update the 2010 Global Recommendations on Physical Activity for Health and established a Guideline Development Group (GDG) comprising expert public health scientists and practitioners to inform the drafting of the 2020 Guidelines on Physical Activity and Sedentary Behavior. The overall task of the GDG was to review the scientific evidence and provide expert advice to the WHO on the amount of physical activity and sedentary behavior associated with optimal health in children and adolescents, adults, older adults (> 64 years), and also specifically in pregnant and postpartum women and people living with chronic conditions or disabilities. Methods The GDG reviewed the available evidence specific to each sub-population using systematic protocols and in doing so, identified a number of gaps in the existing literature. These proposed research gaps were discussed and verified by expert consensus among the entire GDG. Results Evidence gaps across population sub-groups included a lack of information on: 1) the precise shape of the dose-response curve between physical activity and/or sedentary behavior and several of the health outcomes studied; 2) the health benefits of light-intensity physical activity and of breaking up sedentary time with light-intensity activity; 3) differences in the health effects of different types and domains of physical activity (leisure-time; occupational; transportation; household; education) and of sedentary behavior (occupational; screen time; television viewing); and 4) the joint association between physical activity and sedentary time with health outcomes across the life course. In addition, we acknowledge the need to conduct more population-based studies in low- and middle-income countries and in people living with disabilities and/or chronic disease, and to identify how various sociodemographic factors (age, sex, race/ethnicity, socioeconomic status) modify the health effects of physical activity, in order to address global health disparities. Conclusions Although the 2020 WHO Guidelines for Physical Activity and Sedentary Behavior were informed by the most up-to-date research on the health effects of physical activity and sedentary time, there is still substantial work to be done in advancing the global physical activity agenda.

Background Policy analysis is considered essential for achieving successful reforms in health promotion and public health. The only framework for physical activity (PA) policy analysis was developed at a time when the field of PA policy research was in its early stages. PA policy research has since grown, and our understanding of what elements need to be included in a comprehensive analysis of PA policy is now more refined. This study developed a new conceptual framework for PA policy analysis – the Comprehensive Analysis of Policy on Physical Activity (CAPPA) framework. Methods The development of the CAPPA framework was based on: (i) an extensive review of literature; (ii) an open discussion between the authors; (iii) three rounds of a Delphi process; and (iv) two-rounds of consultations with PA policy stakeholders. Results The CAPPA framework specifies 38 elements of a comprehensive analysis of PA policies in the following six categories, which comprise the building blocks of the framework: (i) purpose of analysis (including auditing and assessment of policies); (ii) policy level (including: international; national; subnational; local; and institutional policies); (iii) policy sector (including: health; sport; recreation and leisure; education; transport; environment; urban/rural planning and design; tourism; work and employment; public finance; and research sectors); (iv) type of policy (including: formal written policies; unwritten formal statements; written standards and guidelines; formal procedures; and informal policies); (v) stage of policy cycle (including: agenda setting; formulation; endorsement/legitimisation; implementation; evaluation; maintenance; termination; and succession); and (vi) scope of analysis (including availability; context; processes; actors; political will; content; and effects). Based on the CAPPA framework, we also proposed broad and inclusive definitions of PA policy and PA policy analysis. Conclusion The CAPPA framework may be used to guide future studies related to PA policy and to provide a context for the analysis of its specific components. The framework could be used in the same way for sedentary behaviour policy research. Future research should examine the extent to which PA policy analysis has covered each of the elements specified in the CAPPA framework and analyse the elements for which evidence is lacking. Future studies should also determine whether the existing tools allow for auditing and assessment of all the CAPPA elements and develop new tools if needed to allow for a more comprehensive PA policy analysis.