Don't Blame the Idealizations (revised version)

Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists' attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so in a way that prevents those hypotheses from being false by virtue of their constituent idealizations

Identification and characterization of novel antigenic vaccine candidates of Actinobacillus pleuropneumoniae

Actinobacillus pleuropneumoniae is an important respiratory pathogen of swine, for which there is no highly effective vaccine. A phage expression library of the A. pleuropneumoniae genome was constructed and screened to identify potential vaccine components. Open reading frames within immuno-reactive phage were analyzed in silico to identify conserved outer membrane proteins. Four ORFs, named comL, lolB, lppC and ompA were chosen for further study. The four encoded proteins were shown experimentally to be antigenic, highly conserved, outer membrane, in vivo-expressed proteins. In pig protection studies, none of the proteins was individually capable of protecting pigs from colonization and infection with the homologous A. pleuropneumoniae strain, despite a detectable specific antibody response being induced

Antibody Characterization Report for Optineurin (2023)

<p>This report presents a guide to selecting high-quality commercial antibodies against Optineurin by immunoblot (Western blot), immunoprecipitation and immunofluorescence, using a knockout based validation approach. The research displayed in this study can be considered a subsequent study following the initial Optineurin report published to the YCharOS community in 2021 (DOI:10.5281/zenodo.4730992). Antibodies ab213556**, 60293-1-Ig*, 702766** and 711879**, previously characterized in the initial report, were retested in all three applications, employing our revised standardized protocols. Additionally, new recombinant antibodies were subject to characterization.</p><p>This study was funded in part by Genome Québec's Genomics Integration Program, awarded to the research laboratory of Peter S. McPherson.This target was nominated by the ALS-Reproducible Antibody Platform (ALS-RAP), established as a public-private partnership by three prominent ALS charities - the ALS Association (USA), the Motor Neurone Disease Association (UK), and the ALS Society of Canada.</p><p> </p&gt

Antibody Characterization Report for TATA-binding protein associated factor 2N (TAF15)

<p>In this report, five commercial antibodies against TATA-binding protein associated factor 2N (TAF15) were characterized for use Western Blot, immunoprecipitation, and immunofluorescence, using a standardized experimental protocol based on comparing read-outs in knockout cell lines and isogenic parental controls. </p><p>This work is part of the ALS-Reproducible Antibody Platform (ALS-RAP), established as a public-private partnership by three prominent ALS charities - the ALS Association (USA), the Motor Neurone Disease Association (UK), and the ALS Society of Canada.</p&gt

Antibody Characterization Report for Heterogeneous nuclear ribonucleoproteins A2/B1 (hnRNP A2/B1)

<p>This report presents a guide to selecting high-quality commercial antibodies against Heterogeneous nuclear ribonucleoproteins A2/B1 (hnRNP A2/B1) by immunoblot (Western blot), immunoprecipitation and immunofluorescence, using a knockout based validation approach.</p><p>This study was funded in part by the ALS-Reproducible Antibody Platform (ALS-RAP), established as a public-private partnership by three prominent ALS charities - the ALS Association (USA), the Motor Neurone Disease Association (UK), and the ALS Society of Canada.</p&gt

Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications.

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

Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications

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