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A guide to selecting high-performing antibodies for Heterogeneous nuclear ribonucleoproteins A2/B1(hnRNP A2/B1) (UniProt ID: P22626) for use in western blot, immunoprecipitation, and immunofluorescence

2025· preprint· en· W4415903832 on OpenAlexafffund
Vera Ruíz Moleón, Riham Ayoubi, Charles Alende, Maryam Fothouhi, Joël Ryan, Sara González Bolívar, Donovan Worrall, Thomas M. Durcan, Claire M. Brown, Vincent Francis, Peter S. McPherson, Carl Laflamme

Bibliographic record

VenueF1000Research · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill UniversityStructural Genomics Consortium
FundersGovernment of CanadaOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAOntario GenomicsGenome CanadaGenentechBayerMotor Neurone Disease AssociationPfizerBristol-Myers Squibb
KeywordsRibonucleoproteinAntibodyImmunofluorescenceHeterogeneous nuclear ribonucleoproteinProtocol (science)Messenger RNATranslation (biology)RNA

Abstract

fetched live from OpenAlex

Heterogeneous nuclear ribonucleoprotein A2/B1 (hnRNP A2/B1) is a key RNA-binding protein involved in alternative splicing, mRNA transport, and local translation processes essential for neuronal development and synaptic plasticity. Here we have characterized eight hnRNP A2/B1 commercial antibodies for western blot, immunoprecipitation, and immunofluorescence 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 the 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.342
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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