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Identification of high-performing antibodies for Rab1A and Rab1B for use in Western Blot, immunoprecipitation and immunofluorescence

2023· preprint· en· W4389551065 on OpenAlexafffund
Vera Ruíz Moleón, Maryam Fotouhi, Riham Ayoubi, Sara González Bolívar, Kathleen Southern, Peter S. McPherson, Carl Laflamme

Bibliographic record

VenueF1000Research · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchGovernment of CanadaOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAMitacsOntario GenomicsGenome CanadaGenentechBayerPfizerBristol-Myers Squibb
KeywordsGolgi apparatusWestern blotImmunoprecipitationAntibodyImmunofluorescenceBiologyEndoplasmic reticulumCell biologyGTPaseGene isoformBlotImmunologyGeneBiochemistry

Abstract

fetched live from OpenAlex

Rab1 is a highly conserved small GTPase that exists in humans as two isoforms: Rab1A and Rab1B, sharing 92% sequence identity. These proteins regulate vesicle trafficking between the endoplasmic reticulum (ER) and Golgi and within the Golgi stacks. Rab1A and Rab1B may be oncogenes, as they are frequently dysregulated in various human cancers. Moreover, they contribute to the progression of Parkinson’s disease. The availability of high-quality antibodies specific for Rab1A or Rab1B is essential to understand the distinct functions of these Rab1 proteins in both health and diseaseand to enhance the reproducibility of research involving these proteins. In this study, we characterized seven antibodies targeting Rab1A and five antibodies targeting Rab1B 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 much larger, collaborative initiative seeking to address the antibody reproducibility issue by characterizing commercially available antibodies for human proteins and publishing the results openly as a valuable resource for the scientific community. While uses 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.014

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 head0.046
GPT teacher head0.326
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes2
Has abstractyes

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