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Record W2108349823 · doi:10.1371/journal.pone.0049516

Botulinum Neurotoxin Serotype a Specific Cell-Based Potency Assay to Replace the Mouse Bioassay

2012· article· en· W2108349823 on OpenAlexaboutno aff
Ester Fernández‐Salas, Joanne Wang, Yanira Molina, Jeremy B. Nelson, Birgitte P. S. Jacky, K. Roger Aoki

Bibliographic record

VenuePLoS ONE · 2012
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
FundersAllergan
KeywordsBioassayPotencyPharmacologyBotulinum neurotoxinNeurotoxinBiologyBiochemistryToxinIn vitro

Abstract

fetched live from OpenAlex

Botulinum neurotoxin serotype A (BoNT/A), a potent therapeutic used to treat various disorders, inhibits vesicular neurotransmitter exocytosis by cleaving SNAP25. Development of cell-based potency assays (CBPAs) to assess the biological function of BoNT/A have been challenging because of its potency. CBPAs can evaluate the key steps of BoNT action: receptor binding, internalization-translocation, and catalytic activity; and therefore could replace the current mouse bioassay. Primary neurons possess appropriate sensitivity to develop potential replacement assays but those potency assays are difficult to perform and validate. This report describes a CBPA utilizing differentiated human neuroblastoma SiMa cells and a sandwich ELISA that measures BoNT/A-dependent intracellular increase of cleaved SNAP25. Assay sensitivity is similar to the mouse bioassay and measures neurotoxin biological activity in bulk drug substance and BOTOX® product (onabotulinumtoxinA). Validation of a version of this CBPA in a Quality Control laboratory has led to FDA, Health Canada, and European Union approval for potency testing of BOTOX®, BOTOX® Cosmetic, and Vistabel®. Moreover, we also developed and optimized a BoNT/A CBPA screening assay that can be used for the discovery of novel BoNT/A inhibitors to treat human disease.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.073
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.052
GPT teacher head0.238
Teacher spread0.186 · 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

Citations113
Published2012
Admission routes1
Has abstractyes

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