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Record W4321168864 · doi:10.1002/btpr.3335

Modeling the effect of oxidative stress on <i>Bordetella pertussis</i> fermentations

2023· article· en· W4321168864 on OpenAlexafffund
Michael Vitelli, Ibrahim Melih Tamer, Mark Pritzker, Hector Budman

Bibliographic record

VenueBiotechnology Progress · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsSanofi (Canada)University of Waterloo
FundersMitacs
KeywordsBordetella pertussisOxidative stressOxidative phosphorylationIntracellularBordetellaChemistryBiochemistryFood scienceBacteriaBiologyMicrobiologyGenetics

Abstract

fetched live from OpenAlex

A mathematical model is proposed for Bordetella pertussis with the main goal to better understand and describe the relation between cell growth, oxidative stress and NADPH levels under different oxidative conditions. The model is validated with flask experiments conducted under different conditions of oxidative stress induced by high initial glutamate concentrations, low initial inoculum and secondary culturing following exposure to starvation. The model exhibited good accuracy when calibrated and validated for the different experimental conditions. From comparisons of model predictions to data with different model mechanisms, it was concluded that intracellular reactive oxidative species only have an indirect effect on growth rate by reacting with NADPH and thereby reducing the amount of NADPH that is available for growth.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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 designSimulation or modeling
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

Citations4
Published2023
Admission routes2
Has abstractyes

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