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Record W2649611480 · doi:10.1002/9781119004813.ch60

Regulators of Oxidative Stress Response Genes in<i>Escherichia Coli</i>and Their Conservation in Bacteria

2016· other· en· W2649611480 on OpenAlexaff
Herb E. Schellhorn, Mahi M. Mohiuddin, Sarah M. Hammond, Steven R. Botts

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSuperoxide dismutaseCatalaseOxidative stressReactive oxygen speciesrpoSBiochemistryEscherichia coliChemistryBacteriaOxidative phosphorylationEnzymeRadicalBiologyCell biologyGene expressionGeneGenetics

Abstract

fetched live from OpenAlex

Bacterial responses to oxidative stress are complex, and they include both factors that prevent the accumulation of reactive oxygen species that are a normal by-product of metabolism and factors that repair damage caused by oxidative stress. An important biological imperative in bacteria is reducing the flux of reactive oxygen species within the cell by increasing levels of enzymes, including superoxide dismutase, catalase, and hydroperoxidase, in addition to sequestering transition metals, particularly iron that can exacerbate oxidative stress through the production of hydroxyl radicals. Regulation of protective factors is mediated by conserved regulators, including OxyR, controlling catalase and peroxidases; the SoxRS system, controlling superoxide dismutase; and RpoS, the general stress response regulator that potentiates expression of key protective enzymes in the stationary phase. Other regulators that maintain intracellular iron levels are also key conserved components of the oxidative stress response.

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)0.000
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.225
Teacher spread0.216 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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