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Record W2124027649 · doi:10.1155/2013/784190

<i>α</i>-Ketoglutarate Accumulation Is Not Dependent on Isocitrate Dehydrogenase Activity during Tellurite Detoxification in<i>Escherichia coli</i>

2013· article· en· W2124027649 on OpenAlexaff
Claudia A. Reinoso, Vasu D. Appanna, Claudio C. Vásquez

Bibliographic record

VenueBioMed Research International · 2013
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsLaurentian University
FundersComisión Nacional de Investigación Científica y TecnológicaUniversidad de Santiago de Chile
KeywordsIsocitrate dehydrogenaseToxicantEscherichia coliGlutamate dehydrogenaseDehydrogenaseBiologyBiochemistryEnzymeChemistryGeneGlutamate receptorToxicity

Abstract

fetched live from OpenAlex

Tellurite is toxic to most microorganisms because of its ability to generate oxidative stress. However, the way in which tellurite interferes with cellular processes is not fully understood to date. In this line, it was previously shown that tellurite-exposed cells displayed reduced activity of the α-ketoglutarate dehydrogenase complex (α-KGDH), which resulted in α-ketoglutarate (α-KG) accumulation. In this work, we assessed if α-KG accumulation in tellurite-exposed E. coli could also result from increased isocitrate dehydrogenase (ICDH) and glutamate dehydrogenase (GDH) activities, both enzymes involved in α-KG synthesis. Unexpectedly both activities were found to decrease in the presence of the toxicant, an observation that seems to result from the decreased transcription of icdA and gdhA genes (encoding ICDH and GDH, resp.). Accordingly, isocitrate levels were found to increase in tellurite-exposed E. coli. In the presence of the toxicant, cells lacking icdA or gdhA exhibited decreased reactive oxygen species (ROS) levels and higher tellurite sensitivity as compared to the wild type strain. Finally, a novel branch activity of ICDH as tellurite reductase is presented.

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 score0.201
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.133
GPT teacher head0.394
Teacher spread0.262 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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