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Record W2015775599 · doi:10.1042/bst0300755

The role of oxidative stress in the toxicity of pyridoxal isonicotinoyl hydrazone (PIH) analogues

2002· article· en· W2015775599 on OpenAlexaff
Joan L. Buss, Jiřı́ Neužil, Prem Ponka

Bibliographic record

VenueBiochemical Society Transactions · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsOxidative stressToxicityGlutathioneChemistryBiochemistryLipid peroxidationJurkat cellsReactive oxygen speciesAntioxidantPharmacologyBiologyEnzymeImmunologyOrganic chemistry

Abstract

fetched live from OpenAlex

Pyridoxal isonicotinoyl hydrazone (PIH) analogues are effective iron chelators in vivo and in vitro, and may be of value for the treatment of secondary iron overload. The sensitivity of Jurkat cells to Fe-chelator complexes was enhanced several-fold by the depletion of the antioxidant glutathione, indicating the role of oxidative stress in their toxicity. K562 cells loaded with eicosapentaenoic acid, a fatty acid particularly susceptible to oxidation, were also more sensitive to the toxic effects of the Fe complexes, and toxicity was proportional to lipid peroxidation. Thus Fe-chelator complexes cause oxidative stress, which may be a major component of their toxicity. As was the case for their Fe complexes, the toxicity of PIH analogues was enhanced by glutathione depletion of Jurkat cells and eicosapentaenoic acid-loading of K562 cells. Thus the toxicity of the chelators themselves is also enhanced by compromised cellular redox status. In addition, the toxicity of the chelators was diminished by culturing Jurkat cells under hypoxic conditions, which may limit the production of the reactive oxygen species that initiate oxidative stress. A significant part of the toxicity of the chelators may be due to intracellular formation of Fe-chelator complexes, which oxidatively destroy the cell.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.166

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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.

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

Citations23
Published2002
Admission routes1
Has abstractyes

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