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Record W2029628361 · doi:10.1111/1574-6968.12223

The anticancer drug tirapazamine has antimicrobial activity against<i>Escherichia coli</i>,<i>Staphylococcus aureus</i>and<i>Clostridium difficile</i>

2013· article· en· W2029628361 on OpenAlexafffund
Zarna Ronak Shah, Raya Mahbuba, Bernard Turcotte

Bibliographic record

VenueFEMS Microbiology Letters · 2013
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsMcGill University Health CentreMcGill University
FundersCanadian Institutes of Health Research
KeywordsMicrobiologyStaphylococcus aureusTirapazamineAntimicrobialEscherichia coliClostridium difficileChemistryAntibioticsBacteriaBiologyIn vitroBiochemistryCytotoxicity

Abstract

fetched live from OpenAlex

Rapidly increasing bacterial resistance to existing therapies creates an urgent need for the development of new antibacterials. Tirapazamine (TPZ, 3-amino-1,2,4-benzotriazine 1,4 dioxide) is a prodrug undergoing clinical trials for various types of cancers. In this study, we showed that TPZ has antibacterial activity, particularly at low oxygen levels. With Escherichia coli, TPZ was bactericidal under both aerobic and anaerobic conditions. Escherichia coli mutants deficient in homologous recombination were hypersusceptible to TPZ, suggesting that drug toxicity may be due to DNA damage. Moreover, E. coli strains deleted for genes encoding putative reductases were resistant to TPZ, implying that these enzymes are responsible for conversion of the prodrug to a toxic compound. Fluoroquinolone-resistant E. coli strains were as susceptible to TPZ as a wild-type strain. Methicillin-resistant Staphylococcus aureus strains were also susceptible to TPZ (MIC = 0.5 μg mL(-1) ), as were pathogenic strains of Clostridium difficile (MIC = 7.5 ng mL(-1) ). TPZ may merit additional study as a broad-spectrum antibacterial, particularly for anaerobes.

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 categoriesMeta-epidemiology (narrow)
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 score0.086
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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

Citations22
Published2013
Admission routes2
Has abstractyes

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