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Record W2108992620 · doi:10.1139/w10-066

Effect of diallyldisulphide on an antioxidant enzyme system in<i>Candida</i>species

2010· article· en· W2108992620 on OpenAlexvenueno aff
Snowber Yousuf, Aijaz Ahmad, Amber Khan, Nikhat Manzoor, Luqman Ahmad Khan

Bibliographic record

VenueCanadian Journal of Microbiology · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsnot available
FundersUniversity Grants Commission
KeywordsAntioxidantCandida albicansCatalaseGlutathioneCandida tropicalisSuperoxide dismutaseGlutathione peroxidaseLipid peroxidationGlutathione reductaseOxidative stressBiochemistryChemistryBiologyMicrobiologyEnzyme

Abstract

fetched live from OpenAlex

This study was carried out to show the effect of diallyldisulphide (DADS), an important organosulphur compound found in garlic (Allium sativum), on antioxidant systems in Candida species. Changes in antioxidant metabolites and antioxidant activity in the presence of DADS were found in Candida albicans and Candida tropicalis. Candida cells were treated with sublethal concentrations of DADS. DADS caused a decrease in the activity of all antioxidant enzymes except catalase, resulting in oxidative stress and damaged cells. The amount of oxidative stress generated by DADS was found to be a function of its concentration. A significant decrease in superoxide dismutase, glutathione-S-transferase, and glutathione peroxidase activities but an increase in catalase activity were observed. Increased levels of lipid peroxidation and decreased levels of glutathione were observed in treated cells. Activity of glucose-6-phosphate dehydrogenase decreased significantly following DADS treatment and could be correlated with a decrease in glutathione concentration in both Candida species. These results indicate that diallyl disulphide acts as a pro-oxidant to Candida species and hence may act as a potent antifungal in the management of candidiasis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.201
Teacher spread0.193 · 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

Citations20
Published2010
Admission routes1
Has abstractyes

Explore more

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