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Record W4309243908 · doi:10.1128/spectrum.03183-22

<i>Candida albicans</i> Reactive Oxygen Species (ROS)-Dependent Lethality and ROS-Independent Hyphal and Biofilm Inhibition by Eugenol and Citral

2022· article· en· W4309243908 on OpenAlexafffund
Zinnat Shahina, Easter Ndlovu, Omkaar Persaud, Taranum Sultana, Tanya E. S. Dahms

Bibliographic record

VenueMicrobiology Spectrum · 2022
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of Regina
FundersCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsReactive oxygen speciesBiofilmCandida albicansMicrobiologyEugenolChemistryLethalityBiologyBiochemistryToxicologyBacteriaGenetics

Abstract

fetched live from OpenAlex

Candida albicans is a normal resident on and in the human body that can cause relatively benign infections. However, when our immune system is severely compromised (e.g., cancer chemotherapy patients) or underdeveloped (e.g., newborns), this fungus can become a deadly pathogen, infecting the bloodstream and organs. Since there are only a few effective antifungal agents that can be used to combat fungal infections, these fungi have been exposed to them over and over again, allowing the fungi to develop resistance. Instead of developing antifungal agents that kill the fungi, some of which have undesirable side effects on the human host, researchers have proposed to target the fungal traits that make the fungus more virulent. Here, we show how two components of plant-based essential oils, eugenol and citral, are effective inhibitors of C. albicans virulence traits.

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 score0.002
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.216
Teacher spread0.208 · 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

Citations58
Published2022
Admission routes2
Has abstractyes

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