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Record W3006825747 · doi:10.1128/msphere.00913-19

Metabolic Reprogramming in the Opportunistic Yeast Candida albicans in Response to Hypoxia

2020· article· en· W3006825747 on OpenAlexafffund
Anaïs Burgain, Faïza Tebbji, Inès Khemiri, Adnane Sellam

Bibliographic record

VenuemSphere · 2020
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversité Laval
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchGovernment of CanadaFondation CHU de QuébecCentre Hospitalier Universitaire de QuébecNatural Sciences and Engineering Research Council of Canada
KeywordsLipidomeMetabolomeCandida albicansBiologyMetabolomicsErgosterolBiochemistryMetabolic pathwayPentose phosphate pathwayYeastCell biologyMicrobiologyLipidomicsMetabolismGlycolysisBioinformatics

Abstract

fetched live from OpenAlex

A critical aspect of cell fitness is the ability to sense and adapt to variations in oxygen levels in their local environment. Candida albicans is an opportunistic yeast that is the most prevalent human fungal pathogen. While hypoxia is the predominant condition that C. albicans encounters in most of its niches, its impact on fungal metabolism remains unexplored so far. Here, we provided a detailed landscape of the C. albicans metabolome that emphasized the importance of many metabolic routes for the adaptation of this yeast to oxygen depletion. The fungal hypoxic metabolome identified in this work provides a framework for future investigations to assess the contribution of relevant metabolic pathways in the fitness of C. albicans and other human eukaryotic pathogens with similar colonized human niches. As hypoxia is present at most of the fungal infection foci in the host, hypoxic metabolic pathways are thus an attractive target for antifungal therapy.

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 score0.003

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.301
Teacher spread0.257 · 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

Citations40
Published2020
Admission routes2
Has abstractyes

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