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Effect of trace iron levels and iron withdrawal by chelation on the growth of Candida albicans and Candida vini

2010· article· en· W2164985688 on OpenAlexaff
Bruce E. Holbein, Ramón Mira de Orduña

Bibliographic record

VenueFEMS Microbiology Letters · 2010
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsBeef Farmers of Ontario
Fundersnot available
KeywordsCandida albicansLactoferrinDeferiproneChelationYeastChemistryMicrobiologyFood spoilageBiochemistryBiologyBacteriaInorganic chemistry

Abstract

fetched live from OpenAlex

The iron requirements of the opportunistic pathogenic yeast, Candida albicans, and the related nonpathogenic spoilage yeast Candida vini were investigated along with their responses to various exogenous iron chelators. The influence of iron as well as the exogenous chelating agents lactoferrin, EDTA, deferiprone, desferrioxamine, bathophenanthroline sulphonate and a novel carried chelator with a hydroxypyridinone-like Fe-ligand functionality, DIBI, on fungal growth was studied in a chemically defined medium deferrated to trace iron levels (<1.2 microg L(-1) or 0.02 microM of Fe). Candida albicans competed better at low iron levels compared with C. vini, which was also more susceptible to most added chelators. Candida albicans was resistant to lactoferrin at physiologically relevant concentrations, but was inhibited by low concentrations of DIBI. Candida vini was sensitive to lactoferrin as well as to DIBI, whose inhibitory activity was shown to be Fe reversible. The pathogenic potential of C. albicans and the nonpathogenic nature of C. vini were consistent with their differing abilities to grow under iron-limiting conditions and in the presence of exogenous iron chelators. Both yeasts could be controlled by appropriately strong chelators. This work provides the first evidence of the iron requirements of the spoilage organism C. vini and its response to exogenous chelators. Efficient iron withdrawal has the potential to provide the basis for new fungal growth control strategies.

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 score0.255
Threshold uncertainty score0.358

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 studies0.0000.001
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 head0.004
GPT teacher head0.227
Teacher spread0.223 · 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

Citations36
Published2010
Admission routes1
Has abstractyes

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