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Metal resistance in Candida biofilms

2006· article· en· W1921223503 on OpenAlexafffund
Joe J. Harrison, Maryam Rabiei, Raymond J. Turner, Erin A. Badry, Kimberley M. Sproule, Howard Ceri

Bibliographic record

VenueFEMS Microbiology Ecology · 2006
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiofilmBiologyMetal toxicityCandida tropicalisMetalMicrobiologyMetal ions in aqueous solutionExtracellular polymeric substanceToxicityChelationCandida albicansEnvironmental chemistryBacteriaChemistryInorganic chemistry

Abstract

fetched live from OpenAlex

Yeasts are often successful in metal-polluted environments; therefore, the ability of biofilm and planktonic cell Candida tropicalis to endure metal toxicity was investigated. Fifteen water-soluble metal ions, chosen to represent groups 6A to 6B of the periodic table, were tested against this organism. With in vitro exposures as long as 24 h, biofilms were up to 65 times more tolerant to killing by metals than corresponding planktonic cultures. Of the most toxic heavy metals tested, only very high concentrations of Hg2+, CrO4 (2-) or Cu2+ killed surface-adherent Candida. Metal-chelator precipitates could be formed in biofilms following exposure to the heavy metals Cu2+ and Ni2+. This suggests that Candida biofilms may adsorb metal cations from their surroundings and that sequestration in the extracellular matrix may contribute to resistance. We concluded that biofilm formation may be a strategy for metal resistance and/or tolerance in yeasts.

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)0.001
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.007
GPT teacher head0.240
Teacher spread0.233 · 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

Citations105
Published2006
Admission routes2
Has abstractyes

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