Metal Ions May Suppress or Enhance Cellular Differentiation in <i>Candida albicans</i> and <i>Candida tropicalis</i> Biofilms
Bibliographic record
Abstract
Candida albicans and Candida tropicalis are polymorphic fungi that develop antimicrobial-resistant biofilm communities that are characterized by multiple cell morphotypes. This study investigated cell type interconversion and drug and metal resistance as well as community organization in biofilms of these microorganisms that were exposed to metal ions. To study this, Candida biofilms were grown either in microtiter plates containing gradient arrays of metal ions or in the Calgary Biofilm Device for high-throughput susceptibility testing. Biofilm formation and antifungal resistance were evaluated by viable cell counts, tetrazolium salt reduction, light microscopy, and confocal laser scanning microscopy in conjunction with three-dimensional visualization. We discovered that subinhibitory concentrations of certain metal ions (CrO(4)(2-), Co(2+), Cu(2+), Ag(+), Zn(2+), Cd(2+), Hg(2+), Pb(2+), AsO(2)(-), and SeO(3)(2-)) caused changes in biofilm structure by blocking or eliciting the transition between yeast and hyphal cell types. Four distinct biofilm community structure types were discerned from these data, which were designated "domed," "layer cake," "flat," and "mycelial." This study suggests that Candida biofilm populations may respond to metal ions to form cell-cell and solid-surface-attached assemblages with distinct patterns of cellular differentiation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".