Iron Restriction to Clinical Isolates of Candida albicans by the Novel Chelator DIBI Inhibits Growth and Increases Sensitivity to Azoles<i>In Vitro</i>and<i>In Vivo</i>in a Murine Model of Experimental Vaginitis
Bibliographic record
Abstract
ABSTRACT Candida albicans is an important opportunistic pathogen causing various human infections that are often treated with azole antifungals. The U.S. CDC now regards developing candidal antifungal resistance as a threat, creating a need for new and more effective antifungal treatments. Iron is an essential nutrient for all living cells, and there is growing evidence that interference with iron homeostasis of C. albicans can improve its response to antifungals. This study was aimed at establishing whether withholding iron by currently used medical iron chelators and the novel chelator DIBI could restrict growth and also enhance the activity of azoles against clinical isolates of C. albicans . DIBI, but not deferoxamine or deferiprone, inhibited the growth of C. albicans at relatively low concentrationsin vitro, and this inhibition was reversed by iron addition. DIBI in combination with various azoles demonstrated stronger growth inhibition than the azoles alone and greatly prolonged the inhibition of cell multiplication. In addition, the administration of DIBI along with fluconazole (FLC) to mice inoculated with an FLC-sensitive isolate in a model of experimental C. albicans vaginitis showed a markedly improved clearance of infection. These results suggest that iron chelation by DIBI has the potential to enhance azole efficacy for the treatment of candidiasis.
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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) | 0.001 | 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".