Effects of sertraline hydrochloride and fluconazole combinations on<i>Cryptococcus neoformans</i>and<i>Cryptococcus gattii</i>
Bibliographic record
Abstract
Our study evaluated the efficacy of a combination of fluconazole and the psychoactive compound sertraline against strains of Cryptococcus neoformans and Cryptococcus gattii. Using the chequerboard microdilution method based on CLSI M27-A2 guidelines, we determined the susceptibilities of each drug alone and in combination against 40 strains of serotypes A, D and AD in C. neoformans and 13 strains of serotype B C. gattii. The MIC ranged 10.8–43 and 2–64mg/l for sertraline and fluconazole, respectively. No difference in MICSertraline was observed among the serotypes. However, within C. neoformans, a significant difference in MICFluconazole was observed among the serotypes, as follows: AD >A > D (AD being the most resistant). Strains of C. gattii had MICFluconazole not significantly different from those of serotypes A and AD but significantly higher than serotype D. Synergy (FICI ≤ 0.5) was found for 31 strains, while the remaining 22 strains showed no difference. No evidence for antagonistic interaction was observed. Our study suggests the potential utility of fluconazole–sertraline combination therapy for cryptococcal infections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".