Genotyping and Drug Resistance Profile of Clinical Isolates of Candida Albicans From Vulvovaginal Candidiasis in The Eastern China
Bibliographic record
Abstract
Abstract A total of 244 Candida albicans isolates recovered from VVC patients in Suzhou, Eastern China, were investigated. According to CLSI documents M27-A4 and M59-3ed / M60-2ed, the geometric mean MICs of nine antifungals in increasing order were micafungin(0.048mg/L), anidulafungin (0.132mg/L), caspofungin (0.19mg/L), itraconazole(0.23mg/L), posaconazole(0.25mg/L), voriconazole(0.28mg/L), 5-flucytosine (0.44mg/L), amphotericin B (0.49mg/L) and fluconazole (2.01 mg/L) respectively. Of note, 6.5% (16/244) C. albicans isolates showed resistance mainly to anidulafungin (mono-echinocandin resistance), while voriconazole had the lowest susceptibility rate of 34.8% (85/244), followed by fluconazole 59.4% (145/244), respectively. All isolates were genotyped by allelic combination of 3 microsatellite markers (CEF3, CAIII and LOC4). A total of 129 different allelic genotypes were identified, in which seven different clades were recognized with a discriminatory power of 0.96. Genotype A-D were present in 35% of the isolates. In conclusion, decrease of antifungal drug susceptibility to C. albicans isolates from VVC is alarming. Our findings revealed the genetic diversity of C. albicans isolates among VVC patients and provided insights into the molecular epidemiology of Candida infections in China.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".