Multilocus sequence analyses reveal extensive diversity and multiple origins of fluconazole resistance in Candida tropicalis from tropical China
Bibliographic record
Abstract
Candida tropicalis is among the most prevalent human pathogenic yeast species, second only to C. albicans in certain geographic regions such as East Asia and Brazil. However, compared to C. albicans, relatively little is known about the patterns of genetic variation in C. tropicalis. This study analyzed the genetic diversity and relationships among isolates of C. tropicalis from the southern Chinese island of Hainan. A total of 116 isolates were obtained from seven geographic regions located across the Island. For each isolate, a total of 2677 bp from six gene loci were sequenced and 79 (2.96%) polymorphic nucleotide sites were found in our sample. Comparisons with strains reported from other parts of the world identified significant novel diversities in Hainan, including an average of six novel sequences (with a range 1 to 14) per locus and 80 novel diploid sequence types. Most of the genetic variation was found within individual strains and there was abundant evidence for gene flow among the seven geographic locations within Hainan. Interestingly, our analyses identified no significant correlation between the diploid sequence types at the six loci and fluconazole susceptibility, consistent with multiple origins of fluconazole resistance in the Hainan population of C. tropicalis.
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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 | 0.001 | 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".