Seasonal variations in the prevalence of<i>Cryptococcus neoformans</i>var.<i>grubii</i>and<i>Cryptococcus gattii</i>in decayed wood inside trunk hollows of diverse tree species in north-western India: a retrospective study
Bibliographic record
Abstract
This study presents a 7-year retrospective analysis of seasonal variations in the prevalence of Cryptococcus neoformans var. grubii and Cryptococcus gattii in decayed wood inside trunk hollows of 518 trees belonging to 20 species in north-western India during 2000-2007. Of the 1,439 wood samples investigated, 406 (28.2%) were found to be positive for the Cryptococcus neoformans species complex which included 247 samples from which C. neoformans var. grubii was recovered and 171 which yielded C. gattii. While both of the pathogens were isolated through all the seasons, the overall prevalence of C. neoformans var. grubii was significantly higher (17.2%) than that of C. gattii serotype B (11.9%, P < 0.0001), indicating that decayed wood was as good, if not better, a natural habitat of C. neoformans var. grubii as that of C. gattii. The highest recovery of both yeasts was in the autumn, followed by that in the summer. For C. gattii, the lowest prevalence occurred during the winter and for C. neoformans var. grubii during the rainy season. The low prevalence of C. gattii during winter is similar to that reported from Bogota, Colombia, where C. gattii had a low population density in bark samples but it was not found in decayed wood of trunk hollows investigated during the period of January and February. The prevalence of C. neoformans var. grubii was significantly lower in the rainy season than in the other portions of the year. This finding is similar to the reported low isolation frequency (4%) of C. neoformans var. grubii from chicken feces in the rainy season in northern Thailand. Further investigations are warranted to determine the clinical significance of seasonal variations in the prevalence of C. neoformans var. grubii and C. gattii in decayed trunk wood of various trees in climatically divergent regions of India.
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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".