Environmental prevalence of<i>Cryptococcus neoformans</i>and<i>Cryptococcus gattii</i>in India: An update
Bibliographic record
Abstract
An overview of work done to-date in India on environmental prevalence, population structure, seasonal variations and antifungal susceptibility of Cryptococcus neoformans and Cryptococcus gattii is presented. The primary ecologic niche of both pathogens is decayed wood in trunk hollows of a wide spectrum of host trees, representing 18 species. Overall, C. neoformans showed a higher environmental prevalence than that of C. gattii which was not found in the avian habitats. Apart from their arboreal habitat, both species were demonstrated in soil and air in close vicinity of their tree hosts. In addition, C. neoformans showed a strong association with desiccated avian excreta. An overwhelming number of C. neoformans strains belonged to genotype AFLP1/VNI, var. grubii (serotype A), whereas C. gattii strains were genotype AFLP4/VGI, serotype B. All of the environmental strains of C. neoformans and C. gattii were mating type α (MATα). Contrary to the Australian experience, Eucalyptus trees were among the epidemiologically least important and, therefore, the hypothesis of global spread of C. gattii through Australian export of infected Eucalyptus seeds is rebutted. Reference is made to long-term colonization of an abandoned, old timber beam of sal wood (Shorea robusta) by a melanin positive (Mel(+)) variant of Cryptococcus laurentii that was pathogenic to laboratory mice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".