An Overview of Reptile Fungal Pathogens in the Genera Nannizziopsis, Paranannizziopsis, and Ophidiomyces
Bibliographic record
Abstract
Abstract Two recent molecular analyses of morphologically similar fungal isolates formerly grouped under the appellation “ Chrysosporium anamorph of Nannizziopsis vriesii (CANV) complex” led to major taxonomic revisions and revealed new insights into the biology of these reptile pathogens. All CANV-complex isolates differed from N. vriesii and were assigned to 16 species, either within Nannizziopsis or within the new genera Paranannizziopsis and Ophidiomyces , and 14 of these species were newly described. From these revisions, a trend in host specificity clearly emerged that was not previously apparent. Nannizziopsis now includes nine species associated with chamaeleonid, gekkonid, cordylid, teiid, agamid, and iguanid lizards; crocodiles; and human hosts. Paranannizziopsis includes four species that infect squamates and tuataras. Ophidiomyces , with the single species Ophidiomyces ophiodiicola (formerly Chrysosporium ophiodiicola ), is only associated with terrestrial or semiaquatic snakes. Nannizziopsi guarroi (formerly Chrysosporium guarroi ) is the main causal agent of yellow fungus disease in captive bearded dragons ( Pogona vitticeps ), and O. ophiodiicola is the cause of mycoses in captive snakes and of snake fungal disease, an emergent global threat to populations of endangered wild snakes. Histopathology, polymerase chain reaction assays, and culture are crucial for confirming a diagnosis of fungal infection in reptiles; however, because fungal identification based on morphologic and physiologic features alone is difficult, sequencing should be sought to speciate reptile fungal isolates. Information gathered from PCR assays and molecular speciation will help in outlining pathogenic potential and contagion risks associated with each of these newly recognized fungal species and allow for a more comprehensive understanding of the ecology, distribution, and host range of these pathogens.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".