Identification of a Novel Afipia Species Isolated from an Indian Flying Fox
Bibliographic record
Abstract
An old world fruit bat Pteropus giganteus, held in captivity and suffering from necrosis of its wing digits, failed to respond to antibiotic therapy and succumbed to the infection. Samples submitted to the National Centre for Foreign Animal Disease were tested for viral infection. Vero E6 cells exhibited minor but unique cytopathic effects on second blind passage, and full CPE by passage four. Utilizing an unbiased random amplification technique from cell culture supernatant, we identified a bacterium belonging to the Bradyrhizobiaceae. Purification of cell culture supernatant on TY media revealed a slow growing bacterial isolate. In this study using electron microscopy, 16S rRNA gene analysis and whole genome sequencing, we identify a novel bacterial species associated with the site of infection belonging to the genus Afipia. This genus of bacteria is very diverse, with only a limited number of species characterized. Afipia felis, previously described as the etiological agent to cause cat scratch disease, and Afipia septicemium, most recently shown to cause disease in humans, highlight the potential for members of this genus to form a branch of opportunistic pathogens within the Bradyrhizobiaceae. Increased utilization of next generation sequencing and genomics will aid in classifying additional members of this intriguing bacterial genera.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".