Molecular Detection of <i>Candidatus</i> Bartonella mayotimonensis in North American Bats
Bibliographic record
Abstract
Candidatus Bartonella mayotimonensis was detected in 2010 from an aortic valve sample of a patient with endocarditis from Iowa, the United States of America. The environmental source of the potentially new endocarditis-causing Bartonella remained elusive. We set out to study the prevalence and diversity of bat-associated Bartonella in North America. During 2015, mist nets and harp traps were used to capture 92 bats belonging to two species: little brown myotis (Myotis lucifugus Le Conte 1831, n = 73) and the gray myotis (M. grisescens A.H. Howell 1909, n = 19) in Kentucky, Michigan, Pennsylvania, and Tennessee. DNA preparations of peripheral blood samples from bats were subjected to a three-marker (gltA, rpoB, and intergenic spacer region [ISR]) multilocus sequence analysis. Sequence-verified gltA-positive PCR amplicons were obtained from nine samples. Three sequences were 99.7-100% identical with the gltA sequence of the Iowa endocarditis patient strain. Analysis of rpoB and ISR sequences demonstrated that one little brown myotis sample from the Upper Peninsula of Michigan contained Bartonella DNA, with 100% sequence identity with the Iowa endocarditis patient strain DNA. It appears possible that bats are a reservoir of Candidatus Bartonella mayotimonensis in North America.
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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 | 0.000 | 0.000 |
| 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".