Detection of Pathogenic <i>Leptospira</i> Bacteria in Pinniped Populations via PCR and Identification of a Source of Transmission for Zoonotic Leptospirosis in the Marine Environment
Bibliographic record
Abstract
Leptospirosis, caused by the spirochete Leptospira, is a geographically widespread disease that affects a broad range of mammals, including marine mammals. Among pinniped populations, periodic epizootics of leptospirosis are responsible for significant die-offs. Along the west coast of North America, the most recent leptospirosis epizootic occurred in 2004, during which samples were collected from cases ranging from California to British Columbia. The primary objective of this study was to use this well-defined sample set to determine the feasibility of using PCR techniques to diagnose Leptospira infection among pinniped populations in comparison with diagnostic methodologies commonly used for marine mammals. Successful amplification was achieved from a variety of samples, including freshly collected urine, urine stored at -80 degrees C for less than 6 months, and kidney (freshly collected, frozen, and decomposed), as well as feces- and urine-contaminated sand collected in the vicinity of a live-stranded animal. Pathological examination of tissue collected from Leptospira-infected animals revealed the presence of leptospiral antigen in the kidneys. The use of species-specific primer pairs revealed a pattern of host specificity for Leptospira interrogans in sea lions and Leptospira kirschneri in elephant seals. These studies indicate PCR is a sensitive and specific diagnostic tool for the detection of Leptospira infection in pinnipeds and reveal a potential source for epizootic, enzootic, and zoonotic spread of leptospirosis in a marine environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".