Piscirickettsia salmonis shedding and tissue burden, and hematological responses during cohabitation infections in chum Oncorhynchus keta, pink O. gorbuscha and Atlantic salmon Salmo salar
Bibliographic record
Abstract
BACKGROUND: Salmonid rickettsial septicemia is an emergent and geographically widespread disease of marine-farmed salmonids caused by infection with the water-borne bacterium Piscirickettsia salmonis. Very little is known about the route, timing, or magnitude of bacterial shedding from infected fish. METHODOLOGY/PRINCIPAL FINDINGS: A cohabitation challenge model was used to assess shedding from chum Oncorhynchus keta, pink O. gorbuscha and Atlantic salmon Salmo salar. Infections in donor fish were established by intraperitoneal injection of P. salmonis. Naïve recipients were cohabitated with donor fish after which cumulative percent morbidity and mortality (CMM) was monitored, and bacterial burdens in kidney and in tank water were measured by qPCR. All donor fish died with mean days-to-death (MDD) among species ranging from 17.5 to 23.9. Among recipients, CMM ranged from 42.7% to 77.8% and MDD ranged from 49.7 to 56.4. In each trial, two peaks of bacterial DNA concentrations in tank water closely aligned with the MDD values of donor and recipient fish. Bacterial tissue burden and shedding rate, and plasma physiological parameters were obtained from individual donors and recipients. Statistically significant positive correlations between the shedding rate and P. salmonis kidney burden were measured in donor pink and in donor and recipient chum salmon, but not in donor or recipient Atlantic salmon. In Atlantic salmon, there was a negative correlation between kidney bacterial burden and hematocrit, plasma Ca++ and Mg++ values, whereas in infected chum salmon the correlation was positive for Na+ and Cl- and negative for glucose. CONCLUSIONS: A dependency of bacterial shedding on species-specific patterns of pathogenesis was suggested. The coincidence of bacterial shedding with mortality will inform pathogen transmission models.
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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) | 0.001 | 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".