Acute microcystin exposure induces reversible histopathological changes in Chinook Salmon (<i>Oncorhynchus tshawytscha</i>) and Atlantic Salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
Atlantic Salmon (Salmo salar) and Chinook Salmon (Oncorhynchus tshawytscha) develop a severe liver disease called net-pen liver disease (NPLD), which is characterized by hepatic lesions that include megalocytosis and loss of gross liver structure. Based on studies where salmonids have been exposed to microcystin (MC) via intraperitoneal injection, NPLD is believed to be caused by MC exposure, a hepatotoxin produced by cyanobacteria. Despite the link between MC and NPLD, it remains uncertain if environmentally relevant MC exposure is responsible for NPLD. To determine if we could produce histopathology consistent with NPLD, we compared the response of Atlantic and Chinook Salmon sub-lethal MC exposure. Salmon were orally gavaged with saline or MC containing algal paste and sampled over 2 weeks post-exposure. Liver lesions appeared by 6 h but were resolved 2-weeks post-exposure; histopathological changes observed in other tissues were not as widespread, nor was their severity as great as those in the liver. There was no evidence for NPLD due to the absence of hepatic megalocytosis. These results indicate that the development of NPLD is not due to acute MC exposure but may be associated with higher MC concentration occurring in food, long-term exposure through drinking of contaminated seawater and/or interactions with other marine toxins.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".