Oral Microcystin-LR Does Not Cause Hepatotoxicity in Pigs: Is the Risk of Microcystin-LR Overestimated?
Bibliographic record
Abstract
Abstract The global increase of toxin-producing cyanobacteria poses a serious risk to humans. Many investigations have shown that the cyanotoxin microcystin-LR induces hepatotoxicity in rodents. However, many of these studies applied the toxin intraperitoneally or used high oral concentrations, leading to an unrealistically high bioavailability of the toxin. Such approaches have put into question how these results translate to human exposure scenarios. Epidemiology studies have linked microcystin-LR with hepatotoxicity and liver cancer in humans, though by design these investigations cannot provide direct evidence. The present work investigated the effect of microcystin-LR exposure on pigs closely mimicking real-life human conditions. In two animal experiments, pigs were administered microcystin-LR daily by oral gavage for 35 days. Metabolomic and lipidomic tools were used to analyse blood and liver samples. In addition, blood biochemistry parameters indicative of liver function and health were studied to further investigate the potential hepatotoxic effects of microcystin-LR. Results indicated that the metabolomic and lipidomic analyses did not show a gross treatment effect in blood and liver. Furthermore, no significant alterations were found in the tested blood biochemistry parameters. No evidence of hepatotoxicity was found. These results shed more light onto the effects (or lack of effects) of low-dose oral microcystin-LR exposure. The data suggests that the risk of oral microcystin-LR exposure may be overestimated.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".