Mitochondrial enzyme activity in fish livers is not impacted by parasite presence
Bibliographic record
Abstract
Parasites can impair host performance through various physiological processes, including alterations to host metabolism. Since mitochondria are responsible for cellular energy production, it is likely that disruptions in host cellular metabolism contribute to changes in metabolism at the organismal level. However, some studies investigating parasite-induced alteration in cellular metabolism have been limited by the presence of parasites in the target tissues. Before analyzing these key tissues, it is critical to confirm that the measured enzyme activities reflect those of the hosts rather than the parasites themselves. Here, we tested a parasite extraction protocol to evaluate the extent to which parasite contamination impacts estimates of cellular enzyme activities in hepatic tissues of wild pumpkinseed sunfish (Lepomis gibbosus) infected with bass tapeworm (Proteocephalus ambloplitis). We tested four treatments: uninfected livers, cleaned infected livers, infected livers (repopulated) and parasites alone. We then compared the activity of key metabolic enzymes among groups. PCR tests were used to assess parasitic contamination after applying the parasite extraction protocol on hepatic tissue. Enzyme activities of cleaned livers and contaminated livers were similar even if PCR tests revealed contamination. The intensity of cestode infection also did not influence enzyme activity, which suggests that parasite presence in the livers does not impact the accuracy of the enzyme activity estimates made. Through this protocol, we show that parasite contamination has no effect on metabolism measurements showing that the study of parasitized organs is possible. We also recommend the use of this protocol to avoid any biases in highly infected individuals.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".