Endurance swimming activates trout lipoprotein lipase: plasma lipids as a fuel for muscle
Bibliographic record
Abstract
Fish endurance swimming is primarily powered by lipids supplied to red muscle by the circulation, but the mechanism of delivery remains unknown. By analogy to mammals, previous studies have focused on non-esterified fatty acids (NEFA bound to albumin), but lipoproteins have not been considered as an energy shuttle to working muscles. The effects of exercise on fish lipoprotein lipase (LPL) have never been investigated. We hypothesized that LPL and circulating lipoproteins would be modified by prolonged swimming. Because LPL is naturally bound to the endothelium, we have used heparin to release the enzyme in the circulation and to characterize reserve capacity for lipoprotein catabolism. The effects of exercise (4 days at 1.5 body lengths s(-1) in a swim tunnel) were measured for red muscle LPL, post-heparin plasma LPL, and lipoprotein concentration/composition. Red muscle LPL activity increased from 18+/-5 (rest) to 49+/- 9 nmol fatty acids min(-1) g(-1) (swimming). In resting fish, heparin administration caused a 27-fold increase in plasma LPL activity that reached a maximum of 1.32+/- 0.67 micromol fatty acids min(-1) ml(-1) plasma. This heparin-induced response of plasma LPL was not different between resting controls and exercised fish. Heparin or prolonged swimming had no effect on the concentration/composition of lipoproteins that contain 92% of the energy in total plasma lipids. We conclude that (1) red muscle LPL is strongly activated by endurance swimming, (2) rainbow trout have a high reserve capacity for hydrolyzing lipoproteins, and (3) future studies should aim to measure lipoprotein flux because their concentration does not reflect changes in flux. These novel characteristics of fish LPL imply that lipoproteins are used as a metabolic shuttle between fat reserves and working muscles, a strategy exploiting an abundant source of energy in rainbow trout.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".