Single dose and repeated administrations of liraglutide alter energy metabolism in the brains of young and adult rats
Bibliographic record
Abstract
Liraglutide is a human glucagon-like peptide-1 (GLP-1) analogue that was recently approved to treat obesity in some countries. Considering that liraglutide effects on brain energy metabolism are little known, we evaluated the effects of liraglutide on the energy metabolism. Animals received a single or daily injection of saline or liraglutide during 7 days (25, 50, 100, or 300 μg/kg i.p.). Twenty-four hours after the single or last injection, the rats were euthanized and the hypothalamus, prefrontal cortex, cerebellum, hippocampus, striatum, and posterior cortex were isolated. Our results demonstrated that a single dose of liraglutide in young rats increased the activity of complexes and inhibited creatine kinase activity. Repeated administrations of liraglutide in young rats reduced the activity of complexes and activated creatine kinase activity. In adult rats, a single dose of liraglutide reduced the activity of complex I and creatine kinase and increased the activity of complexes II and IV. Repeated administrations of liraglutide in adult rats increased the activity of complexes I and IV and reduced the activity of complex II and creatine kinase. We concluded that liraglutide may interfere in energy metabolism, because analysis of different times of administrations, concentrations, and level of brain development leads to divergent results.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".