Effect of fluoxetine treatment on mitochondrial bioenergetics in central and peripheral rat tissues
Bibliographic record
Abstract
Recent investigations have focused on the mitochondrion as a direct drug target in the treatment of metabolic diseases (obesity, metabolic syndrome). Relatively few studies, however, have explicitly investigated whether drug therapies aimed at changing behavior by altering central nervous system (CNS) function affect mitochondrial bioenergetics, and none has explored their effect during early neonatal development. The present study was designed to evaluate the effects of chronic treatment of newborn male rats with the selective serotonin reuptake inhibitor fluoxetine on the mitochondrial bioenergetics of the hypothalamus and skeletal muscle during the critical nursing period of development. Male Wistar rat pups received either fluoxetine (Fx group) or vehicle solution (Ct group) from the day of birth until 21 days of age. At 60 days of age, mitochondrial bioenergetics were evaluated. The Fx group showed increased oxygen consumption in several different respiratory states and reduced production of reactive oxygen species, but there was no change in mitochondrial permeability transition pore opening or oxidative stress in either the hypothalamus or skeletal muscle. We observed an increase in glutathione S-transferase activity only in the hypothalamus of the Fx group. Taken together, our results suggest that chronic exposure to fluoxetine during the nursing phase of early rat development results in a positive modulation of mitochondrial respiration in the hypothalamus and skeletal muscle that persists into adulthood. Such long-lasting alterations in mitochondrial activity in the CNS, especially in areas regulating appetite, may contribute to permanent changes in energy balance in treated animals.
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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) | 0.000 | 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 | 0.001 |
| 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".