The impact of high-fat feeding and parkin overexpression on skeletal muscle mass, mitochondrial respiration, and H<sub>2</sub>O<sub>2</sub> emission
Bibliographic record
Abstract
Obesity is a major risk factor for developing various health problems, including insulin resistance and type 2 diabetes. Although controversial, accumulation of mitochondrial dysfunction, and notably an increase in mitochondrial reactive oxygen species (ROS) production, was proposed as a key contributor leading to obesity-induced insulin resistance. Here, our goal was to investigate whether Parkin overexpression, a key regulator of the removal of dysfunctional mitochondria through mitophagy, could confer protection against obesity-induced mitochondrial dysfunction. To this end, intramuscular injections of adeno-associated viruses (AAVs) were performed to overexpress Parkin in limb muscle of 6-mo-old mice fed a control diet (CD) or a high-fat diet (HFD) for 12 wk. An AAV-expressing the green fluorescent protein (GFP) was used as control. HFD increased fat mass, altered glycemia, and resulted in insulin resistance. Parkin overexpression resulted in an increase in muscle mass in both CD and HFD mice. In CD mice, Parkin overexpression increased maximal mitochondrial respiration and lowered H2O2 emission. HFD increased mitochondrial respiration and, surprisingly, also lowered H2O2 emission. Parkin overexpression did not significantly impact mitochondrial function in HFD mice. Taken altogether, our results indicate that Parkin overexpression positively impacts muscle and mitochondrial health under basal conditions and challenges the notion that intrinsic mitochondrial dysfunction is involved in the development of insulin resistance caused by high-fat feeding.
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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) | 0.000 | 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) | 0.001 | 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".