Apoptotic susceptibility, muscle and mitochondrial perturbations in skeletal muscle of p53 wild‐type (WT) and knockout (KO) mice
Bibliographic record
Abstract
Evidence indicates that p53 plays a role in modulating apoptosis, cell‐cycle arrest and aerobic metabolism. Our goal was to evaluate the role of p53 in regulating basal and exercise‐induced apoptosis in skeletal muscle. p53 KO mice had impaired whole muscle cytochrome c oxidase (COX) activity and reduced intermyofibrillar (IMF) state 3 respiration. The rate of reactive oxygen species (ROS) production during state 3 was ∼75% higher in subsarcolemmal (SS) mitochondria and ∼ 2‐fold higher in IMF mitochondria in KO mice. Despite this, KO mice had a 46% lower maximum speed (Vmax) of mitochondrial permeability transition pore (mtPTP) opening and a 19% greater time to Vmax in SS mitochondria. There were no changes in pore kinetics in the IMF mitochondria. However, a ∼2‐fold decrease in basal cytochrome c release in the IMF mitochondria in p53 KO mice was detected. Surprisingly, muscle weight / gram of body weight was 1.7‐fold higher in KO, compared to the WT animals. p53 KO mice that were endurance trained for eight weeks on a running wheel ran ∼5‐fold lower distances than the WT mice, and exhibited a trend towards decreased ROS production in the SS mitochondria. Muscle fatigue, evaluated using in situ muscle contraction, was also greater in KO animals. These data indicate that lack of p53 impairs mitochondrial function, endurance capacity and reduces apoptotic potential in skeletal muscle.
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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 | 0.001 | 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".