Real-time RT-PCR analysis of housekeeping genes in human skeletal muscle following acute exercise
Bibliographic record
Abstract
Studies examining gene expression with RT-PCR typically normalize their mRNA data to a constitutively expressed housekeeping gene. The validity of a particular housekeeping gene must be determined for each experimental intervention. We examined the expression of various housekeeping genes following an acute bout of endurance (END) or resistance (RES) exercise. Twenty-four healthy subjects performed either a interval-type cycle ergometry workout to exhaustion ( approximately 75 min; END) or 300 single-leg eccentric contractions (RES). Muscle biopsies were taken before exercise and 3 h and 48 h following exercise. Real-time RT-PCR was performed on beta-actin, cyclophilin (CYC), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and beta2-microglobulin (beta2M). In a second study, 10 healthy subjects performed 90 min of cycle ergometry at approximately 65% of Vo(2 max), and we examined a fifth housekeeping gene, 28S rRNA, and reexamined beta2M, from muscle biopsy samples taken immediately postexercise. We showed that CYC increased 48 h following both END and RES exercise (3- and 5-fold, respectively; P < 0.01), and 28S rRNA increased immediately following END exercise (2-fold; P = 0.02). beta-Actin trended toward an increase following END exercise (1.85-fold collapsed across time; P = 0.13), and GAPDH trended toward a small yet robust increase at 3 h following RES exercise (1.4-fold; P = 0.067). In contrast, beta2M was not altered at any time point postexercise. We conclude that beta2M and beta-actin are the most stably expressed housekeeping genes in skeletal muscle following RES exercise, whereas beta2M and GAPDH are the most stably expressed following END exercise.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".