Upstream activators of PGC‐1α transcription with acute contractile activity (1164.4)
Bibliographic record
Abstract
PGC‐1α is a potent transcriptional coactivator of numerous genes involved in contractile activity‐induced mitochondrial biogenesis. We sought to describe the role of transcription factors that regulate the PGC‐1α promoter in the context of acute contractile activity along with established downstream targets. A 1.5kb upstream region of the PGC‐1α promoter fused to a luciferase reporter was injected and electroporated into the rat tibialis anterior (TA) muscle bilaterally. Five days after injection the left TA was subjected to in situ contractile activity for 15 mins (5 mins at 1 Hz, 10 mins at 10Hz) while the right TA served as a resting control. Animals were allowed to recover for 2 hours, and then tissues were extracted. During stimulation, muscle force declined to 40% of initial tension. Transcriptional activity of the PGC‐1α promoter was elevated 3.6‐fold in the stimulated TA, while PGC‐1α mRNA was increased by 1.4‐fold. COX IV and NRF‐1, transcriptional targets of PGC‐1α, were each elevated by 1.2‐fold. NF‐E2 related factor 2 (Nrf2), a transcription factor with a putative binding site on the PGC‐1α promoter was increased by 1.4‐fold at the mRNA level, while GATA4, previously identified as a transcriptional regulator of PGC‐1α, remained unchanged. Thus, contractile activity signals lead to large increases in PGC‐1α transcription along with smaller increments in upstream activators, and downstream targets. Grant Funding Source : Supported By NSERC.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".