Abstract 15119: Remote Ischemic Preconditioning Does Not Affect Skeletal Muscle Energy Metabolism Measured by 31-Phosphorus Magnetic Resonance Spectroscopy: A Randomized Crossover Trial
Bibliographic record
Abstract
Background: Remote ischemic preconditioning (RIPC), induced by transient limb ischemia, has been demonstrated to protect organs against ischemia-reperfusion injury and to improve maximal, but not submaximal exercise performance. Nonetheless, the cellular mechanisms remain poorly understood. Phosphocreatinine concentration was recently shown to recover more rapidly during reperfusion in muscle that has undergone local ischemic preconditioning. Therefore, we used 31P-MRS and blood oxygen level dependent MRI (BOLD fMRI) to test the hypothesis that RIPC beneficially modifies muscle metabolism and perfusion during maximal but not submaximal exercise. Method: Ten healthy subjects, 20 to 27 years, were randomised to RIPC (4 cycles of 5 minutes (min) arm ischemia/5 min reperfusion) or sham procedure, then crossed-over to the other intervention. Each subject performed ten 30 seconds (sec) bouts at 65% of the previously determined maximal work rate each separated by 15 sec of rest. Finally, six of the subjects also performed two bouts of 60 sec of maximal (100%) exercise. 31P-MRS and BOLD fMRI data were obtained before and after every testing protocol. Results: There were no differences for ATP production (0.3±0.1 RIPC mmol/L, 0.3±0.1 SHAM, p=0.90), phosphocreatinine to inorganic phosphate ratio (0.9±0.8, 1.0±0.7, p=0.78) or in the half-time of phosphocreatinine recovery (27.1±11.8, 24.6±12.8 sec, p=0.66) during submaximal exercise. There were also no differences in BOLD signal amplitude between RIPC and SHAM (279.3 ± 169.3, 276.6 + 135.9, p=0.96) or for BOLD signal intercept (1614.0 + 373.4, 1522.7 + 332.9, p = 0.1), or for the BOLD signal recovery time constant (75.5 + 154.5, 47.3 + 23.6 sec, p=0.34). Similarly for the maximal exercise protocol, we observed no difference in pre vs. post-exercise pH (0.77±0.26, 0.93±0.14, p= 0.29), post-exercise phosphocreatinine and phosphate ratio (1.9±1.5, 2.4±2.4, p=0.70) or in the half-time of phosphocreatinine recovery (23.0±19.5, 20.2±7.3 sec, p=0.67). Conclusion: The lack of demonstrated effect of RIPC on aerobic and anaerobic energy metabolism, and perfusion, is different than previously shown with local preconditioning and may suggest that different mechanisms play a role in the observed effects of RIPC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".