Strength gains after 12 weeks of resistance training correlate with neurochemical markers of brain health in older adults: a randomized control 1H-MRS study
Bibliographic record
Abstract
Physical exercise is considered a potent countermeasure against various age-associated physiological deterioration processes. We therefore assessed the effect of 12 weeks of resistance training on brain metabolism in older adults (age range: 60-80 years). Participants either underwent two times weekly resistance training program which consisted of four lower body exercises performed for 3 sets of 6-10 repetitions at 70-85% of 1 repetition maximum (n = 20) or served as the passive control group (n = 21). The study used proton magnetic resonance spectroscopy to quantify the ratio of total N-acetyl aspartate, total choline, glutamate-glutamine complex, and myo-inositol relative to total creatine (tNAA/tCr, tCho/tCr, Glx/tCr, and mIns/tCr respectively) in the hippocampus (HPC), sensorimotor (SM1), and prefrontal (dlPFC) cortices. The peak torque (PT at 60°/s) of knee extension and flexion was assessed using an isokinetic dynamometer. We used repeated measures time × group ANOVA to assess time and group differences and correlation coefficient analyses to examine the pre-to-post change (∆) associations between PT and neurometabolite variables. The control group showed significant declines in tNAA/tCr and Glx/tCr of SM1, and tNAA/tCr of dlPFC after 12 weeks, which were not seen in the experimental group. A significant positive correlation was found between ∆PT knee extension and ∆SM1 Glx/tCr, ∆dlPFC Glx/tCr and between ∆PT knee flexion and ∆dlPFC mIns/tCr in the experimental group. Overall, findings suggest that resistance training seems to elicit alterations in various neurometabolites that correspond to exercise-induced "preservation" of brain health, while simultaneously having its beneficial effect on augmenting muscle functional characteristics in older adults.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".