Concurrent training associated with moderate walnut consumption improved isokinetic strength, subjective sleep quality, cognitive performance and postural balance in elderly active men: a randomized controlled trial
Bibliographic record
Abstract
AIMS: To investigate the effects of concurrent training (resistance and endurance) associated with moderate walnut consumption on isokinetic strength, subjective sleep quality, cognitive performance and postural balance in physically active elderly men. METHODS: Twenty healthy elderly men were divided into two matched groups, in a randomized controlled experiment. They have participated in three training sessions per week: concurrent (strength and endurance) training + ad libitum diet with walnuts (15 g/day for 6 weeks, CTW: n = 10) and concurrent training + ad libitum diet (CT: n = 10). Isokinetic strength, Spiegel questionnaire, Montreal cognitive assessment and postural balance parameters were assessed 48 h pre- and post-intervention. RESULTS: Absolute peak torque of knee extensors and knee flexors significantly increased compared to pre-training in CTW (15.2% ± 6.7; 13.2% ± 2.3, p < 0.05, respectively) and CT (10.6% ± 6.8; 7.4% ± 2.9, p < 0.05, respectively). Subjective sleep quality increased compared to pre-training for CTW and CT (24% ± 14.4; 10.5% ± 9.4, p < 0.05, respectively) with a significantly greater increase in CTW (p < 0.05). Cognitive performance measured by Montreal cognitive assessment (MoCA) increased only in CTW compared to baseline (7.7% ± 2.5, p < 0.05). Postural balance parameters with dual task decreased only in CTW compared to baseline. CONCLUSIONS: The present study clearly revealed that concurrent training alone or associated with daily walnut (15 g) consumption for 6 weeks significantly increased knee isokinetic strength, support leg standing parameters and sleep quality. Meanwhile, cognitive performance evaluated by MoCA test and postural balance with dual task were improved for CTW group only.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".