Cognitive gains and cortical thickness changes after 12 weeks of resistance training in older adults with low and high risk of mild cognitive impairment: Findings from a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: In this randomized controlled trial, we assessed the neuroprotective effect of a 12-week resistance training (RT) program on executive control and cortical thickness of the prefrontal, temporal, parietal, and central cortex, regions prone to structural decline in individuals with mild cognitive impairment (MCI). METHODS: Seventy older adults (aged 60-85 y old, 38 females and 32 males) were randomly allocated to a 12-week lower limb RT program or a waiting list control group. The Montreal Cognitive Assessment (MoCA) was used to stratify participants screened for high (< 26) or low (≥ 26) MCI risk. Cognitive measurements consisted of the two-choice reaction time, Go/No-go, mathematical processing, and memory search tests. Cortical thickness was estimated from 3D T1-weighted MR images. RESULTS: ≥ 0.12]. An inspection of these observations revealed an increase in cortical thickness (+1.18 %) and a decrease in response time (-4.35 %) in individuals with high MCI risk allocated to the exercise group (both uncorrected p = 0.08). Decreased response time on the Go/No-go task was associated with increased cortical thickness in the right entorhinal gyrus (uncorrected p = 0.01). CONCLUSIONS: Our study demonstrated that 12 weeks of RT intervention may effectively improve cognitive performance and slow neuronal loss in the hippocampal complex of older adults at high MCI risk. Findings support evidence for the neuroprotective effects of resistance training and its potential role in cognitive health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".