Does exercise protect from cognitive decline by altering brain cytokine and apoptotic protein levels? A systematic review of the literature.
Bibliographic record
Abstract
Regular exercise is thought to provide protection against age-related cognitive decline and possibly reduce risk of dementias. The mechanisms for the exercise protective effects are not known although changes in inflammatory cytokine levels may be involved. We conducted a systematic review of the literature to assess (1) the effects of exercise on cytokines in the brain, (2) the methodological rigour of studies which have examined these exercise effects and (3) the potential role of regular exercise in reducing the pro-inflammatory cytokine milieu that may contribute to dementia. We also reviewed the effects of exercise on concurrent pro and anti-apoptotic protein expression in the brain as related to cytokine changes. Five databases were searched until January 2010 with an initial 630 articles identified; 61 articles were retrieved of which 10 met study inclusion criteria. Investigations of both acute and chronic (training) exercise were assessed for methodological quality using a modified PEDro scale. Two studies were carried out with human participants and eight with mouse or rat models; studies differed markedly in design and methodological rigour; the types, intensities and durations of exercise, the cytokine and apoptotic proteins measured, and the regions of the brain (or proxy compartments) sampled. Despite variations in design, specific cytokine outcomes, and exercise type, the 10 studies provide limited evidence that acute strenuous exercise increases and exercise training decreases pro-inflammatory cytokines centrally. Two animal studies relate training associated decreases in pro-inflammatory cytokines with improved cognitive function using behavioural assessments such as the Morris maze. Recommendations for the design of future research on exercise, central cytokines, and cognition are offered.
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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".