Response of Central Nervous System Biomolecules and Systemic Biomarkers to Aerobic Exercise Following Concussion: A Scoping Review of Human and Animal Research
Bibliographic record
Abstract
The purpose of this study was to identify the response of biomolecules and biomarkers that are associated with the central nervous system to aerobic exercise in human and pre-clinical models of concussion or mild traumatic brain injury (TBI), and to highlight the knowledge gaps in the literature. A systematic scoping review was conducted following a search of EMBASE, MEDLINE, SCOPUS, BIOSIS, and Cochrane Libraries performed on September 8, 2023 (from data base inception). The scoping review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews. Duplicates were removed and article screening was performed using an online systematic review management system. The search resulted in a total of 2,449 articles being identified, with 14 articles meeting the inclusion/exclusion criteria and having their data extracted. One study was conducted in humans, while the remainder of identified studies utilized murine models. The current literature is limited and evaluated many different biomolecules and biomarkers with brain-derived neurotrophic factor being the most researched. Further studies on this topic are needed to better understand the biomarker response to exercise after concussion and mild TBI, especially in the human population.
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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 | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".