Investigating the Association Between Extended Participation in Collision Sports and Fluid Biomarkers Among Masters Athletes
Bibliographic record
Abstract
Traumatic brain injuries (TBIs) and concussions are prevalent in collision sports, and there is evidence that levels of exposure to such sports may increase the risk of neurological abnormalities. Elevated levels of fluid-based biomarkers have been observed after concussions or among athletes with a history of participating in collision sports, and certain biomarkers exhibit sensitivity toward neurodegeneration. This study investigated a cohort of 28 male amateur athletes competing in “Masters” competitions for persons >35 years of age. The primary objective of this study was to compare the levels of blood and saliva biomarkers associated with brain injury, inflammation, aging, and neurodegeneration between athletes with an extensive history of collision sport participation (i.e., median = 27 years; interquartile range = 18–44, minimum = 8) and those with no history. Plasma proteins associated with neural damage and neurodegeneration were measured using Simoa ® assays, and saliva was analyzed for markers associated with inflammation and telomere length using quantitative real-time polymerase chain reaction. There were no significant differences between collision and non-collision sport athletes for plasma levels of glial fibrillary acidic protein, neurofilament light, ubiquitin C-terminal hydrolase L1, tau, tau phosphorylated at threonine 181, and brain-derived neurotrophic factor. Moreover, salivary levels of genes associated with inflammation and telomere length were similar between groups. There were no significant differences between groups in symptom frequency or severity on the Sport Concussion Assessment Tool–5th Edition. Overall, these findings provide preliminary evidence that biomarkers associated with neural tissue damage, neurodegeneration, and inflammation may not exhibit significant alterations in asymptomatic amateur athletes with an extensive history of amateur collision sport participation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".