Impact of BDNF Val66Met polymorphism on olfactory functions of female concussed athletes
Bibliographic record
Abstract
BACKGROUND: Concussions exert persistent effects on asymptomatic athletes, especially women. Among chief mechanisms of concussion recovery are alterations of neuronal plasticity. Olfactory function, often impaired following a concussion, greatly involves plasticity and, therefore, appears as a good candidate to study the deleterious effects of concussions. The BDNF Val66Met polymorphism (BDNFMet), which reduces availability of BDNF in the brain, has surprisingly been associated with better recovery following concussion. OBJECTIVE: This study examines the mediating effect of BDNFMet on olfactory functions in asymptomatic concussed female athletes. METHODS: Participants, 105 female university athletes, were divided into four groups based on their history of concussion (Concussion/No concussion) and BDNF polymorphism (BDNF Val66Val/Val66Met). Odour threshold, discrimination and identification were measured using the Sniffin' Sticks Inventory Test. RESULTS: Concussed female BDNFMet athletes performed significantly better than BDNFVal counterparts on threshold (F(1, 34) = 4.73, p < 0.05), discrimination (F(1, 52) = 5.36, p < 0.05), identification tests (F(1, 52) = 5.65, p < 0.05) and total olfactory scores (F(1, 34) = 9.54, p < 0.05). CONCLUSION: These results support a genotypic effect of the BDNF Val66Met polymorphism on long-term olfactory function following a concussion in young female athletes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".