Neurometabolic and microstructural alterations following a sports-related concussion in female athletes
Bibliographic record
Abstract
BACKGROUND: Sports-related concussions are a major public health concern affecting millions of individuals annually. Neurometabolic and microstructural alterations have been reported in the chronic phase following a concussion in male athletes, while no study has investigated these alterations in female athletes. METHODS: Neurometabolic and microstructural alterations following a concussion were investigated by comparing 10 female athletes with a concussion and 10 control female athletes, using magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI). Athletes with concussion were scanned at least 7 months post-concussion (mean = 18.9 months). RESULTS: MRS revealed a significant lower level of myo-inositol in the hippocampus and the primary motor cortices (M1) bilaterally. DTI analysis using Tract-Based Spatial Statistics (TBSS) showed no difference in fractional anisotropy (FA) while higher level of mean diffusivity (MD) in athletes with concussion was detected in large white matter tracts including the forceps minors, inferior/superior longitudinal fasciculi, inferior fronto-occipital fasciculus, cingulum, uncinate fasciculus, anterior thalamic radiations and corticospinal tract. Moreover, a region of interest approach for the corpus callosum revealed a significant lower level of FA in the segment containing fibres projecting to M1. CONCLUSIONS: This study demonstrates persistent neurometabolic and microstructural alterations in female athletes suffering a sports-related concussion.
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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".