Plasma Soluble Prion Protein, a Potential Biomarker for Sport-Related Concussions: A Pilot Study
Bibliographic record
Abstract
Sport-related mild traumatic brain injury (mTBI) or concussion is a significant health concern to athletes with potential long-term consequences. The diagnosis of sport concussion and return to sport decision making is one of the greatest challenges facing health care clinicians working in sports. Blood biomarkers have recently demonstrated their potential in assisting the detection of brain injury particularly, in those cases with no obvious physical injury. We have recently discovered plasma soluble cellular prion protein (PrP(C)) as a potential reliable biomarker for blast induced TBI (bTBI) in a rodent animal model. In order to explore the application of this novel TBI biomarker to sport-related concussion, we conducted a pilot study at the University of Saskatchewan (U of S) by recruiting athlete and non-athlete 18 to 30 year-old students. Using a modified quantitative ELISA method, we first established normal values for the plasma soluble PrP(C) in male and female students. The measured plasma soluble PrP(C) in confirmed concussion cases demonstrated a significant elevation of this analyte in post-concussion samples. Data collected from our pilot study indicates that the plasma soluble PrP(C) is a potential biomarker for sport-related concussion, which may be further developed into a clinical diagnostic tool to assist clinicians in the assessment of sport concussion and return-to-play decision making.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".