Primary Blast-Induced Traumatic Brain Injury in Rats Leads to Increased Prion Protein in Plasma: A Potential Biomarker for Blast-Induced Traumatic Brain Injury
Bibliographic record
Abstract
Traumatic brain injury (TBI) is deemed the "signature injury" of recent military conflicts in Afghanistan and Iraq, largely because of increased blast exposure. Injuries to the brain can often be misdiagnosed, leading to further complications in the future. Therefore, the use of protein biomarkers for the screening and diagnosis of TBI is urgently needed. In the present study, we have investigated the plasma levels of soluble cellular prion protein (PrPC) as a novel biomarker for the diagnosis of primary blast-induced TBI (bTBI). We hypothesize that the primary blast wave can disrupt the brain and dislodge extracellular localized PrPC, leading to a rise in concentration within the systemic circulation. Adult male Sprague-Dawley rats were exposed to single pulse shockwave overpressures of varying intensities (15-30 psi or 103.4-206.8 kPa] using an advanced blast simulator. Blood plasma was collected 24 h after insult, and PrPC concentration was determined with a modified commercial enzyme-linked immunosorbent assay (ELISA) specific for PrPC. We provide the first report that mean PrPC concentration in primary blast exposed rats (3.97 ng/mL ± 0.13 SE) is significantly increased compared with controls (2.46 ng/mL ± 0.14 SE; two tailed test p < 0.0001). Furthermore, we report a mild positive rank correlation between PrPC concentration and increasing blast intensity (psi) reflecting a plateaued response at higher pressure magnitudes, which may have implications for all military service members exposed to blast events. In conclusion, it appears that plasma levels of PrPC may be a novel biomarker for the detection of primary bTBI.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".