Repetitive Low-Level Blast Exposure Alters Circulating Myeloperoxidase, Matrix Metalloproteinases, and Neurovascular Endothelial Molecules in Experienced Military Breachers
Bibliographic record
Abstract
Repeated exposure to low-level blast overpressure, frequently experienced during explosive breaching and heavy weapons use in training and operations, is increasingly recognised as a serious risk to the neurological health of military personnel. Although research on the underlying pathobiological mechanisms in humans remains limited, this study investigated the effects of such exposure on circulating molecular biomarkers associated with inflammation, neurovascular damage, and endothelial injury. Blood samples from military breachers were analysed for myeloperoxidase (MPO), matrix metalloproteinases (MMPs), and junctional proteins indicative of blood-brain barrier (BBB) disruption and endothelial damage, including occludin (OCLN), zonula occludens-1 (ZO-1), aquaporin-4 (AQP4), and syndecan-1 (SD-1). The results revealed significantly elevated levels of MPO, MMP-3, MMP-9, and MMP-10 in breachers compared to unexposed controls, suggesting heightened inflammation, oxidative stress, and vascular injury. Increased levels of OCLN and SD-1 further indicated BBB disruption and endothelial glycocalyx degradation in breachers. These findings highlight the potential for chronic neurovascular unit damage/dysfunction from repeated blast exposure and underscore the importance of early targeted interventions-such as reducing oxidative stress, reinforcing BBB integrity, and managing inflammation-that could be essential in mitigating the risk of long-term neurological impairment associated with blast exposure.
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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) | 0.000 | 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".