Development of a new militarily-relevant whole-body low-intensity blast model for mild and subconcussive traumatic brain injury: Examination of acute neurological and multi-organ pathological outcomes
Bibliographic record
Abstract
Abstract This work describes a newly developed experimental mouse model reproducing features of blast-induced neurotrauma (BINT), induced in operationally relevant manner using a compressed air-driven shock tube. Mild BINT (smBINT) was induced by one exposure to a low-intensity blast (LIB), whereas subconcussive BINT (rscBINT) was caused by repeated exposures to LIB. To mimic an operational scenario when a soldier is standing when exposed to blast using a quadruped experimental animal (mouse), a whole-body holder was developed to position mice in a bipedal stance, face-on toward the pressure wave generated in a shock tube. This restraint avoids ‘bobble head’ movement, thus prevents tertiary blast effects, and allows administration of fast-acting inhaled anesthetics via nose cone. Using this model, we established and validated paradigms for primary blast-induced mild and repetitive traumatic brain injuries Our results showed that a single exposure to 69 kPa (10 psi) was capable of inducing smBINT, whereas three-rounds of exposure to 41 kPa (6 psi) caused rscBINT. Mice recovered rapidly from both types of BINT without prolonged neurological dysfunction. Mild superficial pathology was found predominantly in the lungs 24h after injury, with equivalent pathology after smBINT or repetitive rscBINT. The Purkinje layer of the cerebellum exhibited neuronal damage persisting up to 7d. Similar to some other models as well as clinical findings, this model reproduces blast-induced cerebellar pathology. In conclusion, this model positioning mice in a bipedal stance and facing front-on toward the shockwave provides realistic representation of operational scenarios and reproduces militarily-relevant smBINT and rscBINT in the laboratory.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".