Aldehydic load as an objective imaging biomarker of mild traumatic brain injury
Bibliographic record
Abstract
Abstract Concussion is a mild traumatic brain injury (mTBI) defined as complex neurological impairment induced by biomechanical forces without structural brain damage. There does not yet exist an objective diagnostic tool for concussion. Downstream injury from mTBI stems from oxidative damage leading to the production of neurotoxic aldehydes. A collagen-based 3D corticomimetic scaffold was developed affording an in vitro model of concussion, which confirmed increased aldehyde production in live neurons following impact. To evaluate total aldehyde levels in vivo following mTBI, a novel CEST-MRI contrast agent, ProxyNA 3 , has been implemented in a new model of closed-head, awake, single-impact concussion developed in aged and young mice with aldehyde dehydrogenase 2 (ALDH2) deficiency. Behavioural tests confirm deficits immediately after injury. ProxyNA 3 -MRI was performed before impact, and on days two- and seven- post-impact. MRI signal enhancement significantly increased at two days post-injury and decreased to baseline seven days post-injury in all mice. An increase in astrocyte activation at seven days post-injury confirms the onset of a neuroinflammatory response following aldehyde production in the brain. The data suggest that advanced age and ALDH2 deficiency contribute to increased aldehydic load following mTBI. Overall, ProxyNA 3 was capable of mapping concussion-associated aldehydes, supporting its application as an objective diagnostic tool for 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 | 0.000 |
| 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 | 0.000 |
| 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".