Should losartan be administered following brain injury?
Bibliographic record
Abstract
Brain injury is a major health concern and associated with delayed neurological complications, including post-injury epilepsy, cognitive and emotional disabilities. Currently, there is no strategy to prevent post-injury delayed complications. We recently showed that dysfunction of the blood-brain barrier, often reported in brain injuries, can lead to epilepsy and neurodegeneration via activation of inflammatory TGF-β signaling in astrocytes. We further showed that the FDA approved angiotensin II type 1 receptor antagonist, losartan, blocks brain TGF-β signaling and prevents epilepsy in the albumin or blood-brain barrier breakdown models of epileptogenesis. Here we discuss the potential of losartan as an anti-epileptogenic and a neuroprotective drug, the rationale of its use following brain injury and the challenges of designing clinical trials. We highlight the urgent need to develop reliable biomarkers for epileptogenesis (and other complications) after brain injury as a pre-requisite to challenge neuroprotective therapies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".