Targeting Uric Acid Prevents Brain Injury and Anxiety in a Rat Model of Hemorrhagic Shock
Bibliographic record
Abstract
ABSTRACT: Secondary brain injury following hemorrhagic shock (HS) is a frequent complication in patients, even in the absence of direct brain trauma, leading to behavioral changes and more specifically anxiety and depression. Despite preclinical studies showing inflammation and apoptosis in the brain after HS, none have addressed the impact of circulating mediators. Our group demonstrated an increased uric acid (UA) circulation in rats following HS. Since UA is implicated in endothelial dysfunction and inflammatory response, we hypothesized UA could alter the blood-brain barrier (BBB) and impact the brain. Male Wistar rats were randomly assigned to: SHAM, HS (hemorrhagic shock) and HS + U (hemorrhagic shock + 1.5 mg/kg of uricase). The uricase intervention, specifically targeting UA, was administered during fluid resuscitation. It prevented BBB dysfunction (fluorescein sodium salt permeability and expression of intercellular adhesion molecule-1) following HS. As for neuroinflammation, all of the results obtained (MPO activity; Iba1 and GFAP expression) showed a significant increase after HS, also prevented by the uricase. The same pattern was observed after quantification of apoptosis (caspase-3 activity and TUNEL) and neurodegeneration (Fluoro-Jade). Finally, the forced swim, elevated plus maze, and social interaction tests detected anxiety-like behavior after HS, which was blunted in rats treated with the uricase. In conclusion, we have identified UA as a new circulatory inflammatory mediator, responsible for brain alterations and anxious behavior after HS in a murine model. The ability to target UA holds the potential of an adjunctive therapeutic solution to reduce brain dysfunction related to hemorrhagic shock in human.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".