The effects of trifluoperazine on brain edema, aquaporin-4 expression and metabolic markers during the acute phase of stroke using photothrombotic mouse model
Bibliographic record
Abstract
Stroke is the second leading cause of death and the third leading cause of disability globally. Edema is a hallmark of stroke resulting from dysregulation of water homeostasis in the central nervous system (CNS) and plays the major role in stroke-associated morbidity and mortality. The overlap between cellular and vasogenic edema makes treating this condition complicated, and to date, there is no pathogenically oriented drug treatment for edema. Water balance in the brain is tightly regulated, primarily by aquaporin 4 (AQP4) channels, which are mainly expressed in perivascular astrocytic end-feet. Targeting AQP4 could be a useful therapeutic approach for treating brain edema; however, there is no approved drug for stroke treatment that can directly block AQP4. In this study, we demonstrate that the FDA-approved drug trifluoperazine (TFP) effectively reduces cerebral edema during the early acute phase in post-stroke mice using a photothrombotic stroke model. This effect was combined with an inhibition of AQP4 expression at gene and protein levels. Importantly, TFP does not appear to induce any deleterious changes on brain electrolytes or metabolic markers, including total protein or lipid levels. Our results support a possible role for TFP in providing a beneficial extra-osmotic effect on brain energy metabolism, as indicated by the increase of glycogen levels. We propose that targeting AQP4-mediated brain edema using TFP is a viable therapeutic strategy during the early and acute phase of stroke that can be further investigated during later stages to help in developing novel CNS edema 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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".