The effects of post stroke Captopril versus Losartan treatment on cerebral blood flow autoregulation after hemorrhagic stroke
Bibliographic record
Abstract
Kyoto Wistar stroke prone hypertensive rats (SHRsp) lose the ability to regulate constant cerebral blood flow (CBF) in response to varying mean arterial pressures (MAP) after hemorrhagic stroke (HS). We tested the ability of Captopril (CAP) and Losartan (LOS) treatment to restore CBF autoregulation after stroke. CAP (50mg/kg/day) or LOS (35 mg/kg/day) were administered orally at the first signs of stroke. Laser Doppler techniques measured alterations in CBF in response to varying MAP (90 to 300 mmHg). Both post stroke treatments expanded the lifespan of SHRsp from 14 to > 60 days without greatly altering blood pressure. Two weeks before HS, SHRsp regulated near constant CBF up to an MAP of 200 mmHg. CBF regulation was lost at the first symptoms of stroke. CBF (relative to maximal flow) increased linearly with MAP and was 2 fold higher than pre‐stroke levels. Post stroke CAP and LOS treatment restored CBF regulation to pre‐stroke levels within 12 days. However, CAP treated SHRsp lost the ability to autoregulate CBF after 32 days of treatment whereas LOS treated rats retained this function to 60 days. It is possible that the ability of angiotensin II to stimulate AT‐2 receptors under conditions of AT‐1 receptor blockade by LOS may be of advantage in producing a more permanent restoration of cerebrovascular function after HS.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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".