Oxidative Stress, Metabolic Impairment and Neuroinflammation are Associated With Target Organ Damage in SHRSP
Bibliographic record
Abstract
Stroke-prone spontaneously hypertensive rats (SHRSP) are widely used as a model to study cerebral small vessel disease (CSVD) and its association with chronic hypertension. This study investigated the relationship between metabolic, cardiovascular, and neuronal comorbidities in 32-week-old SHRSP rats versus Wistar-Kyoto (WKY) controls, with a focus on oxidative stress, inflammation, and metabolic alterations. Despite hypertension and cardiac and renal hypertrophy, no significant cerebral vascular changes or microbleeds and no cerebral edema were detected in SHRSP. NMR-based urinary metabolomics revealed reduced gut microbiome-derived metabolites, such as p-cresylglucuronide, hippurate, and phenylacetylglycine, alongside increases in methylamine and dimethylamine. These findings reflect gut dysbiosis and altered microbial composition in hypertensive conditions. Elevated markers of oxidative stress, including thiobarbituric acid-reactive substances, and increased expression of NADPH oxidase (NOX) 2 and NOX4 in peripheral tissues suggested oxidative damage in SHRSP rats. Astrocytic hyperreactivity, indicated by increased expression of glial fibrillary acidic protein in brain cortex and hippocampus, was suggestive of neuroinflammatory responses. Our findings highlight complex interplay between hypertension, metabolism, and neuroinflammation while underscoring the variability in SHRSP models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".