Abstract P343: Cerebral injury and cognitive performances are correlated with immunoinflammatory markers in hypertensive patients
Bibliographic record
Abstract
Immunity and inflammation play a pivotal role in hypertension onset and cardiovascular organ damage. This role has been thoroughly characterized for classical hypertension targets as the kidneys, the heart and the vasculature. Many studies have characterized this in the experimental context, however immunoinflammatory challenges links with brain injury in the clinical context of hypertension are still lacking. In this study we will characterize how immunoinflammatory mediators can be predictors of cerebral injury characterized by advanced neuroimaging in hypertensive patients. Hypertensive patients underwent cerebral MRI and by advanced neuroimaging we characterized the microstructural injury by DTI fiber tracking. We administered the Montreal Cognitive Assessment to evaluate cognitive function, measured circulating C-reactive protein (hs-CRP) and counted circulating white blood cells (WBC). We found a large cluster of white matter tracts whose integrity parameters were associated with immunoinflammatory biomarkers (Figure A). In particular, a cluster of tracts of the limbic system and encompassing the corpus callosum show a correlation between their loss of integrity and hs-CRP levels. Another cluster of associative tracts spanning the temporal lobe show association between their loss of integrity and the WBC. Finally, the Frontal Aslant and the Uncinate Fasciculus show association with both immunoinflammatory markers (Figure B). In this study we performed advanced neuroimaging analyses to characterize the interplay between immunoinflammatory risk and cerebral alterations in hypertensives. Furthermore, our previous work identified that white matter damage in the Forceps Minor and Superior Longitudinal Fasciculus was a typical trait of hypertensive patients and associated to loss of cognitive functions. Our data further show the inflammatory risk association with worse cognitive functions, suggesting a clinical relevance in terms of damage evidenced by advanced MRI in hypertensive patients.
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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 | 0.001 |
| 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) | 0.004 | 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".