ER stress and Rho kinase activation underlie the vasculopathy of CADASIL
Bibliographic record
Abstract
Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) leads to premature stroke and vascular dementia. Mechanism-specific therapies for this aggressive cerebral small vessel disease are lacking. CADASIL is caused by NOTCH3 mutations that influence vascular smooth muscle cell (VSMC) function through unknown processes. We investigated molecular mechanisms underlying the vasculopathy in CADASIL focusing on endoplasmic reticulum (ER) stress and RhoA/Rho kinase (ROCK). Peripheral small arteries and VSMCs were isolated from gluteal biopsies of CADASIL patients and mesentery of TgNotch3R169C mice (CADASIL model). CADASIL vessels exhibited impaired vasorelaxation, blunted vasoconstriction, and hypertrophic remodeling. Expression of NOTCH3 and ER stress target genes was amplified and ER stress response, Rho kinase activity, superoxide production, and cytoskeleton-associated protein phosphorylation were increased in CADASIL, processes associated with Nox5 upregulation. Aberrant vascular responses and signaling in CADASIL were ameliorated by inhibitors of Notch3 (γ-secretase inhibitor), Nox5 (mellitin), ER stress (4-phenylbutyric acid), and ROCK (fasudil). Observations in human CADASIL were recapitulated in TgNotch3R169C mice. These findings indicate that vascular dysfunction in CADASIL involves ER stress/ROCK interplay driven by Notch3-induced Nox5 activation and that NOTCH3 mutation-associated vascular pathology, typical in cerebral vessels, also manifests peripherally. We define Notch3-Nox5/ER stress/ROCK signaling as a putative mechanism-specific target and suggest that peripheral artery responses may be an accessible biomarker in CADASIL.
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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 | 0.000 |
| 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".