Protein disulfide isomerase-mediated transcriptional upregulation of Nox1 contributes to vascular dysfunction in hypertension
Bibliographic record
Abstract
Nox1 signaling is a causal key element in arterial hypertension. Recently, we identified protein disulfide isomerase A1 (PDI) as a novel regulatory protein that regulates Nox1 signaling in VSMCs. Spontaneously hypertensive rats (SHR) have increased levels of PDI in mesenteric resistance arteries compared with Wistar controls; however, its consequences remain unclear. Herein, we investigated the role of PDI in mediating Nox1 transcriptional upregulation and its effects on vascular dysfunction in hypertension. We demonstrate that PDI contributes to the development of hypertension via enhanced transcriptional upregulation of Nox1 in vascular smooth muscle cells (VSMCs). We show for the first time that PDI sulfenylation by hydrogen peroxide contributes to EGFR activation in hypertension via increased shedding of epidermal growth factor-like ligands. PDI also increases intracellular calcium levels, and contractile responses induced by ANG II. PDI silencing or pharmacological inhibition in VSMCs significantly decreases EGFR activation and Nox1 transcription. Overexpression of PDI in VSMCs enhances ANG II-induced EGFR activation and ATF1 translocation to the nucleus. Mechanistically, PDI increases ATF1-induced Nox1 transcription and enhances the contractile responses to ANG II. Herein we show that ATF1 binding to Nox1 transcription putative regulatory regions is augmented by PDI. Altogether, we provide evidence that HB-EGF in SHR resistance vessels promotes the nuclear translocation of ATF1, under the control of PDI, and thereby induces Nox1 gene expression and increases vascular reactivity. Thus, PDI acts as a thiol redox-dependent enhancer of vascular dysfunction in hypertension and could represent a novel therapeutic target for the treatment of this disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".