Abstract 010: Interplay Between Nox5 And Endoplasmic Reticulum Stress Influences Vascular Smooth Muscle Cell Phenotypic Switching In Human Hypertension
Bibliographic record
Abstract
Vascular remodelling, a hallmark of hypertension, involves vascular smooth muscle cell phenotypic switching. Molecular mechanisms underlying this process are unclear, but redox-dependent processes are important. Here we explored the role of Nox5, oxidative and ER stress in VSMC de-differentiation in hypertension. VSMCs from resistance arteries of normotensive (NT) and hypertensive (HT) subjects were studied. Nox5 compartmentalization (cell fractionation); ROS generation (chemiluminescence); activation of ER stress (IRE1α, PERK phosphorylation), and markers of phenotypic switching (αSMA, SM22, MYOCD KLF4) proliferation (PCNA) and inflammation/fibrosis (IL-6 and IL-8) were assessed. Nox5 and IRE1 were silenced with siRNA. In HT, Nox5 upregulation was compartment-specific: Nox5 levels were increased in the ER fraction (46 % vs NT, p<0.05). IRE1α (95%) and PERK arms (36%) of ER stress were activated in HT (vs NT, p<0.05). ROS scavenging (Tempol, 1mM) and Nox5 silencing reduced ER stress activation in HT (vs Ctl, p<0.05). ER stress (4-PBA, 1mM) and IRE1 inhibition (STF083010, 60μM) reduced ROS levels and Nox5 expression in HT subjects (vs Ctl, p<0.05). Induction of ER stress (tunicamycin, 5μg/ml, 24h) increased Nox5 expression (25% vs Ctl) in NT (p<0.05), suggesting association between Nox5-ROS and ER stress. Subsequently, we examined the impact of Nox5 and ER stress on VSMC phenotypic switching in HT. VSMCs from HT exhibited reduced expression of the VSMC markers αSMA (90%), SM22 (83%), and MYOCD (50%), whereas KLF4 levels (240%) were augmented (vs NT, p<0.05). Additionally, expression of the proliferation marker, PCNA (217%) and pro-collagen I (23±2 vs NT:13±0.3ng/ml), and production of pro-inflammatory cytokines IL-6 (501±23 vs NT:121±6pg/mL) and IL-8 (373±34 vs NT:262±24pg/mL) were increased in HT (vs NT, p<0.05). Nox5 and IRE1 silencing in VSMC from HT reduced PCNA expression, pro-collagen I release, and baseline and LPS-induced IL-6 and IL-8 release (vs Ctl, p<0.05). Our findings indicate a circuitous relationship between Nox5 and ER stress where Nox5 is both upstream and downstream of ER stress. Activation of this system is closely linked to VSMC phenotypic switching, a crucial process in vascular dysfunction associated with hypertension.
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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) | 0.003 | 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".