High Glucose–Enhanced Mesangial Cell Extracellular Signal–Regulated Protein Kinase Activation and α1(IV) Collagen Expression in Response to Endothelin-1
Bibliographic record
Abstract
High glucose (HG) stimulates glomerular mesangial cell (MC) expression of extracellular matrix, a process involving protein kinase C (PKC) isozymes and enhanced signaling by autocrine peptides such as endothelin-1 (ET-1). The purpose of this study was to identify the specific PKC isozymes mediating the effects of HG on MC extracellular signal-regulated protein kinase (ERK1/2) signaling and alpha1(IV) collagen expression in response to ET-1. HG (30 mmol/l for 72 h) enhanced ET-1-stimulated alpha1(IV) collagen mRNA expression from 1.2 +/- 0.1-fold to 1.9 +/- 0.2-fold (P < 0.05 vs. normal glucose [NG] + ET-1), and the effect was significantly reduced by Calphostin C or the MEK (mitogen-activated protein kinase kinase) inhibitor PD98059. In transiently transfected MCs, dominant-negative (DN)-PKC-delta, -epsilon, or -zeta inhibited ET-1 activation of ERK1/2. Likewise, downstream of ERK1/2, ET-1 stimulated Elk-1-driven GAL4 luciferase activity to 11 +/- 1-fold (P < 0.002 vs. NG + ET-1) in HG, and DN-PKC-delta, -epsilon, or -zeta attenuated this response to NG levels. HG enhanced ET-1-stimulated intracellular alpha1(IV) collagen protein expression, assessed by confocal immunofluorescence imaging, showed that individual DN-PKC-delta, -epsilon, -zeta, as well as DN-PKC-alpha and -beta, attenuated the response. Thus, HG-enhanced ET-1 stimulation of alpha1(IV) collagen expression requires PKC-delta, -epsilon, and -zeta to act through an ERK1/2-dependent pathway and via PKC-alpha and -beta, which are independent of ERK1/2.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".