Stretch-induced mesangial cell ERK1/ERK2 activation is enhanced in high glucose by decreased dephosphorylation
Bibliographic record
Abstract
Glomerular hypertension and hyperglycemia are major determinants of diabetic nephropathy. We sought to identify the mechanisms whereby stretch-induced activation of mesangial cell extracellular signal-regulated kinase 1 and 2 (ERK1/ERK2) is enhanced in high glucose (HG). Mesangial cells cultured on fibronectin Flex I plates in normal glucose (NG; 5.6 mM) or HG (30 mM), were stretched by 15% elongation at 60 cycles/min for up to 60 min. In HG, a 5-min stretch increased ERK1/ERK2 phosphorylation by 6.4 +/- 0.4/4.3 +/- 0.3-fold (P < 0.05 vs. NG stretch). In contrast, p38 phosphorylation was increased identically by stretch in NG and HG. Unlike many effects of HG, augmentation of ERK activity by HG was not dependent on protein kinase C (PKC) as indicated by downregulation of PKC with 24-h phorbol ester or inhibition with bisindolylmaleimide IV. In both NG and HG, pretreatment with arginine-glycine-aspartic acid peptide (0.5 mg/ml) to inhibit integrin binding or with cytochalasin D (100 ng/ml) to disassemble filamentous (F) actin, significantly reduced phosphorylation of ERK1/ERK2 and p38. To determine whether the rate of mitogen-activated protein kinase dephosphorylation is affected by HG, cellular kinase activity was inhibited by depleting ATP. Post-ATP depletion, phosphorylation of ERK1/ERK2 was reduced to 36 +/- 9/51 +/- 14% vs. 9 +/- 5/7 +/- 6% in NG (P < 0.05, n = 5). Thus stretch-induced ERK1/ERK2 and p38 activation in both NG and HG is beta(1)-integrin and F-actin dependent. Stretch-induced ERK1/ERK2 is enhanced in high glucose by diminished dephosphorylation, suggesting reduced phosphatase activity in the diabetic milieu. Enhanced mesangial cell ERK1/ERK2 signaling in response to the combined effects of mechanical stretch and HG may contribute to the pathogenesis of diabetic nephropathy.
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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".