Extracellular matrix regulates glomerular epithelial cell survival and proliferation
Bibliographic record
Abstract
Glomerular epithelial cell (GEC) injury and apoptosis may contribute to sclerosis in glomerulonephritis. The present study addresses signals that regulate survival of GEC in culture and in the acute puromycin aminonucleoside nephrosis (PAN) model of GEC injury in vivo. Compared with GEC on plastic substratum, adhesion to collagen increased activation of focal adhesion kinase (FAK), c-Src, and ERK and facilitated survival (prevented apoptosis). GEC on plastic exhibited increased caspase-8 and -9 activities, increased expression of the proapoptotic protein, Bax, and decreased the antiapoptotic protein, Bcl-XL, compared with collagen. Stable expression of constitutively active mutants of FAK (CD2-FAK) or MEK (R4F-MEK) activated the ERK pathway and supplanted the requirement of collagen for survival. In contrast, expression of a Ras mutant that activates phosphatidylinositol 3-kinase but blocks ERK activation or pharmacological inhibition of the ERK pathway decreased survival on collagen. Glomeruli isolated from rats with PAN revealed increased beta1-integrin expression, along with increased activation of FAK, c-Src, and ERK, compared with controls. EGF receptor activation was undetectable in PAN. Therefore, adhesion to collagen, resulting in activation of FAK and the Ras-ERK pathway, supports GEC survival. Analogous signals for GEC survival are activated in PAN.
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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".