Endoplasmic reticulum stress in glomerular epithelial cell injury
Bibliographic record
Abstract
Focal segmental glomerulosclerosis (FSGS) may be associated with glomerular epithelial cell (GEC; podocyte) apoptosis due to acquired injury or mutations in specific podocyte proteins. This study addresses mediation of GEC injury, focusing on endoplasmic reticulum (ER) stress. We studied signaling in cultured GECs in the presence or absence of the extracellular matrix (ECM). Adhesion to collagen supports cell survival, but adhesion to plastic (loss of contact with ECM) leads to apoptosis. Compared with collagen-adherent cells, GECs on plastic showed increased protein misfolding in the ER, and an adaptive-protective ER stress response, including increased expression of ER chaperones, increased phosphorylation of eukaryotic translation initiation factor-2α (eIF2α), and a reduction in protein synthesis. Activation of these ER stress pathways counteracted apoptosis. However, tunicamycin (a potent stimulator of ER stress) changed the ER stress response from protective to cytotoxic, as tunicamycin induced the proapoptotic ER stress gene, C/EBP homologous protein-10, and exacerbated apoptosis in GECs adherent to plastic, but not collagen. In GECs adherent to plastic, adaptive ER stress was associated with an increase in polyubiquitinated proteins and "choking" of the proteasome. Furthermore, pharmacological inhibition of the proteasome induced ER stress in GECs. Finally, we show that ER stress (induction of ER chaperones and eIF2α phosphorylation) was evident in experimental FSGS in vivo. Thus interactions of GECs with ECM may regulate protein folding and induction of the ER stress response. FSGS is associated with induction of ER stress. Enhancing protective aspects of the ER stress response may reduce apoptosis and possibly glomerulosclerosis.
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".