IL‐6 initiated <i>cis</i> ‐signaling in cultured podocytes causes glomerular injury
Bibliographic record
Abstract
The incidence of chronic kidney disease (CKD) parallels the global increase in obesity, diabetes and hypertension that characterize metabolic syndrome‐ a state of systemic inflammation. Glomerular dysfunction in CKD is marked by the loss of unique structure and function of podocytes in the glomerular filtration barrier. We hypothesized that IL‐6, an indicator of systemic inflammation, alters glomerular filtration barrier structure and function in a paracrine manner. Results show that IL‐6 (rIL‐6, 1–100pg/mL, 15min) alters glomerular barrier function demonstrated by increased glomerular albumin permeability (P alb ) of isolated rat glomeruli using videomicroscopy. Increase in P alb (P<0.001, IL‐6 10pg/mL vs. Control) was blocked by α‐IL‐6 antibody. Expression of IL‐6 receptor components IL6‐Rα and gp130 in podocytes was established by immunoblotting and RT‐PCR. IL‐6 (100pg/mL, 15 min)‐induced signaling resulted in down‐regulation of ERK 1/2 phosphorylation (MAPK pathway) without an effect on Akt phosphorylation (PI3K‐Akt pathway). Finally, IL‐6 (1pg‐1ng/mL, 1hr)‐induced change in cell structure was demonstrated by confocal microscopy showing altered actin filaments and adhesion complexes in phalloidin (rhodamine) stained cells. We propose that increased IL‐6 contributes to podocyte injury observed in CKD through cellular IL‐6Rα and IL‐6Rα‐mediated cis ‐signaling.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".