aPKC/Par3/Par6 polarity complexes regulate podocyte motility and crescent formation in the progression of ANCA-associated vasculitis
Post-publication record
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Bibliographic record
Abstract
OBJECTIVES: Podocyte bridging may be a key initial event occurring early in crescent formation. This study aims to probe the underlying mechanism of atypical protein kinase C (aPKC)/protease-activated receptor 3(Par3)/Par6 polarity complexes on podocyte motility and crescent formation during the progression of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). METHODS: The effects of anti-TNF-α monoclonal antibody (mAb) on the crescent formation, localization and expression of aPKC/Par3/Par6 polarity complexes, and activities of small GTPases (Rho/Rac1/Cdc42) were explored in an AAV mouse model. Podocytes were stimulated in vitro by TNF-α and myeloperoxidase (MPO)-ANCA positive serum collected from patients with microscopic polyangiitis (MPA). Then, podocyte motility, aPKC/Par3/Par6 polarity protein expression and small GTPases activity were measured. The impacts of heat shock protein 70 (HSP70), a type of molecular chaperone, on the phosphorylation of aPKC was evaluated. RESULTS: Anti-TNF-α mAb inhibited crescent formation and restored the localization of aPKC/Par3/Par6 polarity complexes in the glomerulus of the AAV mouse model. Both MPO-ANCA-positive serum and TNF-α stimulation significantly induced podocyte motility by inhibiting of aPKC phosphorylation and detachment of aPKC/Par3/Par6 polarity complexes. Overexpression of HSP70 increased p-aPKC level and inhibited podocyte motility stimulated by either MPO-ANCA-positive serum or TNF-α. CONCLUSION: The podocyte polarity preserved by aPKC/Par3/Par6 polarity complexes, especially the phosphorylation status of aPKC, may play an important role in the crescent formation of AAV. The inhibition of TNF-α prevents the crescent formation in AAV via, at least partly, inhibiting podocyte polarity loss and motility.
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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) | 0.001 | 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".