Serum with phospholipase <scp>A</scp>2 receptor autoantibodies interferes with podocyte adhesion to collagen
Bibliographic record
Abstract
BACKGROUND: The majority of sera from patients with primary membranous nephropathy have autoantibodies against the M-type phospholipase A2 receptor (PLA2R) which is expressed on human podocytes. The rabbit variant of PLA2R attaches to collagen type IV via the fibronectin type II domain, which is also present in the human variant of PLA2R. DESIGN: To assess whether the human PLA2R variant is also involved in attachment to collagen type IV, we conducted a cell adhesion assay on a collagen-coated surface using PLA2R-transfected and mock-transfected human embryonic kidney (HEK) cells. To test the hypothesis that sera from patients containing anti-PLA2R antibodies interfere with the adhesion of podocytes to collagen, we performed cell adhesion assays on a collagen type IV-coated surface using positive and negative serum samples from patients and cultured human podocytes in vitro expressing PLA2R. RESULTS: The HEK cell adhesion assay confirmed an enhanced attachment of PLA2R-transfected cells to collagen type IV. We confirmed diminished podocyte adhesion in the presence of serum with anti-PLA2R antibodies. The concentration of anti-PLA2R antibodies correlated with proteinuria and to the degree of diminished adhesion of podocytes. CONCLUSIONS: We demonstrated that serum of patients containing autoantibodies directed to PLA2R interferes with the ability of podocytes to attach to collagen type IV in vitro, providing evidence of a serum soluble pathogenic factor interfering with podocyte adhesion in membranous 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".