The autoimmune architecture of childhood idiopathic nephrotic syndrome
Bibliographic record
Abstract
Idiopathic nephrotic syndrome, the most common glomerular disorder in children, has long been considered an immune-mediated disease based on the efficacy of glucocorticoids at inducing remission. Nevertheless, the immune processes leading to podocytopathy have largely remained elusive. The success of B-cell depletion with rituximab, descriptions of B-cell dysregulation during active disease, and the most recent discovery of autoantibodies targeting the major podocyte antigen nephrin point to an autoimmune humoral etiology for idiopathic nephrotic syndrome. Investigations of the immune factors involved in idiopathic nephrotic syndrome pathogenesis have uncovered common features with other autoimmune disorders that will aid in prognostication and in guiding the expansion of our glucocorticoid-sparing therapeutic arsenal. In this review, we discuss the emerging autoimmune architecture of idiopathic nephrotic syndrome, with a specific focus on pediatric steroid-sensitive disease, including the podocyte-reactive B-cell response that causes anti-podocyte antibodies, the predisposing genetic factors that shape the podocyte-reactive immune landscape, and the immune triggers driving active disease.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".