New insights into the biology and treatment of minimal change disease and focal segmental glomerulosclerosis
Bibliographic record
Abstract
PURPOSE OF REVIEW: Until recently, the underlying pathophysiology of diffuse podocytopathies associated with nephrotic syndrome was not understood. Since the discovery of antinephrin antibodies and antibodies against other slit diaphragm components in a subset of patients with minimal change disease and focal segmental glomerulosclerosis, there has been a transformation of our understanding of disease pathogenesis and treatment rationale. RECENT FINDINGS: Antinephrin antibodies are common in patients with acquired diffuse podocytopathy and are most reliably detected among those patients with treatment-naive nephrotic syndrome. Circulating antibodies correlate with disease activity and may be useful for monitoring patients with podocytopathies. Rituximab represents an effective treatment inducing remission in a majority of patients and reducing the frequency of relapses. Optimal dosing and frequency remain unclear, and randomized trials in this space are ongoing. SUMMARY: Our understanding of immune-mediated podocytopathy is rapidly evolving, and changes in treatment paradigms are likely to continue to change, with emphasis on targeted therapies addressing disease pathogenesis. Future prospective studies are required to understand the optimal use of antinephrin antibodies for diagnosis and monitoring and how to tailor therapy to individual patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".