Regulatory T cells and minimal change nephropathy: in the midst of a complex network
Bibliographic record
Abstract
Minimal change nephrosis (MCN) is an important cause of morbidity in children. In spite of successful therapies having been developed in the last three decades, most aspects related to pathogenesis still remain poorly defined. Evolution in basic immunology and results deriving from animal models of the disease suggest a complex interaction of factors and cells starting from activation of innate immunity and continuing with antigen presentation. Oxidants, CD80 and CD40/CD40L have probably a relevant role at the start. Studies in animal models and in human beings also suggest the possibility that the same molecules (i.e. CD80, CD40) are expressed by podocytes under inflammatory stimuli, representing a direct potential mechanism for proteinuria. B and T cells could play a relevant role this contest. Implication of B cells is suggested indirectly by studies utilizing anti-CD20 monoclonal antibodies as the main therapy. The role of regulatory T cells (Tregs ) is supported mainly by results in animal models of nephrotic syndrome (i.e. adriamycin, puromycin, lipopolysaccharide), showing a protective effect of direct Treg infusion or stimulation by interleukin 2 (IL-2). Limited studies have also shown reduced amounts of circulating Tregs in patients with active MCN cells. The route from bench to bedside would be reduced if results from animal models were confirmed in human pathology. The expansion of Tregs with recombinant IL-2 and new anti-CD20 monoclonal antibodies is the beginning. Blocking antigen-presenting cells with cytotoxic T lymphocyte antigen (CTLA-4)-Ig fusion molecules inhibiting CD80 and/or with blockers of CD40-CD40 ligand interaction represent potential new approaches. The hope is that evolution in therapies of MCN could fill a gap lasting 30 years.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".