MétaCan
Menu
Back to cohort
Record W2158879557 · doi:10.1681/asn.2007111244

Induction of T Regulatory Cells Attenuates Idiopathic Nephrotic Syndrome

2008· article· en· W2158879557 on OpenAlexaff
Ludmilla Le Berre, Sarah Bruneau, Jeanne Naulet, Karine Renaudin, Françoise Buzelin, Claire Usal, Helga Smit, Thomas Condamine, Jean‐Paul Soulillou, Jacques Dantal

Bibliographic record

VenueJournal of the American Society of Nephrology · 2008
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsNephrotic syndromeIdiopathic Nephrotic SyndromeMedicineImmunologyInternal medicineKidneyProteinuria

Abstract

fetched live from OpenAlex

Buffalo/Mna rats spontaneously develop FSGS and nephrotic syndrome as a result of an immune disorder. Similar to some humans with FSGS, the disease recurs after renal transplantation, suggesting the involvement of a circulating factor. Here, we tested the effect of several immunosuppressive treatments on these rats. Although corticosteroids, cyclosporin A, and anti-T cell receptor treatment reduced proteinuria, only the deoxyspergualin derivative LF15-0195 led to a rapid and complete normalization of proteinuria. Furthermore, this compound led to the regression of renal lesions during both the initial disease and posttransplantation recurrence. The frequency of splenic and peripheral CD4+CD25+FoxP3+ T lymphocytes significantly increased with remission. Moreover, the transfer of purified LF15-0195-induced CD4+CD25+ T cells to irradiated Buff/Mna rats significantly reduced their proteinuria compared with the transfer of untreated control cells, suggesting that LF15-0195 induces regulatory T cells that are able to induce regression of rat nephropathy. These data suggest that idiopathic nephrotic syndrome/FSGS disease can be regulated by cellular transfer, but how this regulation leads to the reorganization of the podocyte cytoskeleton remains to be determined.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.250
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations116
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Society of NephrologySame topicRenal Diseases and GlomerulopathiesFrench-language works237,207