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Record W2025144533 · doi:10.1002/dat.20504

Membranous nephropathy: From mechanisms to therapies

2010· article· en· W2025144533 on OpenAlexafffund
Andrey V. Cybulsky

Bibliographic record

VenueDialysis & Transplantation · 2010
Typearticle
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsMcGill University Health Centre
FundersCanadian Institutes of Health ResearchKidney Foundation of Canada
KeywordsPodocyteMembranous nephropathyCell biologyComplement systemSlit diaphragmAntigenPathogenesisImmunologyMedicineGlomerulonephritisImmune systemBiologyKidneyEndocrinology

Abstract

fetched live from OpenAlex

Abstract Membranous nephropathy (MN) is an important glomerular disease characterized by podocyte injury and protein‐uria. The understanding of cellular and molecular mechanisms involved in the pathogenesis of MN has come from studies in the Heymann nephritis model of MN in the rat. MN involves the in situ formation of subepithelial immune deposits of antibodies reactive to podocyte antigens, activation of complement, and assembly of C5b‐9 on podo‐cyte plasma membranes. The podocyte responds to C5b‐9 attack by activating protein kinases, phospholipases, oxidants, transcription factors, growth factors, stress pathways, proteinases, and other mediators. These signals impact on metabolic pathways, structure/function of lipids, proteins in the cytoskeleton and slit diaphragm, and turnover of extracellular matrix components. Some effects of C5b‐9 affect podocyte functions adversely, while other effects may limit injury or promote recovery. Increased understanding of pathogenic antigens, complement activation, and changes in podocyte biology induced by C5b‐9 is an opportunity for new diagnostic and concept‐driven therapeutic approaches to this 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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.007
GPT teacher head0.241
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2010
Admission routes2
Has abstractyes

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