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Record W4406845604 · doi:10.1016/j.ekir.2024.11.498

WCN25-1941 microRNA (miR)-299a-5p PROMOTES APOPTOSIS AND FIBROSIS IN DIABETIC KIDNEY DISEASE BY REGULATING MAP3K2ERK5

2025· article· en· W4406845604 on OpenAlexaff
Ifeanyi Kennedy Nmecha, Urooj Bajwa, Bo Gao, Joan C. Krepinsky

Bibliographic record

VenueKidney International Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsMedicinemicroRNAApoptosisFibrosisDiseaseKidneyKidney diseaseCancer researchBioinformaticsPathologyInternal medicineGeneticsGeneBiology

Abstract

fetched live from OpenAlex

Diabetic kidney disease (DKD) is the leading cause of end-stage renal failure in North America. The transforming growth factor beta 1 family (TGFβ1) has been shown to promote kidney proximal tubular cell apoptosis while contributing to the pathogenesis of DKD by promoting interstitial fibrosis. The mechanism involves the activation of SMAD pathways which release cytokines and growth factors that promote interstitial inflammation and myofibroblast activation, which leads to the increased production and accumulation of extracellular matrix proteins in the interstitium.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.253
Teacher spread0.246 · 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 designBench or experimental
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

Citations0
Published2025
Admission routes1
Has abstractyes

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