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Record W2043461841 · doi:10.1007/s12079-012-0162-6

CCN3: a novel anti-fibrotic treatment in end-stage renal disease?

2012· article· en· W2043461841 on OpenAlexaff
Andrew Leask

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective Tissue Growth Factor Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineGlomerulosclerosisAlbuminuriaFibrosisDiabetic nephropathyRenal functionEnd stage renal diseaseKidney diseaseIn vivoUrologyAngiogenesisNephropathyInternal medicineDiseaseKidneyEndocrinologyPathologyProteinuriaDiabetes mellitusBiology

Abstract

fetched live from OpenAlex

Fibrosis is a major cause of end-stage renal disease (ESRD) a progressive loss in renal function that occurs over a period of months or years, is characterized by a decreased capability of the kidneys to excrete waste products. There is no specific treatment unequivocally shown to slow the worsening of chronic kidney disease. Plasma levels of CCN2, a fibrogenic agent, is a predictor of ESRD and mortality in patients with type 1 diabetic nephropathy. CCN3 has been hypothesized to have antagonistic effects to CCN2 both in vitro and in vivo, including in cultured mesangial cells. In a recent study, van Roeyen and colleagues (Am J Pathol in press, 2012) showed that in vivo overexpression of CCN3 in a model of anti-Thy1.1-induced experimental glomerulonephritis resulted in decreased albuminuria, glomerulosclerosis and reduced cortical collagen type I accumulation. CCN3 enhanced angiogenesis yes suppressed mesangial cell proliferation. Thus CCN3 protein may represent a novel therapeutic approach to help repair glomerular endothelial damage and mesangioproliferative changes and hence prevent renal failure, glomerulosclerosis and tubulointerstitial fibrosis.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.040
GPT teacher head0.314
Teacher spread0.273 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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