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Record W4416867693 · doi:10.1681/asn.20254gr6jqsb

Characterizing New Negative Regulators of Tubular GEF-H1 Signaling: Possible Role in Kidney Fibrosis

2025· article· en· W4416867693 on OpenAlexaff
Katalin Szászi, Brian Wu, Veroni S. Sri Theivakadadcham, Qinghong Dan, Shruthi Venugopal, András Kapùs

Bibliographic record

VenueJournal of the American Society of Nephrology · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsKidneyFibrosisRenal stem cellKidney diseaseKidney tubules

Abstract

fetched live from OpenAlex

Background: Kidney fibrosis is attributed to chronic injury, inflammation and maladaptive repair caused by kidney diseases of various etiologies. Tubular RhoA proteins, activated by cytokines, regulate release of fibrogenic mediators, including Connective Tissue Growth Factor (CTGF/CCN2). These in turn stimulate mesenchymal cells to produce extracellular matrix proteins. This epithelial-mesenchymal crosstalk is crucial for fibrogenesis. The guanine nucleotide exchange factor GEF-H1 (ArhGEF2), activated and upregulated by inflammatory and pro-fibrotic input, is an activator of tubular fibrogenic RhoA signaling. The dynamic activation-inactivation cycle of GEF-H1, and its fibrosis-related dysregulation however remain poorly understood. This study aimed at identifying new druggable regulators of fibrogenic GEF-H1/RhoA signaling and tubular cytokine production. Methods: LLC-PK1 and hTERT-immortalized human renal proximal tubule cells were used. Proteins coimmunoprecipitating with GEF-H1 were identified using mass spectrometry and verified by western blotting. Expression of key proteins were altered by siRNA-mediated silencing or overexpression. RhoA and GEF-H1 activity were assessed by affinity precipitation assays. Fibrosis-related genes were measured using RT2 Profiler™ PCR Array (Qiagen). Protein and mRNA expression changes were explored in a mouse kidney fibrosis model. Results: GEF-H1 associated with subunits of protein phosphatase 6 (PP6) and with Myotonic Dystrophy Kinase-related Cdc42-binding kinase (MRCK)α. Silencing of either the PP6 catalytic domain (PP6C) or MRCKα stimulated GEF-H1 activity and promoted GEF-H1-dependent RhoA activation. We identified several genes upregulated by depletion of PP6C or MRCKα. Notably, depletion of PP6C or MRCKα activated the RhoA effector Myocardin-related Transcription Factor (MRTF), and elevated MRTF-dependent genes, including CTGF/CCN2 and α-smooth muscle actin. Finally, expression of PP6C was decreased in a mouse kidney fibrosis model and in tubular cells stimulated by TGFβ1. Conclusion: We identified PP6 and MRCKα as new suppressors of GEF-H1/RhoA signaling and tubular fibrotic changes. Cytokine-induced downregulation of these regulators may contribute to epithelial-mesenchymal crosstalk and could represent new drug targets for kidney fibrosis. Funding: Government Support – Non-U.S.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.264
Teacher spread0.255 · 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

Explore more

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