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Pathogenesis of renal fibrosis: Role of Proteinase‐activated Receptor‐2

2012· article· en· W3175407343 on OpenAlexaff
Hyunjae Chung, Daniel A. Muruve, Morley D. Hollenberg

Bibliographic record

VenueThe FASEB Journal · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective Tissue Growth Factor Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCTGFFibrosisGrowth factorInternal medicineConnective tissueWestern blotEndocrinologyMyofibroblastReceptorTransforming growth factorChemistryMedicinePathologyBiochemistry

Abstract

fetched live from OpenAlex

OBJECTIVES To evaluate the role of proteinase‐activated receptor‐2 (PAR2) in renal fibrosis. METHODS We used both cultured acutely isolated human‐derived proximal tubular cells (HPTCs) and an in‐vivo murine unilateral ureteral obstruction (UUO) model of renal fibrosis, with wild‐type and PAR2 null mice (Jackson Labs). HPTCs at passage 3 were activated with a PAR2‐activating peptide (PAR2‐AP) and trypsin without or with co‐stimulation by transforming growth factor‐ β (TGF‐ β) and the expression level of connective tissue growth factor (CTGF) was measured by western blot analysis. Cells were activated with and without the signal pathway inhibitors for MAPKinase (PD98059) and Rho‐kinase (Y‐27632). Kidneys from wild‐type and PAR2‐null mice with or without (sham) UUO were obtained at 7, 14, 21 and 28 days after UUO. Renal tissue was fixed and evaluated histopathologically for morphology (H & E), collagen deposition (Masson's Trichrome) and biochemically (western blot) for α‐smooth muscle actin. RESULTS (1) PAR2‐AP activation of HPTCs alone significantly upregulated CTGF expression and did so synergistically to augment TGF‐β‐induced CTGF production. This synergy was reduced by MAPKinase but not Rho‐kinase inhibition. (2) PAR2 null UUO mice had less tubular injury and fibrosis and reduced alpha‐smooth muscle actin at day 7 but not at 28 days. SUMMARY Our results support a role for PAR2 in acute renal 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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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