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Decrease IL33 expression in cardiac fibroblasts with high concentration of glucose leads to collagen IV production: role of PKCβ

2010· article· en· W2307571393 on OpenAlexaff
Zhaoliang Su, Hu Xu, Jingchao Zhang, Claudio M. Martin, Rui Tao

Bibliographic record

VenueThe FASEB Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsWestern UniversityLawson Health Research Institute
Fundersnot available
KeywordsProtein kinase CDiabetic cardiomyopathyInternal medicineEndocrinologyPhosphorylationChemistryFibroblastCardiomyopathyMedicineBiochemistryIn vitroHeart failure

Abstract

fetched live from OpenAlex

Diabetic cardiomyopathy (DiCM) is one of major complications of diabetes mellitus. Increase in collagen production by cardiac fibroblasts has been implicated in the development of the DiCM. In the present study, we assessed the role of PKCβ/IL‐33 pathway in the high glucose (HG)‐induced collagen production in cardiac fibroblasts. Methods Cultures cardiac fibroblasts were exposed to medium containing high concentration of glucose. The PKCβ phosphorylation status, IL33 and collagen production were assessed with Western or real‐time RT‐PCR. Results Treatment of the cardiac fibroblasts with HG led to a decrease in IL33 mRNA and protein expression which was associated with an increase in collagen IV production. Administration of IL‐33 prevented HG‐induced collagen IV production. Expose of cardiac fibroblasts to HG resulted in PKCβ;activation as indicated by increase in phosphorylation of PKCβ;Furthermore, inhibition of PKCβ;with an inhibitor prevented the increase in collagen IV production in HG‐treated cardiac fibroblasts. Conclusion Our results suggest that PKCβ/IL33 pathway plays an important role in regulation of HG‐induced collagen IV production in cardiac fibroblasts. (CIHR MOP‐81303)

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 score0.019
Threshold uncertainty score0.230

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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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