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Record W2313193093 · doi:10.1139/cjpp-2013-0490

Hyperglycemia enhances function and differentiation of adult rat cardiac fibroblasts

2014· article· en· W2313193093 on OpenAlexvenueno aff
Patricia E. Shamhart, Daniel J. Luther, Ravi K. Adapala, Jennifer E. Bryant, Kyle A. Petersen, J. Gary Meszaros, Charles K. Thodeti

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsCardiac fibrosisCardiac function curveEndocrinologyFibroblastInternal medicineMyofibroblastDiabetic cardiomyopathyFibrosisCardiomyopathyHeart failureMedicineBiologyIn vitroBiochemistry

Abstract

fetched live from OpenAlex

Diabetes is an independent risk factor for cardiovascular disease that can eventually cause cardiomyopathy and heart failure. Cardiac fibroblasts (CF) are the critical mediators of physiological and pathological cardiac remodeling; however, the effects of hyperglycemia on cardiac fibroblast function and differentiation is not well known. Here, we performed a comprehensive investigation on the effects of hyperglycemia on cardiac fibroblasts and show that hyperglycemia enhances cardiac fibroblast function and differentiation. We found that high glucose treatment increased collagen I, III, and VI gene expression in rat adult cardiac fibroblasts. Interestingly, hyperglycemia increased CF migration and proliferation that is augmented by collagen I and III. Surprisingly, we found that short term hyperglycemia transiently inhibited ERK1/2 activation but increased AKT phosphorylation. Finally, high glucose treatment increased spontaneous differentiation of cardiac fibroblasts to myofibroblasts with increasing passage compared with low glucose. Taken together, these findings suggest that hyperglycemia induces cardiac fibrosis by modulating collagen expression, migration, proliferation, and differentiation of cardiac fibroblasts.

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)0.000
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 score0.442
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.241
Teacher spread0.233 · 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

Citations48
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicCardiac Fibrosis and RemodelingFrench-language works237,207