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Record W2330575004 · doi:10.1139/bcb-2013-0124

Role of Nodal–PITX2C signaling pathway in glucose-induced cardiomyocyte hypertrophy

2014· article· en· W2330575004 on OpenAlexvenueno aff
Dongmei Su, Jing Sun, Lina Guan, Qian Li, Huiling Zhang, Xu Ma

Bibliographic record

VenueBiochemistry and Cell Biology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsDownregulation and upregulationMuscle hypertrophyGene knockdownInternal medicineEndocrinologyNODALBiologyGeneSignal transductionAtrial natriuretic peptideGene expressionCell biologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Pathological cardiac hypertrophy is a major cause of morbidity and mortality in cardiovascular disease. Recent studies have shown that cardiomyocytes, in response to high glucose (HG) stimuli, undergo hypertrophic growth. While much work still needs to be done to elucidate this important mechanism of hypertrophy, previous works have showed that some pathways or genes play important roles in hypertrophy. In this study, we showed that sublethal concentrations of glucose (25 mmol/L) could induce cardiomyocyte hypertrophy with an increase in the cellular surface area and the upregulation of the atrial natriuretic peptide (ANP) gene, a hypertrophic marker. High glucose (HG) treatments resulted in the upregulation of the Nodal gene, which is under-expressed in cardiomyocytes. We also determined that the knockdown of the Nodal gene resisted HG-induced cardiomyocyte hypertrophy. The overexpression of Nodal was able to induce hypertrophy in cardiomyocytes, which was associated with the upregulation of the PITX2C gene. We also showed that increases in the PITX2C expression, in response to Nodal, were mediated by the Smad4 signaling pathway. This study is highly relevant to the understanding of the effects of the Nodal-PITX2C pathway on HG-induced cardiomyocyte hypertrophy, as well as the related molecular mechanisms.

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 score0.013
Threshold uncertainty score0.408

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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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