MétaCan
Menu
Back to cohort
Record W2416568045 · doi:10.1152/jappl.2001.91.2.771

TGF-β<sub>1</sub>and prepro-ANP mRNAs are differentially regulated in exercise-induced cardiac hypertrophy

2001· article· en· W2416568045 on OpenAlexaff
Angelino Calderone, René J.L. Murphy, Julie L. Lavoie, Federico Colombo, Louise Béliveau

Bibliographic record

VenueJournal of Applied Physiology · 2001
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsUniversité de MontréalInstitut universitaire de cardiologie et de pneumologie de QuébecAcadia UniversityMontreal Heart Institute
Fundersnot available
KeywordsInternal medicineMuscle hypertrophyEndocrinologyVentricleAtrial natriuretic peptideGene expressionBiologyMessenger RNAGene isoformMedicineGene

Abstract

fetched live from OpenAlex

The induction of transforming growth factor (TGF)-beta and prepro-atrial natriuretic peptide (ANP) mRNAs represent hallmark features of pathological cardiac hypertrophy. The present study examined whether this pattern of mRNA expression was conserved in a physiological model of cardiac hypertrophy. To address this thesis, female Sprague-Dawley rats were individually housed and permitted to run freely. Voluntary exercise for 3 and 6 wk resulted in biventricular hypertrophy and increased cytochrome c oxidase activity in the triceps muscle. In the hypertrophied left ventricle, the steady-state mRNA level of the cardiac fetal gene prepro-ANP and the extracellular matrix proteins preprocollagen-alpha(1) and fibronectin were similar in exercise-trained and sedentary rats. By contrast, an increased expression of TGF-beta(1) mRNA was observed, whereas TGF-beta(3) mRNA level was unchanged in the hypertrophied left ventricle of exercise-trained compared with sedentary rats. These data highlight a heterogeneity in the regulation of TGF-beta isoforms, and the increased expression of ventricular TGF-beta(1) mRNA in physiological cardiac hypertrophy may contribute to myocardial remodeling.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.233
Teacher spread0.220 · 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

Citations31
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied PhysiologySame topicCardiac Fibrosis and RemodelingFrench-language works237,207