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Hypertrophied rat hearts are less responsive to the metabolic and functional effects of insulin

2000· article· en· W2414876934 on OpenAlexaff
Michael F. Allard, Richard B. Wambolt, Sarah Longnus, Mark Grist, Carmen Lydell, Hannah L. Parsons, Brian Rodrigues, Jennifer L. Hall, William C. Stanley, Gregory P. Bondy

Bibliographic record

VenueAmerican Journal of Physiology-Endocrinology and Metabolism · 2000
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGlycogenolysisInternal medicineGlycogenEndocrinologyGlycolysisInsulinGlycogen synthaseGlucose transporterCarbohydrate metabolismBiologyGlucose uptakePhosphatidylinositolMetabolismChemistryKinaseBiochemistryMedicine

Abstract

fetched live from OpenAlex

We determined the effect of insulin on the fate of glucose and contractile function in isolated working hypertrophied hearts from rats with an aortic constriction (n = 27) and control hearts from sham-operated rats (n = 27). Insulin increased glycolysis and glycogen in control and hypertrophied hearts. The change in glycogen was brought about by increased glycogen synthesis and decreased glycogenolysis in both groups. However, the magnitude of change in glycolysis, glycogen synthesis, and glycogenolysis caused by insulin was lower in hypertrophied hearts than in control hearts. Insulin also increased glucose oxidation and contractile function in control hearts but not in hypertrophied hearts. Protein content of glucose transporters, protein kinase B, and phosphatidylinositol 3-kinase was not different between the two groups. Thus hypertrophied hearts are less responsive to the metabolic and functional effects of insulin. The reduced responsiveness involves multiple aspects of glucose metabolism, including glycolysis, glucose oxidation, and glycogen metabolism. The absence of changes in content of key regulatory molecules indicates that other sites, pathways, or factors regulating glucose utilization are responsible for these findings.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.443

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 studies0.0000.001
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 head0.009
GPT teacher head0.231
Teacher spread0.223 · 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 designObservational
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

Citations53
Published2000
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Physiology-Endocrinology and MetabolismSame topicCardiovascular Function and Risk FactorsFrench-language works237,207