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Record W2053347353 · doi:10.1097/fjc.0b013e31820014f9

Intracerebroventricular Leptin Administration Differentially Alters Cardiac Energy Metabolism in Mice Fed a Low-fat and High-fat Diet

2010· article· en· W2053347353 on OpenAlexaff
Wendy Keung, Virgilio J. J. Cadete, Arivazhagan Palaniyappan, Amissa Jablonski, Melanie A. Fischer, Gary D. Lopaschuk

Bibliographic record

VenueJournal of Cardiovascular Pharmacology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLeptinEndocrinologyInternal medicineMetabolismBeta oxidationCalorieChemistryBiologyMedicineObesity

Abstract

fetched live from OpenAlex

Leptin directly acts on peripheral tissues and alters energy metabolism in obese mice. It also has acute beneficial effects on these tissues via its hypothalamic action. However, it is not clear what effect chronic intracerebroventrical (ICV) leptin administration has on cardiac energy metabolism. We examined the effects of chronic ICV leptin on glucose and fatty acid metabolism in isolated working hearts from high-fat-fed and low-fat-fed mice. Mice were fed a high-fat (60% calories from fat) or low-fat (10% calories from fat) diet for 8 weeks before ICV leptin (5 [mu]g/d) for 7 days. In low-fat-fed mice, leptin increased glucose oxidation rates in isolated working hearts when compared with control [203 +/- 21 vs. 793 +/- 93 nmol[middle dot](g dry weight)-1[middle dot]min-1]. In high-fat-fed mice leptin inhibited fatty acid oxidation [476 +/- 73 vs. 251 +/- 38 nmol[middle dot](g[middle dot]dry[middle dot]wt)-1[middle dot]min-1]. The increase in glucose oxidation in low-fat-fed mice was accompanied by increased pyruvate dehydrogenase activity. In high-fat-fed mice, leptin increased cardiac malonyl coenzyme A levels, secondary to a decrease in malonyl coenzyme A decarboxylase expression. These results suggest that ICV leptin alters cardiac energy metabolism opposite to its peripheral effects and that these effects differ depending on energy substrate supply to the mice.

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 score0.054
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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