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Record W2121026720 · doi:10.1152/ajpendo.00178.2006

Inactivation of PKCθ leads to increased susceptibility to obesity and dietary insulin resistance in mice

2006· article· en· W2121026720 on OpenAlexfundno aff
Zhan‐Guo Gao, Zhong Wang, Xiaoying Zhang, Andrew A. Butler, Aamir Zuberi, Barbara Gawrońska‐Kozak, Michael Lefevre, David York, Éric Ravussin, Hans‐Rudolf Berthoud, Owen P. McGuinness, William T. Cefalu, Jianping Ye

Bibliographic record

VenueAmerican Journal of Physiology-Endocrinology and Metabolism · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesYork UniversityHoward Hughes Medical Institute
KeywordsInsulin resistanceInternal medicineObesityEndocrinologyMedicineInsulinChemistry

Abstract

fetched live from OpenAlex

In this study, we investigated the metabolic phenotype of PKCtheta knockout mice (C57BL/6J) on chow diet and high-fat diet (HFD). The knockout (KO) mice are normal in growth and reproduction. On the chow diet, body weight and food intake were not changed in the KO mice; however, body fat content was increased with a corresponding decrease in body lean mass. Energy expenditure and spontaneous physical activity were decreased in the KO mice. On HFD, energy expenditure and physical activity remained low in the KO mice. The body weight and fat content were increased rapidly in the KO mice. At 8 wk on HFD, severe insulin resistance was detected in the KO mice with hyperinsulinemic euglycemic clamp and insulin tolerance test. Insulin action in both hepatic and peripheral tissues was reduced in the KO mice. Plamsa free fatty acid was increased, and expression of adiponectin in the adipose tissue was decreased, in the KO mice on HFD. This study suggests that loss of PKCtheta reduces energy expenditure and increases the risk of dietary obesity and insulin resistance in 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)0.000
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 score0.695
Threshold uncertainty score0.490

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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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

Citations65
Published2006
Admission routes1
Has abstractyes

Explore more

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