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AMPK Regulation of Glucose, Lipid and Protein Metabolism: Mechanisms and Nutritional Significance

2017· review· en· W2605957846 on OpenAlexaff
Liuqin He, Xihong Zhou, Niu Huang, Huan Li, Junquan Tian, Yuying Li, Yao Kang, Clares M. Nyachoti, Sung Woo Kim, Yulong Yin

Bibliographic record

VenueCurrent Protein and Peptide Science · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAMPKLipid metabolismAMP-activated protein kinaseRegulatorCarbohydrate metabolismDiabetes mellitusGlucose uptakeUpstream and downstream (DNA)Glucose transporterGlucose homeostasisInflammationNutrient sensingSignal transductionChemistryCell biologyBiologyProtein kinase AEndocrinologyBiochemistryInternal medicineUpstream (networking)MedicineInsulinPhosphorylationInsulin resistanceGene

Abstract

fetched live from OpenAlex

AMP-activated protein kianse (AMPK) is a master sensor of cellular energy levels and a crucial regulator of nutrient metabolism such as the synthesis of fatty acids, glucose and protein as well as their oxidation to CO2 and water . Thus, AMPK signaling has important implications for fat deposition and glucose homeostasis in animals and humans. Much experimental and clinical evidence show that AMPK is a key therapeutic target for the prevention of diseases such as obesity, diabetes, cancer, inflammation and cardiac dysfunction. In this review we highlight recent advances on the upstream and downstream targets of AMPK, as well as the specific mechanisms whereby AMPK regulates digestive functions and chronic energy balance in animals and humans. Keywords: AMPK, glucose, lipid, protein, regulation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.055
GPT teacher head0.337
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations50
Published2017
Admission routes1
Has abstractyes

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