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AXIN-AMPK signaling: Implications for healthy aging

2021· preprint· en· W4200090806 on OpenAlexafffund
Avijit Mallick, Bhagwati P. Gupta

Bibliographic record

VenueF1000Research · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpen peer reviewPlant biologyAMPKPhysiologyNeuroscienceMedicineBiologyCell biologyBioinformaticsKinaseProtein kinase A

Abstract

fetched live from OpenAlex

The energy sensor AMP kinase (AMPK) and the master scaffolding protein, AXIN, are two major regulators of biological processes in metazoans. AXIN-dependent regulation of AMPK activation plays a crucial role in maintaining metabolic homeostasis during glucose-deprived and energy-stressed conditions. The two proteins are also required for muscle function. While studies have refined our knowledge of various cellular events that promote the formation of AXIN-AMPK complexes and the involvement of effector proteins, more work is needed to understand precisely how the pathway is regulated in response to various forms of stress. In this review, we discuss recent data on AXIN and AMPK interaction and its role in physiological changes leading to improved muscle health and an extension of lifespan. We argue that AXIN-AMPK signaling plays an essential role in maintaining muscle function and manipulating the pathway in a tissue-specific manner could delay muscle aging. Therefore, research on understanding the factors that regulate AXIN-AMPK signaling holds the potential for developing novel therapeutics to slow down or revert the age-associated decline in muscle function, thereby extending the healthspan of animals.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
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 head0.079
GPT teacher head0.407
Teacher spread0.328 · 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.

Study designNot applicable
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

Citations6
Published2021
Admission routes2
Has abstractyes

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