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Record W3188694691 · doi:10.1186/s40035-021-00254-1

Roles of physical exercise in neurodegeneration: reversal of epigenetic clock

2021· review· en· W3188694691 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTranslational Neurodegeneration · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of Toronto
FundersScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of ChinaShanghai Center for Brain Science and Brain-Inspired Technology
KeywordsNeurodegenerationEpigeneticsdNaMNeuroscienceNeuroinflammationDiseaseNeurologyDNA methylationMedicineBiologyBioinformaticsGeneticsInternal medicine

Abstract

fetched live from OpenAlex

The epigenetic clock is defined by the DNA methylation (DNAm) level and has been extensively applied to distinguish biological age from chronological age. Aging-related neurodegeneration is associated with epigenetic alteration, which determines the status of diseases. In recent years, extensive research has shown that physical exercise (PE) can affect the DNAm level, implying a reversal of the epigenetic clock in neurodegeneration. PE also regulates brain plasticity, neuroinflammation, and molecular signaling cascades associated with epigenetics. This review summarizes the effects of PE on neurodegenerative diseases via both general and disease-specific DNAm mechanisms, and discusses epigenetic modifications that alleviate the pathological symptoms of these diseases. This may lead to probing of the underpinnings of neurodegenerative disorders and provide valuable therapeutic references for cognitive and motor dysfunction.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.756
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.029
GPT teacher head0.313
Teacher spread0.284 · 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