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Record W4293762877 · doi:10.3389/fnagi.2022.965190

The emerging neuroprotective roles of exerkines in Alzheimer’s disease

2022· review· en· W4293762877 on OpenAlexaff
Tayná Rody, Julia A. De Amorim, Fernanda G. De Felice

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2022
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsQueen's University
FundersFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsNeuroprotectionNeuroscienceDiseaseMedicineMyokinePhysical exerciseCognitive declineDementiaFNDC5NeuropharmacologyBioinformaticsPsychologyInternal medicineBiologyFibronectinCell biology

Abstract

fetched live from OpenAlex

Despite the extensive knowledge of the beneficial effects of physical exercise, a sedentary lifestyle is still a predominant harm in our society. Sedentarism is one of the major modifiable risk factors for metabolic diseases such as diabetes mellitus, obesity and neurological disorders, including Alzheimer's disease (AD)-characterized by synaptic failure, amyloid protein deposition and memory loss. Physical exercise promotes neuroprotective effects through molecules released in circulation and mediates the physiological crosstalk between the periphery and the brain. This literature review summarizes the current understanding of the roles of exerkines, molecules released during physical exercise, as systemic and central factors that mediate the beneficial effects of physical exercise on cognition. We highlight the neuroprotective role of irisin-a myokine released from the proteolytic cleavage of fibronectin type III domain-containing protein 5 (FNDC5) transmembrane protein. Lastly, we review evidence pointing to physical exercise as a potential preventative and interventional strategy against cognitive decline in AD.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.055
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations31
Published2022
Admission routes1
Has abstractyes

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