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Record W3024103478 · doi:10.1111/jnc.15039

Protective actions of exercise‐related FNDC5/Irisin in memory and Alzheimer’s disease

2020· review· en· W3024103478 on OpenAlexafffund
Guilherme B. de Freitas, Mychael V. Lourenco, Fernanda G. De Felice

Bibliographic record

VenueJournal of Neurochemistry · 2020
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsQueen's University
FundersInstitute for Translational NeuroscienceUniversidade Federal do Rio de JaneiroInstituto Nacional de Ciência e Tecnologia de Neurociência TranslacionalFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e TecnológicoAlzheimer SocietyWeston Brain InstituteInternational Society for NeurochemistryAlzheimer's Association
KeywordsFNDC5MyokineNeuroprotectionNeuroscienceDiseaseMedicineCrosstalkBrain agingAlzheimer's diseaseCognitionBioinformaticsPhysical medicine and rehabilitationPsychologyBiologyInternal medicineFibronectinCell biology

Abstract

fetched live from OpenAlex

The proportion of elderly populations is rapidly booming, and human lifespan has considerably increased in the past century because of scientific and medical advances. However, the winds of change brought by the 21st century made sedentarism one of the factors that renders the brain vulnerable to age-related chronic diseases, such as Alzheimer's disease (AD). Conversely, physical exercise has been shown to stimulate molecular mechanisms beneficial to cognition. Here, we review evidence showing the positive effects of physical exercise in the brain. We further discuss recent evidence that irisin, a myokine stimulated by physical exercise derived from fibronectin type III domain-containing protein 5 (FNDC5) transmembrane protein, has neuroprotective actions in the brain. Lastly, we highlight the importance of the crosstalk between the periphery and the brain in cognition and the therapeutic potential of FNDC5/irisin 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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.059
GPT teacher head0.350
Teacher spread0.292 · 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

Citations117
Published2020
Admission routes2
Has abstractyes

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