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Record W4409383677 · doi:10.1016/j.yfrne.2025.101189

Physical activity in Alzheimer’s disease prevention: Sex differences and the roles of BDNF and irisin

2025· review· en· W4409383677 on OpenAlexafffund
Fernanda G. Q. Barros‐Aragão, Emilia Januszkiewicz, T. Hunter, Fernanda G. De Felice

Bibliographic record

VenueFrontiers in Neuroendocrinology · 2025
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsQueen's University
FundersCanadian Institutes of Health ResearchFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroQueen's UniversityCanada Research Chairs
KeywordsDiseasePhysical activityInternal medicineAlzheimer's diseaseMedicineGerontologyPsychologyEndocrinologyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) disproportionately affects women, with postmenopausal hormonal changes contributing to elevated risk. Physical exercise is a promising, non-pharmacological strategy to mitigate cognitive decline and AD progression. Brain-derived neurotrophic factor (BDNF) and irisin are key molecular mediators of exercise-induced brain health and protection against AD pathology by promoting synaptic plasticity, neurogenesis, and reducing amyloidosis, tau pathology, and neuroinflammation in sex-specific mechanisms. This review explores sex and gender influences on exercise outcomes and their interaction with FNDC5/irisin and BDNF signaling pathways in the context of AD prevention. We highlight emerging evidence on the interplay between exercise, sex, and neuroprotective pathways, emphasizing the need for sex-sensitive research designs to advance precision approaches for AD prevention.

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)0.001
metaresearch head score (Gemma)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.345
Teacher spread0.306 · 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

Citations9
Published2025
Admission routes2
Has abstractno

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