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Record W2146688260 · doi:10.4103/1673-5374.150637

Fat cell-secreted adiponectin mediates physical exercise-induced hippocampal neurogenesis: an alternative anti-depressive treatment?

2015· review· en· W2146688260 on OpenAlexaff
Aimin Xu, Kwok‐Fai So, Ang Li

Bibliographic record

VenueNeural Regeneration Research · 2015
Typereview
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNeurogenesisHippocampal formationDepression (economics)HippocampusNeurosciencePhysical exerciseAdiponectinMedicinePsychologyEndocrinologyObesityInsulin resistance

Abstract

fetched live from OpenAlex

Psychological depression is drawing accumulating attention nowadays, due to the skyrocketing incidence worldwide and the enormous burdens it incurs. Physical exercise has been long recognized for its therapeutic effects on depressive disorders, although knowledge of the underlying mechanisms remains limited. Suppressed hippocampal neurogenesis in adult brains has been regarded, at least partly, contributive to depression, whereas physical exercise that restores neurogenesis accordingly exerts the anti-depressive action. Several recent publications have suggested the potential role of adiponectin, a protein hormone secreted by peripheral mature adipocytes, in mediating physical exercise-triggered enhancement of hippocampal neurogenesis and alleviation of depression. Here, we briefly review these novel findings and discuss the possibility of counteracting depression by modulating adiponectin signaling in the hippocampus with interventions including physical exercise and administration of pharmacological agents.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.339
GPT teacher head0.451
Teacher spread0.112 · 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 designSystematic review
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

Citations24
Published2015
Admission routes1
Has abstractyes

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