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Record W2796063182 · doi:10.1186/s12199-018-0701-8

Synergistic effects of brain-derived neurotrophic factor (BDNF) and exercise intensity on memory in the adolescent brain: a commentary

2018· article· en· W2796063182 on OpenAlexaff
Tharmegan Tharmaratnam, Tyler Tabobondung, Taylor A. Tabobondung, Sally Doherty

Bibliographic record

VenueEnvironmental Health and Preventive Medicine · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcMaster UniversityJoseph Brant HospitalUniversity of Toronto
Fundersnot available
KeywordsCardiorespiratory fitnessNeuroplasticityBrain-derived neurotrophic factorNeurotrophic factorsMedicineNeuroscienceAerobic exerciseCognitionPhysical exercisePsychologyInternal medicine

Abstract

fetched live from OpenAlex

This commentary highlights the recently published study by Jeon and Ha (Environ Health Prev Med 22:27, 2017) examining the effects of exercise intensity and brain-derived neurotrophic factor (BDNF) on memory in adolescents. This 12-week training study elicited increases in BDNF and improvements in working memory during moderate- and high-intensity exercise, which may have been achieved through improved brain tissue oxygenation, nutrient delivery, and BDNF mRNA expression. These improvements highlight the positive neuroendocrinological effects of BDNF and its role as a potential candidate molecule, as a mediator of synaptic plasticity. In this commentary, we aim to highlight the strengths and potential areas of consideration of Jeon and Ha (Environ Health Prev Med 22:27, 2017). We also offer insight into the clinical implications of this study, such as advocating for exercise in healthy children and as adjunctive therapy in pathological states. This study is promising and further highlights the importance of cardiorespiratory exercise in improving physiological health and cognitive functioning in youth through the phenomenon of neuroplasticity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.024
GPT teacher head0.300
Teacher spread0.276 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2018
Admission routes1
Has abstractyes

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