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Record W1971643720 · doi:10.1002/mus.21503

Effects of exercise and muscle type on BDNF, NT‐4/5, and TrKB expression in skeletal muscle

2009· article· en· W1971643720 on OpenAlexafffund
Daniel I. Ogborn, Phillip F. Gardiner

Bibliographic record

VenueMuscle & Nerve · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of ManitobaResearch Manitoba
FundersCanadian Institutes of Health Research
KeywordsTropomyosin receptor kinase BSoleus muscleInternal medicineSkeletal muscleEndocrinologyGastrocnemius muscleNeurotrophinBrain-derived neurotrophic factorMedicineChemistryNeurotrophic factorsReceptor

Abstract

fetched live from OpenAlex

Muscle-derived neurotrophins are thought to contribute to the adaptation of skeletal muscle to exercise, but the effects of brief exercise interventions on BDNF, NT-4/5, and trkB are not understood. RNA was extracted for RT-PCR from soleus and medial gastrocnemius of Sprague-Dawley rats exercised on a treadmill at speeds up to 20 m/min at 5% incline for 5 or 10 days. BDNF expression was elevated in soleus following 5 days (184%, P < 0.001) but not 10 days of exercise. NT-4/5 and trkB were not affected at either time-point. BDNF mRNA was significantly higher in soleus at rest when compared with medial gastrocnemius (193%, P < 0.05). No significant effects of muscle type were detected for NT-4/5 and trkB. Our results indicate differential control of BDNF expression between soleus and medial gastrocnemius following 5 days of exercise. BDNF may be a protein with an uncharacterized contribution to the acute adaptation of skeletal muscle to exercise, whereas NT-4/5 shows no response.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.253
Teacher spread0.239 · 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 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

Citations76
Published2009
Admission routes2
Has abstractyes

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