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Record W2171550468 · doi:10.1152/ajpcell.00305.2011

Nitric oxide and voluntary exercise together promote quadriceps hypertrophy and increase vascular density in female 18-mo-old mice

2012· article· en· W2171550468 on OpenAlexaff
Jeff Leiter, Ritika Upadhaya, Judy E. Anderson

Bibliographic record

VenueAmerican Journal of Physiology-Cell Physiology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Manitoba
FundersUniversities Space Research Association
KeywordsMuscle hypertrophyInternal medicineEndocrinologyNitric oxideSarcopeniaMuscle atrophyAtrophyDystrophinMyosinVascular smooth muscleMedicineAnabolismBiologySkeletal muscleCell biology

Abstract

fetched live from OpenAlex

Age-related sarcopenia reduces the size, strength, and function of muscle, and the diameter of muscle fibers. It also disrupts the dystrophin-glycoprotein complex, dislocating nitric oxide synthase 1 (NOS-1) and reducing sarcolemmal integrity. This study of quadriceps muscle in 18-mo-old mice showed that NO-donor treatment with isosorbide dinitrate (I) for 6 wk, in combination with voluntary exercise for 3 wk, increased muscle mass by 25% and stimulated cell proliferation. The resulting fiber hypertrophy was accompanied by a lower ratio of protein:DNA, consistent with myogenic-cell hyperplasia. Treatment enhanced the ratio of NOS-1:β-dystroglycan in correlation with fiber diameter, improved sarcolemmal integrity, and increased vascular density after an increase in vascular endothelial growth factor protein at 3 wk. Results demonstrate that age-related muscle refractoriness to exercise can be overcome with NO-donor treatment. Since activation of muscle stem cells and vascular perfusion are limiting factors in the maintenance, regeneration, and growth of aged muscle, results suggest the feasibility of using NO-donor drugs to combat atrophy and muscle ischemia. Improved function and quality of life from the NO-amplified effects of exercise may be useful in aging and other conditions such as disuse, insulin resistance, or microgravity.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.005
GPT teacher head0.214
Teacher spread0.208 · 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.

Study designBench or experimental
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

Citations49
Published2012
Admission routes1
Has abstractyes

Explore more

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