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Record W7038525972

INFLUENCE OF MUSCLE ARCHITECTURE AND SIZE ON MECHANOMYOGRAPHIC AMPLITUDE OF THE VASTUS LATERALIS

2022· article· en· W7038525972 on OpenAlexaboutno aff

Bibliographic record

VenueTopSCHOLAR (Western Kentucky University) · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsIsometric exerciseVastus lateralis muscleMuscle architectureTorqueAmplitudeElectromyographyDynamometerLinear relationshipMoment (physics)
DOInot available

Abstract

fetched live from OpenAlex

Sergio Perez Jr.1, Stephanie A. Sontag1, Trent J. Herda2, Adam J. Sterczala3, Jonathan D. Miller2, Mandy E. Parra4, Hannah L. Dimmick5, Michael A. Trevino1 1Oklahoma State University, Stillwater, Oklahoma; 2University of Kansas, Lawrence, Kansas; 3University of Pittsburg, Pittsburg, Pennsylvania; 4University of Mary Hardin-Baylor, Belton, Texas; 5University of Calgary, Calgary, Alberta PURPOSE: The purpose of this study was to examine if relationships exist between muscle architecture and mechanomyographic amplitude (MMGRMS)-torque relationships of the vastus lateralis (VL). METHODS: 11 healthy males (means ± SD; age: 20.18 ± 2.04 years; height: 178.51 ± 4.28 cm; body mass: 78.63 ± 9.11 kg) and 12 healthy females (age: 21.33 ± 3.00 years; height: 164.58 ± 6.60 cm; body mass: 60.38 ± 10.24 kg) completed this investigation. B-mode ultrasonography was used to measure pennation angle, muscle thickness, and subcutaneous fat (sFAT) of the VL. Subjects performed three, three-second maximal voluntary contractions (MVCs) of the knee extensors on an isokinetic dynamometer and the highest torque output was designated as the MVC. A MMG sensor was placed on the VL. Participants then performed an isometric submaximal muscle action that included a 7 s linearly increasing segment up to 70% MVC and a 12 s plateau. For the linearly increasing segment, linear regressions models were fit to the log-transformed MMGRMS-torque relationships and the slope (b term) was calculated. MMGRMS was averaged during the steady torque segment. Pearson’s product moment correlation coefficients were calculated comparing the b terms and MMGRMS at steady torque to pennation angle, muscle thickness, and sFAT of the VL. Alpha was set at 0.05. RESULTS: The b terms were significantly correlated with pennation angle (p < 0.001, r = 0.772) and muscle thickness (p = 0.004, r = 0.571), but not with sFAT (p = 0.263). In addition, MMGRMS at steady torque was significantly correlated with pennation angle (p = 0.018, r = 0.500) and muscle thickness (p = 0.014, r = 0.515), but not with sFAT (p = 0.154). CONCLUSION:The mechanical behavior of the muscle, as measured with MMGRMS, was sensitive to differences in pennation angle and muscle thickness of the VL during a high-intensity contraction. MMGRMS may provide a relatively simple measurement to obtain information regarding muscle architecture. Future research should investigate if MMGRMS can quantify potential changes in pennation angle and muscle thickness as a result of exercise training, aging, or disease.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.266

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 studies0.0000.000
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 head0.007
GPT teacher head0.224
Teacher spread0.216 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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