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Record W7067789909

A NONINVASIVE TEST FOR ESTIMATING TYPE I MYOSIN HEAVY CHAIN EXPRESSION IN WOMEN USING MECHANOMYOGRAPHY

2022· article· en· W7067789909 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTopSCHOLAR (Western Kentucky University) · 2022
Typearticle
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsIsometric exerciseMyosinVastus lateralis muscleTorqueLinear regressionHeavy chainMuscle biopsyCorrelation
DOInot available

Abstract

fetched live from OpenAlex

Stephanie A. Sontag1, Mandy E. Parra2, Hannah L. Dimmick3, Adam J. Sterczala4, Jonathan D. Miller5, Jake A. Deckert6, Phillip M. Gallagher5, Andrew C. Fry5, Trent J. Herda5, and Michael A. Trevino1 1Oklahoma State University, Stillwater, OK; 2University of Mary Hardin-Baylor, Belton, TX; 3University of Calgary, Calgary, AB; 4University of Pittsburgh, Pittsburgh, PA; 5University of Kansas, Lawrence, KS; 6Gonzaga University, Spokane, WA PURPOSE: To determine if mechanomyographic amplitude (MMGRMS)-torque relationships can estimate type I percent myosin heavy chain expression (%MHC) of the vastus lateralis (VL) in sedentary women. METHODS: Fifteen healthy women (mean ± SD; age = 21.3 ± 5.3 yrs) volunteered for this study. Subjects performed 3 isometric maximal voluntary contractions (MVCs) of the knee extensors on an isokinetic dynamometer. The highest torque output determined the target torque levels for the subsequent randomly ordered isometric trapezoidal muscle actions at 30% and 70% MVC. An MMG sensor was placed on the VL. Simple linear regression models were fit to the log-transformed MMGRMS-torque relationships for the linear increasing and decreasing segments. MMGRMS was averaged for the steady torque segment. After testing, a muscle biopsy was taken from the VL. %MHC was analyzed with SDS-PAGE. Pearson’s product moment correlation coefficients determined relationships among type I %MHC expression and each MMG variable (6 total). Sequential multiple-regression procedures determined if a predictive model for type I %MHC of the VL could be developed with the MMG variables significantly correlated with type I %MHC. Alpha was set at 0.05. RESULTS: Type I %MHC was correlated with the b terms from the MMGRMS-torque relationships for the linearly increasing segments at 70% MVC (p = 0.003; r = -0.72) and MMGRMS for the steady torque segments at 30% (p = 0.008; r = -0.65) and 70% MVC (p = 0.040; r = -0.54). No other relationships existed (p > 0.05). For the regression model, correlated variables were added in order of significance. The addition of each variable significantly added to the model (p < 0.05) and overall accounted for 81.2% of the variance in type I %MHC (Table 1). CONCLUSION: MMGRMS may provide a noninvasive method for estimating type I %MHC of the VL in untrained women. Future research should investigate the utility of this model in other populations.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.441
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.022
GPT teacher head0.244
Teacher spread0.222 · 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