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Record W3007249276 · doi:10.14440/jbm.2020.307

An optimized procedure for isolation of rodent and human skeletal muscle sarcoplasmic and myofibrillar proteins

2020· article· en· W3007249276 on OpenAlexfundno aff
Michael D. Roberts, Kaelin C. Young, Carlton D. Fox, Christopher G. Vann, Paul A. Roberson, Shelby C. Osburn, Johnathon H. Moore, Petey W. Mumford, Matthew A. Romero, Darren T. Beck, Cody T. Haun, Veera L. D. Badisa, Benjamin Mwashote, Victor Ibeanusi, Andreas N. Kavazis

Bibliographic record

VenueJournal of Biological Methods · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
FundersMcMaster UniversityFlorida State University
KeywordsMyofibrilSkeletal muscleSarcoplasmChemistryIsolation (microbiology)Cell biologyBiochemistryBiologyEndoplasmic reticulumAnatomyBioinformatics

Abstract

fetched live from OpenAlex

Several published protocols exist for isolating contractile or myofibrillar (MF) proteins from skeletal muscle, however, achieving complete resuspension of the myofibril pellet can be technically challenging. We performed several previously published MF isolation methods with the intent of determining which method was most suitable for MF protein isolation and solubilization. Here, we provide an optimized protocol to isolate sarcoplasmic and solubilized MF protein fractions from mammalian skeletal muscle suitable for several downstream assays.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.040
GPT teacher head0.355
Teacher spread0.315 · 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 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

Citations34
Published2020
Admission routes1
Has abstractyes

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