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Record W4367399804 · doi:10.1016/j.xpro.2023.102260

Calcium measurements in enzymatically dissociated or mechanically microdissected mouse primary skeletal muscle fibers

2023· article· en· W4367399804 on OpenAlexfundno aff
Sonia Youhanna, Joseph D. Bruton, Kent Jardemark, Håkan Westerblad, Volker M. Lauschke

Bibliographic record

VenueSTAR Protocols · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeInnovative Medicines InitiativeCentrum för idrottsforskningKungliga Tekniska HögskolanKnut och Alice Wallenbergs StiftelseRobert Bosch StiftungEuropean CommissionEuropean Federation of Pharmaceutical Industries and AssociationsVetenskapsrådetOntario Institute for Cancer ResearchDiamond Light SourceMcGill University
KeywordsCollagenaseMicrodissectionCalciumSkeletal muscleChemistryBiophysicsCalcium in biologyIntracellularBiochemistryAnatomyBiologyEnzyme

Abstract

fetched live from OpenAlex

Here, we provide a protocol for isolation of mouse primary skeletal muscle fibers using two alternative approaches—enzymatic dissociation or mechanical microdissection. We describe the procedures for surgical removal of muscle of interest and isolation of intact single-muscle fibers by either collagenase digestion or mechanical microdissection. We then detail intracellular calcium measurements by microinjecting or loading the isolated muscle fibers with membrane permeable calcium dyes. Finally, we outline steps for intracellular calcium quantification by fluorescent measurement. For complete details on the use and execution of this protocol, please refer to Gineste et al. 1

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.767

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 head0.047
GPT teacher head0.327
Teacher spread0.280 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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