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Record W2170601648 · doi:10.1002/dvg.20794

Mouse transgenic lines that selectively label type I, type IIa, and types IIX+B skeletal muscle fibers

2011· letter· en· W2170601648 on OpenAlexfundno aff
Joe V. Chakkalakal, Shihuan Kuang, Mario Buffelli, Jeff W. Lichtman, Joshua R. Sanes

Bibliographic record

Venuegenesis · 2011
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health Research
KeywordsMotor unitFiber typeDenervationGenetically modified mouseSkeletal muscleBiologyFiberEndocrinologyInternal medicineAnatomyTransgeneNeuroscienceChemistryBiochemistryGeneMedicine

Abstract

fetched live from OpenAlex

Skeletal muscle fibers vary in contractile and metabolic properties. Four main fiber types are present in mammalian trunk and limb muscles; they are called I, IIA, IIX, and IIB, ranging from slowest- to fastest-contracting. Individual muscles contain stereotyped proportions of two or more fiber types. Fiber type is determined by a combination of nerve-dependent and -independent influences, leading to formation of "homogeneous motor units" in which all branches of a single motor neuron form synapses on fibers of a single type. Fiber type composition of muscles can be altered in adulthood by multiple factors including exercise, denervation, hormones, and aging. To facilitate analysis of muscle development, plasticity, and innervation, we generated transgenic mouse lines in which Type I, Type IIA, and Type IIX+B fibers can be selectively labeled with distinguishable fluorophores. We demonstrate their use for motor unit reconstruction and live imaging of nerve-dependent alterations in fiber type.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.023
GPT teacher head0.239
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 source (direct Gemma or distilled Codex), 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

Citations26
Published2011
Admission routes1
Has abstractyes

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