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Record W4378907660 · doi:10.3389/fphys.2023.1180980

Satellite cell contribution to disease pathology in Duchenne muscular dystrophy

2023· review· en· W4378907660 on OpenAlexafffund
Kasun Kodippili, Michael A. Rudnicki

Bibliographic record

VenueFrontiers in Physiology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesCanadian Institutes of Health ResearchStem Cell NetworkMuscular Dystrophy CanadaE-RareMuscular Dystrophy Association
KeywordsDuchenne muscular dystrophyDystrophinMuscular dystrophyMedicinePathologyDegeneration (medical)Muscle weaknessFibrosisMyopathySatelliteRegeneration (biology)DiseaseInflammationSkeletal muscleMuscle disorderInternal medicineBiologyCell biology

Abstract

fetched live from OpenAlex

Progressive muscle weakness and degeneration characterize Duchenne muscular dystrophy (DMD), a lethal, x-linked neuromuscular disorder that affects 1 in 5,000 boys. Loss of dystrophin protein leads to recurrent muscle degeneration, progressive fibrosis, chronic inflammation, and dysfunction of skeletal muscle resident stem cells, called satellite cells. Unfortunately, there is currently no cure for DMD. In this mini review, we discuss how satellite cells in dystrophic muscle are functionally impaired, and how this contributes to the DMD pathology, and the tremendous potential of restoring endogenous satellite cell function as a viable treatment strategy to treat this debilitating and fatal 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 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.012
GPT teacher head0.272
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations54
Published2023
Admission routes2
Has abstractyes

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