Skeletal muscle fibre morphology in childhood—insights into myopenia in pediatric liver disease
Bibliographic record
Abstract
Myopenia (reduced skeletal muscle [SM]) is common in children with end-stage liver disease (ESLD) and suboptimal nutritional status pre- and post-liver transplantation (LTx). Myopenia may result in altered SM morphology (changes in muscle fibre size and types [type I vs. II proportions]) contributing to adverse outcomes and deficits in muscle strength/functionality. Understanding how SM morphology changes in healthy children with age and the potential impact of ESLD on SM morphology offers insight into the effectiveness of rehabilitation strategies for children with ESLD at risk for myopenia. Literature searches in PubMed, Scopus, and Web of Science identified studies examining SM morphology in healthy children and in ESLD. Muscle fibre size increases with age in healthy children. Type I fibres are more prevalent in childhood, whereas type II fibres increase post-puberty. Preliminary evidence indicates that adults with ESLD have reduced muscle fiber size with type II fibre atrophy. No data are available for pediatric ESLD. SM morphology changes with age and may be impacted by the negative physical and metabolic insults associated with ESLD and malnutrition. Take-home message Skeletal muscle morphology in healthy children changes with age. Liver disease may preferentially affect type II fibres in adults with end-stage liver disease (ESLD). More research is needed on the effects of ESLD on muscle morphology in children.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".