The assessment of myopenia and muscle biopsy in pediatric patients with liver disease awaiting liver transplantation—A cross-sectional analysis
Bibliographic record
Abstract
Little is known about the skeletal muscle characteristics (fiber type proportion and size, location of nuclei, presence of fat infiltration) in children with liver disease with radiologically determined myopenia (low muscle mass). During liver transplantation (LTx) surgery, biopsies from the rectus abdominis muscle were collected. Muscle fiber types (I, I/IIA, IIA, IIA/X, IIX) and cross-sectional area index (µm/m 2 ) were determined using immunofluorescence staining. Triacylglycerol and phospholipid content of muscle was determined using gas chromatography. Myopenia was defined using study-specific cutoffs (skeletal muscle index <-2 SD) from age-sex-matched healthy control scans. Myopenia was prevalent in 41% of children. Children also had a high prevalence of high muscle adiposity (37%). Children with myopenia were older (8.4 vs. 0.7 y; p <0.001), had smaller total (median 595 vs. 844 µm/m 2 ; p =0.04) and hybrid IIA/X (612±143 vs. 993±341 µm/m 2 ; p =0.04) muscle fiber size index, lower prevalence of type I fibers (53% vs. 64%; p =0.01) and higher prevalence of type IIA/X hybrid fibers (median 7.5% vs. 0%; p =0.04). Children with myopenia also had a higher prevalence of elevated triacylglycerol content (>75 percentile) within the muscle compared to children without myopenia (36% vs. 0%; p =0.009). Percent of muscle fibers with centralized nuclei was not different between groups. In conclusion, children with myopenia experience differences in skeletal muscle biological characteristics when compared to children without myopenia at LTx, and these findings may have implications for dietary and exercise rehabilitation pre-LTx and post-LTx.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".