Metabolic profiling in Prader–Willi syndrome and nonsyndromic obesity: sex differences and the role of growth hormone
Bibliographic record
Abstract
OBJECTIVES: To identify metabolic factors controlling appetite and insulin sensitivity in PWS and assess effects of GH treatment. METHODS: We compared amino acids, fatty acids and acylcarnitines in GH-treated and untreated PWS children and obese and lean controls to identify biomarkers associated with ghrelin, peptide YY and markers of insulin sensitivity (adiponectin and HOMA-IR). RESULTS: Compared with obese controls (OC), children with PWS had fasting hyperghrelinaemia, hyperadiponectinaemia, hypoinsulinaemia and increased ghrelin/PYY. Hyperghrelinaemia, hyperadiponectinaemia and hypoinsulinaemia were more striking in PWS females than males, and decreases in BCAA were detected only in PWS females. GH-treated PWS subjects had lower leptin and higher IGF-1 and adiponectin than untreated subjects; fasting ghrelin, PYY and insulin levels were comparable. Ghrelin correlated inversely with BCAA in PWS but not OC. Adiponectin correlated negatively with BMIz and HOMA-IR in PWS; in contrast, adiponectin correlated more strongly with BCAA than BMIz or HOMA-IR in OC. CONCLUSIONS: BCAA levels were lower in PWS females than OC females and correlated inversely with ghrelin. Low BCAA in PWS females may promote hyperghrelinaemia and hyperphagia, while hyperadiponectinaemia may maintain insulin sensitivity despite excess weight gain. GH treatment may reduce leptin and increase adiponectin, but does not affect fasting ghrelin or PYY.
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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 | 0.000 | 0.001 |
| 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".