Can stanniocalcin-2 be regarded as a novel non-invasivebiomarker of advanced liver steatosis in obese children?A preliminary study
Bibliographic record
Abstract
Introduction With the increasing prevalence of liver steatosis, non-invasive methods are sought to detect it and to assess the degree of lipid accumulation in the liver. The aim of this preliminary study was to assess the serum concentrations of stanniocalcin-2 (STC-2), pregnancy-associated plasma protein A (PAPP-A) and insulin-like growth factor binding protein (IGFBP-4) among children with obesity, check if they detect liver steatosis and determine whether they differentiate mild and advanced steatosis. Material and methods This prospective study involved 62 obese children (39 boys and 23 girls, median age 13.75 years). Infectious, autoimmune, metabolic and toxic liver conditions were excluded. All subjects underwent body composition analysis, anthropometric measurements, abdominal ultrasound and routine blood chemistry analyses. STC-2, PAPPA and IGFBP-4 were measured using ELISA kits. The control group consisted of 19 non-obese, healthy children with correct body mass index and without organic pathologies. Results The concentration of examined biomarkers in obese children with liver steatosis was significantly higher than in the control group and STC-2 was also significantly higher in children with advanced steatosis in comparison to children with mild steatosis. In the group of obese children with liver steatosis STC-2 positively correlated with: gamma-glutamyltransferase, cholesterol, triglycerides, low-density lipoprotein cholesterol, homeostatic model assessment-insulin resistance and waist-hip ratio. The ability of serum STC-2 to detect advanced liver steatosis was significant (AUC = 0.746, p = 0.0022, cut-off 135.27 pg/ml). Conclusions This preliminary study demonstrated that STC-2 can be regarded as a potential non-invasive marker of advanced liver steatosis in obese children. The other analyzed parameters (PAPP-A and IGFBP-4) seem not to be useful in diagnosis of liver steatosis in obese 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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".