Adipokines as novel biomarkers in paediatric systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVES: Patients with SLE are at risk for premature atherosclerosis and metabolic syndrome. Cytokines produced by adipocytes, adipokines, are important in glucose/lipid metabolism and the development of atherosclerosis. The objectives of this study were to evaluate leptin, adiponectin and ghrelin concentrations in paediatric SLE (pSLE) and to correlate these concentrations with measures of disease activity, serum lipid concentrations, measures of insulin resistance and serum homocysteine concentrations. METHODS: Two hundred and eight samples from 105 patients with pSLE and 77 samples from 77 healthy paediatric controls were evaluated by ELISA to measure leptin, adiopnectin and ghrelin. Students' t-test was used for analysis. Concentrations of adipokines were correlated with disease activity, serum lipids, insulin resistance and homocysteine. RESULTS: Overall 35 SLE patients (34%) had an abnormally elevated leptin level. The only significant correlation of leptin concentrations was with homocysteine concentrations but not disease activity, prednisone dose, lipids or insulin resistance. There was no difference in the mean adiponectin concentrations between the control and patient groups and none of the patient samples were below the normal lower limit while seven were elevated. There was a significant correlation of adiponectin concentrations with prednisone dose, lipid concentrations and insulin resistance but not with disease activity or homocysteine. Elevated ghrelin concentrations were found in 20% of the pSLE patients. The only correlation of ghrelin concentrations was with homocysteine. CONCLUSIONS: Adipokines are novel biomarkers in pSLE. They may represent cardiovascular risk and are not just surrogate markers for disease activity, therapy or serum lipids. Their correlation with atherosclerosis needs to be explored.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".