Role of type 2 diabetes and hemodialysis in serum adipolin concentrations: A preliminary study
Bibliographic record
Abstract
INTRODUCTION: Adipocytokines play a major role in obesity-associated disorders like insulin resistance (IR). IR is prevalent in diabetes and advanced kidney failure. Adipolin is an adipocytokine with major beneficial effects on insulin sensitivity. This study aimed to investigate adipolin concentration and its relationship with IR and other cardiovascular risk factors in patients with diabetes and/or hemodialysis. METHODS: In this preliminary study, 24 obese patients with type 2 diabetes (DM) and 30 with hemodialysis (14 with diabetes and hemodialysis (HD/DM) and 16 with hemodialysis (HD/non-DM)) were studied. Anthropometric indexes, serum concentrations of adipolin, fasting blood glucose (FBG), insulin, homeostatic model assessment of insulin resistance (HOMA-IR), and lipid profile were assessed. FINDINGS: The results showed higher serum adipolin in DM (29 ± 35 ng/mL) than in HD/DM (13 ± 2 ng/mL, P = 0.01) and HD/Non-DM (12 ± 1.6 ng/mL, P = 0.01) groups. Insulin level was lower in DM than HD/DM (P < 0.001) and HD/Non-DM (P < 0.001) groups, and HOMA-IR was also significantly lower in DM compared to HD/DM group (P < 0.001); while, FBG was significantly higher in DM (P < 0.001) and HD/DM (P = 0.006) compared to HD/Non-DM patients. Adipolin was inversely associated with insulin level (r = -0.446, P = 0.001) and HOMA-IR (r = -0.296, P = 0.035). LDL level was higher in DM compared to HD/DM (P = 0.008) and HD/Non-DM (P = 0.005) groups. Adipolin was directly correlated with cholesterol (r = 0.348, P = 0.01) and LDL (r = 0.428, P = 0.001) concentrations. DISCUSSION: Higher adipolin level in DM group might indicate a compensatory elevation in adipolin production or secretion to modulate IR. It might also be due to medications and inflammation. Further studies are required to investigate the precise role of this adipokine in IR.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".