Relationship of Selected Adipokines with Markers of Vascular Damage in Patients with Type 2 Diabetes
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: In this study we compared levels of selected adipokines between patients with type 2 diabetes (T2D) and healthy individuals and we determined their relationship with early vascular damage markers. METHODS: Seventy-seven subjects: 56 patients with T2D (34 men and 22 women) and 21 healthy controls (8 men and 13 women) were examined in this cross-sectional study. Selected adipokines [adiponectin, adipocyte fatty acid-binding protein (A-FABP), fibroblast growth factor 21 (FGF-21), C1q/TNF-related protein 9 (CTRP-9), and allograft inflammatory factor-1 (AIF-1)] with possible cardiovascular impact were measured in all participants. To identify markers of vascular damage von Willebrand factor (vWF), plasminogen activator inhibitor-1 (PAI-1) and arterial stiffness parameters were examined in all the subjects. RESULTS: When compared with healthy controls, T2D had significantly higher levels of A-FABP [50.0 (38.1-68.6) vs. 28.6 (23.6-32.9) ng/mL, P < 0.0001] and lower levels of adiponectin [5.9 (4.3-9.0) vs. 11.3 (8.7-14.8) μg/mL, P < 0.0001]. Differences in other adipokines were not statistically significant. Adiponectin level correlated negatively with vWF levels (ρ = -0.29, P < 0.05) and PAI-1 (ρ = -0.36, P < 0.05) and A-FABP positively with vWF (ρ = 0.61, P < 0.05) and PAI-1 (ρ = 0.47, P < 0.05) and augmentation index (ρ = 0.26, P < 0.05). Multivariate regression analysis showed independent association between A-FABP and vWF (b = 0.24, P < 0.05). CONCLUSIONS: Patients with T2D have significantly higher levels of A-FABP and lower levels of adiponectin. These adipokines correlate with indicators of vascular damage and could contribute to cardiovascular risk in patients with T2D. A-FABP may participate in direct endothelium damage.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 it