White Adipose Tissue Surface Expression of LDLR and CD36 is Associated with Risk Factors for Type 2 Diabetes in Adults with Obesity
Bibliographic record
Abstract
Objective Human conditions with upregulated receptor uptake of low‐density lipoproteins (LDL) are associated with diabetes risk, the reasons for which remain unexplored. LDL induce metabolic dysfunction in murine adipocytes. Thus, it was hypothesized that white adipose tissue (WAT) surface expression of LDL receptor (LDLR) and/or CD36 is associated with WAT and systemic metabolic dysfunction. Whether WAT LDLR and CD36 expression is predicted by plasma lipoprotein‐related parameters was also explored. Methods This was a cross‐sectional analysis of 31 nondiabetic adults (BMI > 25 kg/m2) assessed for WAT surface expression of LDLR and CD36 (immunohistochemistry), WAT function, WAT and systemic inflammation, postprandial fat metabolism, and insulin resistance (IR; hyperinsulinemic‐euglycemic clamp). Results Fasting WAT surface expression of LDLR and CD36 was negatively associated with WAT function (3H‐triglyceride storage, r = −0.45 and −0.66, respectively) and positively associated with plasma IL‐1 receptor antagonist (r = 0.64 and 0.43, respectively). Their expression was suppressed 4 hours postprandially, and reduced LDLR was further associated with IR (M/Iclamp, r = 0.61 women, r = 0.80 men). Plasma apolipoprotein B (apoB)‐to‐PCSK9 ratio predicted WAT surface expression of LDLR and CD36, WAT dysfunction, WAT NLRP3 inflammasome priming and disrupted cholesterol‐sensing genes, and systemic IR independent of sex and body composition. Conclusions Higher fasting and lower postprandial WAT surface expression of LDLR and CD36 is associated with WAT dysfunction, systemic inflammation, and IR in adults with overweight/obesity, anomalies that are predicted by higher plasma apoB‐to‐PCSK9 ratio.
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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 | 0.000 | 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) | 0.003 | 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".