Relationship Between Adiponectin and apoB in Individuals With Diabetes in the Atlantic PATH Cohort
Bibliographic record
Abstract
CONTEXT: The increasing prevalence of obesity and diabetes greatly influences the risk for cardiovascular (CV) comorbidities and affects the quality of life of many people. However, the relationship among diabetes, obesity, and cardiovascular risk is complex and requires further investigation to understand the biological milieu connecting these conditions. OBJECTIVE: The aim of the current study was to explore the relationship between biological markers of adipose tissue function (adiponectin) and CV risk (apolipoprotein B) in body mass index (BMI)-matched participants with and without diabetes. DESIGN: Nested case-control study. SETTING: The Atlantic Partnership for Tomorrow's Health (PATH) cohort represents four Atlantic Canadian provinces: Newfoundland and Labrador, New Brunswick; Nova Scotia; and Prince Edward Island. PARTICIPANTS: The study population (n = 480) was aged 35 to 69 years, 240 with diabetes and 240 without diabetes. MAIN OUTCOME MEASURES: Groups with and without diabetes were matched for sex and BMI. Both measured and self-reported data were used to examine disease status, adiposity, and lifestyle factors. Immunoassays were used to measure plasma markers. RESULTS: In these participants, plasma adiponectin levels were lower among those with diabetes than those without diabetes; these results were sex-specific, with a strong relationship seen in women. In contrast, in participants matched for sex and adiposity, plasma apoB levels were similar between participants with and those without diabetes. CONCLUSION: Measures of adiposity were higher in participants with diabetes. However, when matched for adiposity, the adipokine adiponectin exhibited a strong inverse association with diabetes.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".