Lipocalin-2 Is an Inflammatory Marker Closely Associated with Obesity, Insulin Resistance, and Hyperglycemia in Humans
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Lipocalin-2, a 25-kDa secreted glycoprotein, is a useful biomarker for early detection of various renal injuries. Because lipocalin-2 is abundantly expressed in adipose tissue and liver, we investigated its relevance to obesity-related pathologies. METHODS: We used real-time PCR and in-house immunoassays to quantify the mRNA and serum concentrations of lipocalin-2 in C57BL/KsJ db/db obese mice and their age- and sex-matched lean littermates. We analyzed the association between serum lipocalin-2 concentrations and various metabolic and inflammatory variables in 229 persons (121 men and 108 women) recruited from a previous cross-sectional study, and we evaluated the effect of the insulin-sensitizing drug rosiglitazone on serum lipocalin-2 concentrations in 32 diabetic patients (21 men and 11 women). RESULTS: Compared with the lean littermates, lipocalin-2 mRNA expression in adipose tissue and liver and its circulating concentrations were significantly increased in db/db diabetic/obese mice (P <0.001). These changes were normalized after rosiglitazone treatment. In humans, circulating lipocalin-2 concentrations were positively correlated (P <0.005) with adiposity, hypertriglyceridemia, hyperglycemia, and the insulin resistance index, but negatively correlated (P = 0.002) with HDL cholesterol. There was also a strong positive association between lipocalin-2 concentrations and high sensitivity C-reactive protein (hs-CRP), independent of age, sex, and adiposity (P = 0.007). Furthermore, rosiglitazone-mediated decreases in lipocalin-2 concentrations correlated significantly with increases in insulin sensitivity (r = 0.527; P = 0.002) and decreases in hs-CRP concentrations (r = 0.509; P = 0.003). CONCLUSIONS: Lipocalin-2 is an inflammatory marker closely related to obesity and its metabolic complications. Measurement of serum lipocalin-2 might be useful for evaluating the outcomes of various clinical interventions for obesity-related metabolic and cardiovascular diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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