Ldlr−/− Mice Display Decreased Susceptibility to Western-Type Diet-Induced Obesity Due to Increased Thermogenesis
Bibliographic record
Abstract
The low-density lipoprotein receptor (Ldlr) is a key molecule involved with lipid clearance. The Ldlr(-/-) mouse has been used extensively as a model for studying atherosclerosis. This study sought to characterize the energy balance phenotype of Ldlr(-/-) mice with respect to weight gain, body composition, energy expenditure (EE), glucose homeostasis, and leptin sensitivity. Adult Ldlr(-/-) mice and Ldlr(+/+) controls on a C57Bl/6J background were fed either a chow or a high-fat, high-sucrose Western-type diet (WTD) for eight wk. Physiological studies of food intake, EE, activity, insulin sensitivity, and leptin responsiveness were performed. The effect of these diet interventions on circulating leptin and on leptin gene expression was also examined. On the chow diet, Ldlr(-/-) mice had lower EE and higher activity levels relative to controls. On the WTD, Ldlr(-/-) mice gained less weight relative to Ldlr(+/+) mice, specifically gaining less fat mass. Increased thermogenesis in Ldlr(-/-) mice fed the WTD was detected. Additionally, leptin responsiveness was blunted in chow-fed Ldlr(-/-) mice, suggesting a novel role for the Ldlr pathway that extends to leptin's regulation of energy balance. In addition to its known role in lipid transport, these results demonstrate the importance of the Ldlr in energy homeostasis and suggest a direct physiological link between altered lipid transport and energy balance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".