An accelerated mouse model for atherosclerosis and adipose tissue inflammation
Bibliographic record
Abstract
BACKGROUND: Obesity and particularly the metabolic syndrome, which is often associated with obesity, combine a major risk for type 2 diabetes and cardiovascular disease. Emerging evidence indicate obesity-associated subclinical inflammation primarily originating from adipose tissue as a common cause for type 2 diabetes and cardiovascular disease. However, a suitable and well-characterized mouse model to simultaneously study obesity-associated metabolic disorders and atherosclerosis is not available yet. Here we established and characterized a murine model combining diet-induced obesity and associated adipose tissue inflammation and metabolic deteriorations as well as atherosclerosis, hence reflecting the human situation of cardio-metabolic disease. METHODS: We compared a common high-fat diet with 0.15% cholesterol (HFC), and a high-fat, high-sucrose diet with 0.15% cholesterol (HFSC) fed to LDL receptor-deficient (LDLR-/-) mice. Insulin resistance, glucose tolerance, atherosclerotic lesion formation, hepatic lipid accumulation, and inflammatory gene expression in adipose tissue and liver were assessed. RESULTS: After 12-16 weeks, LDLR-/- mice fed HFSC or HFC developed significant diet-induced obesity, adipose tissue inflammation, insulin resistance, and impaired glucose tolerance compared to lean controls. Notably, HFSC-fed mice developed significantly higher adipose tissue inflammation in parallel with significantly elevated atherosclerotic lesion area compared to those on HFC. Moreover, LDLR-/- mice on HFSC showed increased insulin resistance and impaired glucose tolerance relative to those on HFC. After prolonged feeding (20 weeks), however, no significant differences in inflammatory and metabolic parameters as well as atherosclerotic lesion formation were detectable any more between LDLR-/- mice fed HFSC or HFC. CONCLUSION: The use of high sucrose rather than more complex carbohydrates in high-fat diets significantly accelerates development of obesity-driven metabolic complications and atherosclerotic plaque formation parallel to obesity-induced adipose tissue inflammation in LDLR-/- mice. Hence LDLR-/- mice fed high-fat high-sucrose cholesterol-enriched diet appear to be a suitable and time-saving animal model for cardio-metabolic disease. Moreover our results support the suggested interrelation between adipose tissue inflammation and atherosclerotic plaque formation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".