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Record W2156104118 · doi:10.1186/1475-2840-13-23

An accelerated mouse model for atherosclerosis and adipose tissue inflammation

2014· article· en· W2156104118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCardiovascular Diabetology · 2014
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsnot available
FundersMedizinische Universität WienUniversity of AlbertaÖsterreichische Nationalstiftung für Forschung, Technologie und EntwicklungChildren's Health Research InstituteWomen and Children's Health Research InstituteUniversität Wien
KeywordsAdipose tissueInsulin resistanceInflammationInternal medicineEndocrinologyMetabolic syndromeMedicineType 2 diabetesLesionDiabetes mellitusObesityPathology

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.263
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it