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Record W4220874914 · doi:10.1002/oby.23389

The microsomal triglyceride transfer protein inhibitor lomitapide improves vascular function in mice with obesity

2022· article· en· W4220874914 on OpenAlexaff
Undral Munkhsaikhan, Youngin Kwon, Amal M. Sahyoun, Karima Ait‐Aissa, Adam Kassan, Modar Kassan

Bibliographic record

VenueObesity · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsMcGill University
FundersNational Heart, Lung, and Blood InstituteNational Institutes of Health
KeywordsInternal medicineEndocrinologyTriglycerideMicrosomal triglyceride transfer proteinMedicineAortaCholesterolLipoproteinVery low-density lipoprotein

Abstract

fetched live from OpenAlex

OBJECTIVE: In this study, the effect of lomitapide, a microsomal triglyceride transfer protein inhibitor, on the cardiovascular function in obesity was investigated. METHODS: Eight-week-old C57BL/6 mice were fed with high-fat diet for 12 weeks in the presence and absence of lomitapide. Lomitapide was administered by gavage (1 mg/kg/d) during the last 2 weeks of high-fat feeding. Body weight, blood glucose, body composition, and lipid profile were determined. Vascular function and endothelial function markers were studied in the aorta and mesenteric resistance arteries. RESULTS: Lomitapide treatment reduced body weight in mice with obesity. Blood glucose, percentage of fat mass, total cholesterol, and low-density lipoprotein levels were significantly reduced, and the percentage of lean mass was significantly increased after lomitapide treatment. The vascular response to sodium nitroprusside in the aorta and mesenteric arteries was similar among groups. However, the vascular response to acetylcholine was improved in the treated group. This was associated with decreased levels of vascular endoplasmic reticulum stress, inflammation, and oxidative stress. CONCLUSIONS: Treatment with lomitapide attenuated the increase in body weight in mice with obesity and restored the lipid profile and vascular function. These effects were accompanied by a decrease in inflammation and oxidative stress.

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 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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.004
GPT teacher head0.186
Teacher spread0.181 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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