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Record W4283387003 · doi:10.1155/2022/5850507

Metabolic Syndrome: Lessons from Rodent and <i>Drosophila</i> Models

2022· review· en· W4283387003 on OpenAlexaff
Myroslava Vatashchuk, Maria M. Bayliak, Viktoria Hurza, Kenneth B. Storey, Volodymyr I. Lushchak

Bibliographic record

VenueBioMed Research International · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsCarleton University
FundersMinistry of Education and Science of UkraineNational Research FoundationNational Research Foundation of Ukraine
KeywordsMetabolic syndromeDrosophila (subgenus)Abdominal obesityObesityBiologyRodentRodent modelDrosophila melanogasterAnimal modelOverweightInternal medicineEndocrinologyBioinformaticsMedicineGeneticsGeneEcology

Abstract

fetched live from OpenAlex

Overweight and obesity are health conditions tightly related to a number of metabolic complications collectively called “metabolic syndrome” (MetS). Clinical diagnosis of MetS includes the presence of the increased waist circumference or so‐called abdominal obesity, reduced high density lipoprotein level, elevated blood pressure, and increased blood glucose and triacylglyceride levels. Different approaches, including diet‐induced and genetically induced animal models, have been developed to study MetS pathogenesis and underlying mechanisms. Studies of metabolic disturbances in the fruit fly Drosophila and mammalian models along with humans have demonstrated that fruit flies and small mammalian models like rats and mice have many similarities with humans in basic metabolic functions and share many molecular mechanisms which regulate these metabolic processes. In this paper, we describe diet‐induced, chemically and genetically induced animal models of the MetS. The advantages and limitations of rodent and Drosophila models of MetS and obesity are also analyzed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.002
Research integrity0.0000.001
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 head0.154
GPT teacher head0.407
Teacher spread0.253 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations28
Published2022
Admission routes1
Has abstractyes

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