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Record W1970852069 · doi:10.1152/ajpregu.00275.2005

Genetic and physiological insights into the metabolic syndrome

2005· review· en· W1970852069 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Journal of Physiology-Regulatory, Integrative and Comparative Physiology · 2005
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsMetabolic syndromeBiologyEvolutionary biologyGeneticsObesityEndocrinology

Abstract

fetched live from OpenAlex

The metabolic syndrome (MetS) is a common phenotype that is clinically defined by threshold values applied to measures of central obesity, dysglycemia, dyslipidemia, and/or elevated blood pressure, which must be present concurrently in any one of a variety of combinations. Insulin resistance, although not a defining component of the MetS, is nonetheless considered to be a core feature. MetS is important because it is rapidly growing in prevalence and is strongly related to the development of cardiovascular disease. To define etiology, pathogenesis and expression of MetS, we have studied patients, specifically Canadian families and communities. One example is familial partial lipodystrophy (FPLD), a rare monogenic form of insulin resistance caused by mutations in either LMNA, encoding nuclear lamin A/C (subtype FPLD2), or in PPARG, encoding peroxisomal proliferator-activated receptor-gamma (subtype FPLD3). Because it evolves slowly and recapitulates key clinical and biochemical attributes, FPLD seems to be a useful monogenic model of MetS. A second example is the disparate MetS prevalence between two Canadian aboriginal groups that is mirrored by disparate prevalence of diabetes and cardiovascular disease. Careful phenotypic evaluation of such special cases of human MetS by using a wide range of diagnostic methods, an approach called "phenomics," may help uncover early presymptomatic disease biomarkers, which in turn might reveal new pathways and targets for interventions for MetS, diabetes, and atherosclerosis.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.300
Teacher spread0.274 · 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