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Record W3172379734 · doi:10.1210/endrev/bnab018

Fat Cell Size: Measurement Methods, Pathophysiological Origins, and Relationships With Metabolic Dysregulations

2021· review· en· W3172379734 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEndocrine Reviews · 2021
Typereview
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsUniversité LavalCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsPathophysiologyCell sizeBiologyMedicinePathologyCell biology

Abstract

fetched live from OpenAlex

The obesity pandemic increasingly causes morbidity and mortality from type 2 diabetes, cardiovascular diseases and many other chronic diseases. Fat cell size (FCS) predicts numerous obesity-related complications such as lipid dysmetabolism, ectopic fat accumulation, insulin resistance, and cardiovascular disorders. Nevertheless, the scarcity of systematic literature reviews on this subject is compounded by the use of different methods by which FCS measurements are determined and reported. In this paper, we provide a systematic review of the current literature on the relationship between adipocyte hypertrophy and obesity-related glucose and lipid dysmetabolism, ectopic fat accumulation, and cardiovascular disorders. We also review the numerous mechanistic origins of adipocyte hypertrophy and its relationship with metabolic dysregulation, including changes in adipogenesis, cell senescence, collagen deposition, systemic inflammation, adipokine secretion, and energy balance. To quantify the effect of different FCS measurement methods, we performed statistical analyses across published data while controlling for body mass index, age, and sex.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.144
GPT teacher head0.386
Teacher spread0.242 · 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