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Record W2137246327 · doi:10.7150/jgen.3769

Cellular and Molecular Implications of Mature Adipocyte Dedifferentiation

2013· review· en· W2137246327 on OpenAlexaff
Shengjuan Wei, Márcio de Souza Duarte, Linsen Zan, ‬Min Du, Zhihua Jiang, Le Luo Guan, Jie Chen, Gary J. Hausman, Michael V. Dodson

Bibliographic record

VenueJournal of Genomics · 2013
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAdipogenesisAdipocyteStromal cellCell biologyBiologyCell typeCellular differentiationLipid metabolismCellCell cultureLipid dropletFunction (biology)Stem cellAdipose tissueMesenchymal stem cellGeneBiochemistryGeneticsCancer research

Abstract

fetched live from OpenAlex

There is a voluminous amount of scientific literature dealing with the involvement of adipocytes in molecular regulation of carcass composition, obesity, metabolic syndrome, or diabetes. To form adipocytes (process termed adipogenesis) nearly all scientific papers refer to the use of preadipocytes, adipofibroblasts, stromal vascular cells or adipogenic cell lines, and their differentiation to form lipid-assimilating cells containing storage triacylglyceride. However, mature adipocytes, themselves, possess ability to undergo dedifferentiation, form proliferative-competent progeny cells (the exact plasticity is unknown) and reinitiate formation of cells capable of lipid metabolism and storage. The progeny cells would make a viable (and alternative) cell system for the evaluation of cell ability to reestablish lipid assimilation, ability to differentially express genes (as compared to other adipogenic cells), and to form other types of cells (multi-lineage potential). Understanding the dedifferentiation process itself and/or dedifferentiated fat cells could contribute to our knowledge of normal growth processes, or to disease function. Indeed, the ability of progeny cells to form other cell types could turn-out to be important for processes of tissue reconstruction/engineering and may have implications in clinical, biochemical or molecular processes.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.535

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 head0.030
GPT teacher head0.308
Teacher spread0.278 · 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 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

Citations35
Published2013
Admission routes1
Has abstractyes

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