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Record W2008301678 · doi:10.1073/pnas.1412685111

Ebf2 is a selective marker of brown and beige adipogenic precursor cells

2014· article· en· W2008301678 on OpenAlexaff
Wenshan Wang, Megan Kissig, Sona Rajakumari, Li Huang, Hee‐Woong Lim, Kyoung‐Jae Won, Patrick Seale

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2014
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsInstitute of Nutrition, Metabolism and Diabetes
FundersNational Institute of General Medical SciencesNational Institutes of HealthNational Institute of Diabetes and Digestive and Kidney DiseasesUniversity of Pennsylvania
KeywordsAdipogenesisCell biologyChemistryBiology

Abstract

fetched live from OpenAlex

Brown adipocytes and muscle and dorsal dermis descend from precursor cells in the dermomyotome, but the factors that regulate commitment to the brown adipose lineage are unknown. Here, we prospectively isolated and determined the molecular profile of embryonic brown preadipose cells. Brown adipogenic precursor activity in embryos was confined to platelet-derived growth factor α(+), myogenic factor 5(Cre)-lineage-marked cells. RNA-sequence analysis identified early B-cell factor 2 (Ebf2) as one of the most selectively expressed genes in this cell fraction. Importantly, Ebf2-expressing cells purified from Ebf2(GFP) embryos or brown fat tissue did not express myoblast or dermal cell markers and uniformly differentiated into brown adipocytes. Interestingly, Ebf2-expressing cells from white fat tissue in adult animals differentiated into brown-like (or beige) adipocytes. Loss of Ebf2 in brown preadipose cells reduced the expression levels of brown preadipose-signature genes, whereas ectopic Ebf2 expression in myoblasts activated brown preadipose-specific genes. Altogether, these results indicate that Ebf2 specifically marks and regulates the molecular profile of brown preadipose cells.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.246

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 studies0.0000.001
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 head0.025
GPT teacher head0.294
Teacher spread0.269 · 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 designBench or experimental
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

Citations224
Published2014
Admission routes1
Has abstractyes

Explore more

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