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Record W2075607015 · doi:10.1194/jlr.m200305-jlr200

Nitric oxide promotes differentiation of rat white preadipocytes in culture

2002· article· en· W2075607015 on OpenAlexaff
Hongyun Yan, Edith Aziz, G. Shillabeer, Alex Wong, Deena S. Shanghavi, Abdenaim Kermouni, Mohammed Abdel-Hafez, David C.W. Lau

Bibliographic record

VenueJournal of Lipid Research · 2002
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsOttawa HospitalUniversity of OttawaUniversity of Calgary
Fundersnot available
KeywordsNitric oxideWhite (mutation)ChemistryCell biologyBiologyEndocrinologyBiochemistryGene

Abstract

fetched live from OpenAlex

The putative role of nitric oxide (NO) in modulating adipogenesis was investigated in cultured preadipocytes derived from rat white adipose tissue. The NO releasing reagent, hydroxylamine (HA), and nitric oxide synthase (NOS) substrate L-arginine (Arg) had no influence on cell replication. However, both HA and Arg exhibited significant induction on differentiation, as evidenced by increased lipoprotein lipase (LPL) and glycerol-3-phosphate dehydrogenase (GPDH) activities, as well as accelerated triacylglycerol (TG) accumulation. These observations suggested a positive role of NO in modulating adipogenesis. Preadipocytes were found to produce NO, and a approximately 50% increase over basal level was observed on the first 2 days of differentiation. Deprivation of endogenous NOS activity by a non-selective NOS inhibitor, N(G)-monomethyl-L-arginine (NMMA), partially abrogated the differentiation process, implicating a role for endogenous NO to stimulate preadipocyte differentiation. Both NOS isoforms, eNOS and iNOS, were detected in differentiating preadipocytes. Specific iNOS inhibitors (1400W and aminoguanidine) had little influence on NO production and differentiation, suggesting that eNOS rather than iNOS may be the major isoform involved in modulating adipogenesis.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.051
GPT teacher head0.336
Teacher spread0.284 · 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 designObservational
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

Citations89
Published2002
Admission routes1
Has abstractyes

Explore more

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