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Hypoxia increases adipogenesis and affects adipocytokine production in orbital fibroblasts-a possible explanation of the link between smoking and Graves' ophthalmopathy.

2014· article· en· W109284734 on OpenAlexaff
Chiaw Ling Chng, Oi Fah Lai, Charmaine Sze-Min Chew, Yu Pei Peh, Stephanie Man-Chung Fook-Chong, Lay Leng Seah, D. H. C. Khoo

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsDiscovery Centre
Fundersnot available
KeywordsMedicineAdipogenesisLeptinHypoxia (environmental)EndocrinologyInternal medicineGraves' ophthalmopathyAdipose tissueObesityDiseaseGraves' disease

Abstract

fetched live from OpenAlex

AIM: To assess the effects of hypoxia on human orbital fibroblasts (OF) on adipogenesis and adipocytokine production. METHODS: Human OF were derived from tissues obtained from patients with Graves' ophthalmopathy (GO) and from patients without known thyroid diseases undergoing blepharoplasty. The OF were cultured separately under normoxic and hypoxic conditions. Comparisons of adipocytokine concentrations using multiplex ELISA and lipid accumulation in the cells using Oil Red O staining were subsequently performed. RESULTS: There was increased adipogenesis in OF from GO subject when exposed to hypoxic culture conditions. This was not observed in OF from normal controls. Hypoxia led to an increase in leptin and a decrease in MCP-1 secretion in OF cultures. CONCLUSION: Hypoxia induces adipogenesis in OF and may represent a mechanism by which smoking contributes to deterioration of GO. We also found novel changes to leptin and MCP-1 production in OF cultures exposed to hypoxia suggesting important roles of these cytokines in the disease process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.018
GPT teacher head0.232
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2014
Admission routes1
Has abstractyes

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