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Record W4293066205 · doi:10.1093/labmed/lmac073

Increased Levels of ANGPTL3 and CTRP9 in Patients With Obstructive Sleep Apnea and Their Relation to Insulin Resistance and Lipid Metabolism and Markers of Endothelial Dysfunction

2022· article· en· W4293066205 on OpenAlexaff
Reza Fadaei, Samaneh Mohassel Azadi, Ismail Laher, Habibolah Khazaie

Bibliographic record

VenueLaboratory Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAdiponectinInsulin resistanceInternal medicineEndocrinologyMedicineDyslipidemiaAdipokineEndothelial dysfunctionLeptinObstructive sleep apneaBody mass indexObesity

Abstract

fetched live from OpenAlex

OBJECTIVE: Obstructive sleep apnea (OSA) has a close relation with obesity and perturbation in adipokines and hepatokines, which are linked to OSA consequences such as insulin resistance, dyslipidemia, and endothelial dysfunction. This study aimed to assess the relation of C1q/TNF-related protein 9 (CTRP9) and angiopoietin-like protein 3 (ANGPTL3) with OSA and biochemical measurements. METHODS: Serum levels of ANGPTL3, CTRP9, adiponectin, leptin, intercellular adhesion molecule 1 (ICAM-1), and vascular cell adhesion protein 1 (VCAM-1) were determined in 74 OSA patients and 27 controls using enzyme-linked immunosorbent assay kits. RESULTS: Levels of ANGPTL3, CTRP9, leptin, ICAM-1, and VCAM-1 were increased in the patients compared to the controls, whereas adiponectin levels decreased. ANGPTL3 had a positive correlation with total cholesterol, triglyceride, low-density lipoprotein cholesterol, ICAM-1, and VCAM-1 and was inversely correlated with leptin. CTRP9 showed a positive correlation with body mass index, insulin resistance, ICAM-1, and VCAM-1. CONCLUSION: The results indicated the relation of ANGLTP3 and CTRP9 with OSA and its complications, which suggested a possible role for these factors in the consequences of OSA.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.199
Teacher spread0.194 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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