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Association of the β2-adrenergic receptor gene with essential hypertension in the non-Han Chinese Yi minority human population

2006· article· en· W2057097306 on OpenAlexaff
Hongyan Wu, Wenru Tang, Hongwei Li, Xuhong Zhou, Yang Yang, Haijing Yu, Kaiyuan Li, Chunjie Xiao, Alan Y. Deng

Bibliographic record

VenueJournal of Hypertension · 2006
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineAdrenergic receptorGeneAssociation (psychology)Alpha-1B adrenergic receptorAdrenergicInternal medicineGeneticsChinese populationReceptorEndocrinologyPharmacologyBeta-3 adrenergic receptorGenotype

Abstract

fetched live from OpenAlex

OBJECTIVE: The human beta2-adrenergic receptor (ADRB2) gene is a candidate for contributing to the pathophysiology of essential hypertension. The aims of the present study were to investigate the associations of differing single nucleotide polymorphisms (SNPs) and haplotypes of the ADRB2 gene promoter and coding regions with essential hypertension in genetically homogeneous Hani and Yi minority groups that are non-Han Chinese. METHODS: Four SNPs in the regulatory and seven SNPs in the coding region were genotyped in 271 essential hypertension individuals and 267 controls, and eight haplotypes in the regulatory and five haplotypes in the coding region were determined and tested for association using the likelihood test statistic. RESULTS: There were significant associations of essential hypertension with separate SNPs located in both the regulatory and coding regions in the Yi minority group. In contrast, no associations of essential hypertension were detected with any of single SNPs in the Hani minority group. There is a significant difference in haplotype frequency distributions between the hypertensive participants and the controls in two groups (P < 10). CONCLUSION: The results indicate that variants at the ADRB2 locus may play a role in the pathophysiology of hypertension specifically in the Yi minority group.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.274

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 studies0.0000.000
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 head0.011
GPT teacher head0.239
Teacher spread0.228 · 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

Citations32
Published2006
Admission routes1
Has abstractyes

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