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Record W2083336695 · doi:10.1089/ham.2007.1018

Common Haplotypes in the <i>β</i> -2 Adrenergic Receptor Gene Are Not Associated with Acute Mountain Sickness Susceptibility in Nepalese

2007· article· en· W2083336695 on OpenAlexafffund
Pei Wang, Michael S. Koehle, Jim L. Rupert

Bibliographic record

VenueHigh Altitude Medicine & Biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsCanadian Sport Centre PacificUniversity of British Columbia
FundersUniversity of British ColumbiaMichael Smith Health Research BC
KeywordsInternational HapMap ProjectHaplotypeGeneticsPleiotropyBiologyAlleleGenePopulationMedicineEnvironmental healthPhenotype

Abstract

fetched live from OpenAlex

Acute Mountain Sickness (AMS), the most common and least serious of the altitude-related illnesses, is frequently experienced by sojourners traveling above 2500 m. Although altitude and rate of ascent are likely the most critical factors in determining whether the condition will develop in a person, interindividual variation and patterns of susceptibility suggest that there may be genetic risk factors as well. We hypothesized that variants in the gene that encodes the beta-2 adrenergic receptor (the principal catecholamine receptor in the lungs) are involved in the etiology of AMS and tested this hypothesis in cohorts of Nepalese individuals who developed or did not develop AMS when attending the Purnima Festival at Lake Gosain Kunda at 4380. Polymorphisms that could serve as markers for the common haplotypes encompassing the gene were chosen using the HapMap database. We found no association between any alleles at the seven highly informative polymorphic loci (tagSNPs) that we assayed and AMS status, suggesting that variants in, or near, the beta-2 adrenergic receptor gene do not contribute to AMS susceptibility in this population. This study is the first application of the HapMap database and associated haplotype mapping tools to the understanding of altitude-related pathologies.

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)0.002
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 score0.451
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.274
Teacher spread0.261 · 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

Citations15
Published2007
Admission routes2
Has abstractyes

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