[Association study between single nucleotide polymorphism in AOAH gene and chronic rhinosinusitis in a Chinese population].
Bibliographic record
Abstract
OBJECTIVE: To replicate the polymorphisms in risk genes of chronic rhinosinusitis in a Chinese Han population. METHODS: Enrolled in this study were CRS patients with nasal polyps (n = 306, CRSwNP), CRS patients without nasal polyps (n = 332, CRSsNP), and controls (n = 315) in a Chinese population. All the patients were recruited from clinic of the department of Otorhinolaryngology of Beijing Tongren Hospital between 2008 February and 2009 July. A total of 10 single nucleotide polymorphisms (SNPs) selected from previous identified SNPs associated with CRS in Canadian population were individually genotyped. Allele and genotype frequencies were calculated by frequency counting, the chi-square test or exact method were applied to analyze the results.Final results were corrected by Bonferroni multiple correction.SPSS 13.0 software was used for statistical analysis. RESULTS: One SNP in AOAH gene(rs4504543, P = 1.95 × 10⁻⁵, OR = 0.559 0) was identified to be significantly associated with whole CRS cohort. After subgroup analysis for the presence of nasal polyps (CRSwNP and CRSsNP), the same SNP in AOAH (rs4504543, P = 3.47 × 10⁻¹², OR = 0.284 8) was also found to be significantly associated with CRSsNP cohorts. CONCLUSIONS: AOAH was significantly associated with CRS and its polymorphisms might play a role in the susceptibility to develop CRS in Chinese population.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".