Study on the gene polymorphism of TNF-α-238 in Ankylosing Spondylitis (AS) patients in Hunan population
Bibliographic record
Abstract
Objective:To explore the correlations of TNF-α-238 site gene polymorphism and the onset of Ankylosing Spondylitis(AS)in Hunan Han population.Methods:100 AS samples(including serum and whole blood) were collected from the Department of Immunology and Rheumatology of the Second Xiangya hospital from May 2008 to Jan 2009 and 90 samples of normal people were collected as control group.We detected the TNF-α-238 gene polymorphism of these subjects by using PCR-RFLP technique.The TNF-α level in the serum samples were measured by ELISA and HLA-B27 antigen was detected by flow cytometry(FCM).Then all of the data was analyzed by SPSS13.0 software.Results:There were 95 cases with the TNF-α-238 G/G genotype in 100 AS patients,5 cases with the G/A genotype.While in the control group,TNF-α-238 G/G genotype and G/A genotype were 88 cases and 2 cases respectively.There was no TNF-α-238 A/A genotype in both groups.The allele frequencies of G in AS group was higher than in the control group(98.9% vs.97.5%),while the allele frequencies of A in AS group was lower than in the control group(1.1% vs.2.5%).However,there were no significant difference both A allele frequencies and G allele frequencies(P0.05).In addition,the average TNF-α level in AS group was higher than in the control group significantly(10.16±1.19 pg/ml vs.5.64±1.18 pg/ml).And the average TNF-α level in AS patients with the genotype of G/A was higher than that of with the G/G genotype(13.49±1.27 pg/ml vs.9.44±1.29 pg/ml).There was a very large difference of the positive ratio of HLA-B27 between two groups(χ2=114.975,P=0.000).After gene analysis of HLA-B27and TNF-α-238,the odds ratio(OR)was higher in both G/G genotype and HLA-B27 positive than HLA-B27 lonely.Conclusion:There is probably no relationship between the gene polymorphism of TNF-α-238 site and the onset of AS but the G/G genotype of TNF-α-238 may increase the sicken risk of AS in Hunan population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".