Genetic Polymorphism of Nogo Gene in Han Chinese of Chengdu and Thai Populations
Bibliographic record
Abstract
Neurite growth inhibitor(Nogo) play a major role in inhibiting axonal regeneration in the central nervous system.TATA and CAA insertion deletion polymorphism is related to risk of chronic schizophrenia.RTN4 genotype and allele frequency distribution is differences in various ethnic.The genotypes and allele frequencies of Nogo gene TATC deletion and CAA insertion were analyzed in 205 healthy Han Chinese of Chengdu and 101 Thai individuals using polymerase chain reaction-polyacrylamide gel electrophoresis strat-egy and DNA sequencing.The frequency of the(TATC)2(TATC)2 genotype of TATA deletion was 10.2% in Han Chinese of Chengdu,which was significantly lower than that in Thai population.The frequency of the(TATC)2 allele was 34.9% in Han Chinese of Chengdu,which was significantly lower than that in Thai popu-lation as well.However,there was no significant difference in the genotype and allele frequency of CAA in-sertion between Han Chinese of Chengdu and Thai population.Additionally,the frequency of(TATC)2 allele was significantly lower than that in French-Canadian and Tunisian,which was 45.0% and 49.0% respective-ly.The frequency of(CAA)2 allele was 66.8%,which was significantly higher than that in French-Canadian and Brazilian(53.0% and 37.8%,respectively).The results suggested that TATC deletion and CAA insertion of Nogo gene in diverse populations is significantly different.
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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".