RBPJ polymorphisms associated with cerebral infarction diseases in Chinese Han population
Bibliographic record
Abstract
TRIAL DESIGN: Cerebral small vessel diseases (CSVDs) are a group of brain pathological processes involving cerebral small arteries, brain venules, and capillaries. The recombination signal-binding protein Jκ (RBPJ) is implicated in the pathogenesis of these diseases but its actual roles need confirmation. The aim of this work was to evaluate variations in RBPJ gene for their possible associations with the disease. METHODS: The RBPJ gene was sequenced for 400 patients with cerebral infarction disease and 600 normal controls. The statistical analyses and Hardy-Weinberg equilibrium tests of the patients and control populations were conducted using the SPSS software (version 19.0) and Plink (version 1.9), Haploview software, and online software SNPSpD. RESULTS: We characterized variants rs2871198, rs1397731, rs3822223, rs2077777, rs2270226, and rs2788861 within or near the RBPJ gene. The genetic heterozygosity of rs2871198, rs1397731, rs3822223, rs2077777, and rs2270226 was very high. Statistical analysis showed that the variants rs2270226 and rs2077777 in the gene were associated with the risk of cerebral infarction diseases in the Chinese Han population. CONCLUSIONS: rs2270226 and rs2077777 in the RBPJ gene were associated with the risk of cerebral infarction diseases in the Chinese Han 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".