Significant association of caveolin-1 single nucleotide polymorphisms with childhood leukemia in Taiwan.
Bibliographic record
Abstract
BACKGROUND: A growing body of evidence indicates that caveolin-1 (CAV1) may influence the development of human cancer. However, the exact role of CAV1 in childhood leukemia is still controversial. We investigated six novel polymorphic variants of CAV1, namely C521A (rs1997623), G14713A (rs3807987), G21985A (rs12672038), T28608A (rs3757733), T29107A (rs7804372), and G32124A (rs3807992), and analyzed the association of each specific genotype with susceptibility to childhood leukemia. MATERIALS AND METHODS: In total, 266 patients with childhood leukemia and 266 age-matched healthy controls, recruited from two major medical centers in Taiwan, were genotyped investigating the association of these polymorphisms with childhood leukemia. RESULTS: We found that there were significant differences between childhood leukemia and control groups in the distributions of their genotypes (p=4.1×10(-8) and 0.0167) and allelic frequencies (p=4.9×10(-10) and 3.7×10(-3)) in the CAV1 G14713A and T29107A polymorphisms, respectively. As for the haplotype analysis, those who had GG/AT or GG/AA at CAV1 G14713A/T29107A had a reduced risk of childhood leukemia compared to those with GG/TT, while those with any other combinations were at increased risk. CONCLUSION: The A allele of CAV1 G14713A is risky, while the A allele of CAV1 T29107A is protective for the development of childhood leukemia and these may be novel useful genomic markers for the early detection of childhood leukemia.
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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 | 0.000 | 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".