CTNND<sub>1</sub> 755 T>G Promoter Polymorphism and Risk of Pancreatic Carcinoma in Chinese
Bibliographic record
Abstract
OBJECTIVE: gene, which is associated with the risk of pancreatic carcinoma in Chinese. METHODS: 755 T>G genotypes were determined by PCR-RFLP in 122 pancreatic carcinoma patients and 180 healthy controls matched for age and sex, who did not receive radiotherapy or chemotherapy for newly diagnosed and histopathologically confirmed pancreatic carcinoma. RESULTS: In control subjects, the frequency of T/T and G/T genotypes, and T and G alleles was 79.4%, 17.2%, 88.1%, and 11.9%, respectively. The distribution of genotypes and allelotypes in the pancreatic carcinoma patients was significantly different from that in the controls (P = 0.007, P = 0.012). Combined GG and GT genotypes were found to have a higher OR in male pancreatic carcinoma patients and the group under the age of 70 years (males: OR, 1.409; 95%CI, 0.912~1.921; under 70 years: OR 1.626; 95% CI, 0.878~2.312). This study also showed a distinct difference in the distribution of P120ctn and single nucleotide polymorphisms (SNPs) between Chinese and Canadian (11.9% vs. 3.9%, P = 0.008). CONCLUSION: promoter SNPs is diverse in ethnic populations.
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 | 0.000 | 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".