Expression of DBC1 and SIRT1 Is Associated with Poor Prognosis of Gastric Carcinoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: SIRT1 (silent mating-type information regulation 2 homologue 1) expression has been reported to predict poor survival in some cancers. We therefore investigated the expression levels of SIRT1 and its negative regulator, DBC1 (deleted in breast cancer 1), in gastric cancer patients. EXPERIMENTAL DESIGN: We evaluated immunohistochemical expression of DBC1, SIRT1, and p53 using 3-mm tumor cores from 177 gastric cancer patients for tissue microarray. RESULTS: Positive expressions of DBC1 and SIRT1 were seen in 62% (109 of 177) and in 73% (130 of 177) of patients, respectively. Expression of DBC1 was significantly correlated with tumor stage (P = 0.007), lymph node metastasis (P < 0.001), tumor invasion (P = 0.001), venous invasion (P = 0.001), histologic types (P < 0.001), p53 expression (P < 0.001), and SIRT1 expression (P < 0.001). SIRT1 expression was also significantly correlated with tumor stage (P < 0.001), lymph node metastasis (P < 0.001), tumor invasion (P < 0.001), histologic types (P < 0.001), and p53 expression (P = 0.001). In addition, expression of DBC1 was significantly associated with shorter overall survival and relapse-free survival by univariate analysis (P < 0.001 and P < 0.001, respectively). SIRT1 expression was also significantly associated with shorter overall survival and relapse-free survival by univariate analysis (P = 0.001 and P = 0.001, respectively). Multivariate analysis showed that tumor stage and expression of DBC1 were independent prognostic factors significantly associated with overall survival and relapse-free survival. CONCLUSION: This study shows that expression of DBC1 and SIRT1 is a significant prognostic indicator for gastric carcinoma patients.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it