Lgr5 Contributes to Intestinal Metaplasia During Gastric Carcinogenesis: A Meta analysis
Bibliographic record
Abstract
Lgr5, which is a somatic stem cell biomarker, plays an important role during the carcinogenesis and tumor progression. But in gastric cancer, the functions of Lgr5 still remain controversial. Our meta-analysis is performed to evaluate the potential associations between Lgr5 and the outcome of patients with gastric cancer (GC). In our study, a total of 6 studies comprising 1092 patients were included. Our results demonstrated that high expression of Lgr5 was not associated to the depth of tumor invasion (pooled OR=1.395, CI95%=0.652-2.958, P=0.392, random-effect), gender of patients (pooled OR=1.264, 95%CI=0.933-1.713, P=0.13, fixed effect), tumor distance metastasis (pooled OR=1.1, 95%CI=0.734-3.754, P=0.772, random-effect), tumor size (pooled OR=0.977, 95%CI=0.705-1.353, P=0.887, random-effect), TNM stages (pooled OR=1.304, 95%CI=0.449-3.789, p=0.625, random-effect) and lymph node metastasis (pooled OR=1.507, 95%CI=0.829-2.738, P=0.178, random-effect). But interestingly, the expression of Lgr5 was associated with the age of GC patients (pooled OR=1.731, 95%CI=1.082-2.769, P=0.02) and Lauren type of GC (OR=2.284, 95%CI=1.611-3.238, P<0.001). Our findings indicated that Lgr5 might contribute to the intestinal metaplasia during gastric carcinogenesis. This difference in pathological Lauren's classification is of practical significance for us to make about appropriate treatment options in gastric cancer.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.031 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".