Role of Beclin1 expression in patients with hepatocellular carcinoma: a meta-analysis
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
BACKGROUND AND AIM: Beclin1 has been reported as a vital marker for a number of malignant tumors. However, the role of Beclin1 in hepatocellular carcinoma (HCC) remains inconclusive. Thus, we conducted a meta-analysis to assess the correlation between Beclin1 and its clinicopathological and prognostic values in HCC. METHODS: PubMed, Cochrane Library, Web of Science, EMBASE, Chinese CNKI, and Chinese WanFang databases were searched for published articles on Beclin1 expression in hepatocellular tissues. Standard-compliant articles were screened using the Newcastle-Ottawa Scale for strict quality control of the literature. The correlation of Beclin1 expression with the clinicopathological features and survival outcomes was analyzed. Pooled odds ratios and hazard ratios with 95% confidence intervals were calculated using STATA14.2. RESULTS: Eleven articles with 1,279 patients were included in this meta-analysis. Positive Beclin1 expression was found to be correlated with alpha fetoprotein, liver cirrhosis, and vascular invasion, but not with gender, age, HBsAg, size of tumor, number of tumors, differentiation, and TNM stage. Positive Beclin1 expression was also associated with favorable 5-year overall survival and disease-free survival rates. CONCLUSION: Our meta-analysis indicated that positive Beclin1 expression was negatively related to alpha fetoprotein, liver cirrhosis, and vascular invasion in HCC. Beclin1 could be used as a prognostic biomarker for HCC.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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