Global DNA 5hmC and CK195hmC+ Contents: A Promising Biomarker for Predicting Prognosis in Small Hepatocellular Carcinoma
Bibliographic record
Abstract
Background: 5-Hydroxymethylcytosine (5hmC) with dynamic existence possesses multiple regulatory functions. Whereas, 5hmC’s impact on small hepatocellular carcinoma (SHCC) remains unclear. The present work focused on characterizing 5hmC content within SHCC and assessing the possibility of using global genomic 5hmC level as the predicative factor of clinical outcome. Methods: This study applied ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) in measuring 5mC, 5fC and 5hmC contents. In addition, immunohistochemistry (IHC) was adopted to measure CK19 and 5hmC contents. Results: Research showed 5mC, 5hmC, and 5fC contents from global genomics of SHCC reduced extensively compared with healthy samples (p < 0.001). Moreover, SHCC was associated with lymph node metastasis (LNM). Greater 5mC and 5hmC levels were observed in non-metastasis group compared with the metastasis group (p < 0.001). Correlation analysis between the HBV DNA level and 5mC, 5fC and 5hmC levels exhibited that HBV DNA was associated with 5mC, 5hmC, and 5fC content reduction, which was verified in the cytological experiments. Moreover, 5hmC content had a negative correlation with the expression level of CK19 in SHCC. The decrease in 5hmC and CK19 containing 5hmC positive cell (called CK195hmC+) should be ascribed to the bad prognosis among SHCC patients. Conclusions: The contents of 5hmC and CK195hmC+ of genomic DNA might be adopted for predicting SHCC survival as an important biomarker.
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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 | 0.001 | 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 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".