The significance of Toll-like receptor 4 (TLR4) expression in patients with chronic hepatitis B
Bibliographic record
Abstract
PURPOSE: To investigate the importance of Toll-like receptor 4 (TLR4) expression on hepatocytes obtained from Chronic Hepatitis B patients as well as on hepatocellular carcinoma HepG2 and HepG2.2.15 cell lines. METHODS: Expression of TLR4 in liver tissues was determined by immunohistochemistry in 75 patients with CHB and in10 healthy controls. The protein and mRNA 1eve1s of TLR4 in hepatocellular carcinoma HepG2 and HepG2.2.15 cells were measured by flow cytometry (FCM) and real-time quantitative PCR (RQ-PCR), and endotoxin triggered TNF-alpha secretion in HepG2 and HepG2.2.15 cells was evaluated by ELISA. RESULTS: TLR4 expressed mainly in the cytoplasm and some on cell membrane in hepatocytes. The staining scores of TLR4 expression in the liver tissues of patients with CHB were significantly higher than that of healthy controls. The liver tissues from patients with severe CHB expressed higher level of TLR4 than those from patients with mild CHB. Furthermore, the staining scores of TLR4 expression in the liver tissues of patients with CHB were positively correlated with the grading scores. Our results also showed that the mean fluorescence intensity and TNF-alpha secretion induced by endotoxin as well as the protein and mRNA 1eve1s of TLR4 in HepG2.2.15 cells were all significantly higher than those in HepG2 cells. CONCLUSION: TLR4 was up-regulated in the hepatocytes in patients with CHB. This indicates a potentially important interaction between TLR4 expression and the pathogenesis of CHB.
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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 | 0.000 |
| 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) | 0.002 | 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".