HepG2BD: A Novel and Versatile Cell Line with Inducible HDV Replication and Constitutive HBV Expression
Bibliographic record
Abstract
Individuals chronically infected with hepatitis B virus (HBV) and hepatitis Delta virus (HDV) present an increased risk of developing cirrhosis and hepatocellular carcinoma in comparison to HBV mono-infected individuals. Although HDV only replicates in individuals coinfected or superinfected with HBV, there is currently no in vitro model that can stably express both viruses simultaneously, mimicking the chronic infections seen in HBV/HDV patients. Here, we present the HepG2BD cell line as a novel in vitro culture system for long-term replication of HBV and HDV. HepG2BD cells derive from HepG2.2.15 cells in which a 2 kb HDV cDNA sequence was inserted into the adeno-associated virus safe harbor integration site 1 (AAVS1) using CRISPR-Cas9. A Tet-Off promoter was placed 5' of the genomic HDV sequence for reliable initiation/repression of viral replication and secretion. HBV and HDV replication were then thoroughly characterized. Of note, non-dividing cells adopt a hepatocyte-like morphology associated with an increased production of both HDV and HBV virions. Finally, HDV seems to negatively interfere with HBV in this model system. Altogether, HepG2BD cells will be instrumental to evaluate, in vitro, the fundamental HBV-HDV interplay during simultaneous chronic replication as well as for antivirals screening targeting both viruses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".