You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

Background & Aims: Chronic hepatitis B is an incurable disease. Addressing the unmet medical need for therapies has been hampered by a lack of suitable cell culture models to investigate the HBV life cycle in a single experimental setup. We sought to develop a platform suitable to investigate all aspects of the entire HBV life cycle. Methods: HepG2-NTCPsec+ cells were inoculated with HBV. Supernatants of infected cells were transferred to naive cells. Inhibition of infection was determined in primary and secondary infected cells by high-content imaging of viral and cellular factors. Novel antivirals were triaged in cells infected with cell culture- or patient-derived HBV and in stably virus replicating cells. HBV internalisation and target-based receptor binding assays were conducted. Results: We developed an HBV platform, screened 2,102 drugs and bioactives, and identified 3 early and 38 late novel HBV life cycle inhibitors using infectious HBV genotype D. Two early inhibitors, pranlukast (EC50 4.3 muM; 50% cytotoxic concentration [CC50] >50 muM) and cytochalasin D (EC50 0.07 muM; CC50 >50 muM), and 2 late inhibitors, fludarabine (EC50 0.1 muM; CC50 13.4 muM) and dexmedetomidine (EC50 6.2 muM; CC50 >50 muM), were further investigated. Pranlukast inhibited HBV preS1 binding, whereas cytochalasin D prevented the internalisation of HBV. Fludarabine inhibited the secretion of HBV progeny DNA, whereas dexmedetomidine interfered with the infectivity of HBV progeny. Patient-derived HBV genotype C was efficiently inhibited by fludarabine (EC50 0.08 muM) and dexmedetomidine (EC50 8.7 muM). Conclusions: The newly developed high-content assay is suitable to screen large-scale drug libraries, enables monitoring of the entire HBV life cycle, and discriminates between inhibition of early and late viral life cycle events. Lay summary: HBV infection is an incurable, chronic disease with few available treatments. Addressing this unmet medical need has been hampered by a lack of suitable cell culture models to study the entire viral life cycle in a single experimental setup. We developed an image-based approach suitable to screen large numbers of drugs, using a cell line that can be infected by HBV and produces large amounts of virus particles. By transferring viral supernatants from these infected cells to uninfected target cells, we could monitor the entire viral life cycle. We used this system to screen drug libraries and identified novel anti-HBV inhibitors that potently inhibit HBV in various phases of its life cycle. This assay will be an important new tool to study the HBV life cycle and accelerate the development of novel therapeutic strategies.
["Mechanism", "Treatment"]