hepatitis b surface antigens
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2022 ◽  
Vol 11 (2) ◽  
pp. 387
Author(s):  
Hiroteru Kamimura ◽  
Hirofumi Nonaka ◽  
Masaya Mori ◽  
Taichi Kobayashi ◽  
Toru Setsu ◽  
...  

Deep learning is a subset of machine learning that can be employed to accurately predict biological transitions. Eliminating hepatitis B surface antigens (HBsAgs) is the final therapeutic endpoint for chronic hepatitis B. Reliable predictors of the disappearance or reduction in HBsAg levels have not been established. Accurate predictions are vital to successful treatment, and corresponding efforts are ongoing worldwide. Therefore, this study aimed to identify an optimal deep learning model to predict the changes in HBsAg levels in daily clinical practice for inactive carrier patients. We identified patients whose HBsAg levels were evaluated over 10 years. The results of routine liver biochemical function tests, including serum HBsAg levels for 1, 2, 5, and 10 years, and biometric information were obtained. Data of 90 patients were included for adaptive training. The predictive models were built based on algorithms set up by SONY Neural Network Console, and their accuracy was compared using statistical analysis. Multiple regression analysis revealed a mean absolute percentage error of 58%, and deep learning revealed a mean absolute percentage error of 15%; thus, deep learning is an accurate predictive discriminant tool. This study demonstrated the potential of deep learning algorithms to predict clinical outcomes.


2019 ◽  
pp. 1-3
Author(s):  
Samira Z A Eid ◽  
◽  
Nourtan F Abdeltawab ◽  
Samuel T Melek1 ◽  
Magdy A Amin ◽  
...  

Objectives: We aimed to studythe effect of Schsitosoma mansoni co-infection with hepatitis C virus (HCV) on IL-28B levels. Design: We collected plasma from107outpatients(range30–81 years old) from six governates of Delta, Egypt attending Kasr Al-Aini Hospital, Cairo, Egyptin 2012–2014. Subjects were divided to three groups, 35 healthy controls, 50naïve chronic HCV patientsand 22S. mansoni/HCVco-infected patients.For all participants,anti-schistosomal antibodies levels, hepatitis B surface antigens (HBsAg), HCV viral loadand routine liver function tests were measured. We assayed IL-28B and IFN-γ plasma levels for all participants. Results: We found that IL-28B levelsweresignificantly higher in S. mansoni/HCV co-infected patients than in HCV mono-infection. IFN-γ and IL-28B levels showed positive correlation in both infected groups. Patients with high HCV viral load had significantly higher IFN-γ and IL-28B levelswhether suffering from mono- or co-infection. Conclusions: A strong link between IFN-γ and IL-28B in naïve chronic HCV patients whether mono- or co-infected with S. mansoni. This suggeststhat co-infection with S. mansoni might not affect IFN-γ levels, however, significantly increases IL-28B levels. Therefore, IL-28B plasma levels might be a useful novel biomarker forprognosis and therapy ofS. mansoni/HCV co-infection


2014 ◽  
Vol 44 (7) ◽  
pp. 1981-1991 ◽  
Author(s):  
Petra Riedl ◽  
Michael Reiser ◽  
Katja Stifter ◽  
Jana Krieger ◽  
Reinhold Schirmbeck

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Carolina Alves ◽  
Cristina Branco ◽  
Celso Cunha

The hepatitis delta virus (HDV) is distributed worldwide and related to the most severe form of viral hepatitis. HDV is a satellite RNA virus dependent on hepatitis B surface antigens to assemble its envelope and thus form new virions and propagate infection. HDV has a small 1.7 Kb genome making it the smallest known human virus. This deceivingly simple virus has unique biological features and many aspects of its life cycle remain elusive. The present review endeavors to gather the available information on HDV epidemiology and clinical features as well as HDV biology.


Biologicals ◽  
2012 ◽  
Vol 40 (6) ◽  
pp. 445-450
Author(s):  
Kun-Teng Wang ◽  
Shu-Ching Weng ◽  
Ching-Pang Chou ◽  
Daniel Yang-Chih Shih ◽  
Chi-Fang Lo ◽  
...  

2012 ◽  
Vol 14 (3) ◽  
Author(s):  
Andrew M. Kilale ◽  
Nyagosya S. Range ◽  
Prosper H. Ngowi ◽  
Amos M. Kahwa ◽  
Sayoki G. Mfinanga

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