Although dose prediction for intensity modulated radiation therapy (IMRT) has been accomplished by a deep learning approach, delineation of some structures is needed for the prediction. We sought to develop a fully automated dose-generation framework for IMRT of prostate cancer by entering the patient CT datasets without the contour information into a generative adversarial network (GAN) and to compare its prediction performance to a conventional prediction model trained from patient contours.

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Background: Area differences in life expectancy (LE) and healthy life expectancy (HLE) in large geographical units have been monitored around the world. Area characteristics may be based on culture, history, socioeconomic status and discrimination in smaller geographical units, so it is important to consider these when looking at health inequality. We aimed to evaluate LE, HLE, and non-healthy life expectancy (NHLE) in 1707 municipalities using Areal Deprivation Index (ADI) in Japan for the first time.Methods: We calculated the observed LE, HLE, and NHLE using death, population, and Long-term care insurance data for 2010-2014 and applied the variance weighted least squares model to estimate LE, HLE, and NHLE by 100 percentiles using the standardized ADI. Findings:The estimated LE, HLE, and NHLE became lower as the deprivation index worsened: the differences between the most and least deprived areas for HLE were 2 •49 years for LE and 2 •32 years for HLE in males; 1 •22 years for LE and 0 •93 years for HLE in females. The observed LE and HLE in the most deprived areas were much lower than other areas.Interpretation: Using ADI has enabled us to see the disparity within municipalities precisely. LE and HLE outlier for the 100th percentile might be linked to historical areal deprivation and marginalization. Precise monitoring of socioeconomic status-based health inequalities could help manage these inequalities by identifying the groups most in need of intervention.

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BackgroundViral capsid assembly involves the oligomerization of the capsid nucleoprotein (NP), which is an essential step in viral replication and may represent a potential antiviral target. An in vitro transcription-translation reaction using a wheat germ (WG) extract in combination with a sandwich ELISA assay has recently been used to identify small molecules with antiviral activity against the rabies virus.ResultsHere, we examined the application of this system to viruses with capsids with a different structure, such as the Rift Valley fever virus (RVFV), the etiological agent of a severe emerging infectious disease. The biochemical and immunological characterization of the in vitro-generated RVFV NP assembly products enabled the distinction between intermediately and highly ordered capsid structures. This distinction was used to establish a screening method for the identification of potential antiviral drugs for RVFV countermeasures.ConclusionsThese results indicated that this unique analytical system, which combines nucleoprotein oligomerization with the specific immune recognition of a highly ordered capsid structure, can be extended to various viral families and used both to study the early stages of NP assembly and to assist in the identification of potential antiviral drugs in a cost-efficient manner.ReviewersReviewed by Jeffry Skolnick and Noah Isakov. For the full reviews please go to the Reviewers’ comments section.Electronic supplementary materialThe online version of this article (doi:10.1186/s13062-016-0126-5) contains supplementary material, which is available to authorized users.