A unique bleeding-related complication of sorafenib, a tyrosine kinase inhibitor, in advanced hepatocellular carcinoma: a case report

INTRODUCTION: Sorafenib, a multikinase inhibitor as a standard of care for advanced hepatocellular carcinoma, may lead endothelial cells to an unstable state by blocking the signaling pathway of vascular endothelial growth factor receptor, which may result in the disruption of the architecture and integrity of the microvasculature, and eventually increase the risk of hemorrhage. Hemobilia is a relatively uncommon condition as a consequence of hepatocellular carcinoma and its risk factors remain uncertain. CASE PRESENTATION: Here we report a unique case of hemobilia occurring in a 55-year-old Korean man with hepatitis B virus-related hepatocellular carcinoma on Barcelona Clinic Liver Cancer advanced stage after seven days of treatment with sorafenib. He had received prior radiation therapy. Endoscopy revealed bleeding from the major duodenal papilla and endoscopic retrograde cholangiography revealed an amorphous filling defect throughout the common bile duct. Blood clots were removed by balloon sweeping and a nasobiliary drainage tube was placed. No further bleeding has been detected as of eight months after discontinuation of sorafenib. CONCLUSION: Sorafenib may increase the risk of biliary bleeding in hepatocellular carcinoma patients who were primed with irradiation, by blocking the signaling pathway of the vascular endothelial growth factor receptor. Therefore, sorafenib should be used with caution in patients with advanced hepatocellular carcinoma, especially when combined with radiation therapy

Improving Neural Radiance Field using Near-Surface Sampling with Point Cloud Generation

Neural radiance field (NeRF) is an emerging view synthesis method that samples points in a three-dimensional (3D) space and estimates their existence and color probabilities. The disadvantage of NeRF is that it requires a long training time since it samples many 3D points. In addition, if one samples points from occluded regions or in the space where an object is unlikely to exist, the rendering quality of NeRF can be degraded. These issues can be solved by estimating the geometry of 3D scene. This paper proposes a near-surface sampling framework to improve the rendering quality of NeRF. To this end, the proposed method estimates the surface of a 3D object using depth images of the training set and sampling is performed around there only. To obtain depth information on a novel view, the paper proposes a 3D point cloud generation method and a simple refining method for projected depth from a point cloud. Experimental results show that the proposed near-surface sampling NeRF framework can significantly improve the rendering quality, compared to the original NeRF and a state-of-the-art depth-based NeRF method. In addition, one can significantly accelerate the training time of a NeRF model with the proposed near-surface sampling framework.Comment: 13 figures, 2 table

Physiological responses of two halophytic grass species under drought stress environment

The physiological responses of two halophytic grass species, Halopyrum mucronatum (L.) Staph. and Cenchrus ciliaris (L.), under drought stress were evaluated. Biomass accumulation, relative water content, free proline, H2O2 content, stomatal conductance, photosynthetic performance and quantum yield (Fv/Fm ratio) were studied. Under drought conditions, these halophytic plants expressed differential responses to water defi cit. Stomatal conductance and free proline content were higher in H. mucronatum than in C. ciliaris, while H2O2 content in H. mucronatum was substantially lower than in C. ciliaris. Performance index showed considerable sensitivity to a water deficit condition, more so in C. ciliaris than in H. mucronatum. Results were discussed in relation to comparative physiological performance and antioxidant enzymes activity of both halophytic grasses under drought stress