3D Cascaded U-Net with a Squeeze-and-Exicitation Block for Semantic Segmentation on Kidney and Renal Cell Carcinoma in Abdonimal Volumetric CT

Segmentation is a fundamental process in medical image analysis. Recently, convolutional neural networks (CNNs) has allowed for automatic segmentation; however, segmentaiton of complex organs and diseases including the kidney or renal cell carcinoma (RCC) remains a different task due to limited data and labor-intensive labeling work. The purpose of this study is to segment kideny and RCC in CT using cascaded 3D U-Net with a squeeze-and-excitation (SE) block using a cascaded method. 210 kidneys and their RCC in abdominal CT images were used as training and validation sets. The Dice similarity coefficients (DSCs) of kidney and RCC in test set were 0.963 and 0.734 respectively. The cascaded semantic segmentation can potentially reduce segmentation efforts and increase the efficiency in clinical workflow

Contribution of Cell Elongation to the Biofilm Formation of Pseudomonas aeruginosa during Anaerobic Respiration

Pseudomonas aeruginosa, a gram-negative bacterium of clinical importance, forms more robust biofilm during anaerobic respiration, a mode of growth presumed to occur in abnormally thickened mucus layer lining the cystic fibrosis (CF) patient airway. However, molecular basis behind this anaerobiosis-triggered robust biofilm formation is not clearly defined yet. Here, we identified a morphological change naturally accompanied by anaerobic respiration in P. aeruginosa and investigated its effect on the biofilm formation in vitro. A standard laboratory strain, PAO1 was highly elongated during anaerobic respiration compared with bacteria grown aerobically. Microscopic analysis demonstrated that cell elongation likely occurred as a consequence of defective cell division. Cell elongation was dependent on the presence of nitrite reductase (NIR) that reduces nitrite (NO2−) to nitric oxide (NO) and was repressed in PAO1 in the presence of carboxy-PTIO, a NO antagonist, demonstrating that cell elongation involves a process to respond to NO, a spontaneous byproduct of the anaerobic respiration. Importantly, the non-elongated NIR-deficient mutant failed to form biofilm, while a mutant of nitrate reductase (NAR) and wild type PAO1, both of which were highly elongated, formed robust biofilm. Taken together, our data reveal a role of previously undescribed cell biological event in P. aeruginosa biofilm formation and suggest NIR as a key player involved in such process

Rapid and label-free amplification and detection assay for genotyping of cancer biomarker

10.1016/j.bios.2014.12.039Biosensors and Bioelectronics68107-11

HCCMeshes: Hierarchical-Culling oriented Compact Meshes

Hierarchical culling is a key acceleration technique used to efficiently handle massive models for ray tracing, collision detection, etc. To support such hierarchical culling, bounding volume hierarchies (BVHs) combined with meshes are widely used. However, BVHs may require a very large amount of memory space, which can negate the benefits of using BVHs. To address this problem, we present a novel hierarchical-culling oriented compact mesh representation, HCCMesh, which tightly integrates a mesh and a BVH together. As an in-core representation of the HCCMesh, we propose an i-HCCMesh representation that provides an efficient random hierarchical traversal and high culling efficiency with a small runtime decompression overhead. To further reduce the storage requirement, the in-core representation is compressed to our out-of-core representation, o-HCCMesh, by using a simple dictionary-based compression method. At runtime, o-HCCMeshes are fetched from an external drive and decompressed to the i-HCCMeshes stored in main memory. The i-HCCMesh and o-HCCMesh show 3.6:1 and 10.4:1 compression ratios on average, compared to a naively compressed (e.g., quantized) mesh and BVH representation. We test the HCCMesh representations with ray tracing, collision detection, photon mapping, and non-photorealistic rendering. Because of the reduced data access time, a smaller working set size, and a low runtime decompression overhead, we can handle models ten times larger in commodity hardware without the expensive disk I/O thrashing. When we avoid the disk I/O thrashing using our representation, we can improve the runtime performances by up to two orders of magnitude over using a naively compressed representation.X1146sciescopu

Fully automated, on-site isolation of cfDNA from whole blood for cancer therapy monitoring

The potential utility of circulating tumour DNA (ctDNA) in patient blood for cancer diagnostics and real-time monitoring of disease progression is highly recognized. However, the lack of automated and efficient methods for cell-free DNA (cfDNA) isolation from peripheral blood has remained a challenge for broader acceptance of liquid biopsy in general clinical settings. Here, we demonstrate a lab-on-a-disc system equipped with newly developed, electromagnetically actuated, and reversible diaphragm valves that allows fully automated and rapid (<30 min) isolation of cfDNA from whole blood (>3 ml) to achieve high detection sensitivity by minimizing the degradation of fragile ctDNA as well as contamination of wild-type DNA from abundant blood cells. As a proof of concept study, we used the lab-on-a-disc to isolate cfDNA from patients with non-small cell lung cancer and successfully detected epidermal growth factor receptor gene mutations (L858R, T790M) during targeted drug therapy. The proposed lab-on-a-disc enables a fully automated, rapid, and point-of-care cfDNA enrichment starting from whole blood to facilitate the wide use of liquid biopsy in routine clinical practice