Pharmacological Characteristics and Clinical Applications of K201

K201 is a 1,4-benzothiazepine derivative that is a promising new drug with a strong cardioprotective effect. We initially discovered K201 as an effective suppressant of sudden cardiac cell death due to calcium overload. K201 is a nonspecific blocker of sodium, potassium and calcium channels, and its cardioprotective effect is more marked than those of nicorandil, prazosine, propranolol, verapamil and diltiazem. Recently, K201 has also been shown to have activities indicated for treatment of atrial fibrillation, ventricular fibrillation, heart failure and ischemic heart disease, including action as a multiple-channel blocker, inhibition of diastolic Ca2+ release from the sarcoplasmic reticulum, suppression of spontaneous Ca2+ sparks and Ca2+ waves, blockage of annexin V and provision of myocardial protection, and improvement of norepinephrine-induced diastolic dysfunction. Here, we describe the pharmacological characteristics and clinical applications of K201

Visualization and unsupervised clustering of emphysema progression using t-SNE analysis of longitudinal CT images and SNPs

Chronic obstructive pulmonary disease (COPD) is predicted to become the third leading cause of death worldwide by 2030. A longitudinal study using CT scans of COPD is useful to assess the changes in structural abnormalities. In this study, we performed visualization and unsupervised clustering of emphysema progression using t-distributed stochastic neighbor embedding (t-SNE) analysis of longitudinal CT images, smoking history, and SNPs. The procedure of this analysis is as follows: (1) automatic segmentation of lung lobes using 3D U-Net, (2) quantitative image analysis of emphysema progression in lung lobes, and (3) visualization and unsupervised clustering of emphysema progression using t-SNE. Nine explanatory variables were used for the clustering: genotypes at two SNPs (rs13180 and rs3923564), smoking history (smoking years, number of cigarettes per day, pack-year), and LAV distribution (LAV size and density in upper lobes, LAV size, and density in lower lobes). The objective variable was emphysema progression which was defined as the annual change in low attenuation volume (LAV%/year) using linear regression. The nine-dimensional space was transformed to two-dimensional space by t-SNE, and divided into three clusters by Gaussian mixture model. This method was applied to 37 smokers with 68.2 pack-years and 97 past smokers with 51.1 pack-years. The results demonstrated that this method could be effective for quantitative assessment of emphysema progression by SNPs, smoking history, and imaging features

Association analysis of SNPs with CT image-based phenotype of emphysema progression in heavy smokers

Chronic obstructive pulmonary disease (COPD) is predicted to become the third leading cause of death worldwide by 2030. Smoking is a well-known risk factor in the development of COPD. Association between COPD genes and smoking have been studied. This paper presents an association analysis of single nucleotide polymorphisms (SNPs) with a CT image-based phenotype of emphysema progression in heavy smokers. The emphysema progression was quantitatively represented by the annual increment of low attenuation volume (LAV) on CT scans for five years. 10 candidate SNPs were selected from 316 SNPs in 125 papers of genetic studies of COPD and lung cancer. The genotypes were determined by real-time polymerase chain reaction (PCR) using deoxyribonucleic acid (DNA) extracted from saliva samples. The association analysis was performed by Fisher's exact test and logistic regression analysis. This method was applied to a dataset with 144 participants (71 smokers, 61 past smokers, and 12 non-smokers). The results showed that the genotypes of rs3923564 and rs13180 SNPs were candidate SNPs associated with the CT image based-emphysema progression

Automated Assessment of Aortic and Main Pulmonary Arterial Diameters using Model-Based Blood Vessel Segmentation for Predicting Chronic Thromboembolic Pulmonary Hypertension in Low-Dose CT Lung Screening

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by obstruction of the pulmonary vasculature by residual organized thrombi. A morphological abnormality inside mediastinum of CTEPH patient is enlargement of pulmonary artery. This paper presents an automated assessment of aortic and main pulmonary arterial diameters for predicting CTEPH in low-dose CT lung screening. The distinctive feature of our method is to segment aorta and main pulmonary artery using both of prior probability and vascular direction which were estimated from mediastinal vascular region using principal curvatures of four-dimensional hyper surface. The method was applied to two datasets, 64 low-dose CT scans of lung cancer screening and 19 normal-dose CT scans of CTEPH patients through the training phase with 121 low-dose CT scans. This paper demonstrates effectiveness of our method for predicting CTEPH in low-dose CT screening

Segmentation of aorta and main pulmonary artery of non-contrast CT images using U-Net for chronic thromboembolic pulmonary hypertension : evaluation of robustness to contacts with blood vessels

Enlargement of the pulmonary artery is a morphological abnormality of pulmonary hypertension patients. Diameters of the aorta and main pulmonary artery (MPA) are useful for predicting the presence of pulmonary hypertension. A major problem in the automatic segmentation of the aorta and MPA from non-contrast CT images is the invisible boundary caused by contact with blood vessels. In this study, we applied U-Net to the segmentation of the aorta and MPA from non-contrast CT images for normal and chronic thromboembolic pulmonary hypertension (CTEPH) cases and evaluated the robustness to the contacts between blood vessels. Our approach of the segmentation consists of three steps: (1) detection of trachea branch point, (2) cropping region of interest centered to the trachea branch point, and (3) segmentation of the aorta and MPA using U-Net. The segmentation performances were compared in seven methods: 2D U-Net, 2D U-Net with pre-trained VGG-16 encoder, 2D U-Net with pre-trained VGG-19 encoder, 2D Attention U-Net, 3D U-Net, an ensemble method of them, and our conventional method. The aorta and MPA segmentation methods using these U-Net achieved higher performance than a conventional method. Although the contact boundaries of blood vessels caused lower performance compared with the non-contact boundaries, the mean boundary distances were below about one pixel

Diving behavior in Anopheles gambiae (Diptera: Culicidae): avoidance of a predacious wolf spider (Araneae: Lycosidae) in relation to life stage and water depth.

It has been suggested that mosquito larvae and pupae dive to avoid predators. We tested this predator-avoidance hypothesis by using immature Anopheles gambiae Giles (Diptera: Culicidae) and the wolf spider Pardosa messingerae (Stand) (Araneae: Lycosidae). Because previous studies have suggested that wolf spiders are poor predators of immature mosquitoes, we first examined the predatory ability of the wolf spider and found that the spider was effective at capturing all stages of larvae and pupae. The mortality from experimental cups containing deep water increased with the age of mosquitoes, with the exception of pupae. In contrast, this trend was not observed in shallow water. In particular, mortality was significantly lower in deep water during the second instar. During the third instar, the opposite trend was observed. When the effect of cannibalism was excluded by subtracting the number of missing mosquitoes for the treatment without spiders from those with spiders, the cannibalism corrected mortality was significantly lower in deep water during the second instar. The duration of diving by larvae and pupae decreased with age. With the exception of first instar, diving frequency also decreased with age. We postulate that this diving behavior allows An. gambiae to escape predation by wolf spiders, which supports the predator-avoidance hypothesis. This study indicates some important implications for vector control

Sleeping arrangement and house structure affect bed net use in villages along Lake Victoria

<p>Abstract</p> <p>Background</p> <p>Although insecticide-treated bed nets are effective tools, use often does not follow ownership. House structure and space arrangements may make the attempt to use bed nets difficult, especially for school age children. The objectives of this study were to explore whether an individual's sleeping arrangements and house structure affect bed net use in villages along Lake Victoria in western Kenya.</p> <p>Methods</p> <p>Sleeping arrangements of residents were directly observed for use of a bed net, use of a bed, and location. House size, number and types of rooms, bed availability, and residents' ages were estimated. The family heads and mothers were asked about the reason for not using bed nets. Individual bed net use was examined against age and sleeping arrangement. Net use at the household level was examined against four variables: bed availability, bed net availability, house size, and number of rooms.</p> <p>Results</p> <p>Bed net use by children between five and 15 years of age was lower than that among the other age classes. However, age was dropped from the final model, and sleeping arrangement was significantly associated with net use. Net use was significantly associated with bed availability, number of rooms and their interaction.</p> <p>Conclusion</p> <p>Net use was affected by sleeping arrangement and availability of suitable locations for hanging nets, in addition to net availability. Most residents had likely not realized that sleeping arrangement was a factor in net use. The ease of hanging a net is particularly important for children.</p

An automated distinction of DICOM image for lung cancer CAD system

Automated distinction of medical images is an important preprocessing in Computer-Aided Diagnosis (CAD) systems. The CAD systems have been developed using medical image sets with specific scan conditions and body parts. However, varied examinations are performed in medical sites. The specification of the examination is contained into DICOM textual meta information. Most DICOM textual meta information can be considered reliable, however the body part information cannot always be considered reliable. In this paper, we describe an automated distinction of DICOM images as a preprocessing for lung cancer CAD system. Our approach uses DICOM textual meta information and low cost image processing. Firstly, the textual meta information such as scan conditions of DICOM image is distinguished. Secondly, the DICOM image is set to distinguish the body parts which are identified by image processing. The identification of body parts is based on anatomical structure which is represented by features of three regions, body tissue, bone, and air. The method is effective to the practical use of lung cancer CAD system in medical sites