Very-Low-Dose Pegylated Interferon a2a Plus Ribavirin Therapy for Advanced Liver Cirrhosis Type C: A Possible Therapeutic Alternative without Splenic Intervention

Despite the recent progress in interferon (IFN) therapies for chronic hepatitis C, liver cirrhosis remains refractory. One of the major obstacles to successful IFN therapy is low platelet count. Currently, splenic interventions, such as partial splenic embolization (PSE) or surgical splenectomy, have been applied effectively and make standard IFN therapy possible. However, there may be a group of patients with low platelet counts who can be treated without splenic intervention. We here report two patients with advanced type C liver cirrhosis who were successfully treated using very-low-dose pegylated interferon a2a plus ribavirin. One patient had a very low platelet count (2.5 × 104/μl) due to splenomegaly before treatment. However, pretreatment serum HCV titers were low in both patients and early viral responses were obtained in both. Because PSE or splenectomy may still have some safety concerns, this attenuated IFN treatment protocol can be an alternative therapeutic option for patients with advanced type C liver disease, but good virological factors for sustained virological response

Intra-Abdominal Hypertension and Abdominal Compartment Syndrome in Liver Diseases

Intra-abdominal hypertension (IAH) is defined as an intra-abdominal pressure (IAP) above 12 mmHg. Abdominal compartment syndrome (ACS) is defined as an IAP above 20 mmHg with evidence of organ failure. Moreover, IAH/ACS is a condition that can cause acute renal failure, respiratory failure, circulatory disease, gastrointestinal dysfunction, and liver failure due to elevated IAP. The incidence of IAH/ACS increases in the more critically ill patient and is associated with significantly increased morbidity and mortality. Ascites, blood, or tumors increase IAP. In liver cirrhosis, massive ascites is often encountered. Hence, preventing IAH/ACS conditions may improve outcomes of patients with liver disease

DNA Damage Sensor γ

Background. Phosphorylated histone H2AX (γ-H2AX) is a potential regulator of DNA repair and is a useful tool for detecting DNA damage. To evaluate the clinical usefulness of γ-H2AX in hepatocellular carcinoma (HCC), we measured the level of γ-H2AX in HCC, dysplastic nodule, and nontumorous liver diseases. Methods. The level of γ-H2AX was measured by immunohistochemistry in fifty-eight HCC, 18 chronic hepatitis, 22 liver cirrhosis, and 19 dysplastic nodules. Appropriate cases were also examined by fluorescence analysis and western blotting. Results. All cases with chronic liver disease showed increased levels of γ-H2AX expression. In 40 (69.9%) of 58 cases with HCC, the labeling index (LI) of γ-H2AX was above 50% and was inversely correlated with the histological grade. Mean γ-H2AX LI was the highest in dysplastic nodule (74.1±22.1%), which was significantly higher than HCC (P<0.005). Moreover, γ-H2AX was significantly increased in nontumorous tissues of HCC as compared with liver cirrhosis without HCC (62.5±24.7%, from 5.1 to 96.0%, P<0.005). Conclusions. γ-H2AX was increased in the preneoplastic lesions of HCC and might be a useful biomarker for predicting the risk of HCC

Radiotherapy using a laser proton accelerator

Laser acceleration promises innovation in particle beam therapy of cancer where an ultra-compact accelerator system for cancer beam therapy can become affordable to a broad range of patients. This is not feasible without the introduction of a technology that is radically different from the conventional accelerator-based approach. The laser acceleration method provides many enhanced capabilities for the radiation oncologist. It reduces the overall system size and weight by more than one order of magnitude. The characteristics of the particle beams (protons) make them suitable for a class of therapy that might not be possible with the conventional accelerator, such as the ease for changing pulse intensity, the focus spread, the pinpointedness, and the dose delivery in general. A compact, uncluttered system allows a PET device to be located in the vicinity of the patient in concert with the compact gantry. The radiation oncologist may be able to irradiate a localized tumor by scanning with a pencil-like particle beam while ascertaining the actual dosage in the patient with an improved in-beam PET verification of auto-radioactivation induced by the beam therapy. This should yield an unprecedented flexibility in the feedback radiotherapy by the radiation oncologist. Laser accelerated radiotherapy has a unique niche in a current world of high energy accelerator using synchrotron or cyclotron.Comment: 26 pages, 8 figures, 2 tables, 69 references. International Symposium on Laser-Driven Relativistic Plasmas Applied for Science, Industry and Medicine, Kyoto, Japan, 17-20 September (2007

Predicting Successful Throwing Technique in Judo from Factors of Kumite Posture Based on a Machine-Learning Approach

Identifying the key points of a movement performed by an expert is required for beginners who want to acquire a motor skill. By repeating a learning cycle, the beginner tries the movement, focusing on the key points. We can find many guiding methods for adopting motor skills in the fields of coaching and training for sports. However, the methods strongly depend on the experience of trainers and coaches, who need to select the appropriate methods for different types of athletes. Although methods based on objective information obtained from videos and sensors applicable to individual movements have been proposed in order to overcome the subjectivity of these approaches, we cannot apply those to movements that include external factors, such as pushing and/or attacks from an opponent, as seen in combat sports. Furthermore, such sports require fast feedback of the analysis to the athletes in order to find the key factors of offensive/defensive techniques at the training site. Focusing on judo throwing techniques, this paper proposes a novel real-time prediction method called RT-XSM (Real-Time Extraction method for Successful Movements) that predicts which throwing technique is most likely to be successful based on Kumite posture just before the throw. The RT-XSM uses logistic regression to analyze datasets consisting of the factors of Kumite posture (a standing posture when both players grip each other) and throwing technique classification. To validate the proposed method, this paper also demonstrates experiments of the RT-XSM using datasets acquired from video scenes of the World Judo Championships

Statistical Extraction Method for Revealing Key Factors from Posture before Initiating Successful Throwing Technique in Judo

Many methods such as biomechanics and coaching have been proposed to help people learn a certain movement. There have been proposals for methods to discover characteristics of movement based on information obtained from videos and sensors. Especially in sports, it is expected that these methods can provide hints to improve movement skills. However, conventional methods focus on individual movements, and do not consider cases where external factors influence the movement, such as combat sports. In this paper, we propose a novel method called the Extraction for Successful Movement method (XSM method). Applying the method, this paper focuses on throwing techniques in judo to discover key factors that induce successful throwing from the postures right before initiating the throwing techniques. We define candidate factors by observing the video scenes where the throwing techniques are successfully performed. The method demonstrates the significance of the key factors according to the predominance of factors by χ2 test and residual analysis. Applying the XSM method to the dataset obtained from the videos of the Judo World Championships, we demonstrate the validity of the method with discussing the key factors related to the successful throwing techniques

Predicting Successful Throwing Technique in Judo from Factors of Kumite Posture Based on a Machine-Learning Approach

Identifying the key points of a movement performed by an expert is required for beginners who want to acquire a motor skill. By repeating a learning cycle, the beginner tries the movement, focusing on the key points. We can find many guiding methods for adopting motor skills in the fields of coaching and training for sports. However, the methods strongly depend on the experience of trainers and coaches, who need to select the appropriate methods for different types of athletes. Although methods based on objective information obtained from videos and sensors applicable to individual movements have been proposed in order to overcome the subjectivity of these approaches, we cannot apply those to movements that include external factors, such as pushing and/or attacks from an opponent, as seen in combat sports. Furthermore, such sports require fast feedback of the analysis to the athletes in order to find the key factors of offensive/defensive techniques at the training site. Focusing on judo throwing techniques, this paper proposes a novel real-time prediction method called RT-XSM (Real-Time Extraction method for Successful Movements) that predicts which throwing technique is most likely to be successful based on Kumite posture just before the throw. The RT-XSM uses logistic regression to analyze datasets consisting of the factors of Kumite posture (a standing posture when both players grip each other) and throwing technique classification. To validate the proposed method, this paper also demonstrates experiments of the RT-XSM using datasets acquired from video scenes of the World Judo Championships