Bifidobacterium and Lactobacillus can beneficially affect the host by producing acetic acid and lactic acid, which lower pH and thereby inhibit the growth of pathogens or allow the probiotic bacteria to compete with pathogens for epithelial adhesion sites and nutrients. The transmural migration of enteric organisms into the peritoneal cavity can cause peritonitis in peritoneal dialysis (PD) patients. We hypothesized that the composition of the intestinal microbiota with regard to Lactobacillus species and Bifidobacterium species differed between PD patients and healthy controls. The aim of the study was to investigate these differences by real-time PCR analysis of fecal samples. There is a large, complex, and diverse microbial community in the human intestine. The intestinal microbiota plays an important role in digesting food, metabolizing endogenous and exogenous compounds, and producing essential vitamins. It also stimulates the immune system and prevents the colonization of the gastrointestinal tract by pathogens, and hence it influences human health (7, 9). The gastrointestinal microbiota of an adult human consists of more than 500 species, with 10 11 to 10 12 CFU per gram of stool (12,25). The predominant microorganisms are non-spore-forming, obligate anaerobes, such as Bacteroides, Fusobacterium, Eubacterium, and Bifidobacterium species. Other anaerobic bacteria found in large numbers include Lactobacillus species, various anaerobic Gram-positive cocci, and Clostridium species (4). Hida et al. studied the fecal flora of hemodialysis (HD) patients and healthy controls using traditional plating methods and found quantitative and qualitative differences between the two groups (13). It is plausible to suggest that the chronic inflammatory state in dialysis patients is in part due to a microbial imbalance in the gut, resulting in alteration of proinflammatory cytokines and production of uremic toxins from proteins fermented in the large intestine (16). Moreover, impaired intestinal barrier function in peritoneal dialysis (PD) patients allows enteric organisms to enter the peritoneal cavity by transmural migration and to cause peritonitis (8,27). Peritonitis occasionally causes death and results in significant morbidity, including catheter loss, transfer to hemodialysis, transient loss of ultrafiltration, and possible permanent membrane damage (22). Bifidobacterium and Lactobacillus can beneficially affect the host by inhibiting the growth of pathogens through production of acetic acid and lactic acid, which lower pH, or by competing with pathogens for epithelial adhesion sites and nutrients (10).To the best of our knowledge, no study has investigated the intestinal microbiota in PD patients before. The aim of this study, therefore, was to evaluate the differences in the intestinal microbiota between PD patients and healthy controls by examining fecal samples. We focused on Bifidobacterium species, Lactobacillus species, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterococcus species....

The purpose of this paper is to integrate the technologies of radio frequency identification, global positioning system, global system for mobile communications, and geographic information system (GIS) to construct a stray prevention system for elderly persons suffering from dementia without interfering with their activities of daily livings. We also aim to improve the passive and manpowered way of searching the missing patient with the help of the information technology. Our system provides four monitoring schemes, including indoor residence monitoring, outdoor activity area monitoring, emergency rescue, and remote monitoring modes, and we have developed a service platform to implement these monitoring schemes. The platform consists of a web service server, a database server, a message controller server, and a health-GIS (H-GIS) server. Family members or volunteer workers can identify the real-time positions of missing elderly using mobile phone, PDA, Notebook PC, and various mobile devices through the service platform. System performance and reliability is analyzed. Experiments performed on four different time slots, from three locations, through three mobile telecommunication companies show that the overall transaction time is 34 s and the average deviation of the geographical location is about 8 m. A questionnaire surveyed by 11 users show that eight users are satisfied with the system stability and 10 users would like to carry the locating device themselves, or recommend it to their family members.

Seismocardiogram (SCG) or mechanocardiography is a noninvasive cardiac diagnostic method; however, previous studies used only a single sensor to detect cardiac mechanical activities that will not be able to identify location-specific feature points in a cardiac cycle corresponding to the four valvular auscultation locations. In this study, a multichannel SCG spectrum measurement system was proposed and examined for cardiac activity monitoring to overcome problems like, position dependency, time delay, and signal attenuation, occurring in traditional single-channel SCG systems. ECG and multichannel SCG signals were simultaneously recorded in 25 healthy subjects. Cardiac echocardiography was conducted at the same time. SCG traces were analyzed and compared with echocardiographic images for feature point identification. Fifteen feature points were identified in the corresponding SCG traces. Among them, six feature points, including left ventricular lateral wall contraction peak velocity, septal wall contraction peak velocity, transaortic peak flow, transpulmonary peak flow, transmitral ventricular relaxation flow, and transmitral atrial contraction flow were identified. These new feature points were not observed in previous studies because the single-channel SCG could not detect the location-specific signals from other locations due to time delay and signal attenuation. As the results, the multichannel SCG spectrum measurement system can record the corresponding cardiac mechanical activities with location-specific SCG signals and six new feature points were identified with the system. This new modality may help clinical diagnoses of valvular heart diseases and heart failure in the future.

Gas bubbles induced during the radiofrequency ablation (RFA) of tissues can affect the detection of ablation zones (necrosis zone or thermal lesion) during ultrasound elastography. To resolve this problem, our previous study proposed ultrasound Nakagami imaging for detecting thermal-induced bubble formation to evaluate ablation zones. To prepare for future applications, this study (i) created a novel algorithmic scheme based on the frequency and temporal compounding of Nakagami imaging for enhanced ablation zone visualization, (ii) integrated the proposed algorithm into a clinical scanner to develop a real-time Nakagami imaging system for monitoring RFA, and (iii) investigated the applicability of Nakagami imaging to various types of tissues. The performance of the real-time Nakagami imaging system in visualizing RFA-induced ablation zones was validated by measuring porcine liver (n = 18) and muscle tissues (n = 6). The experimental results showed that the proposed algorithm can operate on a standard clinical ultrasound scanner to monitor RFA in real time. The Nakagami imaging system effectively monitors RFA-induced ablation zones in liver tissues. However, because tissue properties differ, the system cannot visualize ablation zones in muscle fibers. In the future, real-time Nakagami imaging should be focused on the RFA of the liver and is suggested as an alternative monitoring tool when advanced elastography is unavailable or substantial bubbles exist in the ablation zone.