Antihypertensive Effect of Salt-Free Soy Sauce,a New Fermented Seasoning,in Spontaneously Hypertensive Rats

ABSTRACT: In this study, we focused on the antihypertensive effect of newly fermented salt-free soy sauce (SFS) in spontaneously hypertensive rats (SHRs). A 13-wk oral administration of SFS was performed daily in 8- to 21-wk-old SHRs with a dose of 200 mg/kg of body weight/d. The systolic (SBP) and diastolic (DBP) blood pressures were measured for each week during the experimental period. As a result, a significant (P < 0.01) BP lowering effect was observed from the 5th d to the end of the experiment in the SFS group compared with the control group (ΔSBP_21-wk: 27 mmHg, ΔDBP_21-wk: 20 mmHg). In contrast to such substantial effect by SFS intake, angiotensin I-converting enzyme activities in blood and local organs as well as pharmaceutical parameters such as serum Na⁺ or K⁺ level did not show any significant difference between in both SFS and control groups. Vasoconstriction experiment using thoracic aorta rings from 21-wk SHRs provided an interesting result that the rings from the SFS group evoked a >2-fold higher increase in the angiotensin II-stimulated constrictive response compared with the rings from the control group (P = 0.012), which suggested that the SFS-intake would be effective in possessing a higher vessel tone. Practical Application: In this study, we investigated the antihypertensive effect of newly fermented SFS in SHRs. As a result of 13-wk SFS-administration, we found a significant antihypertensive effect of the SFS. This finding strongly demonstrates that the developed SFS would be greatly beneficial for health and useful for health-related industries.     

Channel Models for Medical Implant Communication

Information regarding the propagation media is typically gathered by conducting physical experiments, measuring and processing the corresponding data to obtain channel characteristics. When this propagation media is human body, for example in case of medical implants, then this approach might not be practical. In this paper, an immersive visualization environment is presented, which is used as a scientific instrument that gives us the ability to observe RF propagation from medical implants inside a human body. This virtual environment allows for more natural interaction between experts with different backgrounds, such as engineering and medical sciences. Here, we show how this platform has been used to determine channel models for medical implant communication systems.     

Numerical simulation of critical current performance in Nb3Sn strand subjected to periodic bending deformation

In the ITER Engineering Design Activity (EDA), four NB₃Sn model coils were developed and successfully tested. However, it was revealed that the critical current of the conductor degraded with the increase of electromagnetic force. One of the explanations of this phenomenon is a strand bending caused by enormous electromagnetic force. The authors therefore developed a simulation code using the distributed circuit model to investigate dependency of the critical current performance on the periodic bending deformation. The simulation results were in good agreement with the experiments. The dependence of the critical current on the periodic transverse load, temperature, periodic load pitch, thickness of Ta barrier which prevents Cu stabilizer from being contaminated by Sn, twist pitch of the strand, and RRR of the bronze matrix was investigated using the developed code. The results showed that the critical current degraded less with decreasing the pitch of the transverse load and increasing the Ta barrier thickness. It suggests that the shorter cabling pitch and the larger bending stiffness prevent the critical current degradation. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(3): 7–15, 2010; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20923     

In-vivo human brain molecular imaging with a brain-dedicated PET/MRI system

Advances in the new-generation of ultra-high-resolution, brain-dedicated positron emission tomography-magnetic resonance imaging (PET/MRI) systems have begun to provide many interesting insights into the molecular dynamics of the brain. First, the finely delineated structural information from ultra-high-field MRI can help us to identify accurate landmark structures, thereby making it easier to locate PET activation sites that are anatomically well-correlated with metabolic or ligand-specific organs in the neural structures in the brain. This synergistic potential of PET/MRI imaging is discussed in terms of neuroscience and neurological research from both translational and basic research perspectives. Experimental results from the hippocampus, thalamus, and brainstem obtained with ¹⁸F-fluorodeoxyglucose and ¹¹C-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)benzonitrile are used to demonstrate the potential of this new brain PET/MRI system.     

Parity induced edge-current saturation and current distribution in zigzag-edged graphene nano-ribbon devices

We show computationally that the current-voltage characteristics of the zigzag-edged graphene nanoribbon (ZGNR) with the even width exhibit remarkable current saturation behavior in spite of the absence of the bandgap. Mechanism of such current-saturation behavior can be understood to be originated from the symmetries of the wavefunctions corresponding to the edge states in ZGNR. We further demonstrate that the current-voltage characteristics of ZGNR can be drastically changed even by the presence of a single lattice vacancy, with the strong dependence on the position of the vacancy. The origin of such properties is intuitively understood by analyzing the transmission probabilities through such systems.     

In vitro formation and thermal transition of novel hybrid fibrils from type I fish scale collagen and type I porcine collagen

Novel type I collagen hybrid fibrils were fabricated by neutralizing a mixture of type I fish scale collagen solution and type I porcine collagen solution with a phosphate buffer saline at 28 °C. Their structure was discussed in terms of the volume ratio of fish/porcine collagen solution. Scanning electron and atomic force micrographs showed that the diameter of collagen fibrils derived from the collagen mixture was larger than those derived from each collagen, and all resultant fibrils exhibited a typical D-periodic unit of ∼67 nm, irrespective of volume ratio of both collagens. Differential scanning calorimetry revealed only one endothermic peak for the fibrils derived from collagen mixture or from each collagen solution, indicating that the resultant collagen fibrils were hybrids of type I fish scale collagen and type I porcine collagen.     

Decision methodology of end-milling conditions using data-mining

The purpose of the present study is to apply data-mining methods to support the decision of reasonable cutting conditions. Although an enormous amount of information is listed in a catalog, it is not possible to know all of it. Seen from the viewpoint of the user, this enormous amount of information becomes a hindrance. For example, even if an expert worker does not look at a catalog, in end-mill processing, he can decide the appropriate processing condition efficiently from experience; however, this type of situation creates difficult problems for an unskilled worker or a skilled worker with little experience. The recommended cutting condition for every type of material is listed in a catalog together with the appropriate tool, but it takes much time and labor to search and examine the catalog to find the right tool, and this process is inefficient. The main subject of our research was to support the processing condition of the end-mill for each precision tool efficiently based on end-mill clusters. Our research applied the techniques of data mining, in particular, non-hierarchy clustering and hierarchy clustering, to catalog data. With these techniques, we applied multiple regression analysis and reached the following main conclusions. As a first step, we paid attention to the shape element of catalog data. In addition to using conventional mining processes, we grouped end-mills from the viewpoint of tool shape, which meant the ratio of dimensions, visually by applying the K-means method. We applied variable cluster analysis next to each cluster and extracted an predictor variable to represent each cluster, and we performed multiple regression analysis and derived a cutting condition decision formula. The cutting condition decision formula provided high accuracy. The accuracy was higher than the results achieved through mining of all data. A more highly precise processing condition decision formula was derived by doing mining again, excluding the peculiar data clusters such as small diameter end-mill. We understood what was effective for cutting condition decision to be factors related to blade length and the ratio of the full length, factors which have not been singled out through background knowledge or expert knowledge, but were noticed as an effect of catalog mining.