Heat-Killed Enterococcus faecalis EF-2001 Induces Human Dermal Papilla Cell Proliferation and Hair Regrowth in C57BL/6 Mice

Minoxidil is the most widely used treatment for hair growth, but has been associated with several side effects. In this study, we investigated the effects of heat-killed Enterococcus faecalis EF-2001 on hair loss prevention and regrowth using human dermal papilla cells and male C57BL/6 mice. To examine the effects of EF-2001, we used minoxidil as the positive control. In the in vitro experiments, EF-2001 treatment (75–500 μg/mL) led to the proliferation of human dermal papilla cells in a concentration-dependent manner. In the in vivo experiment, the topical application of 200 µL EF-2001 on the dorsal surface of C57BL/6 male mice led to hair growth. Changes in hair regrowth were examined by visual comparison and hematoxylin and eosin staining of skin sections. We also determined the expression levels of marker genes (Wnt) and growth factors (fibroblast growth factor, insulin growth factor 1, and vascular endothelial growth factor) in the skin tissues of the back of each mouse using a quantitative polymerase chain reaction. EF-2001 accelerated the progression of hair regrowth in mice and promoted hair-follicle conversion from telogen to anagen, likely by increasing the expression levels of growth factors and marker genes.     

Biomimetic micropatterning of silica by surface-initiated polymerization and microcontact printing

Micropatterns of silica on a gold substrate were generated by a biomimetic approach, namely, the biosilicification of silicic acids. The procedure consists of three simple steps: pattern generation of a polymerization initiator, (BrC(CH(3))(2)COO(CH(2))(11)S)(2), by microcontact printing; surface-initiated, atom-transfer radical polymerization of 2-(dimethylamino)ethyl methacrylate (DMAEMA) from the patterned area; and polycondensation of silicic acids. The tertiary amine-containing polymer, pDMAEMA, aided in the spatially controlled polycondensation of silicic acids on surfaces in the presence of phosphate ions, and micropatterns of silica on a gold substrate were successfully generated in combination with the technique of microcontact printing. The procedure could be extended to the controlled fabrication of silica patterns with any size, shape, or thickness.     

Mixture equations of state: Composition dependence

This paper discusses theoretical models for the composition dependence of equations of state and compares the quality of predictions against experimental thermodynamic property data. The mean density approximation (MDA) and the van der Waals one-fluid (VDW1) model are compared with hybrid mixing rules (HMR), in which rigorous composition dependence is used for the second and third virial coefficients and the conformai solution model is used for equation-of-state density terms beyond the third virial term. It is found that when values of unity are used for all binary and three-body unlike interaction parameters, calculated densities for methane-normal heptane mixtures have average absolute deviations of 3.54% for MDA, 4.04% for VDW1, and 2.59% for HMR. When vapor-liquid equilibrium calculations were performed for the methane-normal heptane system, average absolute deviations of calculatedK values from experimental values were 16.7% for methane and 36.4% for normal heptane using HMR, whereas when conformal solution model (CSM) mixing rules were used, the results were 34.8% for methane and 66.7% for normal heptane. When the binary interaction parameter for the characterization of interaction energies is determined, it is found to be less sensitive to state conditions in the case of HMR than either MDA or VDW1. These preliminary results suggest the potential of mixture equation-of-state methods which utilize rigorous composition dependence for the lower-order virial coefficients.Paper presented at the Second U.S.-Japan Joint Seminar on Thermophysical Properties, June 23, 1988, Gaithersburg, Maryland, U.S.A.     

Hierarchical Spatially Varying Coefficient Process Model

The spatially varying coefficient process model is a nonstationary approach to explaining spatial heterogen-eity by allowing coefficients to vary across space. In this article, we develop a methodology for generalizing this model to accommodate geographically hierarchical data. This article considers two-level hierarchical structures and allow for the coefficients of both low-level and high-level units to vary over space. We assume that the spatially varying low-level coefficients follow the multivariate Gaussian process, and the spatially varying high-level coefficients follow the multivariate simultaneous autoregressive model that we develop by extending the standard simultaneous autoregressive model to incorporate multivariate data. We apply the proposed model to transaction data of houses sold in 2014 in a part of the city of Los Angeles. The results show that the proposed model predicts housing prices and fits the data effectively.     

Non-linear analysis for anisotropic materials

An elasto-plastic analysis of anisotropic work-hardening materials, using the finite element method is presented. The analysis is based on the generalized Huber-Mises yield criterion extended by Hill for anisotropic materials. General expressions for the anisotropic parameters in the yield criterion have been derived both for initial yielding as well as subsequent yielding in the case of work-hardening materials. The isoparametric ‘quadratic’ quadrilateral elements have been used for the analysis and the ‘initial stress technique’ has been adopted for the iterative solution of the non-linear problems. The results of the various numerical examples have been compared with the available solutions.     

Pulsed Electromagnetic Field (PEMF) Treatment Reduces Lipopolysaccharide-Induced Septic Shock in Mice

Despite advances in medicine, mortality due to sepsis has not decreased. Pulsed electromagnetic field (PEMF) therapy is emerging as an alternative treatment in many inflammation-related diseases. However, there are few studies on the application of PEMF therapy to sepsis. In the current study, we examined the effect of PEMF therapy on a mouse model of lipopolysaccharide (LPS)-induced septic shock. Mice injected with LPS and treated with PEMF showed higher survival rates compared with the LPS group. The increased survival was correlated with decreased levels of pro-inflammatory cytokine mRNA expression and lower serum nitric oxide levels and nitric oxide synthase 2 mRNA expression in the liver compared with the LPS group. In the PEMF + LPS group, there was less organ damage in the liver, lungs, spleen, and kidneys compared to the LPS group. To identify potential gene targets of PEMF treatment, microarray analysis was performed, and the results showed that 136 genes were up-regulated, and 267 genes were down-regulated in the PEMF + LPS group compared to the LPS group. These results suggest that PEMF treatment can dramatically decrease septic shock through the reduction of pro-inflammatory cytokine gene expression. In a clinical setting, PEMF may provide a beneficial effect for patients with bacteria-induced sepsis and reduce septic shock-induced mortality.