br Experimental design materials and methods For the potenti

Experimental design, materials and methods For the potential oral administration, the six experimental liquid formulations of commercial pine-derived phytosterol (CPP) reduced pH to 2 and increased pH again up to 7 to mimic the human digestive system (Yi et al., 2016) [1]. The concentration of β-sitosterol was different in the six experimental formulations and was supplied as 5% of each solution in water. To make 0.1mM of β-sitosterol in working solution, 50.05μl–74.11μl of pH-adjusted six solutions was added in each of 0.1mM of cholesterol, 0.5mM of monoglyceride (MG), 1mM of oleic acid (OA), 33mM sodium taurocholate (ST) in Hanks buffered saline with magnesium and chloride (HBSS++). The particle size and the zeta-potential were measured by dynamic light scattering at 20°C in triplicates (DelsaMax pro, Beckman-Coulter Indianapolis, USA). To produce absorbable cholesterol-included fat micelles with micelle diameter of 3–25nm (Ashworth and Lawrence, 1966) [2] for application to intestine cells, the bile salt concentration is critical in the intestine fluid. 0.1mM of cholesterol, 0.5mM of MG, and 1mM of OA were mixed with 33mM, 16.5mM, and 6.6mM of ST, and the size of cholesterol-containing micelles was measured by dynamic light scattering (DelsaMax pro, Beckman-Coulter Indianapolis, USA).
Data Data show all five muscarinic MRS 2578 receptor subtypes (mAChR) were present in the mouse duodenum, jejunum, and ileum across all ages of mice by RT-PCR (Fig. 1). Mouse ileum was further imaged with immunofluorescence microscopy and highlighted mAChR2 within intestinal crypts (Fig. 2). mAChR2 was localized to the crypt stem cell compartment (Fig. 3), and further co-localized within Paneth cells in the intestinal crypt with lysozyme (Fig. 4).
Experimental design, materials and methods
Data Factors and their possible outcomes which may be directly or indirectly relevant for the energy consumption of private households in Germany were collected by asking an interdisciplinary group of experts. In a second step the group of experts specified the interactions among the outcomes on a semi-quantitative manner by evaluating the direct influence each outcome has on another one. The factors are subdivided in sectoral, national and international factors for reducing the efforts needed for specifying the links between the factors and to enable the use of the identified network of causes and effects in a Cross-Impact Balance (CIB) framework (see e.g. [2,3]).
Experimental design, materials and methods For each scale the experts nominated descriptors first. After reducing the lists to a manageable size, the experts judged together the strengths of impacts among possible factor specific outcomes evaluating the direct influence of each outcome on another one. Strong positive influences are indicated by using “+3”, strong negative by using “-3” and lower influences by using “+2”, “+1”, “0”, “−2” and “−1”, respectively. Using the software SzenarioWizard 4.11 [4] the resulting matrices of interactions were analyzed with respect to consistency: For each set of outcomes the balance of all incoming impacts on the outcome were added up. If each outcome of the selected set is supported at least as strong as any other outcome of the corresponding factor the selected set is defined as consistent. Based on the selected consistent outcome sets possible future are defined which can be used as storylines for further analyses (e.g. by using bottom-up models) (see [1]).
Data Table 1 contains the data used to make the tiling DNA microarray. The table consists of two columns and 597 rows; one column contains the GI numbers, and the second column contains the corresponding taxonomic assignment of the 16S rRNA gene sequences. Tables 2 and 3 contain the abundances of various 16S rRNA genes in each of the patient samples. The abundances in Table 2 are based on the median value of all individual probes targeting a specific 16S rRNA gene, while the abundances in Table 3 is based on the aggregated values of all probes targeting a specific 16S rRNA gene.