Adherence Across Behavioral Domains in Treatment Promoting Smoking Cessation Plus Weight Control.

The authors tested whether adherence to simultaneous health behavior changes was unitary or domain specific among 76 women who modified smoking, eating, and physical activity to accomplish smoking cessation plus weight control. Random-effects regression analyses showed that adherence to both smoking and diet plans declined linearly and covaried positively; their association tended to grow stronger over time. In contrast, physical activity plan adherence did not change over time and was unrelated to other domains. At the end of treatment, 65%, 30.5%, and 25% adhered well or excellently to smoking, diet, and activity treatments, respectively. Findings support both unitary and domain-specific aspects of adherence and suggest that among smokers, smoking and eating behaviors may have similarities unshared by physical activity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Clinical Trial to Test the Feasibility of a Telehealth Psychoeducational Intervention for Persons With Schizophrenia and Their Families: Intervention and 3-Month Findings.

Objective: To evaluate the feasibility of a telehealth psychoeducation intervention for persons with schizophrenia and their family members. Study Design: Randomized controlled trial. Participants: 30 persons with schizophrenia and 21 family members or other informal support persons. Interventions: Web-based psychoeducation program that provided online group therapy and education. Main Outcome Measures: Measures for persons with schizophrenia included perceived stress and perceived social support; for family members, they included disease-related distress and perceived social support. Results: At 3 months, participants with schizophrenia in the intervention group reported lower perceived stress (p = .04) and showed a trend for a higher perceived level of social support (p = .06). Conclusions: The findings demonstrate the feasibility and impact of providing telehealth-based psychosocial treatments, including online therapy groups, to persons with schizophrenia and their families. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Computer-based determination of size and shape in living cells

Measurement of cell volume in living epithelial cells has become an important technique in studies of membrane transport processes that function in cell volume regulation. Planimetry of video images of optical sections enables the measurement of the cross sectional area of each section. Cell volume is calculated from the measured area of each section and the known focus displacements. In the past the measurement of cross section area has been done by manual positioning of a cursor superimposed on the video image. Each experiment generates approximately 200 images in which two or more cells may be analysed. We have developed a computer-based method that uses one image as a template, and allows automated area determination of successive images by template matching and digital image processing. This new method is comparable to the older method in speed and accuracy, but requires much less effort from the experimenter.     

A distributed simplex algorithm for degenerate linear programs and multi-agent assignments

In this paper we propose a novel distributed algorithm to solve degenerate linear programs on asynchronous peer-to-peer networks with distributed information structures. We propose a distributed version of the well-known simplex algorithm for general degenerate linear programs. A network of agents, running our algorithm, will agree on a common optimal solution, even if the optimal solution is not unique, or will determine infeasibility or unboundedness of the problem. We establish how the multi-agent assignment problem can be efficiently solved by means of our distributed simplex algorithm. We provide simulations supporting the conjecture that the completion time scales linearly with the diameter of the communication graph.     

Establishment and Characterization of Novel Human Intestinal In Vitro Models for Absorption and First-Pass Metabolism Studies

Commonly used intestinal in vitro models are limited in their potential to predict oral drug absorption. They either lack the capability to form a tight cellular monolayer mimicking the intestinal epithelial barrier or the expression of cytochrome P450 3A4 (CYP3A4). The aim of this study was to establish a platform of colorectal cancer patient-derived cell lines for evaluation of human intestinal drug absorption and metabolism. We characterized ten 2D cell lines out of our collection with confluent outgrowth and long-lasting barrier forming potential as well as suitability for high throughput applications with special emphasis on expression and inducibility of CYP3A4. By assessment of the transepithelial electrical resistance (TEER) the cells barrier function capacity can be quantified. Very high TEER levels were detected for HROC60. A high basal CYP3A4 expression and function was found for HROC32. Eight cell lines showed higher CYP3A4 induction by stimulation via the vitamin D receptor compared to Caco-2 cells (5.1- to 16.8-fold change). Stimulation of the pregnane X receptor led to higher CYP3A4 induction in two cell lines. In sum, we identified the two cell lines HROC183 T0 M2 and HROC217 T1 M2 as useful tools for in vitro drug absorption studies. Due to their high TEER values and inducibility by drug receptor ligands, they may be superior to Caco-2 cells to analyze oral drug absorption and intestinal drug–drug interactions. Significance statement: Selecting appropriate candidates is important in preclinical drug development. Therefore, cell models to predict absorption from the human intestine are of the utmost importance. This study revealed that the human cell lines HROC183 T0 M2 and HROC217 T1 M2 may be better suited models and possess higher predictive power of pregnane X receptor- and vitamin D-mediated drug metabolism than Caco-2 cells. Consequently, they represent useful tools for predicting intestinal absorption and simultaneously enable assessment of membrane permeability and first-pass metabolism.     

Daily Treatment of Mice with Type 2 Diabetes with Adropin for Four Weeks Improves Glucolipid Profile,Reduces Hepatic Lipid Content and Restores Elevated Hepatic Enzymes in Serum

Adropin is a peptide hormone encoded by Energy Homeostasis Associated gene. Adropin modulates energy homeostasis and metabolism of lipids and carbohydrates. There is growing evidence demonstrating that adropin enhances insulin sensitivity and lowers hyperlipidemia in obese mice. The aim of this study was to investigate the effects of daily administration of adropin for four weeks in mice with experimentally induced type 2 diabetes (T2D). Adropin improved glucose control without modulating insulin sensitivity. Adropin reduced body weight, size of adipocytes, blood levels of triacylglycerol and cholesterol in T2D mice. T2D mice treated with adropin had lower liver mass, reduced hepatic content of triacylglycerol and cholesterol. Furthermore, adropin attenuated elevated blood levels of hepatic enzymes (ALT, AST, GGT and ALP) in T2D mice. In T2D mice, adropin increased the circulating adiponectin level. Adropin had no effects on circulating insulin and glucagon levels and did not alter pancreatic islets morphology. These results suggest that adropin improves glucose control, lipid metabolism and liver functions in T2D. In conjunction with reduced lipid content in hepatocytes, these results render adropin as an interesting candidate in therapy of T2D.     

Automatic data collection for enterprise architecture models

Enterprise Architecture (EA) is an approach used to provide decision support based on organization-wide models. The creation of such models is, however, cumbersome as multiple aspects of an organization need to be considered, making manual efforts time-consuming, and error prone. Thus, the EA approach would be significantly more promising if the data used when creating the models could be collected automatically—a topic not yet properly addressed by either academia or industry. This paper proposes network scanning for automatic data collection and uses an existing software tool for generating EA models (ArchiMate is employed as an example) based on the IT infrastructure of enterprises. While some manual effort is required to make the models fully useful to many practical scenarios (e.g., to detail the actual services provided by IT components), empirical results show that the methodology is accurate and (in its default state) require little effort to carry out.