Impact of computer training courses on reduction of loneliness of older people in Finland and Slovenia

Previous research has shown loneliness as a threat for the quality of life of older people; therefore the goal of the intervention in a quasi-experimental study was to evaluate and discuss the self-reported level of loneliness of older people in Finland and Slovenia before and after a computer intervention. Intervention in a quasi-experimental study was conducted among 58 older participants at the baseline (M = 72.4 years) and 45 older participants at the follow-up research study (M = 72.9 years). Inferential statistics showed a significant difference in the reduction of loneliness between the countries, and a decreased level of loneliness of older people after completing the computer training course. Although older people experience many age-related problems which may reduce their interest in learning information and communication technology (ICT) skills, it is important that they are computer-proficient, because computer engagement can reduce the level of loneliness of older people and in this way has a positive effect on their quality of life.     

Psychosocial and health consequences of adolescent depression in Black and White young adult women.

Depression in adolescent girls may result in negative consequences in young adulthood. The Center for Epidemiologic Studies Depression Scale (CES-D) was administered to 1,727 Black and White girls ages 16 to 18 years who participated in the National Heart, Lung, and Blood Institute's Growth and Health Study. Three years later, women in the depressed groups were more likely to be current smokers, had attained a lower level of education, and reported lower self-worth relative to the nondepressed group. Body dissatisfaction, eating concerns, and loneliness were greater in the depressed groups. Relative to Black women, White women who were moderately depressed during adolescence reported more health care services utilization in young adulthood. Prevention efforts for depressed adolescents should be broadly focused to improve young adult outcomes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Framework for Sustainable Food Packaging Design

The environmental impacts of packages have been found to be relatively small compared with the food items they contain. Furthermore, from the environmental and operational point of view, the most significant task of the package is to protect the product, which is important to acknowledge in the packaging design process. This study introduces a guiding framework for designing sustainable food packaging. In this approach, the entire life cycle of the product–package combination is taken into consideration. The emphasis is on the prevention of food losses in packaging design as a major environmental criterion. Consideration of the properties of both the package and the product itself when designing the final package will lead to a better end result with smaller product losses and environmental impacts. By using different assessment methods in the different stages of the packaging design, the sustainability of the package can be enhanced. The decision making of the packaging designer is facilitated with methods that are introduced step by step and in a certain order that will also allow for corrective measures through back‐loops in the design process. The purpose is to integrate sustainability aspects at all stages firmly into the design process. Copyright © 2012 John Wiley & Sons, Ltd.     

Can porous polymeric scaffolds be functionalized by stem cells leading to osteogenic differentiation? A systematic review of in vitro studies

The aim of this study was to analyze the influence of nanoporous structure of polymeric biomaterials on the in vitro osteogenic induction of human stem cells. An electronic search in three databases (MEDLINE, SCOPUS, and Web of Science) was performed for articles that were published before May 2018. In vitro studies were included if they met the following criteria: (1) the use of polymeric scaffolds (natural or synthetic); (2) the co-culture of human stem cells with the scaffold; and (3) cell viability, proliferation, and osteogenic differentiation assays. The main characteristics of the published studies were summarized, and a quality assessment tool was used to analyze methodological features. Eighty-eight potential articles were firstly retrieved. Thirteen were eligible for qualitative analysis. Only three studies characterized cell stemness. Nanostructure of the scaffolds showed a significant influence on viability, proliferation, and osteogenic differentiation of human stem cells. Combination of porosity between 72 and 93% and a large range diameter between 50 and 224 μm resulted in more remarkable cellular proliferation and differentiation. Porous polymeric scaffolds can be functionalized by stem cells leading to osteogenic induction. High standards of laboratory practice and accurate methodological reporting are essential for the credibility of the results.     

LXRα Regulates oxLDL-Induced Trained Immunity in Macrophages

Reprogramming of metabolic pathways in monocytes and macrophages can induce a proatherosclerotic inflammatory memory called trained innate immunity. Here, we have analyzed the role of the Liver X receptor (LXR), a crucial regulator of metabolism and inflammation, in oxidized low-density lipoprotein (oxLDL)-induced trained innate immunity. Human monocytes were incubated with LXR agonists, antagonists, and oxLDL for 24 h. After five days of resting time, cells were restimulated with the TLR-2 agonist Pam3cys. OxLDL priming induced the expression of LXRα but not LXRβ. Pharmacologic LXR activation was enhanced, while LXR inhibition prevented the oxLDL-induced inflammatory response. Furthermore, LXR inhibition blocked the metabolic changes necessary for epigenetic reprogramming associated with trained immunity. In fact, enrichment of activating histone marks at the IL-6 and TNFα promotor was reduced following LXR inhibition. Based on the differential expression of the LXR isoforms, we inhibited LXRα and LXRβ genes using siRNA in THP1 cells. As expected, siRNA-mediated knock-down of LXRα blocked the oxLDL-induced inflammatory response, while knock-down of LXRβ had no effect. We demonstrate a specific and novel role of the LXRα isoform in the regulation of oxLDL-induced trained immunity. Our data reveal important aspects of LXR signaling in innate immunity with relevance to atherosclerosis formation.     

Smaller,Stronger, More Stable: Peptide Variants of a SARS-CoV-2 Neutralizing Miniprotein

Based on the structure of a de novo designed miniprotein (LCB1) in complex with the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, we have generated and characterized truncated peptide variants of LCB1, which present only two of the three LCB1 helices, and which fully retained the virus neutralizing potency against different SARS-CoV-2 variants of concern (VOC). This antiviral activity was even 10-fold stronger for a cyclic variant of the two-helix peptides, as compared to the full-length peptide. Furthermore, the proteolytic stability of the cyclic peptide was substantially improved, rendering it a better potential candidate for SARS-CoV-2 therapy. In a more mechanistic approach, the peptides also served as tools to dissect the role of individual mutations in the RBD for the susceptibility of the resulting virus variants to neutralization by the peptides. As the peptides reported here were generated through chemical synthesis, rather than recombinant protein expression, they are amenable to further chemical modification, including the incorporation of a wide range of non-proteinogenic amino acids, with the aim to further stabilize the peptides against proteolytic degradation, as well as to improve the strength, as well the breadth, of their virus neutralizing capacity.     

INDUCTIVE LEARNING FOR PARAMETER OPTIMIZATION

Optimization of simulation model output is one of the most important tasks in a simulation study of a complex system. Efficacy of an optimization approach is expressed in the accuracy of locating a global extremum, as well as in the number of investigated search points. The approach Machine Learning Optimization (ML-Opt), presented in this article, explores functional dependencies between search points in order to reduce the number of evaluations. Functional relations between search points are determined by an inductive learning algorithm, which generates a classifier used as a control structure in the optimization process. The classifier approximates the structure of the unknown goal function given by a simulation model and affects the generation of new search points. A discussion of a numerical example concludes the paper.