The effects of negative social media connotations on subjective wellbeing of an ageing population: A stressor-strain-outcome perspective.

In recent years, users' privacy concerns and reluctance to use have posed a challenge for the social media and wellbeing of its users. There is a paucity of research on elderly users' negative connotations of social media and the way these connotations contribute to developing passive behaviour towards social media use, which, in turn, affects subjective wellbeing. To address this research vacuum we employed the stressor-strain-outcome (SSO) approach to describe the evolution of passive social media use behaviour from the perspective of communication overload, complexity, and privacy. We conceptualized subjective wellbeing as a combination of three components-negative feelings, positive feelings, and life satisfaction. Negative and positive feelings were used to derive an overall affect balance score that fluctuates between 'unhappiest possible' and 'happiest possible'. The proposed research framework was empirically validated through 399 valid responses from elderly social media users. Our findings reveal that communication overload and complexity raise privacy concerns among social media users, which leads to passive usage of social media. This passive social media use improved the subjective wellbeing favourably by lowering negative feelings and raising positive feelings and life satisfaction. The findings also revealed that respondents' overall affect balance leans towards positive feelings as a consequence of passive social media use. This study contributes to the field of technostress by illuminating how the SSO perspective aid the comprehension of the way passive social media use influences the subjective wellbeing of its users.

Long-Term Survival and Quality of Life Following Transcatheter Aortic Valve Replacement in Nonagenarians.

Transcatheter aortic valve replacement (TAVR) has emerged as a successful treatment option for severe aortic stenosis. However, the long-term outcomes of TAVR in nonagenarians is lacking. We aimed to examine the long-term mortality and quality of life in nonagenarians after TAVR. This is a multicenter, retrospective analysis on patients with severe aortic stenosis who underwent TAVR. Patients were divided into 2 groups: nonagenarians (age ≥90 years) and age <90 years. The Kansas City cardiomyopathy questionnaire (KCCQ) and New York Heart Association (NYHA) scores were compared before and after TAVR. All-cause mortality was compared between both groups at 30 days, 1 year, and 5 years after TAVR using the Cox proportional hazard model. A total of 6,896 patients were included, of whom 591 were nonagenarians. Nonagenarians had a higher Society of Thoracic Surgeons perioperative risk of mortality (8.1 ± 4.6% vs 5.4 ± 4.2%, p <0.001) before TAVR. Both groups were similar in KCCQ and NYHA scores at baseline. At 1 year after TAVR, there was no significant difference in improvement in the KCCQ overall score between those aged <90 years and nonagenarians (-4.76, 95% confidence interval [CI] -11.4 to 1.9, p = 0.161). Similarly, there was no statistically significant difference in improvement in NYHA class between the 2 groups at 1 year (odds ratio 1.07, 95% CI 0.85 to 1.25), p = 0.526). The unadjusted 30-day (3.2% vs 2.7%, hazard ratio 1.11, 95% CI 0.70 to 1.80, p = 0.667) and 5-year (28.0% vs 26.6%, hazard ratio 1.05, 95% CI 0.89 to 1.24, p = 0.60) all-cause mortality were similar between the 2 groups. In conclusion, this study demonstrates an excellent long-term mortality rate at 5 years after TAVR in nonagenarians, comparable to patients younger than 90 years. There is a significant and enduring improvement in functional status in nonagenarians, observed up to 1 year after TAVR.

Adaptive Node Clustering Technique for Smart Ocean Under Water Sensor Network (SOSNET).

Abstract: Smart ocean is a term broadly used for monitoring the ocean surface, sea habitat monitoring, and mineral exploration to name a few. Development of an efficient routing protocol for smart oceans is a non-trivial task because of various challenges, such as presence of tidal waves, multiple sources of noise, high propagation delay, and low bandwidth. In this paper, we have proposed a routing protocol named adaptive node clustering technique for smart ocean underwater sensor network (SOSNET). SOSNET employs a moth flame optimizer (MFO) based technique for selecting a near optimal number of clusters required for routing. MFO is a bio inspired optimization technique, which takes into account the movement of moths towards light. The SOSNET algorithm is compared with other bio inspired algorithms such as comprehensive learning particle swarm optimization (CLPSO), ant colony optimization (ACO), and gray wolf optimization (GWO). All these algorithms are used for routing optimization. The performance metrics used for this comparison are transmission range of nodes, node density, and grid size. These parameters are varied during the simulation, and the results indicate that SOSNET performed better than other algorithms.

Comparative analysis of the human and zebrafish kinomes: focus on the development of kinase inhibitors.

Targeting kinases with semi-selective kinase inhibitors is one of the most successful drug development strategies of the 21st century. Zebrafish have become an increasingly useful model for pharmaceutical development. Water-soluble compounds can be screened for zebrafish phenotypes in a high throughput format against a living vertebrate, and cell-signaling events can be imaged in transparent living fish. Despite zebrafish being a more relevant model than more distantly related systems such as the well-annotated kinome of yeast and drosophila, there is no comparative analysis of the human and zebrafish kinome. Furthermore most approved kinase inhibitors, often called 'DFG in' ATP competitive inhibitors, act on conserved active site residues in the kinase. Since the active site residues can be identified by examining the primary sequence, primary sequence identity can be a rough guide as to whether a particular inhibitor will have activity against another kinase. There is a need to evaluate the utility of zebrafish as a drug development model for active site inhibitors of kinases. Here we offer a systematic comparison of the catalytic domains of classical human kinases with the catalytic domains of all annotated zebrafish kinases. We found a high degree of identity between the catalytic domains of most human kinases and their zebrafish homologs, and we ranked 504 human kinase catalytic domains by order of similarity. We found only 23 human kinases with no easily recognizable homologous zebrafish catalytic domain. On the other hand we found 78 zebrafish kinase catalytic domains with no close human counterpart. These 'additional kinase active sites' could represent potential mediators of zebrafish toxicity that may not be relevant to human kinase inhibitors. We used two clinically approved human kinase inhibitors, one targeting a highly homologous target and one targeting a lesser homologous target, and we compared the known human kinase target structures with modeled zebrafish target structures. As expected, the homologous target had high structural identity, but even the less homologous target had high structural identity in residues contacted by the inhibitor. Overall this analysis should help guide researchers interested in studying human kinases and their inhibitors in more tractable systems.