Social environment and healthy ageing

growing numbers of people living to older ages, age-related diseases have become an increasing challenge for societies everywhere. Many age-related diseases however, should rather be considered lifestyle-related diseases since lifestyle plays an important role in the etiology and the treatment of cardiovascular disease, obesity, type 2I diabetes and many forms of cancer. This has led to a large body of literature investigating the possibility to change people’s lifestyle. Interventions with, for example, physiotherapists that engage in daily physical activity with older people have shown substantial benefits, even reversing type 2 diabetes and some characteristics of the ageing process (1,2). Most lifestyle interventions, however, struggle to achieve sustained, long-term behavioural change (3,4). Few individuals can maintain the effort to adopt a new diet or exercise regime themselves, without intensive coaching by professionals. These interventions are therefore expensive and this hinders the widespread and continued delivery to the growing number of older people with unhealthy lifestyle and (risk for) age-related disease. Therefore, it is important to explore novel sustainable and cost-effective methods for lifestyle interventions to combat the burden of agerelated disease in ageing societies. One often overlooked influence on the health behaviour of older people is the effect of the social environment. We believe that peer coaching, in which older people coach each other in achieving lifestyle changes, is such a promising method to deliver health benefits in a sustainable, scalable way. Although there is substantial documentation of the effect of peers on adolescents and children, the influence of peers has been overlooked in older people. In peer coaching, the social environment is applied as a method to deliver an intervention. Peer coaching is a face-to-face intervention in which a group is led by a peer, a non-professional, who shares a common background with the participants. A peer coach uses experiential knowledge to understand the wishes, motivations, possibilities and limitations of the participants. In the secondary prevention of alcohol abuse, peer coaching is already applied very successfully through Alcoholics Anonymous, which delivers health benefits through peer coaching to over two million members spread over 150 countries (5,6). Since increasing physical activity is able to ameliorate so many characteristics of the ageing process, we have studied a proof-of-principle in which peer coaching is applied to establish a sustainable and cost-effective increase in physical activity of a group of older adults in The Netherland

The SOS response of Listeria monocytogenes is involved in stress resistance and mutagenesis

The SOS response is a conserved pathway that is activated under certain stress conditions and is regulated by the repressor LexA and the activator RecA. The food-borne pathogen Listeria monocytogenes contains RecA and LexA homologs, but their roles in Listeria have not been established. In this study, we identified the SOS regulon in L. monocytogenes by comparing the transcription profiles of the wild-type strain and the DeltarecA mutant strain after exposure to the DNA damaging agent mitomycin C. In agreement with studies in other bacteria, we identified an imperfect palindrome AATAAGAACATATGTTCGTTT as the SOS operator sequence. The SOS regulon of L. monocytogenes consists of 29 genes in 16 LexA regulated operons, encoding proteins with functions in translesion DNA synthesis and DNA repair. We furthermore identified a role for the product of the LexA regulated gene yneA in cell elongation and inhibition of cell division. As anticipated, RecA of L. monocytogenes plays a role in mutagenesis; DeltarecA cultures showed considerably lower rifampicin and streptomycin resistant fractions than the wild-type cultures. The SOS response is activated after stress exposure as shown by recA- and yneA-promoter reporter studies. Subsequently, stress survival studies showed DeltarecA mutant cells to be less resistant to heat, H(2)O(2), and acid exposure than wild-type cells. Our results indicate that the SOS response of L. monocytogenes contributes to survival upon exposure to a range of stresses, thereby likely contributing to its persistence in the environment and in the hos

Auditing spreadsheets: With or without a tool?

Spreadsheets are known to be error-prone. Over the last decade, research has been done to determine the causes of the high rate of errors in spreadsheets. This paper examines the added value of a spreadsheet tool (PerfectXL) that visualizes spreadsheet dependencies and determines possible errors in spreadsheets by defining risk areas based on previous work. This paper will firstly discuss the most common mistakes in spreadsheets. Then we will summarize research on spreadsheet tools, focussing on the PerfectXL tool. To determine the perceptions of the usefulness of a spreadsheet tool in general and the PerfectXL tool in particular, we have shown the functionality of PerfectXL to several auditors and have also interviewed them. The results of these interviews indicate that spreadsheet tools support a more effective and efficient audit of spreadsheets; the visualization feature in particular is mentioned by the auditors as being highly supportive for their audit task, whereas the risk feature was deemed of lesser value.Comment: 15 Pages, 2 Tables, 8 Colour Figure

Cytokine activation during attacks of the hyperimmunoglobulinemia D and periodic fever syndrome

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Machine learning modelling of blood lipid biomarkers in familial hypercholesterolaemia versus polygenic/environmental dyslipidaemia

Familial hypercholesterolaemia increases circulating LDL-C levels and leads to premature cardiovascular disease when undiagnosed or untreated. Current guidelines support genetic testing in patients complying with clinical diagnostic criteria and cascade screening of their family members. However, most of hyperlipidaemic subjects do not present pathogenic variants in the known disease genes, and most likely suffer from polygenic hypercholesterolaemia, which translates into a relatively low yield of genetic screening programs. This study aims to identify new biomarkers and develop new approaches to improve the identification of individuals carrying monogenic causative variants. Using a machine-learning approach in a paediatric dataset of individuals, tested for disease causative genes and with an extended lipid profile, we developed new models able to classify familial hypercholesterolaemia patients with a much higher specificity than currently used methods. The best performing models incorporated parameters absent from the most common FH clinical criteria, namely apoB/apoA-I, TG/apoB and LDL1. These parameters were found to contribute to an improved identification of monogenic individuals. Furthermore, models using only TC and LDL-C levels presented a higher specificity of classification when compared to simple cut-offs. Our results can be applied towards the improvement of the yield of genetic screening programs and corresponding costs.This work was supported by UIDB/04046/2020 Research Unit grant from FCT, Portugal (to BioISI). MC is recipient of a fellowship from the BioSys Ph.D. programme PD65-2012 (Ref PD/BD/114387/2016) from FCT (Portugal).info:eu-repo/semantics/publishedVersio

Diagnostic markers based on a computational model of lipoprotein metabolism

Abstract Background: Dyslipidemia is an important risk factor for cardiovascular disease and type II diabetes. Lipoprotein diagnostics, such as LDL cholesterol and HDL cholesterol, help to diagnose these diseases. Lipoprotein profile measurements could improve lipoprotein diagnostics, but interpretational complexity has limited their clinical application to date. We have previously developed a computational model called Particle Profiler to interpret lipoprotein profiles. In the current study we further developed and calibrated Particle Profiler using subjects with specific genetic conditions. We subsequently performed technical validation and worked at an initial indication of clinical usefulness starting from available data on lipoprotein concentrations and metabolic fluxes. Since the model outcomes cannot be measured directly, the only available technical validation was corroboration. For an initial indication of clinical usefulness, pooled lipoprotein metabolic flux data was available from subjects with various types of dyslipidemia. Therefore we investigated how well lipoprotein metabolic ratios derived from Particle Profiler distinguished reported dyslipidemic from normolipidemic subjects. Results: We found that the model could fit a range of normolipidemic and dyslipidemic subjects from fifteen out of sixteen studies equally well, with an average 8.8% ± 5.0% fit error; only one study showed a larger fit error. As initial indication of clinical usefulness, we showed that one diagnostic marker based on VLDL metabolic ratios better distinguished dyslipidemic from normolipidemic subjects than triglycerides, HDL cholesterol, or LDL cholesterol. The VLDL metabolic ratios outperformed each of the classical diagnostics separately; they also added power of distinction when included in a multivariate logistic regression model on top of the classical diagnostics. Conclusions: In this study we further developed, calibrated, and corroborated the Particle Profiler computational model using pooled lipoprotein metabolic flux data. From pooled lipoprotein metabolic flux data on dyslipidemic patients, we derived VLDL metabolic ratios that better distinguished normolipidemic from dyslipidemic subjects than standard diagnostics, including HDL cholesterol, triglycerides and LDL cholesterol. Since dyslipidemias are closely linked to cardiovascular disease and diabetes type II development, lipoprotein metabolic ratios are candidate risk markers for these diseases. These ratios can in principle be obtained by applying Particle Profiler to a single lipoprotein profile measurement, which makes clinical application feasible

Self-organizing peer coach groups to increase daily physical activity in community dwelling older adults

Many older adults do not reach the recommended level of physical activity, despite many professional-delivered physical activity interventions. Here we study the implementation of a novel physical activity intervention for older adults that is self-sustainable (no financial support) and self-organizing (participants act as organizers) due to peer coaching. We implemented three groups and evaluated process and effect using participatory observations, questionnaires, six-minute walk tests and body composition measures from October 2016 to September 2018. The intervention was implemented by staff without experience in physical activity interventions. Facilitators were a motivated initiator and a non-professional atmosphere for participants to take ownership. Barriers were the absence of motivated participants to take ownership and insufficient participants to ensure the presence of participants at every exercise session. The groups exercised outside five days a week and were self-organizing after 114, 216 and 263 days. The initial investments were 170_ for sport equipment and 81-187 h. The groups reached 118 members and a retention of 86.4% in two years. The groups continue to exist at the time of writing and are self-sustainable. Quality of life increased 0.4 on a ten-point scale (95%CI 0.1-0.7; p = 0.02) and six-minute walk test results improved with 33 m (95%CI 18-48; p < 0.01) annually. Self-organizing peer coach groups for physical activity are feasible, have positive effects on health and require only a small investment at the start. It is a sustainable and potentially scalable intervention that could be a promising method to help many older adults age healthier