A qualitative synthesis of factors influencing maintenance of lifestyle behaviour change in individuals with high cardiovascular risk

Management of cardiovascular risk factors includes commitment from patients to adhere to prescribed medications and adopt healthy lifestyles. Unfortunately many fail to take up and maintain the four key healthy behaviours (not smoking, having a balanced diet, limiting alcohol consumption and being more active). Five factors (beliefs, knowledge, transport and other costs, emotions, and friends and family support) are known to predict uptake of lifestyle behaviour change. The key factors influencing maintenance of healthy lifestyles are not known but would be helpful to support the development of relapse prevention programmes for this population. Our review aimed to clarify the main patient perceived factors thought to influence maintenance of changed healthy lifestyles. ; We performed a systematic review of qualitative observational studies and applied the principles of content synthesis and thematic analysis to extract reported factors (barriers and facilitators) considered by individuals to be influential in maintaining changed healthy lifestyle behaviours. Factors were then organised into an existing framework of higher order categories which was followed by an analysis of the interrelationships between factors to identify key themes. ; Twenty two studies met our inclusion criteria. Participants reported barriers and facilitators within 13 categories, the majority of which were facilitators. The most commonly reported influences were those relating to social support (whether provided formally or informally), beliefs (about the self or the causes and management of poor health, and the value of maintaining lifestyle behaviours), and other psychological factors (including attitude, thinking and coping styles, and problem solving skills). Physical activity was the most commonly investigated behaviour in four categories, but overall, the main barriers and facilitators were related to a range of behaviours. Through analysis of the interrelationships between factors within categories, ‘social support’, ‘education and knowledge’, and ‘beliefs and emotions’ were all considered key themes. ; Our review suggests that for the most part, factors that influence lifestyle change are also important for maintaining healthy behaviours. This indicates that addressing these barriers and facilitators within lifestyle support programmes would also be of value in the longer-term

Subanesthetic ketamine treatment promotes abnormal interactions between neural subsystems and alters the properties of functional brain networks

Acute treatment with subanesthetic ketamine, a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist, is widely utilized as a translational model for schizophrenia. However, how acute NMDA receptor blockade impacts on brain functioning at a systems level, to elicit translationally relevant symptomatology and behavioral deficits, has not yet been determined. Here, for the first time, we apply established and recently validated topological measures from network science to brain imaging data gained from ketamine-treated mice to elucidate how acute NMDA receptor blockade impacts on the properties of functional brain networks. We show that the effects of acute ketamine treatment on the global properties of these networks are divergent from those widely reported in schizophrenia. Where acute NMDA receptor blockade promotes hyperconnectivity in functional brain networks, pronounced dysconnectivity is found in schizophrenia. We also show that acute ketamine treatment increases the connectivity and importance of prefrontal and thalamic brain regions in brain networks, a finding also divergent to alterations seen in schizophrenia. In addition, we characterize how ketamine impacts on bipartite functional interactions between neural subsystems. A key feature includes the enhancement of prefrontal cortex (PFC)-neuromodulatory subsystem connectivity in ketamine-treated animals, a finding consistent with the known effects of ketamine on PFC neurotransmitter levels. Overall, our data suggest that, at a systems level, acute ketamine-induced alterations in brain network connectivity do not parallel those seen in chronic schizophrenia. Hence, the mechanisms through which acute ketamine treatment induces translationally relevant symptomatology may differ from those in chronic schizophrenia. Future effort should therefore be dedicated to resolve the conflicting observations between this putative translational model and schizophrenia

Learning HCI Across Institutions, Disciplines and Countries: A Field Study of Cognitive Styles in Analytical and Creative Tasks

Human-computer interaction (HCI) is increasingly becoming a subject taught in universities around the world. However, little is known of the interactions of the HCI curriculum with students in different types of institutions and disciplines internationally. In order to explore these interactions, we studied the performance of HCI students in design, technology and business faculties in universities in UK, India, Namibia, Mexico and China who participated in a common set of design and evaluation tasks. We obtained participants’ cognitive style profiles based on Allinson and Hayes scale in order to gain further insights into their learning styles and explore any relation between these and performance. We found participants’ cognitive style preferences to be predominantly in the adaptive range, i.e. with combined analytical and intuitive traits, compared to normative data for software engineering, psychology and design professionals. We further identified significant relations between students’ cognitive styles and performance in analytical and creative tasks of a HCI professional individual. We discuss the findings in the context of the distinct backgrounds of the students and universities that participated in this study and the value of research that explores and promotes diversity in HCI education

Refugee and Migrant Women's Views of Antenatal Ultrasound on the Thai Burmese Border: A Mixed Methods Study

Antenatal ultrasound suits developing countries by virtue of its versatility, relatively low cost and safety, but little is known about women's or local provider's perspectives of this upcoming technology in such settings. This study was undertaken to better understand how routine obstetric ultrasound is experienced in a displaced Burmese population and identify barriers to its acceptance by local patients and providers.Qualitative (30 observations, 19 interviews, seven focus group discussions) and quantitative methods (questionnaire survey with 644 pregnant women) were used to provide a comprehensive understanding along four major themes: safety, emotions, information and communication, and unintended consequences of antenatal ultrasound in refugee and migrant clinics on the Thai Burmese border. One of the main concerns expressed by women was the danger of childbirth which they mainly attributed to fetal malposition. Both providers and patients recognized ultrasound as a technology improving the safety of pregnancy and delivery. A minority of patients experienced transitory shyness or anxiety before the ultrasound, but reported that these feelings could be ameliorated with improved patient information and staff communication. Unintended consequences of overuse and gender selective abortions in this population were not common.The results of this study are being used to improve local practice and allow development of explanatory materials for this population with low literacy. We strongly encourage facilities introducing new technology in resource poor settings to assess acceptability through similar inquiry

Ketamine induces a robust whole-brain connectivity pattern that can be differentially modulated by drugs of different mechanism and clinical profile

Ketamine, an N-methyl-D-aspartate receptor (NMDAR) antagonist, has been studied in relation to the glutamate hypothesis of schizophrenia and increases dissociation, positive and negative symptom ratings. Ketamine effects brain function through changes in brain activity; these activity patterns can be modulated by pre-treatment of compounds known to attenuate the effects of ketamine on glutamate release. Ketamine also has marked effects on brain connectivity; we predicted that these changes would also be modulated by compounds known to attenuate glutamate release. Here, we perform task-free pharmacological magnetic resonance imaging (phMRI) to investigate the functional connectivity effects of ketamine in the brain and the potential modulation of these effects by pre-treatment of the compounds lamotrigine and risperidone, compounds hypothesised to differentially modulate glutamate release. Connectivity patterns were assessed by combining windowing, graph theory and multivariate Gaussian process classification. We demonstrate that ketamine has a robust effect on the functional connectivity of the human brain compared to saline (87.5 % accuracy). Ketamine produced a shift from a cortically centred, to a subcortically centred pattern of connections. This effect is strongly modulated by pre-treatment with risperidone (81.25 %) but not lamotrigine (43.75 %). Based on the differential effect of these compounds on ketamine response, we suggest the observed connectivity effects are primarily due to NMDAR blockade rather than downstream glutamatergic effects. The connectivity changes contrast with amplitude of response for which no differential effect between pre-treatments was detected, highlighting the necessity of these techniques in forming an informed view of the mechanistic effects of pharmacological compounds in the human brain

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP

Health Conditions and Their Impact among Adolescents and Young Adults with Down Syndrome

Objective: To examine the prevalence of medical conditions and use of health services among young adults with Down syndrome and describe the impact of these conditions upon their lives. Methods: Using questionnaire data collected in 2011 from parents of young adults with Down syndrome we investigated the medical conditions experienced by their children in the previous 12 months. Univariate, linear and logistic regression analyses were performed. Results: We found that in addition to the conditions commonly experienced by children with Down syndrome, including eye and vision problems (affecting 73%), ear and hearing problems (affecting 45%), cardiac (affecting 25%) and respiratory problems (affecting 36%), conditions also found to be prevalent within our young adult cohort included musculoskeletal conditions (affecting 61%), body weight (affecting 57%), skin (affecting 56%) and mental health (affecting 32%) conditions and among young women menstrual conditions (affecting 58%). Few parents reported that these conditions had no impact, with common impacts related to restrictions in opportunities to participate in employment and community leisure activities for the young people, as well as safety concerns. Conclusion: There is the need to monitor, screen and provide appropriate strategies such as through the promotion of healthy lifestyles to prevent the development of comorbidities in young people with Down syndrome and, where present, to reduce their impact

Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>A reverse engineering of gene regulatory network with large number of genes and limited number of experimental data points is a computationally challenging task. In particular, reverse engineering using linear systems is an underdetermined and ill conditioned problem, i.e. the amount of microarray data is limited and the solution is very sensitive to noise in the data. Therefore, the reverse engineering of gene regulatory networks with large number of genes and limited number of data points requires rigorous optimization algorithm.</p> <p>Results</p> <p>This study presents a novel algorithm for reverse engineering with linear systems. The proposed algorithm is a combination of the orthogonal least squares, second order derivative for network pruning, and Bayesian model comparison. In this study, the entire network is decomposed into a set of small networks that are defined as unit networks. The algorithm provides each unit network with P(D|H_i), which is used as confidence level. The unit network with higher P(D|H_i) has a higher confidence such that the unit network is correctly elucidated. Thus, the proposed algorithm is able to locate true positive interactions using P(D|H_i), which is a unique property of the proposed algorithm.</p> <p>The algorithm is evaluated with synthetic and <it>Saccharomyces cerevisiae </it>expression data using the dynamic Bayesian network. With synthetic data, it is shown that the performance of the algorithm depends on the number of genes, noise level, and the number of data points. With Yeast expression data, it is shown that there is remarkable number of known physical or genetic events among all interactions elucidated by the proposed algorithm.</p> <p>The performance of the algorithm is compared with Sparse Bayesian Learning algorithm using both synthetic and <it>Saccharomyces cerevisiae </it>expression data sets. The comparison experiments show that the algorithm produces sparser solutions with less false positives than Sparse Bayesian Learning algorithm.</p> <p>Conclusion</p> <p>From our evaluation experiments, we draw the conclusion as follows: 1) Simulation results show that the algorithm can be used to elucidate gene regulatory networks using limited number of experimental data points. 2) Simulation results also show that the algorithm is able to handle the problem with noisy data. 3) The experiment with Yeast expression data shows that the proposed algorithm reliably elucidates known physical or genetic events. 4) The comparison experiments show that the algorithm more efficiently performs than Sparse Bayesian Learning algorithm with noisy and limited number of data.</p

Neurexin-1 and Frontal Lobe White Matter: An Overlapping Intermediate Phenotype for Schizophrenia and Autism Spectrum Disorders

Background: Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1 gene variation may be related to brain morphology to confer risk for ASD or schizophrenia is unknown. Method/Principal Findings: 53 healthy individuals between 18–59 years of age were genotyped at 11 single nucleotide polymorphisms of the NRXN1 gene. All subjects received structural MRI scans, which were processed to determine cortical gray and white matter lobar volumes, and volumes of striatal and thalamic structures. Each subject’s sensorimotor function was also assessed. The general linear model was used to calculate the influence of genetic variation on neural and cognitive phenotypes. Finally, in silico analysis was conducted to assess potential functional relevance of any polymorphisms associated with brain measures. A polymorphism located in the 39 untranslated region of NRXN1 significantly influenced white matter volumes in whole brain and frontal lobes after correcting for total brain volume, age and multiple comparisons. Follow-up in silico analysis revealed that this SNP is a putative microRNA binding site that may be of functional significance in regulating NRXN1 expression. This variant also influenced sensorimotor performance, a neurocognitive function impaired in both ASD and schizophrenia. Conclusions: Our findings demonstrate that the NRXN1 gene, a vulnerability gene for SCZ and ASD, influences brai