Healthy lifestyle interventions to combat noncommunicable disease : a novel nonhierarchical connectivity model for key stakeholders : a policy statement from the American Heart Association, European Society of Cardiology, European Association for Cardiovascular Prevention and Rehabilitation, and American College of Preventive Medicine

© 2015 Mayo Foundation for Medical Education and Research, and the European Society of Cardiology. This article is being published concurrently in Mayo Clinic Proceedings [1]. The articles are identical except for minor stylistic and spelling differences in keeping with each journal's style. Either citation can be used when citing this article. [1] Arena R, Guazzi M, Lianov L, Whitsel L, Berra K, Lavie CJ, Kaminsky L, Williams M, Hivert M-F, Franklin NC, Myers J, Dengel D, Lloyd-Jones DM, Pinto FJ, Cosentino F, Halle M, Gielen S, Dendale P, Niebauer J, Pelliccia A, Giannuzzi P, Corra U, Piepoli MF, Guthrie G, Shurney D. Healthy Lifestyle Interventions to Combat Noncommunicable Diseased - A Novel Nonhierarchical Connectivity Model for Key Stakeholders: A Policy Statement From the American Heart Association, European Society of Cardiology, European Association for Cardiovascular Prevention and Rehabilitation, and American College of Preventive Medicine. Mayo Clinic Proceedings 2015; DOI: 10.1016/j.mayocp.2015.05.001 [In Press]Noncommunicable diseases (NCDs) have become the primary health concern for most countries around the world. Currently, more than 36 million people worldwide die from NCDs each year, accounting for 63% of annual global deaths; most are preventable. The global financial burden of NCDs is staggering, with an estimated 2010 global cost of $6.3 trillion (US dollars) that is projected to increase to$13 trillion by 2030. A number of NCDs share one or more common predisposing risk factors, all related to lifestyle to some degree: (1) cigarette smoking, (2) hypertension, (3) hyperglycemia, (4) dyslipidemia, (5) obesity, (6) physical inactivity, and (7) poor nutrition. In large part, prevention, control, or even reversal of the aforementioned modifiable risk factors are realized through leading a healthy lifestyle (HL). The challenge is how to initiate the global change, not toward increasing documentation of the scope of the problem but toward true action-creating, implementing, and sustaining HL initiatives that will result in positive, measurable changes in the previously defined poor health metrics. To achieve this task, a paradigm shift in how we approach NCD prevention and treatment is required. The goal of this American Heart Association/European Society of Cardiology/European Association for Cardiovascular Prevention and Rehabilitation/American College of Preventive Medicine policy statement is to define key stakeholders and highlight their connectivity with respect to HL initiatives. This policy encourages integrated action by all stakeholders to create the needed paradigm shift and achieve broad adoption of HL behaviors on a global scale.info:eu-repo/semantics/publishedVersio

Risk-taking in disorders of natural and drug rewards: neural correlates and effects of probability, valence, and magnitude.

Pathological behaviors toward drugs and food rewards have underlying commonalities. Risk-taking has a fourfold pattern varying as a function of probability and valence leading to the nonlinearity of probability weighting with overweighting of small probabilities and underweighting of large probabilities. Here we assess these influences on risk-taking in patients with pathological behaviors toward drug and food rewards and examine structural neural correlates of nonlinearity of probability weighting in healthy volunteers. In the anticipation of rewards, subjects with binge eating disorder show greater risk-taking, similar to substance-use disorders. Methamphetamine-dependent subjects had greater nonlinearity of probability weighting along with impaired subjective discrimination of probability and reward magnitude. Ex-smokers also had lower risk-taking to rewards compared with non-smokers. In the anticipation of losses, obesity without binge eating had a similar pattern to other substance-use disorders. Obese subjects with binge eating also have impaired discrimination of subjective value similar to that of the methamphetamine-dependent subjects. Nonlinearity of probability weighting was associated with lower gray matter volume in dorsolateral and ventromedial prefrontal cortex and orbitofrontal cortex in healthy volunteers. Our findings support a distinct subtype of binge eating disorder in obesity with similarities in risk-taking in the reward domain to substance use disorders. The results dovetail with the current approach of defining mechanistically based dimensional approaches rather than categorical approaches to psychiatric disorders. The relationship to risk probability and valence may underlie the propensity toward pathological behaviors toward different types of rewards.This is the final version. It was first published by NPG at http://www.nature.com/npp/journal/v40/n4/full/npp2014242a.htm

Perceptions About Work/Life Balance Among DU Community Members with Young Children

Background: In the past fifty years, families in the USA have changed in configuration, size and dynamics. The percentage of families that do not conform to the traditional family unit (married mother and father with children) has increased as there are more single-parent families, LGBTQ families and interracial families. The proportion of unmarried or divorced families has also increased, as it has the number of married and unmarried couples that opt to not have children and, additionally, more couples are opting for adoption and foster parenting (Pew Research Center 2010). Furthermore, the percentage of households where all the adults work has increased, which impacts the amount and quality of time available for family activities and household chores (Bianchi, Robinson and Milkie 2006). These and other trends have led to the identification of “work-family balance” as an important challenge of our times, one that families have been facing for decades and that institutions are only starting to pay attention to (Hochschild 2013). Although there are many aspects of family life that are challenging to balance with workplace demands, childcare has been specifically identified as one that needs attention (Desilver 2014). Methods: Study goal: To describe the perceptions that some DU community members with children have about work-family balance with attention to challenges, difficulties and institutional responses. Study design: Descriptive, cross-sectional, qualitative study. Population and sample: We recruited 63 University of Denver students (13), staff (14) and faculty (36) who are responsible of parenting at least one child under 10 years of age. We used purposive sampling. which consists in actively finding individuals who meet the criteria. Data collection: Semi structured interviews (January 23-February 8, 2017), in person, audio recorded and transcribed within one week. Participants’ autonomy, confidentiality and anonymity were protected throughout the process. Data analysis: Thematic analysis, which consists in the systematic identification of themes in the interview transcripts, followed by their conceptual organization and hierarchization. Research team: sixty-six undergraduate students taking Cultural Anthropology (ANTH 2010) in winter 2017, four graduate teaching assistants and one course instructor. Findings: Student participants portrayed work/life balance as set of interconnected situations and relations that go from the deeply personal to the interpersonal, communal and institutional. Aiming at capturing such complexity, we organized our findings in four themes: work/life balance, family dynamics, personal challenges and support. Participants told us about their struggles when negotiating work and life responsibilities which often lead to feelings of guilt, which are mediated by their colleagues’ reactions, schedule flexibility, their job situation and the presence or absence of maternity leave. Family dynamics reflected a tension between a narrative of independence and one of dependence in raising children, highlighting the importance of social networks, both of which are also affected by immigration status and intra-household negotiations particularly, Perceptions about work/life balance among DU community members with young children Cultural Anthropology (ANTH 2010) winter 2017 4 with their partners. Personal challenges relate primarily with time management and establishing clear boundaries between work and family, which related to managing emails, organization and scheduling of activities, maintaining a financial balance, and solving transportation needs, all of which were mediated the ability parents have of controlling a flexible work schedule, an ability greatly diminished among students. Support parents need related to child care goes from the one that happens in interpersonal interactions with neighbors, friends, relatives and colleagues, to the institutionalized forms of support, where participants expressed their frustration for the insufficiency of accessible options in Denver, the lack of options at DU, and the inaccessibility of DU’s Fisher Early Learning Center. Conclusions and recommendations: Participant’s ability to control their schedules together with their financial and social capital seem to shape important differences in the ability that parents have for balancing work and life. Students, single parents and recent immigrants seem to have a combination of elements that add to the challenges. At the interpersonal level, simple acts of kindness, sympathy and empathy in the everyday interactions seem to make an important difference to parents. The perception that many of the student participants expressed about the academy not being comfortable with children, families or parents could be addressed by making it normal to talk about all these aspects of life. At the institutional level, efforts could be made at reaching out to parents, especially students and single parents, to offer them guidance and support that is already in place at DU, such as counselling and wellbeing resources, as well as orientation related to institutional policies. Policies related to maternity and paternity leave should be refined to ensure that they do not negatively affect those they are supposed to support. Convenient, affordable and sustainable on-campus child care options should be seriously considered given that they would enhance the possibilities for parents to participate in activities at DU. Events should be organized where members of the DU community have the opportunity to share not as students, staff or faculty, but as members of families

Comprehensive review:Computational modelling of Schizophrenia

Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behavior (e.g. Bayesian models - top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist and neural networks - bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i.e. understanding behavioral vs. neurobiological anomalies) about the nature of the disorder. As such, these computational studies have mostly supported diverging hypotheses of schizophrenia's pathophysiology, resulting in a literature that is not always expanding coherently. Some of these hypotheses are however ripe for revision using novel empirical evidence.Here we present a review that first synthesizes the literature of computational modelling for schizophrenia and psychotic symptoms into categories supporting the dopamine, glutamate, GABA, dysconnection and Bayesian inference hypotheses respectively. Secondly, we compare model predictions against the accumulated empirical evidence and finally we identify specific hypotheses that have been left relatively under-investigated

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Climate seasonality limits leaf carbon assimilation and wood productivity in tropical forests

The seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and 35 litter productivity measurements), their associated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonality in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rainfall is  < 2000 mm yr⁻¹ (water-limited forests) and to radiation otherwise (light-limited forests). On the other hand, independent of climate limitations, wood productivity and litterfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosynthetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest productivity in a drier climate in water-limited forest, and in current light-limited forest with future rainfall  < 2000 mm yr⁻¹

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease