Youth Can! Grow their Community: Qualitative Evaluation of a Gardening-Enhanced Positive Youth Development Program

Background: Rates of obesity and overweight for children and adolescents have remained above objectives and disproportionately affect minority youth. Diet quality is one factor related to overweight and obesity and is suboptimal for American youth. Nutrition education programs with additional components including gardening have targeted factors related to diet quality such as increasing fruit and vegetable intake and youth development strategies have been used to empower youth to make healthy changes. This study, in which participants engaged in a nutrition education and gardening program with a focus on improving the health of their community, evaluated the participants’ perceived ability to participate in research, level of intent to be involved in improving the health of their community, and perceived understanding of nutrition concepts as a result of participating in the program.Methods: Participants attended two hour-long weekly lessons for a total of eight weeks at a predominantly minority community youth center. The lessons pertained to nutrition with gardening elements, all while empowering youth and training them to design their own research. The program was evaluated using in-depth interviews with participants. The interviews were coded by two research assistants and analyzed using content analysis.Results: A total of 11 youth participated in the interviews. The interview results suggest that most participants expressed increased self-efficacy to help their community. Participants were able to describe barriers to healthy eating and provide potential solutions to these barriers, and some reported positive changes in their diet and nutrition knowledge. Although the participants designed a research project on their own, they did not seem to recognize the research experience gained from participating in the program.Discussion: The results of this program suggest that youth can gain self-efficacy to improve the health of their community as a result of participating in a gardening-enhanced nutrition education program with youth development strategies. However, participants did not appear to gain self-efficacy to engage in research. Further, participants provided useful feedback which can be used to strengthen the design of similar programs

Starving for Attention: Legitimizing Northern Ireland's Prison Hunger Strike of 1981 through the Print Media

In 1981, ten men starved themselves to death in Northern Ireland’s Maze prison to prove to the world and their government that they were not common criminals. These men were part of Republican paramilitary organizations that had plagued the land with violence for over a decade as they attempted to rid Northern Ireland of the British government’s rule. They sought to be recognized by the government as special category prisoners, thereby affirming that their offenses were of political rather than criminal nature. To legitimize their cause and actions, they chose to embark on a hunger strike to the death in the hopes of amassing enough support and acknowledgement from the public as to pressure the government into conceding their demands. However, the hunger strike ended prematurely and they were unable to achieve the support necessary for their political demands to be met. In this study, I explore the strike from the perspective of the public by analyzing its related coverage in newspapers based in Belfast and Dublin, the capitals of Northern Ireland and the Republic of Ireland respectively. In order to understand why the Republican prisoners were unsuccessful in gaining the public’s support, I sought to categorize the essential components of legitimacy for the prisoners and analyze how these components were affected through media interpretation. The compiled data demonstrate that the strike did not amass the support it had sought nor were the components of legitimacy upheld through its coverage in the papers. Ultimately this shows the potential power that the media may have to influence the public’s perception of paramilitary organizations. Because of this, this research provides an important framework for combating the future emergence of support for organizations of violence.No embarg

The Effects of Stress at Work and at Home on Inflammation and Endothelial Dysfunction

This study examined whether stress at work and at home may be related to dysregulation of inflammation and endothelial function, two important contributors to the development of cardiovascular disease. In order to explore potential biological mechanisms linking stress with cardiovascular health, we investigated cross-sectional associations between stress at work and at home with an inflammation score (n's range from 406–433) and with two endothelial biomarkers (intercellular and vascular adhesion molecules, sICAM-1 and sVCAM-1; n's range from 205–235) in a cohort of healthy US male health professionals. No associations were found between stress at work or at home and inflammation. Men with high or medium levels of stress at work had significantly higher levels of sVCAM-1 (13% increase) and marginally higher levels of sICAM-1 (9% increase), relative to those reporting low stress at work, independent of health behaviors. Men with high levels of stress at home had marginally higher levels of both sVCAM-1 and sICAM-1 than those with low stress at home. While lack of findings related to inflammation are somewhat surprising, if replicated in future studies, these findings may suggest that endothelial dysfunction is an important biological mechanism linking stress at work with cardiovascular health outcomes in men

Arizona\u27s Vulnerable Populations

Arizona’s vulnerable populations are struggling on a daily basis but usually do so in silence, undetected by traditional radar and rankings, often unaware themselves of their high risk for being pushed or pulled into a full crisis. Ineligible for financial assistance under strict eligibility guidelines, they don’t qualify as poor because vulnerable populations are not yet in full crisis. To be clear, this report is not about the “poor,” at least not in the limited sense of the word. It is about our underemployed wage earners, our single-parent households, our deployed or returning military members, our under-educated and unskilled workforce, our debt-ridden neighbors, our uninsured friends, our family members with no savings for an emergency, much less retirement

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

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

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