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"Communities Maps."
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Where we live : mapping neighborhoods of kids around the globe
\"For fans of Aleksandra Mizielinska and Daniel Mizielinska's Maps, and our own Around the World series, is this illustrated map book that explores the neighborhoods of 16 kids around the world. Based on real kids and their families, the book highlights significant places in the community through the child's eyes, such as where they live, where they go to school and their favorite places to play. Where We Live is filled with fascinating stories that depict what real life is like for kids from every corner of the globe. Bruno in Antarctica has to climb out the window when the snow mound blocks his front door. Namisha lives in a small village in Zambia and has to stay home from school whenever there's a hippo sighting. And in the evenings, Anani in Ethiopia helps his mother with the coffee ceremony at their home, where the community gathers. Author Margriet Ruurs is a frequent guest speaker at international schools and an avid world traveler. The stories featured in the book are based on people she has met on her travels. The end matter includes an author's note, activities to help kids make connections between the children in the book and to their own lives, a glossary and an index. Where We Live is both a valuable resource for learning about global cultures and an insightful look at how much kids around the world have in common.\"-- Provided by publisher.
CHILDBOOK
Large-scale pathway specific polygenic risk and transcriptomic community network analysis identifies novel functional pathways in Parkinson disease
Polygenic inheritance plays a central role in Parkinson disease (PD). A priority in elucidating PD etiology lies in defining the biological basis of genetic risk. Unraveling how risk leads to disruption will yield disease-modifying therapeutic targets that may be effective. Here, we utilized a high-throughput and hypothesis-free approach to determine biological processes underlying PD using the largest currently available cohorts of genetic and gene expression data from International Parkinson’s Disease Genetics Consortium (IPDGC) and the Accelerating Medicines Partnership-Parkinson’s disease initiative (AMP-PD), among other sources. We applied large-scale gene-set specific polygenic risk score (PRS) analyses to assess the role of common variation on PD risk focusing on publicly annotated gene sets representative of curated pathways. We nominated specific molecular sub-processes underlying protein misfolding and aggregation, post-translational protein modification, immune response, membrane and intracellular trafficking, lipid and vitamin metabolism, synaptic transmission, endosomal–lysosomal dysfunction, chromatin remodeling and apoptosis mediated by caspases among the main contributors to PD etiology. We assessed the impact of rare variation on PD risk in an independent cohort of whole-genome sequencing data and found evidence for a burden of rare damaging alleles in a range of processes, including neuronal transmission-related pathways and immune response. We explored enrichment linked to expression cell specificity patterns using single-cell gene expression data and demonstrated a significant risk pattern for dopaminergic neurons, serotonergic neurons, hypothalamic GABAergic neurons, and neural progenitors. Subsequently, we created a novel way of building de novo pathways by constructing a network expression community map using transcriptomic data derived from the blood of PD patients, which revealed functional enrichment in inflammatory signaling pathways, cell death machinery related processes, and dysregulation of mitochondrial homeostasis. Our analyses highlight several specific promising pathways and genes for functional prioritization and provide a cellular context in which such work should be done.
Journal Article
Mutation of a kinase allosteric node uncouples dynamics linked to phosphotransfer
The expertise of protein kinases lies in their dynamic structure, wherein they are able to modulate cellular signaling by their phosphotransferase activity. Only a few hundreds of protein kinases regulate key processes in human cells, and protein kinases play a pivotal role in health and disease. The present study dwells on understanding the working of the protein kinase-molecular switch as an allosteric network of “communities” composed of congruently dynamic residues that make up the protein kinase core. Girvan–Newman algorithm-based community maps of the kinase domain of cAMP-dependent protein kinase A allow for a molecular explanation for the role of protein conformational entropy in its catalytic cycle. The community map of a mutant, Y204A, is analyzed vis-à-vis the wild-type protein to study the perturbations in its dynamic profile such that it interferes with transfer of the γ-phosphate to a protein substrate. Conventional biochemical measurements are used to ascertain the effect of these dynamic perturbations on the kinetic profiles of both proteins. These studies pave the way for understanding how mutations far from the kinase active site can alter its dynamic properties and catalytic function even when major structural perturbations are not obvious from static crystal structures.
Journal Article
Dynamic allostery-based molecular workings of kinase
A dense interplay between structure and dynamics underlies the working of proteins, especially enzymes. Protein kinases are molecular switches that are optimized for their regulation rather than catalytic turnover rates. Using long-simulations dynamic allostery analysis, this study describes an exploration of the dynamic kinase:peptide complex. We have used protein kinase A (PKA) as a model system as a generic prototype of the protein kinase superfamily of signaling enzymes. Our results explain the role of dynamic coupling of active-site residues that must work in coherence to provide for a successful activation or inhibition response from the kinase. Amino acid networks-based community analysis allows us to ponder the conformational entropy of the kinase:nucleotide:peptide ternary complex. We use a combination of 7 peptides that include 3 types of PKA-binding partners: Substrates, products, and inhibitors. The substrate peptides provide for dynamic insights into the enzyme:substrate complex, while the product phospho-peptide allows for accessing modes of enzyme: product release. Mapping of allosteric communities onto the PKA structure allows us to locate the more unvarying and flexible dynamic regions of the kinase. These distributions, when correlated with the structural elements of the kinase core, allow for a detailed exploration of key dynamics-based signatures that could affect peptide recognition and binding at the kinase active site. These studies provide a unique dynamic allostery-based perspective to kinase:peptide complexes that have previously been explored only in a structural or thermodynamic context.
Journal Article
Most dominant roles of insect gut bacteria: digestion, detoxification, or essential nutrient provision?
Background
The insect gut microbiota has been shown to contribute to the host’s digestion, detoxification, development, pathogen resistance, and physiology. However, there is poor information about the ranking of these roles. Most of these results were obtained with cultivable bacteria, whereas the bacterial physiology may be different between free-living and midgut-colonizing bacteria. In this study, we provided both proteomic and genomic evidence on the ranking of the roles of gut bacteria by investigating the anal droplets from a weevil,
Cryptorhynchus lapathi
.
Results
The gut lumen and the anal droplets showed qualitatively and quantitatively different subsets of bacterial communities. The results of 16S rRNA sequencing showed that the gut lumen is dominated by Proteobacteria and Bacteroidetes, whereas the anal droplets are dominated by Proteobacteria. From the anal droplets, enzymes involved in 31 basic roles that belong to 7 super roles were identified by Q-TOF MS. The cooperation between the weevil and its gut bacteria was determined by reconstructing community pathway maps, which are defined in this study. A score was used to rank the gut bacterial roles. The results from the proteomic data indicate that the most dominant role of gut bacteria is amino acid biosynthesis, followed by protein digestion, energy metabolism, vitamin biosynthesis, lipid digestion, plant secondary metabolite (PSM) degradation, and carbohydrate digestion, while the order from the genomic data is amino acid biosynthesis, vitamin biosynthesis, lipid digestion, energy metabolism, protein digestion, PSM degradation, and carbohydrate digestion. The PCA results showed that the gut bacteria form functional groups from the point of view of either the basic role or super role, and the MFA results showed that there are functional variations among gut bacteria. In addition, the variations between the proteomic and genomic data, analyzed with the HMFA method from the point of view of either the bacterial community or individual bacterial species, are presented.
Conclusion
The most dominant role of gut bacteria is essential nutrient provisioning, followed by digestion and detoxification. The weevil plays a pioneering role in diet digestion and mainly digests macromolecules into smaller molecules which are then mainly digested by gut bacteria.
Journal Article
Maximizing benefits from crowdsourced data
Crowds of people can solve some problems faster than individuals or small groups. A crowd can also rapidly generate data about circumstances affecting the crowd itself. This crowdsourced data can be leveraged to benefit the crowd by providing information or solutions faster than traditional means. However, the crowdsourced data can hardly be used directly to yield usable information. Intelligently analyzing and processing crowdsourced information can help prepare data to maximize the usable information, thus returning the benefit to the crowd. This article highlights challenges and investigates opportunities associated with mining crowdsourced data to yield useful information, as well as details how crowdsource information and technologies can be used for response-coordination when needed, and finally suggests related areas for future research.
Journal Article
Prediction of National Vegetation Classification communities in the British uplands using environmental data at multiple spatial scales, aerial images and the classifier random forest
1. High-resolution vegetation maps are a valuable resource for conservation, land management and research. In Great Britain, the National Vegetation Classification (NVC) is widely used to describe vegetation communities. NVC maps are typically produced from ground surveys which are prohibitively expensive for large areas. An approach to produce NVC maps more cost-effectively for large areas would be valuable. 2. Creation of vegetation community maps from aerial or satellite images has often had limited success as the clusters separable by spectral reflectance frequently do not correspond well to vegetation community classes. Such maps have also been produced by exploring correlations between community occurrence and environmental variables. The latter approach can have limitations where anthropogenic activities have altered the distribution of vegetation communities. We combined these two approaches and classified 24 common NVC classes of the Yorkshire Dales and an additional class 'wood' consisting of trees and bushes at a resolution of 5 m from mostly remotely sensed variables with the algorithm random forest. 3. Classification accuracy was highest when environmental variables at low and high resolution (50 and 5—10 m, respectively) were added to aerial image information aggregated to a resolution of 5 m. Low-resolution environmental variables are likely to be correlated with the dominant vegetation surrounding a location and thus could represent critical area requirements or local species pool effects, while high-resolution environmental variables represent the environmental conditions at the location. 4. Overall classification accuracy was 87—92%. The median producer's and user's class accuracies were 95% (58—100%) and 92% (67—100%), respectively. 5. Synthesis and applications. The classification accuracies achieved in this study, the number of classes differentiated, their level of detail and the resolution were high compared with those of other studies. This approach could allow the production of good-quality NVC maps for large areas. In contrast to existing maps of broad land cover types, such maps would provide more detailed vegetation community data for applications like the monitoring of vegetation in a changing climate, the study of animal—habitat relationships, conservation management or land use planning.
Journal Article
The use of visual methods to explore how children construct and assign meaning to the \self\ within two urban communities in the Western Cape, South Africa
This study aimed to explore how children construct and assign meaning to the \"self\" within two urban communities of Cape Town in South Africa. Using a child participation methodological framework data were collected using Photovoice and community maps with 54 participants between the ages of 9 and 12. Feelings of safety, social connectedness, and children's spaces were found to be central to the ways in which the participants constructed and assigned meaning to the \"self.\" The study provides implications for intervention programmes aimed at improving children's well-being to be inclusive of activities aimed at improving children's self-concept, including the construction of safe spaces for children to play, learn, and form meaningful relationships.
Journal Article
Urbanization alters the relative importance of local and landscape factors affecting plant communities in the Tokyo megacity
Plant communities are impacted by local factors (related to environmental filtering) and landscape factors (related to dispersal limitation). While many studies have shown that the relative importance of these factors in understanding plant community dynamics due to urbanization, little is known about how they are altered by urbanization—a significant threat to biodiversity. This study evaluates the relative importance of local environmental (local factors), landscape, and spatial (landscape factors) variables that influence plant communities in 34 urban green spaces comprising two different habitats (forests and grasslands) along the urban–rural gradients in the Tokyo megacity, Japan. To continuously assess the relative importance of each factor along the urban–rural gradients, we extracted 1000 landscapes within a certain range that contained several sites. Subsequently, the relative importance of each factor and urbanization rate (proportion of artificial built‐up area) were estimated for each landscape. Our study found that the relative importance of both local and landscape factors decreased, while that of local factor for native species in forest habitats and that of landscape factors for native species in grassland habitats increased. Collectively, these findings suggest that city size and habitat characteristics must be considered when predicting changes in plant communities caused by urbanization. We investigated local and landscape factors driving plant communities in the Tokyo metropolitan area. The results revealed that the drivers of plant communities change along the urban–rural gradient.
Journal Article