Mobile GIS: The Development of Spatial Analysis Tools in an Integrated Environment for Emergency Responders

Bringing GIS to the field has many limitations to the end user due to currently available mobile computing and connectivity shortcomings. Of major concern is the lack of spatial analysis and querying abilities currently available in commercial off-the-shelf (COTS) software for mobile applications. Current mobile GIS offers mapping and visualization capabilities, while providing no analytical means to discover the data spatially. Adding spatially-based analysis tools will enable emergency responders to more accurately record the state of a particular area and better understand their surroundings while collecting important field assessments. This allows for more timely and accurate assessments by emergency planners to better allocate resources in the field. This paper outlines the development of both connected or server run, and disconnected analysis tools for emergency responders in a mobile framework. The proposed tools were developed with ESRI‟s ArcGIS Server Mobile Software Development Kit utilizing server technology. They leverage the mobile application based data and internet-based services to perform these tasks. This project is focused on the development, and subsequent inclusion into, an enterprise emergency response system: PREACT

The Inflammatory Response and Cardiac Repair After Myocardial Infarction

One of the most important therapeutic targets of current cardiology practice is to determine optimal strategies for the minimization of myocardial necrosis and optimization of cardiac repair following an acute myocardial infarction. Myocardial necrosis after acute myocardial infarction induces complement activation and free radical generation, triggering a cytokine cascade initiated by tumor necrosis factor-alpha (TNF-α) release. When reperfusion of the infarcted area is initiated, intense inflammation follows. Chemokines, cytokines and the complement system play an important role in recruiting neutrophils in the ischemic and reperfused myocardium. Cytokines promote adhesive interactions between leukocytes and endothelial cells, resulting in transmigration of inflammatory cells into the site of injury. The recruited neutrophils have potent cytotoxic effects through the release of proteolytic enzymes, and they interact with adhesion molecules on cardiomyocytes. In spite of the potential injury, reperfusion enhances cardiac repair; this may be related to the inflammatory response. Monocyte chemoattractant protein (MCP)-1 is upregulated in reperfused myocardium and can induce monocyte recruitment in the infarcted area. Monocyte subsets play a role in phagocytosis of dead cardiomyocytes and in granulation tissue formation. In addition, the transforming growth factor (TGF)-β plays a crucial role in cardiac repair by suppressing inflammation. Resolution of inflammatory infiltration, containment of inflammation and the reparative response affecting the infarcted area are essential for optimal infarct healing. Here, we review the current literature on the inflammatory response and cardiac repair after myocardial infarction

Ancient DNA suggests modern wolves trace their origin to a late Pleistocene expansion from Beringia.

Grey wolves (Canis lupus) are one of the few large terrestrial carnivores that have maintained a wide geographic distribution across the Northern Hemisphere throughout the Pleistocene and Holocene. Recent genetic studies have suggested that, despite this continuous presence, major demographic changes occurred in wolf populations between the late Pleistocene and early Holocene, and that extant wolves trace their ancestry to a single late Pleistocene population. Both the geographic origin of this ancestral population and how it became widespread remain unknown. Here, we used a spatially and temporally explicit modelling framework to analyse a dataset of 90 modern and 45 ancient mitochondrial wolf genomes from across the Northern Hemisphere, spanning the last 50,000 years. Our results suggest that contemporary wolf populations trace their ancestry to an expansion from Beringia at the end of the Last Glacial Maximum, and that this process was most likely driven by Late Pleistocene ecological fluctuations that occurred across the Northern Hemisphere. This study provides direct ancient genetic evidence that long-range migration has played an important role in the population history of a large carnivore, and provides an insight into how wolves survived the wave of megafaunal extinctions at the end of the last glaciation. Moreover, because late Pleistocene grey wolves were the likely source from which all modern dogs trace their origins, the demographic history described in this study has fundamental implications for understanding the geographical origin of the dog.L.L., K.D. and G.L. were supported by the Natural Environment Research Council, UK (grant numbers NE/K005243/1, NE/K003259/1); LL was also supported by the European Research Council grant (339941‐ADAPT); A.M. and A.E. were supported by the European Research Council Consolidator grant (grant number 647787‐LocalAdaptation); L.F. and G.L. were supported by the European Research Council grant (ERC‐2013‐StG 337574‐UNDEAD); T.G. was supported by a European Research Council Consolidator grant (681396‐Extinction Genomics) & Lundbeck Foundation grant (R52‐5062); O.T. was supported by the National Science Center, Poland (2015/19/P/NZ7/03971), with funding from EU's Horizon 2020 programme under the Marie Skłodowska‐Curie grant agreement (665778) and Synthesys Project (BETAF 3062); V.P., E.P. and P.N. were supported by the Russian Science Foundation grant (N16‐18‐10265 RNF); A.P. was supported by the Max Planck Society; M.L‐G. was supported by a Czech Science Foundation grant (GAČR15‐06446S)

Ancient DNA suggests modern wolves trace their origin to a late Pleistocene expansion from Beringia.

Grey wolves (Canis lupus) are one of the few large terrestrial carnivores that have maintained a wide geographic distribution across the Northern Hemisphere throughout the Pleistocene and Holocene. Recent genetic studies have suggested that, despite this continuous presence, major demographic changes occurred in wolf populations between the late Pleistocene and early Holocene, and that extant wolves trace their ancestry to a single late Pleistocene population. Both the geographic origin of this ancestral population and how it became widespread remain unknown. Here, we used a spatially and temporally explicit modelling framework to analyse a dataset of 90 modern and 45 ancient mitochondrial wolf genomes from across the Northern Hemisphere, spanning the last 50,000 years. Our results suggest that contemporary wolf populations trace their ancestry to an expansion from Beringia at the end of the Last Glacial Maximum, and that this process was most likely driven by Late Pleistocene ecological fluctuations that occurred across the Northern Hemisphere. This study provides direct ancient genetic evidence that long-range migration has played an important role in the population history of a large carnivore, and provides an insight into how wolves survived the wave of megafaunal extinctions at the end of the last glaciation. Moreover, because late Pleistocene grey wolves were the likely source from which all modern dogs trace their origins, the demographic history described in this study has fundamental implications for understanding the geographical origin of the dog.L.L., K.D. and G.L. were supported by the Natural Environment Research Council, UK (grant numbers NE/K005243/1, NE/K003259/1); LL was also supported by the European Research Council grant (339941‐ADAPT); A.M. and A.E. were supported by the European Research Council Consolidator grant (grant number 647787‐LocalAdaptation); L.F. and G.L. were supported by the European Research Council grant (ERC‐2013‐StG 337574‐UNDEAD); T.G. was supported by a European Research Council Consolidator grant (681396‐Extinction Genomics) & Lundbeck Foundation grant (R52‐5062); O.T. was supported by the National Science Center, Poland (2015/19/P/NZ7/03971), with funding from EU's Horizon 2020 programme under the Marie Skłodowska‐Curie grant agreement (665778) and Synthesys Project (BETAF 3062); V.P., E.P. and P.N. were supported by the Russian Science Foundation grant (N16‐18‐10265 RNF); A.P. was supported by the Max Planck Society; M.L‐G. was supported by a Czech Science Foundation grant (GAČR15‐06446S)

Resolution of LPS-induced airway inflammation and goblet cell hyperplasia is independent of IL-18

BACKGROUND: The resolution of inflammatory responses in the lung has not been described in detail and the role of specific cytokines influencing the resolution process is largely unknown. METHODS: The present study was designed to describe the resolution of inflammation from 3 h through 90 d following an acute injury by a single intratracheal instillation of F344/N rats with LPS. We documented the inflammatory cell types and cytokines found in the bronchoalveolar lavage fluid (BALF), and epithelial changes in the axial airway and investigated whether IL-18 may play a role in the resolution process by reducing its levels with anti-IL-18 antibodies. RESULTS: Three major stages of inflammation and resolution were observed in the BALF during the resolution. The first stage was characterized by PMNs that increased over 3 h to 1 d and decreased to background levels by d 6–8. The second stage of inflammation was characterized by macrophage influx reaching maximum numbers at d 6 and decreasing to background levels by d 40. A third stage of inflammation was observed for lymphocytes which were elevated over d 3–6. Interestingly, IL-18 and IL-9 levels in the BALF showed a cyclic pattern with peak levels at d 4, 8, and 16 while decreasing to background levels at d 1–2, 6, and 12. Depletion of IL-18 caused decreased PMN numbers at d 2, but no changes in inflammatory cell number or type at later time points. CONCLUSION: These data suggest that IL-18 plays a role in enhancing the LPS-induced neutrophilic inflammation of the lung, but does not affect the resolution of inflammation

Spontaneous DNA damage to the nuclear genome promotes senescence,redox imbalance and aging

Accumulation of senescent cells over time contributes to aging and age-related diseases. However, what drives senescence in vivo is not clear. Here we used a genetic approach to determine if spontaneous nuclear DNA damage is sufficient to initiate senescence in mammals. Ercc1-/Δ mice with reduced expression of ERCC1-XPF endonuclease have impaired capacity to repair the nuclear genome. Ercc1-/Δ mice accumulated spontaneous, oxidative DNA damage more rapidly than wild-type (WT) mice. As a consequence, senescent cells accumulated more rapidly in Ercc1-/Δ mice compared to repair-competent animals. However, the levels of DNA damage and senescent cells in Ercc1-/Δ mice never exceeded that observed in old WT mice. Surprisingly, levels of reactive oxygen species (ROS) were increased in tissues of Ercc1-/Δ mice to an extent identical to naturally-aged WT mice. Increased enzymatic production of ROS and decreased antioxidants contributed to the elevation in oxidative stress in both Ercc1-/Δ and aged WT mice. Chronic treatment of Ercc1-/Δ mice with the mitochondrial-targeted radical scavenger XJB-5–131 attenuated oxidative DNA damage, senescence and age-related pathology. Our findings indicate that nuclear genotoxic stress arises, at least in part, due to mitochondrial-derived ROS, and this spontaneous DNA damage is sufficient to drive increased levels of ROS, cellular senescence, and the consequent age-related physiological decline

Spontaneous DNA damage to the nuclear genome promotes senescence, T redox imbalance and aging

Accumulation of senescent cells over time contributes to aging and age-related diseases. However, what drives senescence in vivo is not clear. Here we used a genetic approach to determine if spontaneous nuclear DNA damage is sufficient to initiate senescence in mammals. Ercc1-/Δ mice with reduced expression of ERCC1-XPF endonuclease have impaired capacity to repair the nuclear genome. Ercc1-/Δ mice accumulated spontaneous, oxidative DNA damage more rapidly than wild-type (WT) mice. As a consequence, senescent cells accumulated more rapidly in Ercc1-/Δ mice compared to repair-competent animals. However, the levels of DNA damage and senescent cells in Ercc1-/Δ mice never exceeded that observed in old WT mice. Surprisingly, levels of reactive oxygen species (ROS) were increased in tissues of Ercc1-/Δ mice to an extent identical to naturally-aged WT mice. Increased enzymatic production of ROS and decreased antioxidants contributed to the elevation in oxidative stress in both Ercc1-/Δ and aged WT mice. Chronic treatment of Ercc1-/Δ mice with the mitochondrial-targeted radical scavenger XJB-5–131 attenuated oxidative DNA damage, senescence and age-related pathology. Our findings indicate that nuclear genotoxic stress arises, at least in part, due to mitochondrial-derived ROS, and this spontaneous DNA damage is sufficient to drive increased levels of ROS, cellular senescence, and the consequent age-related physiological decline

Using Pre-existing Microarray Datasets to Increase Experimental Power: Application to Insulin Resistance

Although they have become a widely used experimental technique for identifying differentially expressed (DE) genes, DNA microarrays are notorious for generating noisy data. A common strategy for mitigating the effects of noise is to perform many experimental replicates. This approach is often costly and sometimes impossible given limited resources; thus, analytical methods are needed which increase accuracy at no additional cost. One inexpensive source of microarray replicates comes from prior work: to date, data from hundreds of thousands of microarray experiments are in the public domain. Although these data assay a wide range of conditions, they cannot be used directly to inform any particular experiment and are thus ignored by most DE gene methods. We present the SVD Augmented Gene expression Analysis Tool (SAGAT), a mathematically principled, data-driven approach for identifying DE genes. SAGAT increases the power of a microarray experiment by using observed coexpression relationships from publicly available microarray datasets to reduce uncertainty in individual genes' expression measurements. We tested the method on three well-replicated human microarray datasets and demonstrate that use of SAGAT increased effective sample sizes by as many as 2.72 arrays. We applied SAGAT to unpublished data from a microarray study investigating transcriptional responses to insulin resistance, resulting in a 50% increase in the number of significant genes detected. We evaluated 11 (58%) of these genes experimentally using qPCR, confirming the directions of expression change for all 11 and statistical significance for three. Use of SAGAT revealed coherent biological changes in three pathways: inflammation, differentiation, and fatty acid synthesis, furthering our molecular understanding of a type 2 diabetes risk factor. We envision SAGAT as a means to maximize the potential for biological discovery from subtle transcriptional responses, and we provide it as a freely available software package that is immediately applicable to any human microarray study

Rare variant analysis of 4241 pulmonary arterial hypertension cases from an international consortium implicates FBLN2, PDGFD, and rare de novo variants in PAH

Abstract: Background: Pulmonary arterial hypertension (PAH) is a lethal vasculopathy characterized by pathogenic remodeling of pulmonary arterioles leading to increased pulmonary pressures, right ventricular hypertrophy, and heart failure. PAH can be associated with other diseases (APAH: connective tissue diseases, congenital heart disease, and others) but often the etiology is idiopathic (IPAH). Mutations in bone morphogenetic protein receptor 2 (BMPR2) are the cause of most heritable cases but the vast majority of other cases are genetically undefined. Methods: To identify new risk genes, we utilized an international consortium of 4241 PAH cases with exome or genome sequencing data from the National Biological Sample and Data Repository for PAH, Columbia University Irving Medical Center, and the UK NIHR BioResource – Rare Diseases Study. The strength of this combined cohort is a doubling of the number of IPAH cases compared to either national cohort alone. We identified protein-coding variants and performed rare variant association analyses in unrelated participants of European ancestry, including 1647 IPAH cases and 18,819 controls. We also analyzed de novo variants in 124 pediatric trios enriched for IPAH and APAH-CHD. Results: Seven genes with rare deleterious variants were associated with IPAH with false discovery rate smaller than 0.1: three known genes (BMPR2, GDF2, and TBX4), two recently identified candidate genes (SOX17, KDR), and two new candidate genes (fibulin 2, FBLN2; platelet-derived growth factor D, PDGFD). The new genes were identified based solely on rare deleterious missense variants, a variant type that could not be adequately assessed in either cohort alone. The candidate genes exhibit expression patterns in lung and heart similar to that of known PAH risk genes, and most variants occur in conserved protein domains. For pediatric PAH, predicted deleterious de novo variants exhibited a significant burden compared to the background mutation rate (2.45×, p = 2.5e−5). At least eight novel pediatric candidate genes carrying de novo variants have plausible roles in lung/heart development. Conclusions: Rare variant analysis of a large international consortium identified two new candidate genes—FBLN2 and PDGFD. The new genes have known functions in vasculogenesis and remodeling. Trio analysis predicted that ~ 15% of pediatric IPAH may be explained by de novo variants

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security