700 research outputs found
Hydrologic and Agricultural Earth Observations and Modeling for the Water-Food Nexus
In a globalizing and rapidly-developing world, reliable, sustainable access to water and food are inextricably linked to each other and basic human rights. Achieving security and sustainability in both requires recognition of these linkages, as well as continued innovations in both science and policy. We present case studies of how Earth observations are being used in applications at the nexus of water and food security: crop monitoring in support of G20 global market assessments, water stress early warning for USAID, soil moisture monitoring for USDA's Foreign Agricultural Service, and identifying food security vulnerabilities for climate change assessments for the UN and the UK international development agency. These case studies demonstrate that Earth observations are essential for providing the data and scalability to monitor relevant indicators across space and time, as well as understanding agriculture, the hydrological cycle, and the water-food nexus. The described projects follow the guidelines for co-developing useable knowledge for sustainable development policy. We show how working closely with stakeholders is essential for transforming NASA Earth observations into accurate, timely, and relevant information for water-food nexus decision support. We conclude with recommendations for continued efforts in using Earth observations for addressing the water-food nexus and the need to incorporate the role of energy for improved food and water security assessment
Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging
Recently CMOS Active Pixels Sensors (APSs) have become a valuable alternative to amorphous Silicon and Selenium Flat Panel Imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ≤ 1.9%. The uniformity of the image quality performance has been further investigated in a typical X-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practise. Finally, in order to compare the detection capability of this novel APS with the currently used technology (i.e. FPIs), theoretical evaluation of the Detection Quantum Efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, X-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications
Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC) Toxicity Management Working Group.
Cancer immunotherapy has transformed the treatment of cancer. However, increasing use of immune-based therapies, including the widely used class of agents known as immune checkpoint inhibitors, has exposed a discrete group of immune-related adverse events (irAEs). Many of these are driven by the same immunologic mechanisms responsible for the drugs\u27 therapeutic effects, namely blockade of inhibitory mechanisms that suppress the immune system and protect body tissues from an unconstrained acute or chronic immune response. Skin, gut, endocrine, lung and musculoskeletal irAEs are relatively common, whereas cardiovascular, hematologic, renal, neurologic and ophthalmologic irAEs occur much less frequently. The majority of irAEs are mild to moderate in severity; however, serious and occasionally life-threatening irAEs are reported in the literature, and treatment-related deaths occur in up to 2% of patients, varying by ICI. Immunotherapy-related irAEs typically have a delayed onset and prolonged duration compared to adverse events from chemotherapy, and effective management depends on early recognition and prompt intervention with immune suppression and/or immunomodulatory strategies. There is an urgent need for multidisciplinary guidance reflecting broad-based perspectives on how to recognize, report and manage organ-specific toxicities until evidence-based data are available to inform clinical decision-making. The Society for Immunotherapy of Cancer (SITC) established a multidisciplinary Toxicity Management Working Group, which met for a full-day workshop to develop recommendations to standardize management of irAEs. Here we present their consensus recommendations on managing toxicities associated with immune checkpoint inhibitor therapy
The Southern Levantine pig from domestication to Romanization: A biometrical approach
Zooarchaeological research has begun to expose the long and complex history of the pig in the southern Levant. In this paper, we present the first large-scale synthesis of biometrical data from pigs and wild boar in the southern Levant from sites dating from the Paleolithic through the Islamic period. We show broad morphological change over this multi-millennium period. We find the first evidence of morphological change associated with domestication in the Pre-Pottery Neolithic C (c. 7000-6400 cal. BC), at the site of Motza. This date is contemporaneous with the first evidence from kill-off patterns and relative abundance data indicating management of morphologically wild boar. Taken together, we argue for a process of local pig domestication. We also present tentative evidence for increased body size correlating with the genetic replacement in the Iron Age, when European-derived mitochondrial haplogroups replaced those of local origin. Finally, the data indicate variability in tooth size in the Roman period (c. 63 BCE – 330 CE), suggesting the exploitation of different populations of pigs. The data suggest sophisticated management techniques underwrote the upsurge in pig husbandry in the Levant in the Classical period
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Prebiotic effects: metabolic and health benefits
The different compartments of the gastrointestinal tract are inhabited by populations of micro-organisms. By far the most important predominant populations are in the colon where a true symbiosis with the host exists that is a key for well-being and health. For such a microbiota, 'normobiosis' characterises a composition of the gut 'ecosystem' in which micro-organisms with potential health benefits predominate in number over potentially harmful ones, in contrast to 'dysbiosis', in which one or a few potentially harmful micro-organisms are dominant, thus creating a disease-prone situation. The present document has been written by a group of both academic and industry experts (in the ILSI Europe Prebiotic Expert Group and Prebiotic Task Force, respectively). It does not aim to propose a new definition of a prebiotic nor to identify which food products are classified as prebiotic but rather to validate and expand the original idea of the prebiotic concept (that can be translated in 'prebiotic effects'), defined as: 'The selective stimulation of growth and/or activity(ies) of one or a limited number of microbial genus(era)/species in the gut microbiota that confer(s) health benefits to the host.' Thanks to the methodological and fundamental research of microbiologists, immense progress has very recently been made in our understanding of the gut microbiota. A large number of human intervention studies have been performed that have demonstrated that dietary consumption of certain food products can result in statistically significant changes in the composition of the gut microbiota in line with the prebiotic concept. Thus the prebiotic effect is now a well-established scientific fact. The more data are accumulating, the more it will be recognised that such changes in the microbiota's composition, especially increase in bifidobacteria, can be regarded as a marker of intestinal health. The review is divided in chapters that cover the major areas of nutrition research where a prebiotic effect has tentatively been investigated for potential health benefits. The prebiotic effect has been shown to associate with modulation of biomarkers and activity(ies) of the immune system. Confirming the studies in adults, it has been demonstrated that, in infant nutrition, the prebiotic effect includes a significant change of gut microbiota composition, especially an increase of faecal concentrations of bifidobacteria. This concomitantly improves stool quality (pH, SCFA, frequency and consistency), reduces the risk of gastroenteritis and infections, improves general well-being and reduces the incidence of allergic symptoms such as atopic eczema. Changes in the gut microbiota composition are classically considered as one of the many factors involved in the pathogenesis of either inflammatory bowel disease or irritable bowel syndrome. The use of particular food products with a prebiotic effect has thus been tested in clinical trials with the objective to improve the clinical activity and well-being of patients with such disorders. Promising beneficial effects have been demonstrated in some preliminary studies, including changes in gut microbiota composition (especially increase in bifidobacteria concentration). Often associated with toxic load and/or miscellaneous risk factors, colon cancer is another pathology for which a possible role of gut microbiota composition has been hypothesised. Numerous experimental studies have reported reduction in incidence of tumours and cancers after feeding specific food products with a prebiotic effect. Some of these studies (including one human trial) have also reported that, in such conditions, gut microbiota composition was modified (especially due to increased concentration of bifidobacteria). Dietary intake of particular food products with a prebiotic effect has been shown, especially in adolescents, but also tentatively in postmenopausal women, to increase Ca absorption as well as bone Ca accretion and bone mineral density. Recent data, both from experimental models and from human studies, support the beneficial effects of particular food products with prebiotic properties on energy homaeostasis, satiety regulation and body weight gain. Together, with data in obese animals and patients, these studies support the hypothesis that gut microbiota composition (especially the number of bifidobacteria) may contribute to modulate metabolic processes associated with syndrome X, especially obesity and diabetes type 2. It is plausible, even though not exclusive, that these effects are linked to the microbiota-induced changes and it is feasible to conclude that their mechanisms fit into the prebiotic effect. However, the role of such changes in these health benefits remains to be definitively proven. As a result of the research activity that followed the publication of the prebiotic concept 15 years ago, it has become clear that products that cause a selective modification in the gut microbiota's composition and/or activity(ies) and thus strengthens normobiosis could either induce beneficial physiological effects in the colon and also in extra-intestinal compartments or contribute towards reducing the risk of dysbiosis and associated intestinal and systemic pathologies
Post-Transcriptional Regulation of BCL2 mRNA by the RNA-Binding Protein ZFP36L1 in Malignant B Cells
The human ZFP36 zinc finger protein family consists of ZFP36, ZFP36L1, and ZFP36L2. These proteins regulate various cellular processes, including cell apoptosis, by binding to adenine uridine rich elements in the 3′ untranslated regions of sets of target mRNAs to promote their degradation. The pro-apoptotic and other functions of ZFP36 family members have been implicated in the pathogenesis of lymphoid malignancies. To identify candidate mRNAs that are targeted in the pro-apoptotic response by ZFP36L1, we reverse-engineered a gene regulatory network for all three ZFP36 family members using the ‘maximum information coefficient’ (MIC) for target gene inference on a large microarray gene expression dataset representing cells of diverse histological origin. Of the three inferred ZFP36L1 mRNA targets that were identified, we focussed on experimental validation of mRNA for the pro-survival protein, BCL2, as a target for ZFP36L1. RNA electrophoretic mobility shift assay experiments revealed that ZFP36L1 interacted with the BCL2 adenine uridine rich element. In murine BCL1 leukemia cells stably transduced with a ZFP36L1 ShRNA lentiviral construct, BCL2 mRNA degradation was significantly delayed compared to control lentiviral expressing cells and ZFP36L1 knockdown in different cell types (BCL1, ACHN, Ramos), resulted in increased levels of BCL2 mRNA levels compared to control cells. 3′ untranslated region luciferase reporter assays in HEK293T cells showed that wild type but not zinc finger mutant ZFP36L1 protein was able to downregulate a BCL2 construct containing the BCL2 adenine uridine rich element and removal of the adenine uridine rich core from the BCL2 3′ untranslated region in the reporter construct significantly reduced the ability of ZFP36L1 to mediate this effect. Taken together, our data are consistent with ZFP36L1 interacting with and mediating degradation of BCL2 mRNA as an important target through which ZFP36L1 mediates its pro-apoptotic effects in malignant B-cells
A unified data representation theory for network visualization, ordering and coarse-graining
Representation of large data sets became a key question of many scientific
disciplines in the last decade. Several approaches for network visualization,
data ordering and coarse-graining accomplished this goal. However, there was no
underlying theoretical framework linking these problems. Here we show an
elegant, information theoretic data representation approach as a unified
solution of network visualization, data ordering and coarse-graining. The
optimal representation is the hardest to distinguish from the original data
matrix, measured by the relative entropy. The representation of network nodes
as probability distributions provides an efficient visualization method and, in
one dimension, an ordering of network nodes and edges. Coarse-grained
representations of the input network enable both efficient data compression and
hierarchical visualization to achieve high quality representations of larger
data sets. Our unified data representation theory will help the analysis of
extensive data sets, by revealing the large-scale structure of complex networks
in a comprehensible form.Comment: 13 pages, 5 figure
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Cleaning up the record on the maximal information coefficient and equitability
Unveiling relationships between crime and property in England and Wales via density scale-adjusted metrics and network tools
Scale-adjusted metrics (SAMs) are a significant achievement of the urban scaling hypothesis. SAMs remove the inherent biases of per capita measures computed in the absence of isometric allometries. However, this approach is limited to urban areas, while a large portion of the world’s population still lives outside cities and rural areas dominate land use worldwide. Here, we extend the concept of SAMs to population density scale-adjusted metrics (DSAMs) to reveal relationships among different types of crime and property metrics. Our approach allows all human environments to be considered, avoids problems in the definition of urban areas, and accounts for the heterogeneity of population distributions within urban regions. By combining DSAMs, cross-correlation, and complex network analysis, we find that crime and property types have intricate and hierarchically organized relationships leading to some striking conclusions. Drugs and burglary had uncorrelated DSAMs and, to the extent property transaction values are indicators of affluence, twelve out of fourteen crime metrics showed no evidence of specifically targeting affluence. Burglary and robbery were the most connected in our network analysis and the modular structures suggest an alternative to "zero-tolerance" policies by unveiling the crime and/or property types most likely to affect each other
HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity
The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis
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