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  • 1
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    American Association for the Advancement of Science (AAAS)
    Publication Date: 1997-06-13
    Description: Most natural actions are accomplished with a seamless combination of individual movements. Such coordination poses a problem: How does the motor system orchestrate multiple movements to produce a single goal-directed action? The results from current experiments suggest one possible solution. Oculomotor neurons in the superior colliculus of a primate responded to mismatches between eye and target positions, even when the animal made two different types of eye movements. This neuronal activity therefore does not appear to convey a command for a specific type of eye movement but instead encodes an error signal that could be used by multiple movements. The use of shared inputs is one possible strategy for ensuring that different movements share a common goal.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Krauzlis, R J -- Basso, M A -- Wurtz, R H -- New York, N.Y. -- Science. 1997 Jun 13;276(5319):1693-5.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/9180078" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Eye Movements/*physiology ; Fixation, Ocular/physiology ; Macaca mulatta ; Motor Neurons/*physiology ; Pursuit, Smooth/physiology ; Saccades/physiology ; Superior Colliculi/cytology/*physiology ; Visual Pathways
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2008-03-26
    Description: Regulatory T cells (T(reg)) expressing the transcription factor Foxp3 control the autoreactive components of the immune system. The development of T(reg) cells is reciprocally related to that of pro-inflammatory T cells producing interleukin-17 (T(H)17). Although T(reg) cell dysfunction and/or T(H)17 cell dysregulation are thought to contribute to the development of autoimmune disorders, little is known about the physiological pathways that control the generation of these cell lineages. Here we report the identification of the ligand-activated transcription factor aryl hydrocarbon receptor (AHR) as a regulator of T(reg) and T(H)17 cell differentiation in mice. AHR activation by its ligand 2,3,7,8-tetrachlorodibenzo-p-dioxin induced functional T(reg) cells that suppressed experimental autoimmune encephalomyelitis. On the other hand, AHR activation by 6-formylindolo[3,2-b]carbazole interfered with T(reg) cell development, boosted T(H)17 cell differentiation and increased the severity of experimental autoimmune encephalomyelitis in mice. Thus, AHR regulates both T(reg) and T(H)17 cell differentiation in a ligand-specific fashion, constituting a unique target for therapeutic immunomodulation.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Quintana, Francisco J -- Basso, Alexandre S -- Iglesias, Antonio H -- Korn, Thomas -- Farez, Mauricio F -- Bettelli, Estelle -- Caccamo, Mario -- Oukka, Mohamed -- Weiner, Howard L -- AI435801/AI/NIAID NIH HHS/ -- NS38037/NS/NINDS NIH HHS/ -- P01 NS038037/NS/NINDS NIH HHS/ -- R01 AI073542/AI/NIAID NIH HHS/ -- R01 AI073542-01/AI/NIAID NIH HHS/ -- R01 AI073542-02/AI/NIAID NIH HHS/ -- R01 NS059996/NS/NINDS NIH HHS/ -- R01AI073542-01/AI/NIAID NIH HHS/ -- England -- Nature. 2008 May 1;453(7191):65-71. doi: 10.1038/nature06880. Epub 2008 Mar 23.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts 02115, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/18362915" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Carbazoles/metabolism/pharmacology ; *Cell Differentiation ; Encephalomyelitis, Autoimmune, Experimental/chemically induced/immunology ; Forkhead Transcription Factors/genetics/metabolism ; Humans ; Indoles/metabolism/pharmacology ; Interleukin-17/*metabolism ; Ligands ; Mice ; Mice, Inbred C57BL ; Receptors, Aryl Hydrocarbon/genetics/*metabolism ; T-Lymphocytes, Helper-Inducer/*cytology/drug effects/*metabolism ; T-Lymphocytes, Regulatory/*cytology/drug effects/*metabolism ; Tetrachlorodibenzodioxin/metabolism/pharmacology ; Transforming Growth Factor beta1/immunology/metabolism
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 3
    Publication Date: 2013-11-23
    Description: Oxamniquine resistance evolved in the human blood fluke (Schistosoma mansoni) in Brazil in the 1970s. We crossed parental parasites differing ~500-fold in drug response, determined drug sensitivity and marker segregation in clonally derived second-generation progeny, and identified a single quantitative trait locus (logarithm of odds = 31) on chromosome 6. A sulfotransferase was identified as the causative gene by using RNA interference knockdown and biochemical complementation assays, and we subsequently demonstrated independent origins of loss-of-function mutations in field-derived and laboratory-selected resistant parasites. These results demonstrate the utility of linkage mapping in a human helminth parasite, while crystallographic analyses of protein-drug interactions illuminate the mode of drug action and provide a framework for rational design of oxamniquine derivatives that kill both S. mansoni and S. haematobium, the two species responsible for 〉99% of schistosomiasis cases worldwide.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4136436/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4136436/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Valentim, Claudia L L -- Cioli, Donato -- Chevalier, Frederic D -- Cao, Xiaohang -- Taylor, Alexander B -- Holloway, Stephen P -- Pica-Mattoccia, Livia -- Guidi, Alessandra -- Basso, Annalisa -- Tsai, Isheng J -- Berriman, Matthew -- Carvalho-Queiroz, Claudia -- Almeida, Marcio -- Aguilar, Hector -- Frantz, Doug E -- Hart, P John -- LoVerde, Philip T -- Anderson, Timothy J C -- 098051/Wellcome Trust/United Kingdom -- 5R21-AI072704/AI/NIAID NIH HHS/ -- 5R21-AI096277/AI/NIAID NIH HHS/ -- C06 RR013556/RR/NCRR NIH HHS/ -- HHSN272201000005I/PHS HHS/ -- R01 AI097576/AI/NIAID NIH HHS/ -- R01-AI097576/AI/NIAID NIH HHS/ -- R21 AI072704/AI/NIAID NIH HHS/ -- R21 AI096277/AI/NIAID NIH HHS/ -- New York, N.Y. -- Science. 2013 Dec 13;342(6164):1385-9. doi: 10.1126/science.1243106. Epub 2013 Nov 21.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Departments of Biochemistry and Pathology, University of Texas Health Science Center, San Antonio, TX 78229, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24263136" target="_blank"〉PubMed〈/a〉
    Keywords: Amino Acid Sequence ; Animals ; Drug Resistance/*genetics ; Gene Knockdown Techniques ; Genetic Linkage ; Helminth Proteins/*genetics ; Humans ; Molecular Sequence Data ; Mutation ; Oxamniquine/*pharmacology ; Phylogeny ; Protein Conformation ; Quantitative Trait Loci ; RNA Interference ; Schistosoma mansoni/*drug effects/*genetics ; Schistosomicides/*pharmacology ; Sulfotransferases/chemistry/classification/*genetics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 4
    Publication Date: 2010-12-24
    Description: Chromatin is composed of DNA and a variety of modified histones and non-histone proteins, which have an impact on cell differentiation, gene regulation and other key cellular processes. Here we present a genome-wide chromatin landscape for Drosophila melanogaster based on eighteen histone modifications, summarized by nine prevalent combinatorial patterns. Integrative analysis with other data (non-histone chromatin proteins, DNase I hypersensitivity, GRO-Seq reads produced by engaged polymerase, short/long RNA products) reveals discrete characteristics of chromosomes, genes, regulatory elements and other functional domains. We find that active genes display distinct chromatin signatures that are correlated with disparate gene lengths, exon patterns, regulatory functions and genomic contexts. We also demonstrate a diversity of signatures among Polycomb targets that include a subset with paused polymerase. This systematic profiling and integrative analysis of chromatin signatures provides insights into how genomic elements are regulated, and will serve as a resource for future experimental investigations of genome structure and function.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3109908/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3109908/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kharchenko, Peter V -- Alekseyenko, Artyom A -- Schwartz, Yuri B -- Minoda, Aki -- Riddle, Nicole C -- Ernst, Jason -- Sabo, Peter J -- Larschan, Erica -- Gorchakov, Andrey A -- Gu, Tingting -- Linder-Basso, Daniela -- Plachetka, Annette -- Shanower, Gregory -- Tolstorukov, Michael Y -- Luquette, Lovelace J -- Xi, Ruibin -- Jung, Youngsook L -- Park, Richard W -- Bishop, Eric P -- Canfield, Theresa K -- Sandstrom, Richard -- Thurman, Robert E -- MacAlpine, David M -- Stamatoyannopoulos, John A -- Kellis, Manolis -- Elgin, Sarah C R -- Kuroda, Mitzi I -- Pirrotta, Vincenzo -- Karpen, Gary H -- Park, Peter J -- R01 GM071923/GM/NIGMS NIH HHS/ -- R01 GM082798/GM/NIGMS NIH HHS/ -- R01 HG004037/HG/NHGRI NIH HHS/ -- R37 GM45744/GM/NIGMS NIH HHS/ -- RC1 HG005334/HG/NHGRI NIH HHS/ -- RC2 HG005639/HG/NHGRI NIH HHS/ -- U01 HG004258/HG/NHGRI NIH HHS/ -- U01 HG004258-04/HG/NHGRI NIH HHS/ -- U01 HG004279/HG/NHGRI NIH HHS/ -- U01HG004258/HG/NHGRI NIH HHS/ -- U54 HG004592/HG/NHGRI NIH HHS/ -- England -- Nature. 2011 Mar 24;471(7339):480-5. doi: 10.1038/nature09725. Epub 2010 Dec 22.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02115, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21179089" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Cell Line ; Chromatin/*genetics/*metabolism ; Chromatin Immunoprecipitation ; Chromosomal Proteins, Non-Histone/analysis/metabolism ; Deoxyribonuclease I/metabolism ; Drosophila Proteins/genetics ; Drosophila melanogaster/embryology/*genetics/growth & development ; Exons/genetics ; Gene Expression Regulation/genetics ; Genes, Insect/genetics ; Genome, Insect/genetics ; Histones/chemistry/metabolism ; Male ; Molecular Sequence Annotation ; Oligonucleotide Array Sequence Analysis ; Polycomb Repressive Complex 1 ; RNA/analysis/genetics ; Sequence Analysis ; Transcription, Genetic/genetics
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    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 5
    Publication Date: 1996-09-13
    Description: The neuropeptide corticotropin-releasing factor (CRF) is well known to act on the central nervous system in ways that mimic stress and result in decreases in exploration, increases in sympathetic activity, decreases in parasympathetic outflow, and decreases in appetitive behavior. Urocortin, a neuropeptide related to CRF, binds with high affinity to the CRF2 receptor, is more potent than CRF in suppressing appetite, but is less potent than CRF in producing anxiety-like effects and activation. Doses as low as 10 nanograms injected intracerebroventricularly were effective in decreasing food intake in food-deprived and free-feeding rats. These results suggest that urocortin may be an endogenous CRF-like factor in the brain responsible for the effects of stress on appetite.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Spina, M -- Merlo-Pich, E -- Chan, R K -- Basso, A M -- Rivier, J -- Vale, W -- Koob, G F -- 1 F05 TW05262/TW/FIC NIH HHS/ -- DK 26741/DK/NIDDK NIH HHS/ -- New York, N.Y. -- Science. 1996 Sep 13;273(5281):1561-4.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Neuropharmacology, Scripps Research Institute, 10666 North Torrey Pines Road, La Jolla, CA 92037, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/8703220" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Appetite/*drug effects ; Appetite Depressants/administration & dosage/metabolism/*pharmacology ; Behavior, Animal/drug effects ; Blood Pressure/drug effects ; Carrier Proteins/metabolism ; Corticotropin-Releasing Hormone/administration & dosage/metabolism/*pharmacology ; Dose-Response Relationship, Drug ; Eating/drug effects ; Fasting ; Injections, Intraventricular ; Motor Activity/drug effects ; Rats ; Rats, Wistar ; Receptors, Corticotropin-Releasing Hormone/metabolism ; Urocortins ; Urotensins/pharmacology
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 6
    Publication Date: 2019-07-13
    Description: Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop model scan give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 2438 for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN28990 , Global Change Biology; 21; 2; 911-925
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  • 7
    Publication Date: 2019-07-13
    Description: AgMIP (www.agmip.org) is an international community of climate, crop, livestock, economics, and IT experts working to further the development and application of multi-model, multi-scale, multi-disciplinary agricultural models that can inform policy and decision makers around the world. This meeting will engage the AGU community by providing a brief overview of AgMIP, in particular its new plans for a Coordinated Global and Regional Assessment of climate change impacts on agriculture and food security for AR6. This Town Hall will help identify opportunities for participants to become involved in AgMIP and its 30+ activities.
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN28978 , AGU Fall Meeting 2015; Dec 14, 2015 - Dec 18, 2015; San Francisco, CA; United States
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  • 8
    Publication Date: 2019-07-13
    Description: Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN46910 , Agricultural Systems (ISSN 0308-521X)
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  • 9
    Publication Date: 2019-07-13
    Description: Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1,3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN14953 , Nature Climate Change; 3; 827-832
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  • 10
    Publication Date: 2019-07-13
    Description: We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.
    Keywords: Meteorology and Climatology; Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN37260 , Agricultural Systems (ISSN 0308-521X)
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