134 research outputs found

    Antigenic and genetic characterization of a divergent African virus, Ikoma lyssavirus

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    In 2009, a novel lyssavirus (subsequently named Ikoma lyssavirus, IKOV) was detected in the brain of an African civet (Civettictis civetta) with clinical rabies in the Serengeti National Park of Tanzania. The degree of nucleotide divergence between the genome of IKOV and those of other lyssaviruses predicted antigenic distinction from, and lack of protection provided by, available rabies vaccines. In addition, the index case was considered likely to be an incidental spillover event, and therefore the true reservoir of IKOV remained to be identified. The advent of sensitive molecular techniques has led to a rapid increase in the discovery of novel viruses. Detecting viral sequence alone, however, only allows for prediction of phenotypic characteristics and not their measurement. In the present study we describe the in vitro and in vivo characterization of IKOV, demonstrating that it is (1) pathogenic by peripheral inoculation in an animal model, (2) antigenically distinct from current rabies vaccine strains and (3) poorly neutralized by sera from humans and animals immunized against rabies. In a laboratory mouse model, no protection was elicited by a licensed rabies vaccine. We also investigated the role of bats as reservoirs of IKOV. We found no evidence for infection among 483 individuals of at least 13 bat species sampled across sites in the Serengeti and Southern Kenya

    Neural dynamics of error processing in medial frontal cortex.

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    Contains fulltext : 56338.pdf (publisher's version ) (Closed access)Adaptive behavior requires an organism to evaluate the outcome of its actions, such that future behavior can be adjusted accordingly and the appropriate response selected. During associative learning, the time at which such evaluative information is available changes as learning progresses, from the delivery of performance feedback early in learning to the execution of the response itself during learned performance. Here, we report a learning-dependent shift in the timing of activation in the rostral cingulate zone of the anterior cingulate cortex from external error feedback to internal error detection. This pattern of activity is seen only in the anterior cingulate, not in the presupplementary motor area. The dynamics of these reciprocal changes are consistent with the claim that the rostral cingulate zone is involved in response selection on the basis of the expected outcome of an action. Specifically, these data illustrate how the anterior cingulate receives evaluative information, indicating that an action has not produced the desired result

    Pathogenesis of bat rabies in a natural reservoir: Comparative susceptibility of the straw-colored fruit bat (Eidolon helvum) to three strains of Lagos bat virus.

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    Rabies is a fatal neurologic disease caused by lyssavirus infection. People are infected through contact with infected animals. The relative increase of human rabies acquired from bats calls for a better understanding of lyssavirus infections in their natural hosts. So far, there is no experimental model that mimics natural lyssavirus infection in the reservoir bat species. Lagos bat virus is a lyssavirus that is endemic in straw-colored fruit bats (Eidolon helvum) in Africa. Here we compared the susceptibility of these bats to three strains of Lagos bat virus (from Senegal, Nigeria, and Ghana) by intracranial inoculation. To allow comparison between strains, we ensured the same titer of virus was inoculated in the same location of the brain of each bat. All bats (n = 3 per strain) were infected, and developed neurological signs, and fatal meningoencephalitis with lyssavirus antigen expression in neurons. There were three main differences among the groups. First, time to death was substantially shorter in the Senegal and Ghana groups (4 to 6 days) than in the Nigeria group (8 days). Second, each virus strain produced a distinct clinical syndrome. Third, the spread of virus to peripheral tissues, tested by hemi-nested reverse transcriptase PCR, was frequent (3 of 3 bats) and widespread (8 to 10 tissues positive of 11 tissues examined) in the Ghana group, was frequent and less widespread in the Senegal group (3/3 bats, 3 to 6 tissues positive), and was rare and restricted in the Nigeria group (1/3 bats, 2 tissues positive). Centrifugal spread of virus from brain to tissue of excretion in the oral cavity is required to enable lyssavirus transmission. Therefore, the Senegal and Ghana strains seem most suitable for further pathogenesis, and for transmission, studies in the straw-colored fruit bat

    NRQCD matrix elements in polarization of J-Psi produced from b-decay

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    We present the non-relativistic QCD (NRQCD) prediction for the polarization of the J-Psi produced in b to J-Psi + X, as well as the helicity-summed production rate. We propose that these observables provide a means of measuring the three most important color-octet NRQCD matrix elements involved in J-Psi production. Anticipating the measurement of the polarization parameter alpha, we determine its expected range given current experimental bounds on the color-octet matrix elements.Comment: 9 pages, Revtex, 2 figure

    Obstetric Outcomes in Women with Rheumatic Disease and COVID-19 in the Context of Vaccination Status

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    OBJECTIVE: To describe obstetric outcomes based on COVID-19 vaccination status, in women with rheumatic and musculoskeletal diseases (RMDs) who developed COVID-19 during pregnancy. METHODS: Data regarding pregnant women entered into the COVID-19 Global Rheumatology Alliance registry from 24 March 2020-25 February 2022 were analysed. Obstetric outcomes were stratified by number of COVID-19 vaccine doses received prior to COVID-19 infection in pregnancy. Descriptive differences between groups were tested using the chi -square or Fisher's exact test. RESULTS: There were 73 pregnancies in 73 women with RMD and COVID-19. Overall, 24.7% (18) of pregnancies were ongoing, while of the 55 completed pregnancies 90.9% (50) of pregnancies resulted in livebirths. At the time of COVID-19 diagnosis, 60.3% (n = 44) of women were unvaccinated, 4.1% (n = 3) had received one vaccine dose while 35.6% (n = 26) had two or more doses. Although 83.6% (n = 61) of women required no treatment for COVID-19, 20.5% (n = 15) required hospital admission. COVID-19 resulted in delivery in 6.8% (n = 3) of unvaccinated women and 3.8% (n = 1) of fully vaccinated women. There was a greater number of preterm births (PTB) in unvaccinated women compared with fully vaccinated 29.5% (n = 13) vs 18.2%(n = 2). CONCLUSION: In this descriptive study, unvaccinated pregnant women with RMD and COVID-19 had a greater number of PTB compared with those fully vaccinated against COVID-19. Additionally, the need for COVID-19 pharmacological treatment was uncommon in pregnant women with RMD regardless of vaccination status. These results support active promotion of COVID-19 vaccination in women with RMD who are pregnant or planning a pregnancy

    A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens

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    Understanding the mechanisms by which plants trigger host defenses in response to viruses has been a challenging problem owing to the multiplicity of factors and complexity of interactions involved. The advent of genomic techniques, however, has opened the possibility to grasp a global picture of the interaction. Here, we used Arabidopsis thaliana to identify and compare genes that are differentially regulated upon infection with seven distinct (+)ssRNA and one ssDNA plant viruses. In the first approach, we established lists of genes differentially affected by each virus and compared their involvement in biological functions and metabolic processes. We found that phylogenetically related viruses significantly alter the expression of similar genes and that viruses naturally infecting Brassicaceae display a greater overlap in the plant response. In the second approach, virus-regulated genes were contextualized using models of transcriptional and protein-protein interaction networks of A. thaliana. Our results confirm that host cells undergo significant reprogramming of their transcriptome during infection, which is possibly a central requirement for the mounting of host defenses. We uncovered a general mode of action in which perturbations preferentially affect genes that are highly connected, central and organized in modules. © 2012 Rodrigo et al.This work was supported by the Spanish Ministerio de Ciencia e Innovacion (MICINN) grants BFU2009-06993 (S. F. E.) and BIO2006-13107 (C. L.) and by Generalitat Valenciana grant PROMETEO2010/016 (S. F. E.). G. R. is supported by a graduate fellowship from the Generalitat Valenciana (BFPI2007-160) and J.C. by a contract from MICINN grant TIN2006-12860. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Rodrigo Tarrega, G.; Carrera Montesinos, J.; Ruiz-Ferrer, V.; Del Toro, F.; Llave, C.; Voinnet, O.; Elena Fito, SF. (2012). A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens. PLoS ONE. 7(7):40526-40526. https://doi.org/10.1371/journal.pone.0040526S405264052677Peng, X., Chan, E. Y., Li, Y., Diamond, D. L., Korth, M. J., & Katze, M. G. (2009). Virus–host interactions: from systems biology to translational research. Current Opinion in Microbiology, 12(4), 432-438. doi:10.1016/j.mib.2009.06.003Dodds, P. N., & Rathjen, J. P. (2010). Plant immunity: towards an integrated view of plant–pathogen interactions. Nature Reviews Genetics, 11(8), 539-548. doi:10.1038/nrg2812Maule, A., Leh, V., & Lederer, C. (2002). The dialogue between viruses and hosts in compatible interactions. Current Opinion in Plant Biology, 5(4), 279-284. doi:10.1016/s1369-5266(02)00272-8Whitham, S. A., Quan, S., Chang, H.-S., Cooper, B., Estes, B., Zhu, T., … Hou, Y.-M. (2003). Diverse RNA viruses elicit the expression of common sets of genes in susceptibleArabidopsis thalianaplants. The Plant Journal, 33(2), 271-283. doi:10.1046/j.1365-313x.2003.01625.xBailer, S., & Haas, J. (2009). Connecting viral with cellular interactomes. Current Opinion in Microbiology, 12(4), 453-459. doi:10.1016/j.mib.2009.06.004Whitham, S. A., Yang, C., & Goodin, M. M. (2006). Global Impact: Elucidating Plant Responses to Viral Infection. Molecular Plant-Microbe Interactions, 19(11), 1207-1215. doi:10.1094/mpmi-19-1207MacPherson, J. I., Dickerson, J. E., Pinney, J. W., & Robertson, D. L. (2010). Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems. PLoS Computational Biology, 6(7), e1000863. doi:10.1371/journal.pcbi.1000863Jenner, R. G., & Young, R. A. (2005). Insights into host responses against pathogens from transcriptional profiling. Nature Reviews Microbiology, 3(4), 281-294. doi:10.1038/nrmicro1126Andeweg, A. C., Haagmans, B. L., & Osterhaus, A. D. (2008). Virogenomics: the virus–host interaction revisited. Current Opinion in Microbiology, 11(5), 461-466. doi:10.1016/j.mib.2008.09.010Elena, S. F., Carrera, J., & Rodrigo, G. (2011). A systems biology approach to the evolution of plant–virus interactions. Current Opinion in Plant Biology, 14(4), 372-377. doi:10.1016/j.pbi.2011.03.013Tan, S.-L., Ganji, G., Paeper, B., Proll, S., & Katze, M. G. (2007). Systems biology and the host response to viral infection. Nature Biotechnology, 25(12), 1383-1389. doi:10.1038/nbt1207-1383De la Fuente, A. (2010). From ‘differential expression’ to ‘differential networking’ – identification of dysfunctional regulatory networks in diseases. Trends in Genetics, 26(7), 326-333. doi:10.1016/j.tig.2010.05.001Albert, R. (2005). Scale-free networks in cell biology. Journal of Cell Science, 118(21), 4947-4957. doi:10.1242/jcs.02714Yu, H., Braun, P., Yildirim, M. A., Lemmens, I., Venkatesan, K., Sahalie, J., … Vidal, M. (2008). High-Quality Binary Protein Interaction Map of the Yeast Interactome Network. Science, 322(5898), 104-110. doi:10.1126/science.1158684Barabási, A.-L., & Oltvai, Z. N. (2004). Network biology: understanding the cell’s functional organization. Nature Reviews Genetics, 5(2), 101-113. doi:10.1038/nrg1272Albert, R., Jeong, H., & Barabási, A.-L. (2000). Error and attack tolerance of complex networks. Nature, 406(6794), 378-382. doi:10.1038/35019019Mukhtar, M. S., Carvunis, A.-R., Dreze, M., Epple, P., Steinbrenner, J., … Moore, J. (2011). Independently Evolved Virulence Effectors Converge onto Hubs in a Plant Immune System Network. Science, 333(6042), 596-601. doi:10.1126/science.1203659Calderwood, M. A., Venkatesan, K., Xing, L., Chase, M. R., Vazquez, A., Holthaus, A. M., … Johannsen, E. (2007). Epstein-Barr virus and virus human protein interaction maps. Proceedings of the National Academy of Sciences, 104(18), 7606-7611. doi:10.1073/pnas.0702332104De Chassey, B., Navratil, V., Tafforeau, L., Hiet, M. S., Aublin‐Gex, A., Agaugué, S., … Lotteau, V. (2008). Hepatitis C virus infection protein network. Molecular Systems Biology, 4(1), 230. doi:10.1038/msb.2008.66Shapira, S. D., Gat-Viks, I., Shum, B. O. V., Dricot, A., de Grace, M. M., Wu, L., … Hacohen, N. (2009). A Physical and Regulatory Map of Host-Influenza Interactions Reveals Pathways in H1N1 Infection. Cell, 139(7), 1255-1267. doi:10.1016/j.cell.2009.12.018Dyer, M. D., Murali, T. M., & Sobral, B. W. (2008). The Landscape of Human Proteins Interacting with Viruses and Other Pathogens. PLoS Pathogens, 4(2), e32. doi:10.1371/journal.ppat.0040032Golem, S., & Culver, J. N. (2003). Tobacco mosaic virusInduced Alterations in the Gene Expression Profile ofArabidopsis thaliana. Molecular Plant-Microbe Interactions, 16(8), 681-688. doi:10.1094/mpmi.2003.16.8.681Espinoza, C., Medina, C., Somerville, S., & Arce-Johnson, P. (2007). Senescence-associated genes induced during compatible viral interactions with grapevine and Arabidopsis. Journal of Experimental Botany, 58(12), 3197-3212. doi:10.1093/jxb/erm165Yang, C., Guo, R., Jie, F., Nettleton, D., Peng, J., Carr, T., … Whitham, S. A. (2007). Spatial Analysis ofArabidopsis thalianaGene Expression in Response toTurnip mosaic virusInfection. Molecular Plant-Microbe Interactions, 20(4), 358-370. doi:10.1094/mpmi-20-4-0358Agudelo-Romero, P., Carbonell, P., de la Iglesia, F., Carrera, J., Rodrigo, G., Jaramillo, A., … Elena, S. F. (2008). Changes in the gene expression profile of Arabidopsis thaliana after infection with Tobacco etch virus. Virology Journal, 5(1), 92. doi:10.1186/1743-422x-5-92Agudelo-Romero, P., Carbonell, P., Perez-Amador, M. A., & Elena, S. F. (2008). Virus Adaptation by Manipulation of Host’s Gene Expression. PLoS ONE, 3(6), e2397. doi:10.1371/journal.pone.0002397Ascencio-Ibáñez, J. T., Sozzani, R., Lee, T.-J., Chu, T.-M., Wolfinger, R. D., Cella, R., & Hanley-Bowdoin, L. (2008). Global Analysis of Arabidopsis Gene Expression Uncovers a Complex Array of Changes Impacting Pathogen Response and Cell Cycle during Geminivirus Infection. Plant Physiology, 148(1), 436-454. doi:10.1104/pp.108.121038Babu, M., Griffiths, J. S., Huang, T.-S., & Wang, A. (2008). Altered gene expression changes in Arabidopsis leaf tissues and protoplasts in response to Plum pox virus infection. BMC Genomics, 9(1), 325. doi:10.1186/1471-2164-9-325De Vienne, D. M., Giraud, T., & Martin, O. C. (2007). A congruence index for testing topological similarity between trees. Bioinformatics, 23(23), 3119-3124. doi:10.1093/bioinformatics/btm500Wise, R. P., Moscou, M. J., Bogdanove, A. J., & Whitham, S. A. (2007). Transcript Profiling in Host–Pathogen Interactions. Annual Review of Phytopathology, 45(1), 329-369. doi:10.1146/annurev.phyto.45.011107.143944Handford, M. G., & Carr, J. P. (2007). A defect in carbohydrate metabolism ameliorates symptom severity in virus-infected Arabidopsis thaliana. Journal of General Virology, 88(1), 337-341. doi:10.1099/vir.0.82376-0Hou, B., Lim, E.-K., Higgins, G. S., & Bowles, D. J. (2004). N-Glucosylation of Cytokinins by Glycosyltransferases ofArabidopsis thaliana. Journal of Biological Chemistry, 279(46), 47822-47832. doi:10.1074/jbc.m409569200Schwender, J., Goffman, F., Ohlrogge, J. B., & Shachar-Hill, Y. (2004). Rubisco without the Calvin cycle improves the carbon efficiency of developing green seeds. Nature, 432(7018), 779-782. doi:10.1038/nature03145Pagán, I., Alonso-Blanco, C., & García-Arenal, F. (2008). Host Responses in Life-History Traits and Tolerance to Virus Infection in Arabidopsis thaliana. PLoS Pathogens, 4(8), e1000124. doi:10.1371/journal.ppat.1000124Carrera, J., Rodrigo, G., Jaramillo, A., & Elena, S. F. (2009). Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions. Genome Biology, 10(9), R96. doi:10.1186/gb-2009-10-9-r96Geisler-Lee, J., O’Toole, N., Ammar, R., Provart, N. J., Millar, A. H., & Geisler, M. (2007). A Predicted Interactome for Arabidopsis. Plant Physiology, 145(2), 317-329. doi:10.1104/pp.107.103465Ma, S., Gong, Q., & Bohnert, H. J. (2007). An Arabidopsis gene network based on the graphical Gaussian model. Genome Research, 17(11), 1614-1625. doi:10.1101/gr.6911207Yamada, T., & Bork, P. (2009). Evolution of biomolecular networks — lessons from metabolic and protein interactions. Nature Reviews Molecular Cell Biology, 10(11), 791-803. doi:10.1038/nrm2787Humphries, M. D., & Gurney, K. (2008). Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence. PLoS ONE, 3(4), e0002051. doi:10.1371/journal.pone.0002051Stumpf, M. P. H., & Ingram, P. J. (2005). Probability models for degree distributions of protein interaction networks. Europhysics Letters (EPL), 71(1), 152-158. doi:10.1209/epl/i2004-10531-8Khanin, R., & Wit, E. (2006). How Scale-Free Are Biological Networks. Journal of Computational Biology, 13(3), 810-818. doi:10.1089/cmb.2006.13.810Daudin, J.-J., Picard, F., & Robin, S. (2007). A mixture model for random graphs. Statistics and Computing, 18(2), 173-183. doi:10.1007/s11222-007-9046-7Uetz, P. (2006). Herpesviral Protein Networks and Their Interaction with the Human Proteome. Science, 311(5758), 239-242. doi:10.1126/science.1116804Choi, I.-R., Stenger, D. C., & French, R. (2000). Multiple Interactions among Proteins Encoded by the Mite-Transmitted Wheat Streak Mosaic Tritimovirus. Virology, 267(2), 185-198. doi:10.1006/viro.1999.0117Guo, D., Saarma, M., Rajamäki, M.-L., & Valkonen, J. P. T. (2001). Towards a protein interaction map of potyviruses: protein interaction matrixes of two potyviruses based on the yeast two-hybrid system. Journal of General Virology, 82(4), 935-939. doi:10.1099/0022-1317-82-4-935Lin, L., Shi, Y., Luo, Z., Lu, Y., Zheng, H., Yan, F., … Wu, Y. (2009). Protein–protein interactions in two potyviruses using the yeast two-hybrid system. Virus Research, 142(1-2), 36-40. doi:10.1016/j.virusres.2009.01.006Shen, W., Wang, M., Yan, P., Gao, L., & Zhou, P. (2010). Protein interaction matrix of Papaya ringspot virus type P based on a yeast two-hybrid system. Acta Virologica, 54(1), 49-54. doi:10.4149/av_2010_01_49Redner, S. (2008). Teasing out the missing links. Nature, 453(7191), 47-48. doi:10.1038/453047aIrizarry, R. A. (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics, 4(2), 249-264. doi:10.1093/biostatistics/4.2.249Smyth, G. K. (2004). Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments. Statistical Applications in Genetics and Molecular Biology, 3(1), 1-25. doi:10.2202/1544-6115.1027Allemeersch, J., Durinck, S., Vanderhaeghen, R., Alard, P., Maes, R., Seeuws, K., … Kuiper, M. T. R. (2005). Benchmarking the CATMA Microarray. A Novel Tool forArabidopsis Transcriptome Analysis. Plant Physiology, 137(2), 588-601. doi:10.1104/pp.104.051300Cleveland, W. S. (1979). Robust Locally Weighted Regression and Smoothing Scatterplots. Journal of the American Statistical Association, 74(368), 829-836. doi:10.1080/01621459.1979.10481038Tarraga, J., Medina, I., Carbonell, J., Huerta-Cepas, J., Minguez, P., Alloza, E., … Dopazo, J. (2008). GEPAS, a web-based tool for microarray data analysis and interpretation. Nucleic Acids Research, 36(Web Server), W308-W314. doi:10.1093/nar/gkn303Al-Shahrour, F., Minguez, P., Vaquerizas, J. M., Conde, L., & Dopazo, J. (2005). BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments. Nucleic Acids Research, 33(Web Server), W460-W464. doi:10.1093/nar/gki456Al-Shahrour, F., Minguez, P., Tárraga, J., Medina, I., Alloza, E., Montaner, D., & Dopazo, J. (2007). FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments. Nucleic Acids Research, 35(suppl_2), W91-W96. doi:10.1093/nar/gkm260Mueller, L. A., Zhang, P., & Rhee, S. Y. (2003). AraCyc: A Biochemical Pathway Database for Arabidopsis. Plant Physiology, 132(2), 453-460. doi:10.1104/pp.102.017236Navratil, V., de Chassey, B., Combe, C., & Lotteau, V. (2011). When the human viral infectome and diseasome networks collide: towards a systems biology platform for the aetiology of human diseases. BMC Systems Biology, 5(1), 13. doi:10.1186/1752-0509-5-13Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379-423. doi:10.1002/j.1538-7305.1948.tb01338.

    The Athena X-ray Integral Field Unit (X-IFU)

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    The X-ray Integral Field Unit (X-IFU) is the high resolution X-ray spectrometer of the ESA Athena X-ray observatory. Over a field of view of 5' equivalent diameter, it will deliver X-ray spectra from 0.2 to 12 keV with a spectral resolution of 2.5 eV up to 7 keV on similar to 5 '' pixels. The X-IFU is based on a large format array of super-conducting molybdenum-gold Transition Edge Sensors cooled at similar to 90 mK, each coupled with an absorber made of gold and bismuth with a pitch of 249 mu m. A cryogenic anti-coincidence detector located underneath the prime TES array enables the non X-ray background to be reduced. A bath temperature of similar to 50 mK is obtained by a series of mechanical coolers combining 15K Pulse Tubes, 4K and 2K Joule-Thomson coolers which pre-cool a sub Kelvin cooler made of a He-3 sorption cooler coupled with an Adiabatic Demagnetization Refrigerator. Frequency domain multiplexing enables to read out 40 pixels in one single channel. A photon interacting with an absorber leads to a current pulse, amplified by the readout electronics and whose shape is reconstructed on board to recover its energy with high accuracy. The defocusing capability offered by the Athena movable mirror assembly enables the X-IFU to observe the brightest X-ray sources of the sky (up to Crab-like intensities) by spreading the telescope point spread function over hundreds of pixels. Thus the X-IFU delivers low pile-up, high throughput (> 50%), and typically 10 eV spectral resolution at 1 Crab intensities, i.e. a factor of 10 or more better than Silicon based X-ray detectors. In this paper, the current X-IFU baseline is presented, together with an assessment of its anticipated performance in terms of spectral resolution, background, and count rate capability. The X-IFU baseline configuration will be subject to a preliminary requirement review that is scheduled at the end of 2018. The X-IFU will be provided by an international consortium led by France, the Netherlands and Italy, with further ESA member state contributions from Belgium, Czech Republic, Finland, Germany, Ireland, Poland, Spain, Switzerland and contributions from Japan and the United States.Peer reviewe

    Critical care admission of South African (SA) surgical patients: Results of the SA Surgical Outcomes Study

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    Background. Appropriate critical care admissions are an important component of surgical care. However, there are few data describing postoperative critical care admission in resource-limited low- and middle-income countries.Objective. To describe the demographics, organ failures, organ support and outcomes of non-cardiac surgical patients admitted to critical care units in South Africa (SA).Methods. The SA Surgical Outcomes Study (SASOS) was a 7-day national, multicentre, prospective, observational cohort study of all patients ≥16 years of age undergoing inpatient non-cardiac surgery between 19 and 26 May 2014 at 50 government-funded hospitals. All patients admitted to critical care units during this study were included for analysis.Results. Of the 3 927 SASOS patients, 255 (6.5%) were admitted to critical care units; of these admissions, 144 (56.5%) were planned, and 111 (43.5%) unplanned. The incidence of confirmed or strongly suspected infection at the time of admission was 35.4%, with a significantly higher incidence in unplanned admissions (49.1 v. 24.8%, p<0.001). Unplanned admission cases were more frequently hypovolaemic, had septic shock, and required significantly more inotropic, ventilatory and renal support in the first 48 hours after admission. Overall mortality was 22.4%, with unplanned admissions having a significantly longer critical care length of stay and overall mortality (33.3 v. 13.9%, p<0.001).Conclusion. The outcome of patients admitted to public sector critical care units in SA is strongly associated with unplanned admissions. Adequate ‘high care-dependency units’ for postoperative care of elective surgical patients could potentially decrease the burden on critical care resources in SA by 23%. This study was registered on ClinicalTrials.gov (NCT02141867)

    White matter disturbances in major depressive disorder : a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

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    Altres ajuts: The ENIGMA-Major Depressive Disorder working group gratefully acknowledges support from the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to PMT) and NIH grant R01 MH116147 (PMT). LS is supported by an NHMRC MRFF Career Development Fellowship (APP1140764). We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. NESDA: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10-000-1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. M-JvT was supported by a VENI grant (NWO grant number 016.156.077). UCSF: This work was supported by the Brain and Behavior Research Foundation (formerly NARSAD) to TTY; the National Institute of Mental Health (R01MH085734 to TTY; K01MH117442 to TCH) and by the American Foundation for Suicide Prevention (PDF-1-064-13) to TCH. Stanford: This work was supported by NIMH Grants R01MH59259 and R37101495 to IHG. MS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. Muenster: This work was funded by the German Research Foundation (SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). Marburg: This work was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD; KI 588/ 14-1, KI 588/14-2 to TK; KR 3822/7-1, KR 3822/7-2 to AK; JA 1890/ 7-1, JA 1890/7-2 to AJ). IMH-MDD: This work was supported by the National Healthcare Group Research Grant (SIG/15012) awarded to KS. Barcelona: This study was funded by two grants of the Fondo de Investigación Sanitaria from the Instituto de Salud Carlos III, by the Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM). The author is funded through 'Miguel Servet' research contract (CP16-0020), co-financed by the European Regional Development Fund (ERDF) (2016-2019). QTIM: We thank the twins and singleton siblings who gave generously of their time to participate in the QTIM study. We also thank the many research assistants, radiographers, and IT support staff for data acquisition and DNA sample preparation. This study was funded by White matter disturbances in major depressive disorder: a coordinated analysis across 20 international. . . 1521 the National Institute of Child Health & Human Development (RO1 HD050735); National Institute of Biomedical Imaging and Bioengineering (Award 1U54EB020403-01, Subaward 56929223); National Health and Medical Research Council, Australia (Project Grants 496682, 1009064). NIH ENIGMA-BD2K U54 EB020403 (Thompson); R01 MH117601 (Jahanshad/Schmaal). Magdeburg: M.L. and M.W. are funded by SFB 779. Bipolar Family Study: This study has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013). This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award (104036/Z/14/Z). Minnesota Adolescent Depression Study: The study was funded by the National Institute of Mental Health (K23MH090421), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, the Minnesota Medical Foundation, and the Biotechnology Research Center (P41 RR008079 to the Center for Magnetic Resonance Research), University of Minnesota, and the Deborah E. Powell Center for Women's Health Seed Grant, University of Minnesota. Dublin: This study was supported by Science Foundation Ireland through a Stokes Professorhip grant to TF. MPIP: The MPIP Sample comprises patients included in the Recurrent Unipolar Depression (RUD) Case-Control study at the clinic of the Max Planck Institute of Psychiatry, Munich, German. The RUD study was supported by GlaxoSmithKline.Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD

    The Athena X-ray Integral Field Unit: a consolidated design for the system requirement review of the preliminary definition phase

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    The Athena X-ray Integral Unit (X-IFU) is the high resolution X-ray spectrometer, studied since 2015 for flying in the mid-30s on the Athena space X-ray Observatory, a versatile observatory designed to address the Hot and Energetic Universe science theme, selected in November 2013 by the Survey Science Committee. Based on a large format array of Transition Edge Sensors (TES), it aims to provide spatially resolved X-ray spectroscopy, with a spectral resolution of 2.5 eV (up to 7 keV) over an hexagonal field of view of 5 arc minutes (equivalent diameter). The X-IFU entered its System Requirement Review (SRR) in June 2022, at about the same time when ESA called for an overall X-IFU redesign (including the X-IFU cryostat and the cooling chain), due to an unanticipated cost overrun of Athena. In this paper, after illustrating the breakthrough capabilities of the X-IFU, we describe the instrument as presented at its SRR, browsing through all the subsystems and associated requirements. We then show the instrument budgets, with a particular emphasis on the anticipated budgets of some of its key performance parameters. Finally we briefly discuss on the ongoing key technology demonstration activities, the calibration and the activities foreseen in the X-IFU Instrument Science Center, and touch on communication and outreach activities, the consortium organisation, and finally on the life cycle assessment of X-IFU aiming at minimising the environmental footprint, associated with the development of the instrument. Thanks to the studies conducted so far on X-IFU, it is expected that along the design-to-cost exercise requested by ESA, the X-IFU will maintain flagship capabilities in spatially resolved high resolution X-ray spectroscopy, enabling most of the original X-IFU related scientific objectives of the Athena mission to be retained. (abridged).Comment: 48 pages, 29 figures, Accepted for publication in Experimental Astronomy with minor editin
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