Recent meta-heuristic algorithms with a novel premature covergence method for determining the parameters of pv cells and modules

Currently, the incorporation of solar panels in many applications is a booming trend, which necessitates accurate simulations and analysis of their performance under different operating conditions for further decision making. In this paper, various optimization algorithms are addressed comprehensively through a comparative study and further discussions for extracting the unknown parameters. Efficient use of the iterations within the optimization process may help meta-heuristic algorithms in accelerating convergence plus attaining better accuracy for the final outcome. In this paper, a method, namely, the premature convergence method (PCM), is proposed to boost the convergence of meta-heuristic algorithms with significant improvement in their accuracies. PCM is based on updating the current position around the best-so-far solution with two-step sizes: the first is based on the distance between two individuals selected randomly from the population to encourage the exploration capability, and the second is based on the distance between the current position and the best-so-far solution to promote exploitation. In addition, PCM uses a weight variable, known also as a controlling factor, as a trade-off between the two-step sizes. The proposed method is integrated with three well-known meta-heuristic algorithms to observe its efficacy for estimating efficiently and effectively the unknown parameters of the single diode model (SDM). In addition, an RTC France Si solar cell, and three PV modules, namely, Photowatt-PWP201, Ultra 85-P, and STM6-40/36, are investigated with the improved algorithms and selected standard approaches to compare their performances in estimating the unknown parameters for those different types of PV cells and modules. The experimental results point out the efficacy of the PCM in accelerating the convergence speed with improved final outcomes

Parameters identification of pv triple-diode model using improved generalized normal distribution algorithm

To simulate the behaviors of photovoltaic (PV) systems properly, the best values of the uncertain parameters of the PV models must be identified. Therefore, this paper proposes a novel optimization framework for estimating the parameters of the triple-diode model (TDM) of PV units with different technologies. The proposed methodology is based on the generalized normal distribution optimization (GNDO) with two novel strategies: (i) a premature convergence method (PCM), and (ii) a ranking-based updating method (RUM) to accelerate the convergence by utilizing each individual in the population as much as possible. This improved version of GNDO is called ranking-based generalized normal distribution optimization (RGNDO). RGNDO is experimentally investigated on three commercial PV modules (Kyocera KC200GT, Ultra 85-P and STP 6-120/36) and a solar unit (RTC Si solar cell France), and its extracted parameters are validated based on the measured dataset points extracted at generalized operating conditions. It can be reported here that the best scores of the objective function are equal to 0.750839 mA, 28.212810 mA, 2.417084 mA, and 13.798273 mA for RTC cell, KC200GT, Ultra 85-P, and STP 6-120/36; respectively. Additionally, the principal performance of this methodology is evaluated under various statistical tests and for convergence speed, and is compared with a number of the well-known recent state-of-the-art algorithms. RGNDO is shown to outperform the other algorithms in terms of all the statistical metrics as well as convergence speed. Finally, the performance of the RGNDO is validated in various operating conditions under varied temperatures and sun irradiance levels.</p

An improved artificial jellyfish search optimizer for parameter identification of photovoltaic models

The optimization of photovoltaic (PV) systems relies on the development of an accurate model of the parameter values for the solar/PV generating units. This work proposes a modified artificial jellyfish search optimizer (MJSO) with a novel premature convergence strategy (PCS) to define effectively the unknown parameters of PV systems. The PCS works on preserving the diversity among the members of the population while accelerating the convergence toward the best solution based on two motions: (i) moving the current solution between two particles selected randomly from the population, and (ii) searching for better solutions between the best-so-far one and a random one from the population. To confirm its efficacy, the proposed method is validated on three different PV technologies and is being compared with some of the latest competitive computational frameworks. The numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy of the final results and convergence rate. In addition, to assess the performance of the proposed approach under different operation conditions for the solar cells, two additional PV modules (multi-crystalline and thin-film) are investigated, and the demonstrated scenarios highlight the utility of the proposed MJSO-based methodology.</p

Impact of Sofosbuvir and Daclatasvir therapy on the expression levels of inflammasomes in chronic hepatitis C infected patients

Background and Aim:&nbsp;&nbsp;Hepatitis C virus (HCV) infection is a leading cause of chronic hepatitis. Inflammasomes are multi-protein complexes that sense specific microbial molecules and trigger signaling cascades, leading to caspase1 activation and generation of pro-inflammatory cytokines, including IL-1β and IL-18. We aimed to investigate the expression levels of NLRP3, AIM2 and IFI16 inflammasome genes and serum levels of IL-18 in chronic HCV infected patients before treatment and after SVR12.&nbsp;Methods:&nbsp;The study included 30 chronic HCV infected patients and 30 healthy controls. The expression levels of inflammasome genes were evaluated by Quantitative real-time PCR (qPCR) and serum levels of IL-18 were evaluated by ELISA at baseline and after SVR12 with three months regimen of Sofosbuvir and Daclatasvir.&nbsp;Results:&nbsp;At baseline, the expression level of NLRP3, AIM2 and IFI16 inflammasome genes were higher in comparison to controls (p &lt; /em&gt; = 0.018, 0.000 and 0.155 respectively). In addition, the level of serum IL-18 was up regulated in comparison to controls (p &lt; /em&gt; = 0.000). After treatment, there was a statically significant decrease in the expression level of NLRP3, AIM2 and IFI16 inflammasome genes (p &lt; /em&gt; &lt; 0.0001 for all). Also, there was a statically significant down regulation in the level of serum IL-18 (p &lt; /em&gt; = 0.000).&nbsp;Conclusion:&nbsp;Direct acting antiviral (DAA) therapy not only cause viral eradication but also has an immunological restitution effect as it decreases the expression level of NLRP3, AIM2 and IFI16 inflammasome genes and serum level of IL-18. This down regulation may decrease the risk of HCC development in chronic HCV infected patients

Minimally Invasive Approach in Surgical Management of Renal Neoplasms National Cancer Institute Experience

BACKGROUND: Minimally invasive nephrectomy is considered a technically challenging procedure requiring a long learning curve to reach acceptable warm ischemia time and perioperative complications. These minimally invasive techniques result in a shorter hospital stay and less post-operative pain. AIM: This study aims to demonstrate the National Cancer Institute experience regarding the benefits of laparoscopic and robot-assisted nephrectomy over open technique. METHODS: This is a retrospective descriptive cohort study including 62 patients with renal masses treated with nephrectomy whether partial, total or radical, 26 cases were treated by minimally invasive techniques (8 robotic and 18 laparoscopic), while 36 cases were treated by open technique. Inclusion criteria were patients between 20 and 70 years with renal neoplasm without renal vein thrombosis, with tumor stage T1 or T2 N0 M0. Exclusion criteria were patients with medical comorbidities that preclude surgical management or minimally invasive techniques and patients refusing surgery in general. RESULTS: Minimally invasive nephrectomy resulted in shorter hospital stay (mean hospital stay was 2.2 days for the minimally invasive group and 3.6 days for the open group) and less post-operative pain than open technique (p &lt; 0.001 and = 0.002, respectively), while open technique resulted in shorter operation time (p = 0.039, mean operation time 147.8 min compared to 184.8 in the minimally invasive group). CONCLUSION: Minimally invasive nephrectomy (laparoscopic and robotic) resulted in less post-operative pain and shorter hospital stay compared to open technique despite consuming longer operation time which may be decreased by improving the learning curve of operating surgeons

Mapping and Introgression of QTL Involved in Fruit Shape Transgressive Segregation into 'Piel de Sapo' Melon (Cucucumis melo L.)

A mapping F-2 population from the cross 'Piel de Sapo' x PI124112 was selectively genotyped to study the genetic control of morphological fruit traits by QTL (Quantitative Trait Loci) analysis. Ten QTL were identified, five for FL (Fruit Length), two for FD (Fruit Diameter) and three for FS (Fruit Shape). At least one robust QTL per character was found, flqs8.1 (LOD = 16.85, R-2 = 34%), fdqs12.1 (LOD = 3.47, R-2 = 11%) and fsqs8.1 (LOD = 14.85, R-2 = 41%). flqs2.1 and fsqs2.1 cosegregate with gene a (andromonoecious), responsible for flower sex determination and with pleiotropic effects on FS. They display a positive additive effect (a) value, so the PI124112 allele causes an increase in FL and FS, producing more elongated fruits. Conversely, the negative a value for flqs8.1 and fsqs8.1 indicates a decrease in FL and FS, what results in rounder fruits, even if PI124112 produces very elongated melons. This is explained by a significant epistatic interaction between fsqs2.1 and fsqs8.1, where the effects of the alleles at locus a are attenuated by the additive PI124112 allele at fsqs8.1. Roundest fruits are produced by homozygous for PI124112 at fsqs8.1 that do not carry any dominant A allele at locus a (PiPiaa). A significant interaction between fsqs8.1 and fsqs12.1 was also detected, with the alleles at fsqs12.1 producing more elongated fruits. fsqs8.1 seems to be allelic to QTL discovered in other populations where the exotic alleles produce elongated fruits. This model has been validated in assays with backcross lines along 3 years and ultimately obtaining a fsqs8.1-NIL (Near Isogenic Line) in 'Piel de Sapo' background which yields round melons.This work was supported by grants AGL2009-12698-C02-02 and AGL2012-40130-C02-02 from the Spanish Ministry of Economy and Competitiveness to AJM. AD was supported by a JAE-Doc contract from CSIC, MF by a Postdoctoral contract from GRAG, IE by a fellowship from the former Spanish Ministry of Education and BZ by a fellowship from Instituto Agronomico Mediterraneo de Zaragoza (IAMZ), Spain. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Díaz Bermúdez, A.; Zarouri, B.; Fergany, M.; Eduardo, I.; Álvarez, JA.; Picó Sirvent, MB.; Monforte Gilabert, AJ. (2014). Mapping and Introgression of QTL Involved in Fruit Shape Transgressive Segregation into 'Piel de Sapo' Melon (Cucucumis melo L.). PLoS ONE. 9(8):104188-104188. https://doi.org/10.1371/journal.pone.0104188S10418810418898FAO (2014) Food and Agricultural Organization of the United Nations: FAOSTAT http://faostat3.fao.org/faostat-gateway/go/to/download/Q/QC/EFerguson, A. R. (1999). KIWIFRUIT CULTIVARS: BREEDING AND SELECTION. Acta Horticulturae, (498), 43-52. doi:10.17660/actahortic.1999.498.4Butelli, E., Titta, L., Giorgio, M., Mock, H.-P., Matros, A., Peterek, S., … Martin, C. (2008). Enrichment of tomato fruit with health-promoting anthocyanins by expression of select transcription factors. Nature Biotechnology, 26(11), 1301-1308. doi:10.1038/nbt.1506Stepansky, A., Kovalski, I., & Perl-Treves, R. (1999). Intraspecific classification of melons (Cucumis melo L.) in view of their phenotypic and molecular variation. Plant Systematics and Evolution, 217(3-4), 313-332. doi:10.1007/bf00984373José, M. A., Iban, E., Silvia, A., & Pere, A. (2005). Inheritance mode of fruit traits in melon: Heterosis for fruit shape and its correlation with genetic distance. Euphytica, 144(1-2), 31-38. doi:10.1007/s10681-005-0201-yPitrat M (2008) Melon. In: Prohens J, Nuez F, editors. Handbook of Plant Breeding, vol Vegetables I: Asteraceae, Brassicaceae, Chenopodiaceae, and Cucurbitaceae. Heidelberg: Springer, pp. 283–315.Roy, A., Bal, S. S., Fergany, M., Kaur, S., Singh, H., Malik, A. A., … Dhillon, N. P. S. (2011). Wild melon diversity in India (Punjab State). Genetic Resources and Crop Evolution, 59(5), 755-767. doi:10.1007/s10722-011-9716-3Monforte, A. J., Garcia-Mas, J., & Arus, P. (2003). Genetic variability in melon based on microsatellite variation. Plant Breeding, 122(2), 153-157. doi:10.1046/j.1439-0523.2003.00848.xEsteras, C., Formisano, G., Roig, C., Díaz, A., Blanca, J., Garcia-Mas, J., … Picó, B. (2013). SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium. Theoretical and Applied Genetics, 126(5), 1285-1303. doi:10.1007/s00122-013-2053-5Boualem, A., Fergany, M., Fernandez, R., Troadec, C., Martin, A., Morin, H., … Bendahmane, A. (2008). A Conserved Mutation in an Ethylene Biosynthesis Enzyme Leads to Andromonoecy in Melons. Science, 321(5890), 836-838. doi:10.1126/science.1159023C., P., L., H., N., G., D., B., C., D., & M., P. (2002). Genetic control of fruit shape acts prior to anthesis in melon ( Cucumis melo L.). Molecular Genetics and Genomics, 266(6), 933-941. doi:10.1007/s00438-001-0612-yMonforte, A. J., Oliver, M., Gonzalo, M. J., Alvarez, J. M., Dolcet-Sanjuan, R., & Arús, P. (2003). Identification of quantitative trait loci involved in fruit quality traits in melon (Cucumis melo L.). Theoretical and Applied Genetics, 108(4), 750-758. doi:10.1007/s00122-003-1483-xEduardo, I., Arús, P., Monforte, A. J., Obando, J., Fernández-Trujillo, J. P., Martínez, J. A., … van der Knaap, E. (2007). Estimating the Genetic Architecture of Fruit Quality Traits in Melon Using a Genomic Library of Near Isogenic Lines. Journal of the American Society for Horticultural Science, 132(1), 80-89. doi:10.21273/jashs.132.1.80Paris, M. K., Zalapa, J. E., McCreight, J. D., & Staub, J. E. (2008). Genetic dissection of fruit quality components in melon (Cucumis melo L.) using a RIL population derived from exotic × elite US Western Shipping germplasm. Molecular Breeding, 22(3), 405-419. doi:10.1007/s11032-008-9185-3Fernández-Silva, I., Moreno, E., Eduardo, I., Arús, P., Álvarez, J. M., & Monforte, A. J. (2008). On the Genetic Control of Heterosis for Fruit Shape in Melon (Cucumis Melo L.). Journal of Heredity, 100(2), 229-235. doi:10.1093/jhered/esn075Fernandez-Silva, I., Moreno, E., Essafi, A., Fergany, M., Garcia-Mas, J., Martín-Hernandez, A. M., … Monforte, A. J. (2010). Shaping melons: agronomic and genetic characterization of QTLs that modify melon fruit morphology. Theoretical and Applied Genetics, 121(5), 931-940. doi:10.1007/s00122-010-1361-2Tomason, Y., Nimmakayala, P., Levi, A., & Reddy, U. K. (2013). Map-based molecular diversity, linkage disequilibrium and association mapping of fruit traits in melon. Molecular Breeding, 31(4), 829-841. doi:10.1007/s11032-013-9837-9Syvänen, A.-C. (2001). Accessing genetic variation: genotyping single nucleotide polymorphisms. Nature Reviews Genetics, 2(12), 930-942. doi:10.1038/35103535Davey, J. W., Hohenlohe, P. A., Etter, P. D., Boone, J. Q., Catchen, J. M., & Blaxter, M. L. (2011). Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nature Reviews Genetics, 12(7), 499-510. doi:10.1038/nrg3012Fridman, E., Pleban, T., & Zamir, D. (2000). A recombination hotspot delimits a wild-species quantitative trait locus for tomato sugar content to 484 bp within an invertase gene. Proceedings of the National Academy of Sciences, 97(9), 4718-4723. doi:10.1073/pnas.97.9.4718Frary, A. (2000). fw2.2: A Quantitative Trait Locus Key to the Evolution of Tomato Fruit Size. Science, 289(5476), 85-88. doi:10.1126/science.289.5476.85Liu, J., Van Eck, J., Cong, B., & Tanksley, S. D. (2002). A new class of regulatory genes underlying the cause of pear-shaped tomato fruit. Proceedings of the National Academy of Sciences, 99(20), 13302-13306. doi:10.1073/pnas.162485999Cong, B., Barrero, L. S., & Tanksley, S. D. (2008). Regulatory change in YABBY-like transcription factor led to evolution of extreme fruit size during tomato domestication. Nature Genetics, 40(6), 800-804. doi:10.1038/ng.144Xiao, H., Jiang, N., Schaffner, E., Stockinger, E. J., & van der Knaap, E. (2008). A Retrotransposon-Mediated Gene Duplication Underlies Morphological Variation of Tomato Fruit. Science, 319(5869), 1527-1530. doi:10.1126/science.1153040Li, C. (2006). Rice Domestication by Reducing Shattering. Science, 311(5769), 1936-1939. doi:10.1126/science.1123604Yano, M., Katayose, Y., Ashikari, M., Yamanouchi, U., Monna, L., Fuse, T., … Sasaki, T. (2000). Hd1, a Major Photoperiod Sensitivity Quantitative Trait Locus in Rice, Is Closely Related to the Arabidopsis Flowering Time Gene CONSTANS. The Plant Cell, 12(12), 2473-2483. doi:10.1105/tpc.12.12.2473Takahashi, Y., Shomura, A., Sasaki, T., & Yano, M. (2001). Hd6, a rice quantitative trait locus involved in photoperiod sensitivity, encodes the   subunit of protein kinase CK2. Proceedings of the National Academy of Sciences, 98(14), 7922-7927. doi:10.1073/pnas.111136798Kojima, S., Takahashi, Y., Kobayashi, Y., Monna, L., Sasaki, T., Araki, T., & Yano, M. (2002). Hd3a, a Rice Ortholog of the Arabidopsis FT Gene, Promotes Transition to Flowering Downstream of Hd1 under Short-Day Conditions. Plant and Cell Physiology, 43(10), 1096-1105. doi:10.1093/pcp/pcf156Doi, K. (2004). Ehd1, a B-type response regulator in rice, confers short-day promotion of flowering and controls FT-like gene expression independently of Hd1. Genes & Development, 18(8), 926-936. doi:10.1101/gad.1189604Doebley, J., Stec, A., & Hubbard, L. (1997). The evolution of apical dominance in maize. Nature, 386(6624), 485-488. doi:10.1038/386485a0Thornsberry, J. M., Goodman, M. M., Doebley, J., Kresovich, S., Nielsen, D., & Buckler, E. S. (2001). Dwarf8 polymorphisms associate with variation in flowering time. Nature Genetics, 28(3), 286-289. doi:10.1038/90135Salvi, S., Sponza, G., Morgante, M., Tomes, D., Niu, X., Fengler, K. A., … Tuberosa, R. (2007). Conserved noncoding genomic sequences associated with a flowering-time quantitative trait locus in maize. Proceedings of the National Academy of Sciences, 104(27), 11376-11381. doi:10.1073/pnas.0704145104Salvi S, Tuberosa R (2007) Cloning QTLs in plants. In: Varshney R, Tuberosa R, editors. Genomics-assisted crop improvement, vol 1. Netherlands: Springer, pp. 207–225.Alonso-Blanco, C., Aarts, M. G. M., Bentsink, L., Keurentjes, J. J. B., Reymond, M., Vreugdenhil, D., & Koornneef, M. (2009). What Has Natural Variation Taught Us about Plant Development, Physiology, and Adaptation? The Plant Cell, 21(7), 1877-1896. doi:10.1105/tpc.109.068114Eduardo, I., Arús, P., & Monforte, A. J. (2005). Development of a genomic library of near isogenic lines (NILs) in melon (Cucumis melo L.) from the exotic accession PI161375. Theoretical and Applied Genetics, 112(1), 139-148. doi:10.1007/s00122-005-0116-yVegas, J., Garcia-Mas, J., & Monforte, A. J. (2013). Interaction between QTLs induces an advance in ethylene biosynthesis during melon fruit ripening. Theoretical and Applied Genetics, 126(6), 1531-1544. doi:10.1007/s00122-013-2071-3Essafi, A., Díaz-Pendón, J. A., Moriones, E., Monforte, A. J., Garcia-Mas, J., & Martín-Hernández, A. M. (2008). Dissection of the oligogenic resistance to Cucumber mosaic virus in the melon accession PI 161375. Theoretical and Applied Genetics, 118(2), 275-284. doi:10.1007/s00122-008-0897-xHayden, M. J., Nguyen, T. M., Waterman, A., & Chalmers, K. J. (2008). Multiplex-Ready PCR: A new method for multiplexed SSR and SNP genotyping. BMC Genomics, 9(1), 80. doi:10.1186/1471-2164-9-80Deleu, W., Esteras, C., Roig, C., González-To, M., Fernández-Silva, I., Gonzalez-Ibeas, D., … Garcia-Mas, J. (2009). A set of EST-SNPs for map saturation and cultivar identification in melon. BMC Plant Biology, 9(1), 90. doi:10.1186/1471-2229-9-90Lander, E. S., Green, P., Abrahamson, J., Barlow, A., Daly, M. J., Lincoln, S. E., & Newburg, L. (1987). MAPMAKER: An interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics, 1(2), 174-181. doi:10.1016/0888-7543(87)90010-3KOSAMBI, D. D. (1943). THE ESTIMATION OF MAP DISTANCES FROM RECOMBINATION VALUES. Annals of Eugenics, 12(1), 172-175. doi:10.1111/j.1469-1809.1943.tb02321.xVoorrips, R. E. (2002). MapChart: Software for the Graphical Presentation of Linkage Maps and QTLs. Journal of Heredity, 93(1), 77-78. doi:10.1093/jhered/93.1.77Wang S, Basten CJ, Zeng ZB (2007) Windows QTL cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh, NC.Zeng, Z. B. (1993). Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proceedings of the National Academy of Sciences, 90(23), 10972-10976. doi:10.1073/pnas.90.23.10972Diaz, A., Fergany, M., Formisano, G., Ziarsolo, P., Blanca, J., Fei, Z., … Monforte, A. J. (2011). A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.). BMC Plant Biology, 11(1), 111. doi:10.1186/1471-2229-11-111Noguera, F. J., Capel, J., Alvarez, J. I., & Lozano, R. (2005). Development and mapping of a codominant SCAR marker linked to the andromonoecious gene of melon. Theoretical and Applied Genetics, 110(4), 714-720. doi:10.1007/s00122-004-1897-0Esteras, C., Gomez, P., Monforte, A. J., Blanca, J., Vicente-Dolera, N., Roig, C., … Pico, B. (2012). High-throughput SNP genotyping in Cucurbita pepo for map construction and quantitative trait loci mapping. BMC Genomics, 13(1), 80. doi:10.1186/1471-2164-13-80Kenigsbuch, D., & Cohen, Y. (1990). The inheritance of gynoecy in muskmelon. Genome, 33(3), 317-320. doi:10.1139/g90-049Marguerit, E., Boury, C., Manicki, A., Donnart, M., Butterlin, G., Némorin, A., … Decroocq, S. (2009). Genetic dissection of sex determinism, inflorescence morphology and downy mildew resistance in grapevine. Theoretical and Applied Genetics, 118(7), 1261-1278. doi:10.1007/s00122-009-0979-4Monforte AJ, Díaz A, Caño-Delgado A, van der Knaap E (2014) The genetic basis of fruit morphology in horticultural crops: lessons from tomato and melon. J Exp Bot (online).Harel-Beja, R., Tzuri, G., Portnoy, V., Lotan-Pompan, M., Lev, S., Cohen, S., … Katzir, N. (2010). A genetic map of melon highly enriched with fruit quality QTLs and EST markers, including sugar and carotenoid metabolism genes. Theoretical and Applied Genetics, 121(3), 511-533. doi:10.1007/s00122-010-1327-4Chen, K.-Y., & Tanksley, S. D. (2004). High-Resolution Mapping and Functional Analysis of se2.1. Genetics, 168(3), 1563-1573. doi:10.1534/genetics.103.022558Khavkin, E., & Coe, E. H. (1997). Mapped genomic locations for developmental functions and QTLs reflect concerted groups in maize (Zea mays L.). Theoretical and Applied Genetics, 95(3), 343-352. doi:10.1007/s001220050569TUBEROSA, R. (2002). Mapping QTLs Regulating Morpho-physiological Traits and Yield: Case Studies, Shortcomings and Perspectives in Drought-stressed Maize. Annals of Botany, 89(7), 941-963. doi:10.1093/aob/mcf134Yuan, X. J., Pan, J. S., Cai, R., Guan, Y., Liu, L. Z., Zhang, W. W., … Zhu, L. H. (2008). Genetic mapping and QTL analysis of fruit and flower related traits in cucumber (Cucumis sativus L.) using recombinant inbred lines. Euphytica, 164(2), 473-491. doi:10.1007/s10681-008-9722-5Li, D., Cuevas, H. E., Yang, L., Li, Y., Garcia-Mas, J., Zalapa, J., … Weng, Y. (2011). Syntenic relationships between cucumber (Cucumis sativus L.) and melon (C. melo L.) chromosomes as revealed by comparative genetic mapping. BMC Genomics, 12(1). doi:10.1186/1471-2164-12-396Garcia-Mas, J., Benjak, A., Sanseverino, W., Bourgeois, M., Mir, G., Gonzalez, V. M., … Puigdomenech, P. (2012). The genome of melon (Cucumis melo L.). Proceedings of the National Academy of Sciences, 109(29), 11872-11877. doi:10.1073/pnas.1205415109Fazio, G., Staub, J. E., & Stevens, M. R. (2003). Genetic mapping and QTL analysis of horticultural traits in cucumber (Cucumis sativus L.) using recombinant inbred lines. Theoretical and Applied Genetics, 107(5), 864-874. doi:10.1007/s00122-003-1277-1Van der Knaap, E., & Tanksley, S. D. (2003). The making of a bell pepper-shaped tomato fruit: identification of loci controlling fruit morphology in Yellow Stuffer tomato. Theoretical and Applied Genetics, 107(1), 139-147. doi:10.1007/s00122-003-1224-1E., F., Y., L., L., C.-G., A., G., M., S., T., P., … D., Z. (2002). Two tightly linked QTLs modify tomato sugar content via different physiological pathways. Molecular Genetics and Genomics, 266(5), 821-826. doi:10.1007/s00438-001-0599-4Van der Knaap, E., Lippman, Z. B., & Tanksley, S. D. (2002). Extremely elongated tomato fruit controlled by four quantitative trait loci with epistatic interactions. Theoretical and Applied Genetics, 104(2), 241-247. doi:10.1007/s00122-001-0776-

A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.)

Background A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS). Results Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org webcite), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in a broad array of melon germplasm. Conclusions Even though relatively unsaturated genetic maps in a diverse set of melon market types have been published, the integrated saturated map presented herein should be considered the initial reference map for melon. Most of the mapped markers contained in the reference map are polymorphic in diverse collection of germplasm, and thus are potentially transferrable to a broad array of genetic experimentation (e.g., integration of physical and genetic maps, colinearity analysis, map-based gene cloning, epistasis dissection, and marker-assisted selection).This work was supported in part by SNC Laboratoire ASL, Ruiter Seeds B.V., Enza Zaden B.V., Gautier Semences S.A., Nunhems B.V., Rijk Zwaan B.V., Sakata Seed Inc, Semillas Fito S. A., Seminis Vegetable Seeds Inc, Syngenta Seeds B. V., Takii and Company Ltd, Vilmorin & Cie S. A., and Zeraim Gedera Ltd (all of them as part of the support to the ICuGI); the grants AGL2009-12698-C02-02 from the Spanish "Ministerio de Ciencia e Innovacion" to AJM. NK lab was supported in part by Research Grant Award No. IS-4223-09C from BARD, the United States - Israel Binational Agricultural Research and Development Fund, and in part by Israel Science Foundation Grant No. 38606, De Ruiter Seeds, Enza Zaden, Keygene, Rijk Zwaan, Sakata Seed Corporation, Semillas Fito, Syngenta Seeds and Vilmorin Clause & Cie. AD was supported by a JAE-Doc contract from "Consejo Superior de Investigaciones Cientificas" (CSIC-Spain). MF was supported by a postdoctoral contract from CRAG. The research carried out at YX's laboratory was supported by Chinese funds (Grant No. 2008-Z42(3), 5100001, 2010AA101907).Díaz Bermúdez, A.; Fergany, M.; Formisano, G.; Ziarsolo, P.; Blanca Postigo, JM.; Fei, Z.; Staub, JE.... (2011). A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon. BMC Plant Biology. 11. https://doi.org/10.1186/1471-2229-11-111S1

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Global economic burden of unmet surgical need for appendicitis

Background: There is a substantial gap in provision of adequate surgical care in many low-and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods: Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results: Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion: For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially