43 research outputs found

    Towards a TILLING platform for functional genomics in Piel de Sapo melons

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    Background The availability of genetic and genomic resources for melon has increased significantly, but functional genomics resources are still limited for this crop. TILLING is a powerful reverse genetics approach that can be utilized to generate novel mutations in candidate genes. A TILLING resource is available for cantalupensis melons, but not for inodorus melons, the other main commercial group. Results A new ethyl methanesulfonate-mutagenized (EMS) melon population was generated for the first time in an andromonoecious non-climacteric inodorus Piel de Sapo genetic background. Diverse mutant phenotypes in seedlings, vines and fruits were observed, some of which were of possible commercial interest. The population was first screened for mutations in three target genes involved in disease resistance and fruit quality (Cm-PDS, Cm-eIF4E and Cm-eIFI(iso)4E). The same genes were also tilled in the available monoecious and climacteric cantalupensis EMS melon population. The overall mutation density in this first Piel de Sapo TILLING platform was estimated to be 1 mutation/1.5 Mb by screening four additional genes (Cm-ACO1, Cm-NOR, Cm-DET1 and Cm-DHS). Thirty-three point mutations were found for the seven gene targets, six of which were predicted to have an impact on the function of the protein. The genotype/phenotype correlation was demonstrated for a loss-of-function mutation in the Phytoene desaturase gene, which is involved in carotenoid biosynthesis. Conclusions The TILLING approach was successful at providing new mutations in the genetic background of Piel de Sapo in most of the analyzed genes, even in genes for which natural variation is extremely low. This new resource will facilitate reverse genetics studies in non-climacteric melons, contributing materially to future genomic and breeding studies.González, M.; Xu, M.; Esteras Gómez, C.; Roig Montaner, MC.; Monforte Gilabert, AJ.; Troadec, C.; Pujol, M.... (2011). Towards a TILLING platform for functional genomics in Piel de sapo melons. BMC Research Notes. 4(289):289-299. doi:10.1186/1756-0500-4-289S2892994289The International Cucurbit Genomics Initiative (ICuGI). [ http://www.icugi.org ]González-Ibeas D, Blanca J, Roig C, González-To M, Picó B, Truniger V, Gómez P, Deleu W, Caño-Delgado A, Arús P, Nuez F, García-Mas J, Puigdomènech P, Aranda MA: MELOGEN: an EST database for melon functional genomics. BMC Genomics. 2007, 8: 306-10.1186/1471-2164-8-306.Fita A, Picó B, Monforte A, Nuez F: Genetics of Root System Architecture Using Near-isogenic Lines of Melon. J Am Soc Hortic Sci. 2008, 133: 448-458.Fernandez-Silva I, Eduardo I, Blanca J, Esteras C, Picó B, Nuez F, Arús P, Garcia-Mas J, Monforte AJ: Bin mapping of genomic and EST-derived SSRs in melon (Cucumis melo L.). Theor Appl Genet. 2008, 118: 139-150. 10.1007/s00122-008-0883-3.Deleu W, Esteras C, Roig C, González-To M, Fernández-Silva I, Blanca J, Aranda MA, Arús P, Nuez F, Monforte AJ, Picó MB, Garcia-Mas J: A set of EST-SNPs for map saturation and cultivar identification in melon. BMC Plant Biol. 2009, 9: 90-10.1186/1471-2229-9-90.Mascarell-Creus A, Cañizares J, Vilarrasa J, Mora-García S, Blanca J, González-Ibeas D, Saladié M, Roig C, Deleu W, Picó B, López-Bigas N, Aranda MA, Garcia-Mas J, Nuez F, Puigdomènech P, Caño-Delgado A: An oligo-based microarray offers novel transcriptomic approaches for the analysis of pathogen resistance and fruit quality traits in melon (Cucumis melo L.). BMC Genomics. 2009, 10: 467-10.1186/1471-2164-10-467.Blanca JM, Cañizares J, Ziarsolo P, Esteras C, Mir G, Nuez F, Garcia-Mas J, Pico B: Melon transcriptome characterization. SSRs and SNPs discovery for high throughput genotyping across the species. Plant Genome. 2011, 4 (2): 118-131. 10.3835/plantgenome2011.01.0003.González VM, Benjak A, Hénaff EM, Mir G, Casacuberta JM, Garcia-Mas J, Puigdomènech P: Sequencing of 6.7 Mb of the melon genome using a BAC pooling strategy. BMC Plant Biology. 2010, 10: 246-10.1186/1471-2229-10-246.Moreno E, Obando JM, Dos-Santos N, Fernández-Trujillo JP, Monforte AJ, Garcia-Mas J: Candidate genes and QTLs for fruit ripening and softening in melon. Theor Appl Genet. 2007, 116: 589-602.Essafi A, Díaz-Pendón JA, Moriones E, Monforte AJ, Garcia-Mas J, Martín-Hernández AM: Dissection of the oligogenic resistance to Cucumber mosaic virus in the melon accession PI 161375. Theor Appl Genet. 2009, 118: 275-284. 10.1007/s00122-008-0897-x.Comai L, Henikoff S: TILLING: practical single-nucleotide mutation discovery. Plant J. 2006, 45: 684-94. 10.1111/j.1365-313X.2006.02670.x.Cooper JL, Till BJ, Laport RG, Darlow MC, Kleffner JM, Jamai A, El-Mellouki T, Liu S, Ritchie R, Nielsen N, et al: TILLING to detect induced mutations in soybean. BMC Plant Biol. 2008, 8 (1): 9-10.1186/1471-2229-8-9.Dalmais M, Schmidt J, Le Signor C, Moussy F, Burstin J, Savois V, Aubert G, de Oliveira Y, Guichard C, Thompson R, Bendahmane A: UTILLdb, a Pisum sativum in silico forward and reverse genetics tool. Genome Biol. 2008, 9: R43-10.1186/gb-2008-9-2-r43.Dierking EC, Bilyeu KD: New sources of soybean meal and oil composition traits identified through TILLING. BMC Plant Biol. 2009, 9: 89-10.1186/1471-2229-9-89.Perry J, Brachmann A, Welham T, Binder A, Charpentier M, Groth M, Haage K, Markmann K, Wang TL, Parniske M: TILLING in Lotus japonicus identified large allelic series for symbiosis genes and revealed a bias in functionally defective ethyl methanesulfonate alleles toward glycine replacements. Plant Physiol. 2009, 151 (3): 1281-1291. 10.1104/pp.109.142190.Caldwell DG, McCallum N, Shaw P, Muehlbauer GJ, Marshall DF, Waugh R: A structured mutant population for forward and reverse genetics in Barley (Hordeum vulgare L.). Plant J. 2004, 40 (1): 143-150. 10.1111/j.1365-313X.2004.02190.x.Henikoff S, Bradley JT, Comai L: TILLING. Traditional mutagenesis meets functional genomics. Plant Physiol. 2004, 135: 630-636. 10.1104/pp.104.041061.Wu JL, Wu C, Lei C, Baraoidan M, Bordeos A, Madamba MR, Ramos-Pamplona M, Mauleon R, Portugal A, Ulat VJ, et al: Chemical- and irradiation-induced mutants of indica rice IR64 for forward and reverse genetics. Plant Mol Biol. 2005, 59 (1): 85-97. 10.1007/s11103-004-5112-0.Slade AJ, Fuerstenberg SI, Loeffler D, Steine MN, Facciotti D: A reverse genetic, nontransgenic approach to wheat crop improvement by TILLING. Nat Biotechnol. 2005, 23: 75-81. 10.1038/nbt1043.Till BJ, Cooper J, Tai TH, Colowit P, Greene EA, Henikoff S, Comai L: Discovery of chemically induced mutations in rice by TILLING. BMC Plant Biol. 2007, 7: 19-10.1186/1471-2229-7-19.Xin Z, Wang ML, Barkley NA, Burow G, Franks C, Pederson G, Burke J: Applying genotyping (TILLING) and phenotyping analyses to elucidate gene function in a chemically induced sorghum mutant population. BMC Plant Biol. 2008, 8: 103-10.1186/1471-2229-8-103.Dong C, Dalton-Morgan J, Vincent K, Sharp P: A modified TILLING method for wheat breeding. Plant Genome. 2009, 2: 39-47. 10.3835/plantgenome2008.10.0012.Sestili F, Botticella E, Bedo Z, Phillips A, Lafiandra D: Production of novel allelic variation for genes involved in starch biosynthesis through mutagenesis. Mol Breeding. 2010, 25: 145-154. 10.1007/s11032-009-9314-7.Watanabe S, Mizoguchi T, Aoki K, Kubo Y, Mori H, Imanishi S, Yamazaki Y, Shibata D, Ezura H: Ethylmethanesulfonate (EMS) mutagenesis of Solanum lycopersicum cv. Micro-Tom for large-scale mutant screens. Plant Biotech. 2007, 24: 33-38. 10.5511/plantbiotechnology.24.33.Elias R, Till BJ, Mba Ch, Al-Safadi B: Optimizing TILLING and Ecotilling techniques for potato (Solanum tuberosum L). BMC Res Notes. 2009, 2: 141-10.1186/1756-0500-2-141.Piron F, Nicolaı M, Minoıa S, Piednoir E, Moretti A, Salgues A, Zamir D, Caranta C, Bendahmane A: An induced mutation in tomato eIF4E leads to immunity to two Potyviruses. PLoS ONE. 2010, 5 (6): e11313-10.1371/journal.pone.0011313.Himelblau E, Gilchrist EJ, Buono K, Bizell C, Mentzer L, Vogelzang R, Osborn T, Amasino RM, Parkin IAP, Haughn : Forward and reverse genetics of papid cycling Brassica oleracea. Theor Appl Genet. 2009, 118: 953-961. 10.1007/s00122-008-0952-7.Stephenson P, Baker D, Girin T, Perez A, Amoah S, King GJ, Østergaard L: A rich TILLING resource for studying gene function in Brassica rapa. BMC Plant Biol. 2010, 10: 62-10.1186/1471-2229-10-62.Pitrat M: Melon (Cucumis melo L.). Handbook of Crop Breeding Vol I. Vegetables. Edited by: Prohens J, Nuez F. 2008, New York:Springer, 283-315.Dahmani-Mardas F, Troadec Ch, Boualem A, Leveque S, Alsadon AA, Aldoss AA, Dogimont C, Bendahman A: Engineering Melon Plants with Improved Fruit Shelf Life Using the TILLING Approach. PLoS ONE. 2010, 5: e15776-10.1371/journal.pone.0015776.Nieto C, Piron F, Dalmais M, Marco CF, Moriones E, Gómez-Guillamón ML, Truniger V, Gómez P, Garcia-Mas J, Aranda MA, Bendahmane A: EcoTILLING for the identification of allelic variants of melon eIF4E, a factor that controls virus susceptibility. BMC Plant Biol. 2007, 7: 34-10.1186/1471-2229-7-34.Qin G, Gu H, Ma L, Peng Y, Deng XW, Chen Z, Qu LJ: Disruption of phytoene desaturase gene results in albino and dwarf phenotypes in Arabidopsis by impairing chlorophyll, carotenoid, and gibberellin biosynthesis. Cell Res. 2007, 17: 471-482. 10.1038/cr.2007.40.Codons Optimized to Deliver Deleterious Lesions (CODDLe). [ http://www.proweb.org/input ]Lasserre E, Bouquin T, Hernández JA, Bull J, Pech JC, Balague C: Structure and expression of three genes encoding ACC oxidase homologs from melon (Cucumis melo L.). Mol Gen Genet. 1996, 251 (1): 81-90.Giovannoni JJ: Fruit ripening mutants yield insights into ripening control. Curr Opin Plant Biol. 2007, 10: 1-7. 10.1016/j.pbi.2006.11.012.Davuluri GR, van Tuinen A, Mustilli AC, Manfredonia A, Newman R, Burgess D, Brummell DA, King SR, Palys J, Uhlig J, Pennings HMJ, Bowler C: Manipulation of DET1 expression in tomato results in photomorphogenic phenotypes caused by post-transcriptional gene silencing. Plant J. 2004, 40: 344-354. 10.1111/j.1365-313X.2004.02218.x.Wei S, Li X, Gruber MI, Li R, Zhou R, Zebarjadi A, Hannoufa A: RNAi-mediated suppression of DET1 alters the levels of carotenoids and sinapate esters in seeds of Brassica napus. J Agric Food Chem. 2009, 57 (12): 5326-5333. 10.1021/jf803983w.Wang TW, Zhang CG, Wu W, Nowack LM, Madey E, Thompson JE: Antisense suppression of deoxyhypusine synthase in tomato delays fruit softening and alters growth and development DHS mediates the first of two sequential enzymatic reactions that activate eukaryotic translation initiation factor-5A. Plant Physiol. 2005, 138: 1372-1382. 10.1104/pp.105.060194.Ng PC, Henikoff S: SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003, 31 (13): 3812-3814. 10.1093/nar/gkg509.Guzman P, Ecker JR: Exploiting the triple response of Arabidopsis to identify ethylene-related mutants. The Plant Cell. 1990, 2: 513-523.Henikoff S, Comai L: Single-nucleotide mutations for plant functional genomics. Ann Rev Plant Biol. 2003, 54: 375-401. 10.1146/annurev.arplant.54.031902.135009.Greene EA, Codomo CA, Taylor NE, Henikoff JG, Till BJ, Reynolds SH, Enns LC, Burtner C, Johnson JE, Odden AR, et al: Spectrum of chemically induced mutations from a large-scale reverse genetic screen in Arabidopsis. Genetics. 2003, 164 (2): 731-740.Britt AB: DNA damage and repair in plants. Annu Rev Plant Physiol Plant Mol Biol. 1996, 47: 75-100. 10.1146/annurev.arplant.47.1.75.Truniger V, Nieto C, González-Ibeas D, Aranda M: Mechanism of plant eIF4E-mediated resistance against a Carmovirus (Tombusviridae): cap-independent translation of a viral RNA controlled in cis by an (a)virulence determinant. Plant J. 2008, 56 (5): 716-727. 10.1111/j.1365-313X.2008.03630.x.Gao Z, Johansen E, Eyers S, Thomas CL, Ellis THN, Maule AJ: The potyvirus recessive resistance gene, sbm1, identifies a novel role for translation initiation factor eIF4E in cell-to-cell trafficking. Plant J. 2004, 40 (3): 376-385. 10.1111/j.1365-313X.2004.02215.x.Kang BC, Yeam I, Frantz JD, Murphy JF, Jahn MM: The pvr1 locus in Capsicum encodes a translation initiation factor eIF4E that interacts with Tobacco etch virus VPg. Plant J. 2005, 42 (3): 392-405. 10.1111/j.1365-313X.2005.02381.x.Ruffel S, Gallois J, Lesage M, Caranta C: The recessive potyvirus resistance gene pot-1 is the tomato orthologue of the pepper pvr2-eiF4 genes. Mol Genet Genom. 2005, 274 (4): 346-353. 10.1007/s00438-005-0003-x.Nicaise V, German-Retana S, Sanjuán R, Dubrana MP, Mazier M, Maisonneuve B, Candresse T, Caranta C, LeGall O: The Eukaryotic Translation Initiation Factor 4E Controls Lettuce Susceptibility to the Potyvirus Lettuce mosaic virus1. Plant Physiol. 2003, 132: 1272-1282. 10.1104/pp.102.017855.Esteras C, Pascual L, Saladie M, Dogimont C, Garcia-Mas J, Nuez F, Picó B: Use of Ecotilling to identify natural allelic variants of melon candidate genes involved in fruit ripening. Proceedings Plant GEM8 Lisbon. 2009Levin I, Frankel P, Gilboa N, Tanny S, Lalazar A: The tomato dark green mutation is a novel allele of the tomato homolog of the DEETIOLATED1 gene. Theor Appl Genet. 2003, 106: 454-460.Kolotilin I, Koltai H, Tadmor Y, Bar-Or C, Reuveni M, Meir A, Nahon S, Shlomo S, Chen L, I Levin: Transcriptional profiling of high pigment-2dg tomato mutant links early fruit plastid biogenesis with its overproduction of phytonutrients. Plant Physiol. 2007, 145: 389-401. 10.1104/pp.107.102962

    Syntenic relationships between cucumber (Cucumis sativus L.) and melon (C. melo L.) chromosomes as revealed by comparative genetic mapping

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    <p>Abstract</p> <p>Background</p> <p>Cucumber, <it>Cucumis sativus </it>L. (2n = 2 × = 14) and melon, <it>C. melo </it>L. (2n = 2 × = 24) are two important vegetable species in the genus <it>Cucumis </it>(family Cucurbitaceae). Both species have an Asian origin that diverged approximately nine million years ago. Cucumber is believed to have evolved from melon through chromosome fusion, but the details of this process are largely unknown. In this study, comparative genetic mapping between cucumber and melon was conducted to examine syntenic relationships of their chromosomes.</p> <p>Results</p> <p>Using two melon mapping populations, 154 and 127 cucumber SSR markers were added onto previously reported F<sub>2</sub>- and RIL-based genetic maps, respectively. A consensus melon linkage map was developed through map integration, which contained 401 co-dominant markers in 12 linkage groups including 199 markers derived from the cucumber genome. Syntenic relationships between melon and cucumber chromosomes were inferred based on associations between markers on the consensus melon map and cucumber draft genome scaffolds. It was determined that cucumber Chromosome 7 was syntenic to melon Chromosome I. Cucumber Chromosomes 2 and 6 each contained genomic regions that were syntenic with melon chromosomes III+V+XI and III+VIII+XI, respectively. Likewise, cucumber Chromosomes 1, 3, 4, and 5 each was syntenic with genomic regions of two melon chromosomes previously designated as II+XII, IV+VI, VII+VIII, and IX+X, respectively. However, the marker orders in several syntenic blocks on these consensus linkage maps were not co-linear suggesting that more complicated structural changes beyond simple chromosome fusion events have occurred during the evolution of cucumber.</p> <p>Conclusions</p> <p>Comparative mapping conducted herein supported the hypothesis that cucumber chromosomes may be the result of chromosome fusion from a 24-chromosome progenitor species. Except for a possible inversion, cucumber Chromosome 7 has largely remained intact in the past nine million years since its divergence from melon. Meanwhile, many structural changes may have occurred during the evolution of the remaining six cucumber chromosomes. Further characterization of the genomic nature of <it>Cucumis </it>species closely related to cucumber and melon might provide a better understanding of the evolutionary history leading to modern cucumber.</p

    The immunopathology of canine vector-borne diseases

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    The canine vector-borne infectious diseases (CVBDs) are an emerging problem in veterinary medicine and the zoonotic potential of many of these agents is a significant consideration for human health. The successful diagnosis, treatment and prevention of these infections is dependent upon firm understanding of the underlying immunopathology of the diseases in which there are unique tripartite interactions between the microorganism, the vector and the host immune system. Although significant advances have been made in the areas of molecular speciation and the epidemiology of these infections and their vectors, basic knowledge of the pathology and immunology of the diseases has lagged behind. This review summarizes recent studies of the pathology and host immune response in the major CVBDs (leishmaniosis, babesiosis, ehrlichiosis, hepatozoonosis, anaplasmosis, bartonellosis and borreliosis). The ultimate application of such immunological investigation is the development of effective vaccines. The current commercially available vaccines for canine leishmaniosis, babesiosis and borreliosis are reviewed

    Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults.

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    BACKGROUND: Underweight, overweight, and obesity in childhood and adolescence are associated with adverse health consequences throughout the life-course. Our aim was to estimate worldwide trends in mean body-mass index (BMI) and a comprehensive set of BMI categories that cover underweight to obesity in children and adolescents, and to compare trends with those of adults. METHODS: We pooled 2416 population-based studies with measurements of height and weight on 128·9 million participants aged 5 years and older, including 31·5 million aged 5-19 years. We used a Bayesian hierarchical model to estimate trends from 1975 to 2016 in 200 countries for mean BMI and for prevalence of BMI in the following categories for children and adolescents aged 5-19 years: more than 2 SD below the median of the WHO growth reference for children and adolescents (referred to as moderate and severe underweight hereafter), 2 SD to more than 1 SD below the median (mild underweight), 1 SD below the median to 1 SD above the median (healthy weight), more than 1 SD to 2 SD above the median (overweight but not obese), and more than 2 SD above the median (obesity). FINDINGS: Regional change in age-standardised mean BMI in girls from 1975 to 2016 ranged from virtually no change (-0·01 kg/m2 per decade; 95% credible interval -0·42 to 0·39, posterior probability [PP] of the observed decrease being a true decrease=0·5098) in eastern Europe to an increase of 1·00 kg/m2 per decade (0·69-1·35, PP>0·9999) in central Latin America and an increase of 0·95 kg/m2 per decade (0·64-1·25, PP>0·9999) in Polynesia and Micronesia. The range for boys was from a non-significant increase of 0·09 kg/m2 per decade (-0·33 to 0·49, PP=0·6926) in eastern Europe to an increase of 0·77 kg/m2 per decade (0·50-1·06, PP>0·9999) in Polynesia and Micronesia. Trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. By contrast, the rise in BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. Global age-standardised prevalence of obesity increased from 0·7% (0·4-1·2) in 1975 to 5·6% (4·8-6·5) in 2016 in girls, and from 0·9% (0·5-1·3) in 1975 to 7·8% (6·7-9·1) in 2016 in boys; the prevalence of moderate and severe underweight decreased from 9·2% (6·0-12·9) in 1975 to 8·4% (6·8-10·1) in 2016 in girls and from 14·8% (10·4-19·5) in 1975 to 12·4% (10·3-14·5) in 2016 in boys. Prevalence of moderate and severe underweight was highest in India, at 22·7% (16·7-29·6) among girls and 30·7% (23·5-38·0) among boys. Prevalence of obesity was more than 30% in girls in Nauru, the Cook Islands, and Palau; and boys in the Cook Islands, Nauru, Palau, Niue, and American Samoa in 2016. Prevalence of obesity was about 20% or more in several countries in Polynesia and Micronesia, the Middle East and north Africa, the Caribbean, and the USA. In 2016, 75 (44-117) million girls and 117 (70-178) million boys worldwide were moderately or severely underweight. In the same year, 50 (24-89) million girls and 74 (39-125) million boys worldwide were obese. INTERPRETATION: The rising trends in children's and adolescents' BMI have plateaued in many high-income countries, albeit at high levels, but have accelerated in parts of Asia, with trends no longer correlated with those of adults. FUNDING: Wellcome Trust, AstraZeneca Young Health Programme

    Multiband variability studies and novel broadband SED modeling of Mrk 501 in 2009

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    Aims. We present an extensive study of the BL Lac object Mrk 501 based on a data set collected during the multi-instrument campaign spanning from 2009 March 15 to 2009 August 1, which includes, among other instruments, MAGIC, VERITAS, Whipple 10 m, and Fermi-LAT to cover the gamma-ray range from 0.1 GeV to 20 TeV; RXTE and Swift to cover wavelengths from UV to hard X-rays; and GASP-WEBT, which provides coverage of radio and optical wavelengths. Optical polarization measurements were provided for a fraction of the campaign by the Steward and St. Petersburg observatories. We evaluate the variability of the source and interband correlations, the gamma-ray flaring activity occurring in May 2009, and interpret the results within two synchrotron self-Compton (SSC) scenarios.Methods. The multiband variability observed during the full campaign is addressed in terms of the fractional variability, and the possible correlations are studied by calculating the discrete correlation function for each pair of energy bands where the significance was evaluated with dedicated Monte Carlo simulations. The space of SSC model parameters is probed following a dedicated grid-scan strategy, allowing for a wide range of models to be tested and offering a study of the degeneracy of model-to-data agreement in the individual model parameters, hence providing a less biased interpretation than the "single-curve SSC model adjustment" typically reported in the literature.Results. We find an increase in the fractional variability with energy, while no significant interband correlations of flux changes are found on the basis of the acquired data set. The SSC model grid-scan shows that the flaring activity around May 22 cannot be modeled adequately with a one-zone SSC scenario (using an electron energy distribution with two breaks), while it can be suitably described within a two (independent) zone SSC scenario. Here, one zone is responsible for the quiescent emission from the averaged 4.5-month observing period, while the other one, which is spatially separated from the first, dominates the flaring emission occurring at X-rays and very-high-energy (> 100 GeV, VHE) gamma-rays. The flaring activity from May 1, which coincides with a rotation of the electric vector polarization angle (EVPA), cannot be satisfactorily reproduced by either a one-zone or a two-independent-zone SSC model, yet this is partially affected by the lack of strictly simultaneous observations and the presence of large flux changes on sub-hour timescales (detected at VHE gamma rays).Conclusions. The higher variability in the VHE emission and lack of correlation with the X-ray emission indicate that, at least during the 4.5-month observing campaign in 2009, the highest energy (and most variable) electrons that are responsible for the VHE gamma rays do not make a dominant contribution to the similar to 1 keV emission. Alternatively, there could be a very variable component contributing to the VHE gamma-ray emission in addition to that coming from the SSC scenario. The studies with our dedicated SSC grid-scan show that there is some degeneracy in both the one-zone and the two-zone SSC scenarios probed, with several combinations of model parameters yielding a similar model-to-data agreement, and some parameters better constrained than others. The observed gamma-ray flaring activity, with the EVPA rotation coincident with the first gamma-ray flare, resembles those reported previously for low frequency peaked blazars, hence suggesting that there are many similarities in the flaring mechanisms of blazars with different jet properties

    Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

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    Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30–79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30–79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306–359) million women and 317 (292–344) million men in 1990 to 626 (584–668) million women and 652 (604–698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55–62) of women and 49% (46–52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43–51) of women and 38% (35–41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20–27) for women and 18% (16–21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings. Funding WHO

    Rising rural body-mass index is the main driver of the global obesity epidemic in adults

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    Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities. This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity. Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories

    Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

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    Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified
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