Solid-tumor mortality in the vicinity of uranium cycle facilities and nuclear power plants in Spain.

To ascertain solid tumor mortality in towns near Spain's four nuclear power plants and four nuclear fuel facilities from 1975 to 1993, we conducted a mortality study based on 12,245 cancer deaths in 283 towns situated within a 30-km radius of the above installations. As nonexposed areas, we used 275 towns lying within a 50- to 100-km radius of each installation, matched by population size and sociodemographic characteristics (income level, proportion of active population engaged in farming, proportion of unemployed, percentage of illiteracy, and province). Using log-linear models, we examined relative risk for each area and trends in risk with increasing proximity to an installation. The results reveal a pattern of solid-tumor mortality in the vicinity of uranium cycle facilities, basically characterized by excess lung [relative risk (RR) 1.12, 95% confidence interval (CI), 1.02-1.25] and renal cancer mortality (RR 1.37, 95% CI, 1.07-1.76). Besides the effects of natural radiation, these results could well be evincing the influence on public health exerted by the environmental impact of mining. No such well-defined pattern appeared in the vicinity of nuclear power plants. Monitoring of cancer incidence and mortality is recommended in areas surrounding nuclear fuel facilities and nuclear power plants, and more specific studies are called for in areas adjacent to installations that have been fully operational for longer periods. In this regard, it is important to use dosimetric information in all future studies

Enhanced cortical neural stem cell identity through short SMAD and WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells

Cerebral organoids exhibit broad regional heterogeneity accompanied by limited cortical cellular diversity despite the tremendous upsurge in derivation methods, suggesting inadequate patterning of early neural stem cells (NSCs). Here we show that a short and early Dual SMAD and WNT inhibition course is necessary and sufficient to establish robust and lasting cortical organoid NSC identity, efficiently suppressing non-cortical NSC fates, while other widely used methods are inconsistent in their cortical NSC-specification capacity. Accordingly, this method selectively enriches for outer radial glia NSCs, which cyto-architecturally demarcate well-defined outer sub-ventricular-like regions propagating from superiorly radially organized, apical cortical rosette NSCs. Finally, this method culminates in the emergence of molecularly distinct deep and upper cortical layer neurons, and reliably uncovers cortex-specific microcephaly defects. Thus, a short SMAD and WNT inhibition is critical for establishing a rich cortical cell repertoire that enables mirroring of fundamental molecular and cyto-architectural features of cortical development and meaningful disease modelling

Education and Training of Future Nuclear Engineers at DIN: From Advanced Computer Codes to an Interactive Plant Simulator

ABSTRACT This paper summarizes the work being performed at the Department of Nuclear Engineering (www.din.upm.es) of the Universidad Politécnica de Madrid to improve the education and training of future Spanish nuclear engineers according to the Bologna rules. We present two main efforts introduced in our programme: i) the understanding of the current computational methodologies/codes starting from the nuclear data processing, then the lattice and core calculations codes, and finally the power plant simulators, ii) the development of practical teaching-learning experiences with an Interactive Graphical Simulator of a real nuclear power plant

Identifying the Profile of Helicobacter pylori-Negative Gastric Cancers: A Case-Only Analysis within the Stomach Cancer Pooling (StoP) Project

Background: The prevalence of Helicobacter pylori-negative gastric cancer (HpNGC) can be as low as 1%, when infection is assessed using more sensitive tests or considering the presence of gastric atrophy. HpNGC may share a high-risk profile contributing to the occurrence of cancer in the absence of infection. We estimated the proportion of HpNGC, using different criteria to define infection status, and compared HpNGC and positive cases regarding gastric cancer risk factors. Methods: Cases from 12 studies from the Stomach cancer Pooling (StoP) Project providing data on H. pylori infection status determined by serologic test were included. HpNGC was reclassified as positive (eight studies) when cases presented CagA markers (four studies), gastric atrophy (six studies), or advanced stage at diagnosis (three studies), and were compared with positive cases. A two-stage approach (random-effects models) was used to pool study-specific prevalence and adjusted odds ratios (OR). Results: Among non-cardia cases, the pooled prevalence of HpNGC was 22.4% (n = 166/853) and decreased to 7.0% (n = 55) when considering CagA status; estimates for all criteria were 21.8% (n = 276/1, 325) and 6.6% (n = 97), respectively. HpNGC had a family history of gastric cancer more often [OR = 2.18; 95% confidence interval (CI), 1.03-4.61] and were current smokers (OR = 2.16; 95% CI, 0.52-9.02). Conclusion: This study found a low prevalence of HpNGC, who are more likely to have a family history of gastric cancer in first-degree relatives. Impact: Our results support that H. pylori infection is present in most non-cardia gastric cancers, and suggest that HpNGC may have distinct patterns of exposure to other risk factors.S. Morais, B. Peleteiro, N. Araújo, and N. Lunet received national funding from the Foundation for Science and Technology – FCT (Portuguese Ministry of Science, Technology and Higher Education), under the Unidade de Investigação em Epidemiologia – Instituto de Saúde Pública da Universidade do Porto (EPIUnit; UIDB/04750/2020). S. Morais received funding under the scope of the project “NEON-PC - Neuro-oncological complications of prostate cancer: longitudinal study of cognitive decline” (POCI-01-0145-FEDER-032358; ref. PTDC/SAU-EPI/32358/2017) funded by FEDER through the Operational Program Competitiveness and Internationalization, and national funding from FCT, and the EPIunit – Junior Research – Prog Financing (UIDP/04750/2020). N. Araújo received an individual grant (SFRH/BD/119390/2016) funded by FCT and the ‘Programa Operacional Capital Humano’ (POCH/FSE). C. La Vecchia received funding from the Italian Association for Cancer Research (AIRC, investigator grant no. 21378). All authors received support from the European Cancer Prevention (ECP) Organization for project meetings. All authors thank all MCC-Spain study collaborators (CIBERESP, ISCIII, ISGlobal, ICO, University of Huelva, University of Oviedo, University of Cantabria, University of León, ibs. Granada, Instituto Salud Pública de Navarra, FISABIO, Murcia Regional Health Authority and cols). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact

Inverse Association between Dietary Iron Intake and Gastric Cancer: A Pooled Analysis of Case‐Control Studies of the Stop Consortium

Background: Inconsistent findings have been reported regarding the relationship between dietary iron intake and the risk of gastric cancer (GC). Methods: We pooled data from 11 case‐control studies from the Stomach Cancer Pooling (StoP) Project. Total dietary iron intake was derived from food frequency questionnaires combined with national nutritional tables. We derived the odds ratios (ORs) and 95% confidence intervals (CIs) for quartiles of dietary iron through multivariable unconditional logistic regression models. Secondary analyses stratified by sex, smoking status, caloric intake, anatomical subsite and histological type were performed. Results: Among 4658 cases and 12247 controls, dietary iron intake was inversely associated with GC (per quartile OR 0.88; 95% CI: 0.83–0.93). Results were similar between cardia (OR = 0.85, 95% CI = 0.77–0.94) and non‐cardia GC (OR = 0.87, 95% CI = 0.81–0.94), and for diffuse (OR = 0.79, 95% CI = 0.69–0.89) and intestinal type (OR = 0.88, 95% CI = 0.79–0.98). Iron intake exerted an independent effect from that of smoking and salt intake. Additional adjustment by meat and fruit/vegetable intake did not alter the results. Conclusions: Dietary iron is inversely related to GC, with no difference by subsite or histological type. While the results should be interpreted with caution, they provide evidence against a direct effect of iron in gastric carcinogenesis. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.This study was supported by the Fondazione AIRC per la Ricerca sul Cancro, Project no. 21378 (Investigator Grant). The Unidade de Investigação em Epidemiologia—Instituto de Saúde Pública da Universidade do Porto (EPIUnit; UIDB/04750/2020) and the Laboratório para a Investigação Integrativa e Translacional em Saúde Populacional (ITR; LA/P/0064/2020) were funded by the Foundation for Science and Technology—FCT (Portuguese Ministry of Science, Technology and Higher Education). SM was supported by the project “NEON‐PC—Neuro‐oncological complications of prostate cancer: longitudinal study of cognitive decline” (POCI‐01‐0145‐FEDER‐032358; ref. PTDC/SAU‐EPI/32358/2017), which is funded by FEDER through the Operational Programme competitiveness and Internationalization, and national funding from FCT and the EPIUnit—Junior Research—Prog Financing (UIDP/04750/2020). The authors thank the European Cancer Prevention (ECP) Organization for providing support for the StoP Project meetings and all MCC‐Spain study collaborators (CIBERESP, ISCIII, ISGlobal, ICO, University of Huelva, University of Oviedo, University of Cantabria, ibs.Granada, Instituto Salud Pública de Navarra, FISABIO, Murcia Regional Health Authority and cols)

A mutation in the melon Vacuolar Protein Sorting 41prevents systemic infection of Cucumber mosaic virus

[EN] In the melon exotic accession PI 161375, the gene cmv1, confers recessive resistance to Cucumber mosaic virus (CMV) strains of subgroup II. cmv1 prevents the systemic infection by restricting the virus to the bundle sheath cells and impeding viral loading to the phloem. Here we report the fine mapping and cloning of cmv1. Screening of an F2 population reduced the cmv1 region to a 132 Kb interval that includes a Vacuolar Protein Sorting 41 gene. CmVPS41 is conserved among plants, animals and yeast and is required for post-Golgi vesicle trafficking towards the vacuole. We have validated CmVPS41 as the gene responsible for the resistance, both by generating CMV susceptible transgenic melon plants, expressing the susceptible allele in the resistant cultivar and by characterizing CmVPS41 TILLING mutants with reduced susceptibility to CMV. Finally, a core collection of 52 melon accessions allowed us to identify a single amino acid substitution (L348R) as the only polymorphism associated with the resistant phenotype. CmVPS41 is the first natural recessive resistance gene found to be involved in viral transport and its cellular function suggests that CMV might use CmVPS41 for its own transport towards the phloem.The TILLING platform is supported by the Program Saclay Plant Sciences (SPS, ANR-10-LABX-40) and the European Research Council (ERC-SEXYPARTH). This work was supported by grants AGL2009-12698-C02-01 and AGL2012-40130-C02-01 from the Spanish Ministry of Science and Innovation, the Spanish Ministry of Econom and Competitiveness, through the "Severo Ochoa Programme for Centres of Excellence in R&D" 2016-2019 (SEV-2015-0533)" and the CERCA Programme/Generalitat de Catalunya.Giner, A.; Pascual, L.; Bourgeois, M.; Gyetvai, G.; Rios, P.; Picó Sirvent, MB.; Troadec, C.... (2017). A mutation in the melon Vacuolar Protein Sorting 41prevents systemic infection of Cucumber mosaic virus. Scientific Reports. 7:1-12. https://doi.org/10.1038/s41598-017-10783-3S1127Anderson, P. K. et al. Emerging infectious diseases of plants: pathogen pollution, climate change and agrotechnology drivers. Trends in Ecology & Evolution 19, 535–544, doi: 10.1016/j.tree.2004.07.021 (2004).Nicaise, V. Crop immunity against viruses: outcomes and future challenges. Frontiers in Plant Science 5, 660, doi: 10.3389/fpls.2014.00660 (2014).Kang, B.-C., Yeam, I. & Jahn, M. Genetics of plant virus resistance. Annual Review of Phytopathology 43, 581–621, doi: 10.1146/annurev.phyto.43.011205.141140 (2005).Fraser, R. S. S. The genetics of plant-virus interactions: implications for plant breeding. Euphytica 63, 175–185, doi: 10.1007/bf00023922 (1992).Truniger, V. & Aranda, M. Recessive resistance to plant viruses. Advances in virus research 119–159 (2009).Sanfaçon, H. Plant translationfactors and virus resistance. Viruses 7, 3392–3419, doi: 10.3390/v7072778 (2015).Yang, P. et al. PROTEIN DISULFIDE ISOMERASE LIKE 5-1 is a susceptibility factor to plant viruses. Proceedings of the National Academy of Sciences of the United States of America 111, 2104–2109, doi: 10.1073/pnas.1320362111 (2014).Ouibrahim, L. et al. Cloning of the Arabidopsis rwm1 gene for resistance to Watermelon mosaic virus points to a new function for natural virus resistance genes. The Plant Journal 79, 705–716, doi: 10.1111/tpj.12586 (2014).Rubio, M., Nicolaï, M., Caranta, C. & Palloix, A. Allele mining in the pepper gene pool provided new complementation effects between pvr2-eIF4E and pvr6-eIF(iso)4E alleles for resistance to pepper veinal mottle virus. Journal of General Virology 90, 2808–2814, doi: 10.1099/vir.0.013151-0 (2009).Ibiza, V. P., Cañizares, J. & Nuez, F. EcoTILLING in Capsicum species: searching for new virus resistances. BMC Genomics 11, 631–631, doi: 10.1186/1471-2164-11-631 (2010).Chandrasekaran, J. et al. Development of broad virus resistance in non-transgenic cucumber using CRISPR/Cas9 technology. Molecular Plant Pathology. doi: 10.1111/mpp.12375 (2016).Rodríguez-Hernández, A. et al. Melon RNA interference (RNAi) lines silenced for Cm-eIF4E show broad virus resistance. Molecular plant pathology 13, 755–763, doi: 10.1111/j.1364-3703.2012.00785.x (2012).Edwardson, J. R. & Christie, R. G. In CRC Handbook of Viruses Infecting Legumes (eds J.R. Edwardson & R.G. Christie) 293–319 (CRC Press, 1991).Roossinck, M. J. Cucumber mosaic virus, a model for RNA virus evolution. Molecular Plant Pathology 2, 59–63 (2001).Caranta, C. et al. QTLs involved in the restriction of Cucumber mosaic virus (CMV) long-distance movement in pepper. Theor Appl Genet 104, 586–591 (2002).Valkonen, J. P. & Watanabe, K. N. Autonomous cell death, temperature sensitivity and the genetic control associated with resistance to Cucumber mosaic virus (CMV) in diploid potatoes (Solanum spp). Theor Appl Genet 99, 996–1005 (1999).Ohnishi, S. et al. Multigenic system controlling viral systemic infection determined by the interactions between Cucumber mosaic virus genes and quantitative trait loci of soybean cultivars. Phytopathology 101, 575–582, doi: 10.1094/phyto-06-10-0154 (2011).Kobori, T., Satoshi, T. & Osaki, T. Movement of Cucumber mosaic virus is restricted at the interface between mesophyll and phloem pathway in Cucumis figarei. Journal of General Plant Pathology 66, 159–166, doi: 10.1007/pl00012939 (2000).Argyris, J. M., Pujol, M., Martín-Hernández, A. M. & Garcia-Mas, J. Combined use of genetic and genomics resources to understand virus resistance and fruit quality traits in melon. Physiologia Plantarum 155, 4–11, doi: 10.1111/ppl.12323 (2015).Diaz, J. A. et al. Potential sources of resistance for melon to nonpersistently aphid-borne viruses. Plant Disease 87, 960–964 (2003).Karchi, Z., Cohen, S. & Govers, A. Inheritance of resistance to Cucumber Mosaic virus in melons. Phytopathology 65, 479–481 (1975).Risser, G., Pitrat, M. & Rode, J. C. Etude de la résistance du melon (Cucumis melo L.) au virus de la mosaïque du concombre. Ann Amél Plant 27, 509–522 (1977).Dogimont, C. et al. Identification of QTLs contributing to resistance to different strains of Cucumber mosaic cucumovirus in melon. Acta Hortic 510, 391–398 (2000).Essafi, A. et al. Dissection of the oligogenic resistance to Cucumber mosaic virus in the melon accession PI 161375. Theoretical and Applied Genetics 118, 275–284 (2009).Guiu-Aragonés, C., Díaz-Pendón, J. A. & Martín-Hernández, A. M. Four sequence positions of the movement protein of Cucumber mosaic virus determine the virulence against cmv1-mediated resistance in melon. Molecular Plant Pathology 16, 675–684, doi: 10.1111/mpp.12225 (2015).Guiu-Aragonés, C. et al. The complex resistance to Cucumber mosaic cucumovirus (CMV) in the melon accession PI 161375 is governed by one gene and at least two quantitative trait loci. Molecular Breeding 34, 351–362, doi: 10.1007/s11032-014-0038-y (2014).Guiu-Aragonés, C. et al. cmv1 is a gate for Cucumber mosaic virus transport from bundle sheath cells to phloem in melon. Mol. Plant Pathology 17, 973–984 (2016).Sanseverino, W. et al. Transposon Insertions, Structural Variations, and SNPs Contribute to the Evolution of the Melon Genome. Molecular Biology and Evolution 32, 2760–2774, doi: 10.1093/molbev/msv152 (2015).Pols, M. S., ten Brink, C., Gosavi, P., Oorschot, V. & Klumperman, J. The HOPS Proteins hVps41 and hVps39 Are Required for Homotypic and Heterotypic Late Endosome Fusion. Traffic 14, 219–232, doi: 10.1111/tra.12027 (2013).Asensio, C. S. et al. Self-assembly of VPS41 promotes sorting required for biogenesis of the regulated secretory pathway. Developmental cell 27, 425–437, doi: 10.1016/j.devcel.2013.10.007 (2013).Kolesnikova, L. et al. Vacuolar protein sorting pathway contributes to the release of Marburg virus. Journal of Virology8 3, 2327–2337, doi: 10.1128/JVI.02184-08 (2009).Nuñez-Palenius, H. G. et al. Melon Fruits: Genetic Diversity, Physiology, and Biotechnology Features. Critical Reviews in Biotechnology 28, 13–55, doi: 10.1080/07388550801891111 (2008).Castelblanque, L. et al. Improving the genetic transformation efficiency of Cucumis melo subsp. melo “Piel de Sapo” via Agrobacterium. Procedings of the IXth UECARPIA Meeting on Genetics and Breeding of Cucurbitaceae, 21-24th May, Avignon,, 627–631 (2008).Dahmani-Mardas, F. et al. Engineering melon plants with improved fruit shelf life using the TILLING approach. PLoS ONE 5, doi: 10.1371/journal.pone.0015776 (2010).Esteras, C. et al. SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium. Theoretical and Applied Genetics 126, 1285–1303, doi: 10.1007/s00122-013-2053-5 (2013).Leida, C. et al. Variability of candidate genes, genetic structure and association with sugar accumulation and climacteric behavior in a broad germplasm collection of melon (Cucumis melo L.). BMC Genetics 16, 28, doi: 10.1186/s12863-015-0183-2 (2015).Balderhaar, H. Jk & Ungermann, C. CORVET and HOPS tethering complexes – coordinators of endosome and lysosome fusion. Journal of Cell Science 126, 1307–1316, doi: 10.1242/jcs.107805 (2013).Darsow, T., Katzmann, D. J., Cowles, C. R. & Emr, S. D. Vps41p Function in the Alkaline Phosphatase Pathway Requires Homo-oligomerization and Interaction with AP-3 through Two Distinct Domains. Molecular Biology of the Cell 12, 37–51 (2001).Ostrowicz, C. W. et al. Defined subunit arrangement and Rab interactions are required for functionality of the HOPS tethering complex. Traffic 11, 1334–1346, doi: 10.1111/j.1600-0854.2010.01097.x (2010).Solinger, J. A. & Spang, A. Tethering complexes in the endocytic pathway: CORVET and HOPS. FEBS Journal 280, 2743–2757, doi: 10.1111/febs.12151 (2013).Rehling, P., Dawson, T., Katzmann, D. J. & Emr, S. D. Formation of AP-3 transport intermediates requires Vps41 function. Nature Cell Biology 1, 346–353 (1999).Niihama, M., Takemoto, N., Hashiguchi, Y., Tasaka, M. & Morita, M. T. ZIP genes encode proteininvolved inmembrane trafficking of the TGN–PVC/Vacuoles. Plant and Cell Physiology 50, 2057–2068, doi: 10.1093/pcp/pcp137 (2009).Wang, A. & Krishnaswamy, S. Eukaryotic translation initiation factor 4E-mediated recessive resistance to plant viruses and its utility in crop improvement. Molecular Plant Pathology 13, 795–803, doi: 10.1111/j.1364-3703.2012.00791.x (2012).Ruffel, S. et al. A natural recessive resistance gene against potato virus Y in pepper corresponds to the eukaryotic initiation factor 4E (eIF4E). The Plant Journal 32, 1067–1075, doi: 10.1046/j.1365-313X.2002.01499.x (2002).Morosky, S., Lennemann, N. J. & Coyne, C. B. BPIFB6 regulatessecretory pathway trafficking and Enterovirus replication. Journal of Virology 90, 5098–5107, doi: 10.1128/jvi.00170-16 (2016).Serra-Soriano, M., Pallás, V. & Navarro, J. A. A model for transport of a viral membrane protein through the early secretory pathway: minimal sequence and endoplasmic reticulum lateral mobility requirements. The Plant Journal 77, 863–879, doi: 10.1111/tpj.12435 (2014).Vale-Costa, S. & Amorim, M. J. Recycling Endosomes and Viral Infection. Viruses 8, 64, doi: 10.3390/v8030064 (2016).Carette, J. E. et al. Ebola virus entry requires the cholesterol transporter Niemann-Pick C1. Nature 477, 340–343, doi: 10.1038/nature10348 (2011).Barajas, D., Martín, I. Fd. C., Pogany, J., Risco, C. & Nagy, P. D. Noncanonical role for the host Vps4 AAA + ATPase ESCRT protein in the formation of Tomato bushy stunt virus replicase. PLoS Pathog 10, e1004087, doi: 10.1371/journal.ppat.1004087 (2014).Richardson, L. G. L. et al. A unique N-Tterminal sequence in the Carnation Italian ringspot virus p36 replicase-associated protein interacts with the host cell ESCRT-I component Vps23. Journal of Virology 88, 6329–6344, doi: 10.1128/JVI.03840-13 (2014).Jiang, J., Patarroyo, C., Garcia Cabanillas, D., Zheng, H. & Laliberté, J.-F. The vesicle-forming 6K2 protein of Turnip mosaic virus interacts with the COPII coatomer Sec. 24a for viral systemic infection. Journal of Virology 89, 6695–6710, doi: 10.1128/jvi.00503-15 (2015).Genovés, A., Navarro, J. A. & Pallás, V. Theintra- and intercellular movement of Melon necrotic spot virus (MNSV) depends on an active secretory pathway. Molecular Plant-Microbe Interactions 23, 263–272, doi: 10.1094/MPMI-23-3-0263 (2010).Amano, M. et al. High-resolution mapping of zym, a recessive gene for Zucchini yellow mosaic virus resistance in cucumber. Theoretical and Applied Genetics 126, 2983–2993, doi: 10.1007/s00122-013-2187-5 (2013).Lewis, J. D. & Lazarowitz, S. G. Arabidopsis synaptotagmin SYTA regulates endocytosis and virus movement protein cell-to-cell transport. Proceedings of the National Academy of Sciences of the United States of America 107, 2491–2496, doi: 10.1073/pnas.0909080107 (2010).Rizzo, T. & Palukaitis, P. Construction of full-length cDNA clones of Cucumber mosaic virus RNAs 1, 2 and 3: Generation of infectious RNA transcripts. Molecular and General Genetics 122, 249–256 (1990).Zhang, L., Handa, K. & Palukaitis, P. Mapping local and systemic symptom determinants of Cucumber mosaic cucumovirus in tobacco. The Journal of General Virology 75, 3185–3191 (1994).Fukino, N., Sakata, Y., Kunihisa, M. & S., M. Characterisation of novel simple sequence repeat (SSR) markers for melon (Cucumis melo L.) and their use for genotype identification. Journal of Horticultural Science & Biotechnology 82, 330–334 (2007).Garcia-Mas, J. et al. The genome of melon (Cucumis melo L.). Proceedings of the National Academy of Sciences 109, 11872–11877, doi: 10.1073/pnas.1205415109 (2012).Untergasser, A. et al. Primer3—new capabilities and interfaces. Nucleic Acids Research 40, e115–e115, doi: 10.1093/nar/gks596 (2012).Gonzalo, M. J. et al. Simple-sequence repeat markers used in merging linkage maps of melon (Cucumis melo L.). Theor Appl Genet 110, 802–811 (2005).Doyle, J. J. & Doyle, J. L. Isolation of plant DNA from fresh tissue. Focus1 2, 13–15 (1990).Argyris, J. M. et al. Use of targeted SNP selection for an improved anchoring of the melon (Cucumis melo L.) scaffold genome assembly. BMC Genomics 16, 4, doi: 10.1186/s12864-014-1196-3 (2015).Proost, S. et al. PLAZA 3.0: an access point for plant comparative genomics. Nucleic Acids Research 43, D974–D981, doi: 10.1093/nar/gku986 (2015).Choi, Y., Sims, G. E., Murphy, S., Miller, J. R. & Chan, A. P. Predicting the Functional Effect of Amino Acid Substitutions and Indels. PLoS ONE 7, e46688, doi: 10.1371/journal.pone.0046688 (2012).Li, B. et al. Automated inference of molecular mechanisms of disease from amino acid substitutions. Bioinformatics 25, 2744–2750, doi: 10.1093/bioinformatics/btp528 (2009).Earley, K. W. et al. Gateway-compatible vectors for plant functional genomics and proteomics. The Plant Journal 45, 616–629, doi: 10.1111/j.1365-313X.2005.02617.x (2006).Gonzalez-Ibeas, D. et al. MELOGEN: an EST database for melon functional genomics. BMC Genomics 8, 306 (2007).Pfaffl, M. W. A new mathematical model for relative quantification in real-time RT–PCR. Nucleic Acids Research 29, 2002–2007 (2001).Dalmais, M. et al. UTILLdb, a Pisum sativum in silico forward and reverse genetics tool. Genome Biology 9, R43–R43, doi: 10.1186/gb-2008-9-2-r43 (2008).Saladié, M. et al. Comparative transcriptional profiling analysis of developing melon (Cucumis melo L.) fruit from climacteric and non-climacteric varieties. BMC Genomics 16, 440, doi: 10.1186/s12864-015-1649-3 (2015)

Association of time of breakfast and nighttime fasting duration with breast cancer risk in the multicase-control study in Spain

Circadian nutritional behaviors, defined by the daily eating/fasting cycle, have been linked with breast cancer. This study aimed to further disentangle the association of nighttime fasting duration and time of breakfast with breast cancer risk. We analyzed data from 1,181 breast cancer cases and 1,326 population controls from the Spanish multicase-control study (MCC-Spain), 2008-2013. We collected circadian nutritional behaviors at mid-age via a telephonic interview. We applied logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CIs) for the association of nighttime fasting duration and time of breakfast with breast cancer risk in all women and stratified by menopausal status. Models were adjusted for age, center, education, family history of breast cancer, age at menarche, number of children, breastfeeding, age at first child, body mass index (BMI), contraceptive use, and hormonal replacement therapy (HRT). A later time of breakfast was associated with a non-significant increased risk of breast cancer (OR = 1.05, 95% CI: 0.95-1.16, per hour increase). This association was stronger among premenopausal women, among whom each hour later, the time of breakfast was associated with an 18% increase in breast cancer risk (OR = 1.18, 95% CI: 1.01-1.40). The association was not observed in postmenopausal women. We did not observe an association between nighttime fasting duration and breast cancer risk after adjusting for the time of breakfast. In this study, late breakfast was associated with increased breast cancer risk, especially among premenopausal women, compared with early breakfast. Aside from nutritional quality, circadian nutritional behaviors should be further studied in relation to cancer

Association of time of breakfast and nighttime fasting duration with breast cancer risk in the multicase-control study in Spain

Circadian nutritional behaviors, defined by the daily eating/fasting cycle, have been linked with breast cancer. This study aimed to further disentangle the association of nighttime fasting duration and time of breakfast with breast cancer risk. We analyzed data from 1,181 breast cancer cases and 1,326 population controls from the Spanish multicase-control study (MCC-Spain), 2008-2013. We collected circadian nutritional behaviors at mid-age via a telephonic interview. We applied logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CIs) for the association of nighttime fasting duration and time of breakfast with breast cancer risk in all women and stratified by menopausal status. Models were adjusted for age, center, education, family history of breast cancer, age at menarche, number of children, breastfeeding, age at first child, body mass index (BMI), contraceptive use, and hormonal replacement therapy (HRT). A later time of breakfast was associated with a non-significant increased risk of breast cancer (OR = 1.05, 95% CI: 0.95-1.16, per hour increase). This association was stronger among premenopausal women, among whom each hour later, the time of breakfast was associated with an 18% increase in breast cancer risk (OR = 1.18, 95% CI: 1.01-1.40). The association was not observed in postmenopausal women. We did not observe an association between nighttime fasting duration and breast cancer risk after adjusting for the time of breakfast. In this study, late breakfast was associated with increased breast cancer risk, especially among premenopausal women, compared with early breakfast. Aside from nutritional quality, circadian nutritional behaviors should be further studied in relation to cancer

On decoding and rewriting genomes: a psychoanalytical reading of a scientific revolution

In various documents the view emerges that contemporary biotechnosciences are currently experiencing a scientific revolution: a massive increase of pace, scale and scope. A significant part of the research endeavours involved in this scientific upheaval is devoted to understanding and, if possible, ameliorating humankind: from our genomes up to our bodies and brains. New developments in contemporary technosciences, such as synthetic biology and other genomics and “post-genomics” fields, tend to blur the distinctions between prevention, therapy and enhancement. An important dimension of this development is “biomimesis”: i.e. the tendency of novel technologies and materials to mimic or plagiarize nature on a molecular and microscopic level in order to optimise prospects for the embedding of technological artefacts in natural systems such as human bodies and brains. In this paper, these developments are read and assessed from a psychoanalytical perspective. Three key concepts from psychoanalysis are used to come to terms with what is happening in research laboratories today. After assessing the general profile of the current revolution in this manner, I will focus on a particular case study, a line of research that may serve as exemplification of the vicissitudes of contemporary technosciences, namely viral biomaterials. Viral life forms can be genetically modified (their genomes can be rewritten) in such a manner that they may be inserted in human bodies in order to produce substances at specific sites such as hormones (testosterone), neurotransmitters (dopamine), enzymes (insulin) or bone and muscle tissue. Notably, certain target groups such as top athletes, soldiers or patients suffering from degenerative diseases may become the pioneers serving as research subjects for novel applications. The same technologies can be used for various purposes ranging from therapy up to prevention and enhancement