Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Purificación del virus del síndrome de la hoja amarilla de la caña de azúcar (Sugarcane yellow leaf luteovirus ScYLV) y producción de antisuero

Plantas de la variedad SP 71-6163 afectadas por el virus del síndrome de la hoja amarilla de la cana de azúcar (ScYLV), se sembraron en condiciones de invernadero para purificar el agente causal y producir anticuerpos específicos. La metodología de purificación utilizada fue la de Lockhart (1999) modificada, agregando la enzima Celluclast 1,5 L al 2% a la solución de extracción. Las preparaciones parcialmente purificadas fueron evaluados por microscopia electrónica en el laboratorio de la unidad de virología del CIAT para verificar la concentración de partículas virales. Una vez obtenida una alta concentración el semipurificado se ultracentrifugó en un gradiente de densidad de sucrosa de 10-40% para incrementar la pureza del virus. El purificado obtenido se empleó como antígeno en la producción de immunoglobulinas especificas inyectando conejos de la raza Nueva Zelandia durante cuatro semanas en una concentración de 1mg ScYLV/ml, para luego evaluar el antisuero mediante técnicas de microscopia electrónica y TBIA. Se encontró una alta concentración de partículas virales en semipurificados empleando Celluclast 1,5 L al 2%. La relación de absorbancia A260/A280 fue de 1,49 y la concentración viral aproximada de 1,87 mg/ml. El anticuerpo producido se utilizará en pruebas serológicas de ISEM y tissue-blot para el diagnóstico del ScYLV en la zona azucarera del Valle del Cauca. = Plants of SP 71-6163 variety positive for the virus of the sugarcane yellow leaf syndrome (ScYLV) were sowed under greenhouse conditions to purify the causal agent and to produce specific antibodies. The methodology used for purification was that of Lockhart (1999) modified by CENICAÑA, adding the Celluclast 1,5 L to 2% enzyme to the extraction buffer. The purified of the obtained virus were evaluated by electronic microscopy in the laboratory of the Virology Unit at CIAT inn order to verify viral particles concentration. Once obtained a high concentration of virus particles, the purified were put on a sucrose gradient with density of 10-40 % to increase the purity of the virus which was determined later in the spectrophotometer. The purified obtained was used as antigen in the production of inmunoglobulin by injecting New Zealand rabbits during four weeks by a concentration of 1mg ScYLV/ml. The antiserum was evaluated by ISEM and TBIA. High concentration of virus particles was found by adding 2 % Celluclast 1,5 L. The absorbance A200/A280 was of 1.49 and the approximate viral concentration of 1.87 mg/ml. The antibody produced will be used for serological tests of ISEM and TBIA in the diagnosis of the ScYLV in the sugarcane area of the Cauca Valley

Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10-8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies

Novel genetic variants for cartilage thickness and hip osteoarthritis

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10-8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies

Genome-wide association study for radiographic vertebral fractures: a potential role for the 16q24 BMD locus.

Vertebral fracture risk is a heritable complex trait. The aim of this study was to identify genetic susceptibility factors for osteoporotic vertebral fractures applying a genome-wide association study (GWAS) approach. The GWAS discovery was based on the Rotterdam Study, a population-based study of elderly Dutch individuals aged > 55 years; and comprising 329 cases and 2666 controls with radiographic scoring (McCloskey–Kanis) and genetic data. Replication of one top-associated SNP was pursued by de-novo genotyping of 15 independent studies across Europe, the United States, and Australia and one Asian study. Radiographic vertebral fracture assessment was performed using McCloskey–Kanis or Genant semi-quantitative definitions. SNPs were analyzed in relation to vertebral fracture using logistic regression models corrected for age and sex. Fixed effects inverse variance and Han–Eskin alternative random effects meta-analyses were applied. Genome-wide significance was set at p < 5 × 10− 8. In the discovery, a SNP (rs11645938) on chromosome 16q24 was associated with the risk for vertebral fractures at p = 4.6 × 10− 8. However, the association was not significant across 5720 cases and 21,791 controls from 14 studies. Fixed-effects meta-analysis summary estimate was 1.06 (95% CI: 0.98–1.14; p = 0.17), displaying high degree of heterogeneity (I2 = 57%; Qhet p = 0.0006). Under Han–Eskin alternative random effects model the summary effect was significant (p = 0.0005). The SNP maps to a region previously found associated with lumbar spine bone mineral density (LS-BMD) in two large meta-analyses from the GEFOS consortium. A false positive association in the GWAS discovery cannot be excluded, yet, the low-powered setting of the discovery and replication settings (appropriate to identify risk effect size > 1.25) may still be consistent with an effect size < 1.10, more of the type expected in complex traits. Larger effort in studies with standardized phenotype definitions is needed to confirm or reject the involvement of this locus on the risk for vertebral fractures