350 research outputs found

    Genotypic Characterization of Non-O157 Shiga Toxin–Producing Escherichia coli in Beef Abattoirs of Argentina

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    The non-O157 Shiga toxin-producing Escherichia coli (STEC) contamination in carcasses and feces of 811 bovines in nine beef abattoirs from Argentina was analyzed during a period of 17 months. The feces of 181 (22.3%) bovines were positive for non-O157 STEC, while 73 (9.0%) of the carcasses showed non-O157 STEC contamination. Non-O157 STEC strains isolated from feces (227) and carcasses (80) were characterized. The main serotypes identified were O178:H19, O8:H19, O130:H11, and O113:H21, all of which have produced sporadic cases of hemolytic-uremic syndrome in Argentina and worldwide. Twenty-two (7.2%) strains carried a fully virulent stx/eae/ehxA genotype. Among them, strains of serotypes O103:[H2], O145:NM, and O111:NM represented 4.8% of the isolates. XbaI pulsed-field gel electrophoresis pattern analysis showed 234 different patterns, with 76 strains grouped in 30 clusters. Nine of the clusters grouped strains isolated from feces and from carcasses of the same or different bovines in a lot, while three clusters were comprised of strains distributed in more than one abattoir. Patterns AREXSX01.0157, AREXBX01.0015, and AREXPX01.0013 were identified as 100% compatible with the patterns of one strain isolated from a hemolytic-uremic syndrome case and two strains previously isolated from beef medallions, included in the Argentine PulseNet Database. In this survey, 4.8% (39 of 811) of the bovine carcasses appeared to be contaminated with non- O157 STEC strains potentially capable of producing sporadic human disease, and a lower proportion (0.25%) with strains able to produce outbreaks of severe disease.Fil: Masana, Marcelo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos; ArgentinaFil: D´Astek, B. A.. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorio e Instituto de Salud “Dr. C. G. Malbrán”; ArgentinaFil: Palladino, Pablo Martín. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos; ArgentinaFil: Galli, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentina. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: del Castillo, Lourdes Leonor. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Agroindustria. Instituto de Tecnología de Alimentos; ArgentinaFil: Carbonari, Claudia Carolina. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: Leotta, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentina. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: Vilacoba, Elisabet. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; ArgentinaFil: Irino, K.. Instituto Adolfo Lutz. Seção de Bacteriologia; BrasilFil: Rivas, M.. Dirección Nacional de Institutos de Investigación. Administración Nacional de Laboratorios e Institutos de Salud. Instituto Nacional de Enfermedades Infecciosas; Argentin

    Targeting of multiple myeloma-related angiogenesis by miR-199a-5p mimics: in vitro and in vivo anti-tumor activity

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    Multiple myeloma (MM) cells induce relevant angiogenic effects within the human bone marrow milieu (huBMM) by the aberrant expression of angiogenic factors. Hypoxia triggers angiogenic events within the huBMM and the transcription factor hypoxia-inducible factor-1α (HIF-1α) is over-expressed by MM cells. Since synthetic miR-199a-5p mimics negatively regulates HIF-1α, we here investigated a miRNA-based therapeutic strategy against hypoxic MM cells. We indeed found that enforced expression of miR-199a-5p led to down-modulated expression of HIF-1α as well as of other pro-angiogenic factors such as VEGF-A, IL-8, and FGFb in hypoxic MM cells in vitro. Moreover, miR-199a-5p negatively affected MM cells migration, while it increased the adhesion of MM cells to bone marrow stromal cells (BMSCs) in hypoxic conditions. Furthermore, transfection of MM cells with miR-199a-5p significantly impaired also endothelial cells migration and down-regulated the expression of endothelial adhesion molecules such as VCAM-1 and ICAM-1. Finally, we identified a hypoxia\AKT/miR-199a-5p loop as a potential molecular mechanism responsible of miR-199a-5p down-regulation in hypoxic MM cells. Taken together our results indicate that miR-199a-5p has an important role for the pathogenesis of MM and support the hypothesis that targeting angiogenesis via a miRNA/HIF-1α pathway may represent a novel potential therapeutical approach for this still lethal diseas

    Strong Association of De Novo Copy Number Mutations with Autism

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    We tested the hypothesis that de novo copy number variation (CNV) is associated with autism spectrum disorders (ASDs). We performed comparative genomic hybridization (CGH) on the genomic DNA of patients and unaffected subjects to detect copy number variants not present in their respective parents. Candidate genomic regions were validated by higher-resolution CGH, paternity testing, cytogenetics, fluorescence in situ hybridization, and microsatellite genotyping. Confirmed de novo CNVs were significantly associated with autism (P = 0.0005). Such CNVs were identified in 12 out of 118 (10%) of patients with sporadic autism, in 2 out of 77 (3%) of patients with an affected first-degree relative, and in 2 out of 196 (1%) of controls. Most de novo CNVs were smaller than microscopic resolution. Affected genomic regions were highly heterogeneous and included mutations of single genes. These findings establish de novo germline mutation as a more significant risk factor for ASD than previously recognized

    Prevalencia de Campylobacter jejuni y Campylobacter coli en carcasas de pollo procedentes de frigoríficos, faena tradicional y kosher, y de locales de expendio

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    El objetivo del estudio fue determinar y comparar la prevalencia de Campylobacter jejuni y Campylobacter coli en carcasas de pollo obtenidas en frigoríficos por faena convencional y kosher, y en locales de expendio. La prevalencia de Campylobacter spp. termotolerante fue del 94,0 (kosher) y del 32,0% (convencional) (p < 0,0001). La prevalencia de muestras contaminadas con C. jejuni, C. coli y con ambas especies fue del 36,0, del 2,0 y del 56,0% (Kosher) y del 26,0, del 4,0 y del 2,0% (convencional) (p < 0,0001), respectivamente. Se tomaron muestras de carcasas (n = 25) y superficies (tablas, n = 25; cuchilla, n = 25) en 25 locales. Los locales fueron categorizados como de riesgo alto (n = 11), moderado (n = 11) y bajo (n = 3). Diecinueve (76,0%) carcasas, 20 (80,0%) tablas y 18 (72,0%) cuchillas fueron positivas para Campylobacter spp. Frigoríficos y locales fueron fuente de contaminación de carcasas con Campylobacter spp. La prevalencia de Campylobacter spp. fue mayor en carcasas kosher. Campylobacter coli fue la especie más prevalente en carcasas de locales.We studied and compared the prevalence of Campylobacter jejuni and C. coliin chicken carcasses from conventional and kosher broiler abattoirs and retail stores. The prevalence of thermotolerant Campylobacter-positive carcasses was 94.0 (kosher) and 32.0% (conventional) (p < 0.0001), while the prevalence of samples contaminated with C. jejuni, C. coli and simultaneously with both species was 36.0, 2.0 and 56.0% (kosher) and 26.0, 4.0 and 2.0% (conventional) (p < 0.0001), respectively. Samples of chicken carcasses (n = 25) and food contact surfaces (tables, n = 25; knives, n = 25) from 25 retails were collected and risk quantification was performed. Retails were categorized as high-risk (n = 11), moderate-risk (n = 11) and low-risk (n = 3). Nineteen (76.0%) carcasses, 20 (80.0%) tables and 18 (72.0%) knives were Campylobacter-positive. Retails and abattoirs proved to be sources of carcass contamination with Campylobacter spp. Carcasses from kosher abattoirs were mostly contaminated with Campylobacter spp., whereas C. coli was the most prevalent species isolated from carcasses inretail stores.Fil: Guirin, Guillermo Federico. Laboratorio AGGA; ArgentinaFil: Brusa, Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; ArgentinaFil: Adriani, Cristian D.. Buenos Aires. Municipalidad de Berisso. Departamento de Seguridad Alimentaria; ArgentinaFil: Leotta, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico CONICET- La Plata. Instituto de Genética Veterinaria "Ing. Fernando Noel Dulout". Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias. Instituto de Genética Veterinaria; Argentin

    Composing Smart Data Services in Shop Floors Through Large Language Models

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    Recent years have witnessed an ever-growing use of Large Language Models (LLMs) to lower the technical barrier for several tasks, ranging from coding to querying relational databases to composing services. In this work, we focus on using LLMs to simplify access to data in the industrial scenario, by allowing humans operating on the shop floor to submit a query in natural language and then materializing a table integrating data gathered from different data sources including machines and information systems. In particular, we introduce COSMADS, which takes as input a query from an operator on the shop floor and automatically synthesizes a pipeline that leverages existing data sources accessible as services (data services), to compose a table output fulfilling the user’s information need. The proposed solution is evaluated using a real case study, showing that results obtained by taking into account available data service descriptions and previous pipelines outperform those obtained by naively employing a state-of-the-art code generation tool

    Communications Biophysics

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    Contains reports on seven research projects split into three sections.National Institutes of Health (Grant 5 PO1 NS13126)National Institutes of Health (Grant 1 RO1 NS18682)National Institutes of Health (Training Grant 5 T32 NS07047)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 1 F33 NS07202-01)National Institutes of Health (Grant 5 RO1 NS10916)National Institutes of Health (Grant 5 RO1 NS12846)National Institutes of Health (Grant 1 RO1 NS16917)National Institutes of Health (Grant 1 RO1 NS14092-05)National Science Foundation (Grant BNS 77 21751)National Institutes of Health (Grant 5 R01 NS11080)National Institutes of Health (Grant GM-21189

    Communications Biophysics

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    Contains research objectives and reports on eight research projects split into three sections.National Institutes of Health (Grant 2 PO1 NS13126)National Institutes of Health (Grant 5 RO1 NS18682)National Institutes of Health (Grant 5 RO1 NS20322)National Institutes of Health (Grant 1 RO1 NS 20269)National Institutes of Health (Grant 5 T32 NS 07047)Symbion, Inc.National Institutes of Health (Grant 5 R01 NS10916)National Institutes of Health (Grant 1 RO NS 16917)National Science Foundation (Grant BNS83-19874)National Science Foundation (Grant BNS83-19887)National Institutes of Health (Grant 5 RO1 NS12846)National Institutes of Health (Grant 1 RO1 NS21322-01)National Institutes of Health (Grant 5 T32-NS07099-07)National Institutes of Health (Grant 1 RO1 NS14092-06)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 5 RO1 NS11080

    Communication Biophysics

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    Contains reports on six research projects.National Institutes of Health (Grant 5 PO1 NS13126)National Institutes of Health (Grant 5 RO1 NS18682)National Institutes of Health (Grant 5 RO1 NS20322)National Institutes of Health (Grant 5 R01 NS20269)National Institutes of Health (Grant 5 T32NS 07047)Symbion, Inc.National Science Foundation (Grant BNS 83-19874)National Science Foundation (Grant BNS 83-19887)National Institutes of Health (Grant 6 RO1 NS 12846)National Institutes of Health (Grant 1 RO1 NS 21322
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