Multiplex SNaPshot for detection of BRCA1/2 common mutations in Spanish and Spanish related breast/ovarian cancer families

<p>Abstract</p> <p>Background</p> <p>It is estimated that 5–10% of all breast cancer are hereditary and attributable to mutations in the highly penetrance susceptibility genes <it>BRCA1 </it>and <it>BRCA2</it>. The genetic analysis of these genes is complex and expensive essentially because their length. Nevertheless, the presence of recurrent and founder mutations allows a pre-screening for the identification of the most frequent mutations found in each geographical region. In Spain, five mutations in <it>BRCA1 </it>and other five in <it>BRCA2 </it>account for approximately 50% of the mutations detected in Spanish families.</p> <p>Methods</p> <p>We have developed a novel PCR multiplex SNaPshot reaction that targets all ten recurrent and founder mutations identified in <it>BRCA1 </it>and <it>BRCA2 </it>in Spain to date.</p> <p>Results</p> <p>The SNaPshot reaction was performed on samples previously analyzed by direct sequencing and all mutations were concordant. This strategy permits the analysis of approximately 50% of all mutations observed to be responsible for breast/ovarian cancer in Spanish families using a single reaction per patient sample.</p> <p>Conclusion</p> <p>The SNaPshot assay developed is sensitive, rapid, with minimum cost per sample and additionally can be automated for high-throughput genotyping. The SNaPshot assay outlined here is not only useful for analysis of Spanish breast/ovarian cancer families, but also e.g. for populations with Spanish ancestry, such as those in Latin America.</p

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81&nbsp;years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

Detection of hidden explosives in different scenarios with the use of nuclear probes

Abstract The detection of landmines by using available technologies is a time consuming, expensive and extremely dangerous job, so that there is a need for a technological breakthrough in this field. Atomic and nuclear physics based sensors might offer new possibilities in de-mining. Technology and methods derived from the studies applied to the detection of landmines can be successfully applied to the screening of cargo in customs inspections

MCNP calculations for container inspection with tagged neutrons

We are developing an innovative tagged neutrons inspection system (TNIS) for cargo containers: the system will allow us to assay the chemical composition of suspect objects, previously identified by a standard X-ray radiography. The operation of the system is extensively being simulated by using the MCNP Monte Carlo code to study different inspection geometries, cargo loads and hidden threat materials. Preliminary simulations evaluating the signal and the signal over background ratio expected as a function of the system parameters are presented. The results for a selection of cases are briefly discussed and demonstrate that the system can operate successfully in different filling condition

Metal(loid)s role in the pathogenesis of amyotrophic lateral sclerosis: Environmental, epidemiological, and genetic data

Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder of the motor system. The etiology is still unknown and the pathogenesis remains unclear. ALS is familial in the 10% of cases with a Mendelian pattern of inheritance. In the remaining sporadic cases, a multifactorial origin is supposed in which several predisposing genes interact with environmental factors. The etiological role of environmental factors, such as pesticides, exposure to electromagnetic fields, and metals has been frequently investigated, with controversial findings. Studies in the past two decades have highlighted possible roles of metals, and ionic homeostasis dysregulation has been proposed as the main trigger to motor-neuron degeneration. This study aims at evaluating the possible role of environmental factors in etiopathogenesis of ALS, with a particular attention on metal contamination, focusing on the industrial Briga area in the province of Novara (Piedmont region, North Italy), characterized by: i) a higher incidence of sporadic ALS (sALS) in comparison with the entire province, and ii) the reported environmental pollution. Environmental data from surface, ground and discharge waters, and from soils were collected and specifically analyzed for metal content. Considering the significance of genetic mechanisms in ALS, a characterization for the main ALS genes has been performed to evaluate the genetic contribution for the sALS patients living in the area of study. The main findings of this study are the demonstration that in the Briga area the most common metal contaminants are Cu, Zn, Cr, Ni (widely used in tip-plating processes), that are above law limits in surface waters, discharge waters, and soil. In addition, other metals and metalloids, such as Cd, Pb, Mn, and As show a severe contamination in the same area. Results of genetic analyses show that sALS patients in the Briga area do not carry recurrent mutations or an excess of mutations in the four main ALS causative genes (SOD1, TARDBP, FUS, C9ORF72) and for ATXN2 CAG repeat locus. This study supports the hypothesis that the higher incidence of sALS in Briga area may be related to environmental metal(loid)s contamination, along with other environmental factors. Further studies, implementing analysis of genetic polymorphisms, as well as investigation with long term follow-up, may yield to key aspects into the etiology of ALS. The interplay between different approaches (environmental, chemical, epidemiological, genetic) of our work provides new insights and methodology to the comprehension of the disease etiology

Physiological responses in roots of the grapevine rootstock 140 Ruggeri subjected to Fe deficiency and Fe-heme nutrition

Background and aims In many important viticultural areas of the Mediterranean basin, plants often face prolonged periods of scarce iron (Fe) availability in the soil.The objective of the present work was to perform a comparative analysis of physiological and biochemical responses of Vitis genotypes to severe Fe deficiency. Methods Three grapevine rootstocks differing in susceptibility to Fe chlorosis were grown with and without Fe in the nutrient solution. Results Rootstock 101-14, susceptible to Fe chlorosis, responded to severe Fe deficiency by reducing the root activity of phosphoenolpyruvate carboxylase (PEPC) and malate dehydrogenase(MDH),however,it accumulated high levels of citric acid. By contrast, rootstock 110 Richter, tolerant to Fe chlorosis, maintained an active metabolism of organic acids,but citric acid accumulation was lower than in101-14.Similarly to101-14, rootstock SO4 showed a strong decrease in PEPC and MDH activities. Nevertheless it maintained moderate citric acid levels in the roots, mimicking the response by 110 Richter. Conclusions Root PEPC and MDH activities can be used as tools for screening Fe chlorosis tolerance. Conversely, organic acids accumulation in roots may not be a reliable indicator of Fe chlorosis tolerance, particularly under conditions of severe Fe deficiency, because of their probable exudation by roots.Our results show that drawing sound conclusions from screening programs involving Fe deficiency tolerance requires short as well as long-term assessment of responses to Fe deprivation

Mutational burden of resectable pancreatic cancer, as determined by whole transcriptome and whole exome sequencing, predicts a poor prognosis

Despite the genomic characterization of pancreatic cancer&nbsp;(PC), marked advances in the development of prognosis classification and novel therapeutic strategies have yet to come. The present study aimed to better understand the genomic alterations associated with the invasive phenotype of PC, in order to improve patient selection for treatment options. A total of 30&nbsp;PC samples were analysed by either whole transcriptome (9&nbsp;samples) or exome sequencing (21&nbsp;samples) on an Illumina platform (75X2 or 100X2&nbsp;bp), and the results were matched with normal DNA to identify somatic events. Single nucleotide variants and insertions and deletions were annotated using public databases, and the pathogenicity of the identified variants was defined according to prior knowledge and mutation-prediction tools. A total of 43&nbsp;recurrently altered genes were identified, which were involved in numerous pathways, including chromatin remodelling and DNA damage repair. In addition, an analysis limited to a subgroup of early stage patients (50% of samples) demonstrated that poor prognosis was significantly associated with a higher number of known PC mutations (P=0.047). Samples from patients with a better overall survival (&gt;25&nbsp;months) harboured an average of 24&nbsp;events, whereas samples from patients with an overall survival of &lt;25&nbsp;months presented an average of 40&nbsp;mutations. These findings indicated that a complex genetic profile in the early stage of disease may be associated with increased aggressiveness, thus suggesting an urgent requirement for an innovative approach to classify this disease

Detection of hidden explosives in different scenarios with the use of nuclear probes

The detection of landmines by using available technologies is a time consuming, expensive and extremely dangerous job, so that there is a need for a technological breakthrough in this field. Atomic and nuclear physics based sensors might offer new possibilities in de-mining. Technology and methods derived from the studies applied to the detection of landmines can be successfully applied to the screening of cargo in customs inspections