Seismic Vulnerability Assessment of a Historical Church: Limit Analysis and Nonlinear Finite Element Analysis

The seismic vulnerability of a historical Basilica church located in Italy is studied by means of limit analysis and nonlinear finite element (FE) analysis. Attention is posed to the failure mechanisms involving the façade of the church and its interaction with the lateral walls. In particular, the limit analysis and the nonlinear FE analysis provide an estimate of the load collapse multiplier of the failure mechanisms. Results obtained from both approaches are in agreement and can support the selection of possible retrofitting measures to decrease the vulnerability of the church under seismic loads

An Algorithm for Probabilistic Alternating Simulation

In probabilistic game structures, probabilistic alternating simulation (PA-simulation) relations preserve formulas defined in probabilistic alternating-time temporal logic with respect to the behaviour of a subset of players. We propose a partition based algorithm for computing the largest PA-simulation, which is to our knowledge the first such algorithm that works in polynomial time, by extending the generalised coarsest partition problem (GCPP) in a game-based setting with mixed strategies. The algorithm has higher complexities than those in the literature for non-probabilistic simulation and probabilistic simulation without mixed actions, but slightly improves the existing result for computing probabilistic simulation with respect to mixed actions.Comment: We've fixed a problem in the SOFSEM'12 conference versio

Lithium-ion batteries towards circular economy: A literature review of opportunities and issues of recycling treatments

Nowadays, Lithium-ion batteries are widely used in advanced technological devices and Electric and Hybrid Vehicles, due to their high energy density for weight, reduced memory effect and significant number of supported charging/discharging cycles. As a consequence, the production and the use of Lithium-ion batteries will continuously increase in the near future, focusing the global attention on their End-of-Life management. Unfortunately, wasted Lithium-ion batteries treatments are still under development, far from the optimization of recycling processes and technologies, and currently recycling represents the only alternative for the social, economic and environmental sustainability of this market, able to minimize toxicity of End-of-Life products, to create a monetary gain and to lead to the independence from foreign resources or critical materials. This paper analyses the current alternatives for the recycling of Lithium-ion batteries, specifically focusing on available procedures for batteries securing and discharging, mechanical pre-treatments and materials recovery processes (i.e. pyro- and hydrometallurgical), and it highlights the pros and cons of treatments in terms of energy consumption, recovery efficiency and safety issues. Target metals (e.g. Cobalt, Nickel and Lithium) are listed and prioritized, and the economic advantage deriving by the material recovery is outlined. An in-depth literature review was conducted, analysing the existing industrial processes, to show the on-going technological solutions proposed by research projects and industrial developments, comparing best results and open issues and criticalities

Genetic diagnosis of endocrine diseases by NGS: novel scenarios and unpredictable results and risks

The technological advancements in genetics produced a profound impact on the research and diagnostics of non-communicable diseases. The availability of next-generation sequencing (NGS) allowed the identification of novel candidate genes but also an in-depth modification of the understanding of the architecture of several endocrine diseases. Several different NGS approaches are available allowing the sequencing of several regions of interest or the whole exome or genome (WGS, WES or targeted NGS), with highly variable costs, potentials and limitations that should be clearly known before designing the experiment. Here, we illustrate the NGS scenario, describe the advantages and limitations of the different protocols and review some of the NGS results obtained in different endocrine conditions. We finally give insights on the terminology and requirements for the implementation of NGS in research and diagnostic labs

Correlating qrt-pcr, dpcr and viral titration for the identification and quantification of sars-cov-2: A new approach for infection management

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in Wuhan, China, in late 2019 and is the causative agent of the coronavirus disease 2019 (COVID-19) pandemic. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) represents the gold standard for diagnostic assays even if it cannot precisely quantify viral RNA copies. Thus, we decided to compare qRT-PCR with digital polymerase chain reaction (dPCR), which is able to give an accurate number of RNA copies that can be found in a specimen. However, the aforementioned methods are not capable to discriminate if the detected RNA is infectious or not. For this purpose, it is necessary to perform an endpoint titration on cell cultures, which is largely used in the research field and provides a tissue culture infecting dose per mL (TCID50/mL) value. Both research and diagnostics call for a model that allows the comparison between the results obtained employing different analytical methods. The aim of this study is to define a comparison among two qRT-PCR protocols (one with preliminary RNA extraction and purification and an extraction-free qRT-PCR), a dPCR and a titration on cell cultures. The resulting correlations yield a faithful estimation of the total number of RNA copies and of the infectious viral burden from a Ct value obtained with diagnostic routine tests. All these estimations take into consideration methodological errors linked to the qRT-PCR, dPCR and titration assays

Successful pregnancy in a patient with short bowel syndrome after surgical rehabilitation and sGLP-2 treatment: novel report on endogenous GLP-2 levels at delivery and during breastfeeding

Pregnant patients with short bowel syndrome (SBS) and chronic intestinal failure (CIF) can successfully reach to term their pregnancies while on parenteral nutrition (PN) but with high rates of complications. The combination of rehabilitation surgery, combined with the use of novel treatment with enterohormones, especially semisynthetic glucagon-like peptide 2 (sGLP-2), has increased the chances to achieve intestinal sufficiency. Here, we report the case of a 33-year-old female with SBS/CIF (anatomy type 2), weaned off PN using sGLP-2 for 3.7 years, discontinued when she became pregnant. She was able to carry the pregnancy to term without any additional PN support. Considering that, we queried if the endogenous GLP-2 (eGLP-2) levels in this SBS patient, during the pregnancy and breastfeeding period, could be like those presented in healthy pregnant women and in non-pregnant SBS patients. Also, we inquired if there was any passage or increase in the plasmatic eGLP-2 from the fetus to the mother. Thus, we determined eGLP-2 levels in paired neonatal (cord blood) and maternal plasma samples from the SBS pregnant patient (n = 1), healthy pregnant women (controls, n = 2), and non-pregnant SBS patients (n = 12). The results indicated that the SBS pregnant patient showed higher eGLP-2 levels than non-SBS pregnant patients and healthy pregnant women along all the period studied. Furthermore, we found that the maternal sample had higher eGLP-2 levels than the neonatal sample, suggesting that fetal contribution to maternal eGLP2 levels would be minor. In conclusion, this study not only reports for the first time a case of a patient with SBS that was able to achieve intestinal adaptation after combining the use of autologous reconstructive surgery and sGLP-2, but also enlightens the possibility of carrying out an uneventful pregnancy and lactation without any nutritional support and remaining independent of sGLP-2.Fil: Gentilini, Maria Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional, Trasplante y Bioingeniería. Fundación Favaloro. Instituto de Medicina Traslacional, Trasplante y Bioingeniería; ArgentinaFil: Doeyo, M.. Fundación Favaloro; ArgentinaFil: Ortega, M.. Fundación Favaloro; ArgentinaFil: Illidge Perez, L.. Fundación Favaloro; ArgentinaFil: Rumbo, C.. Fundación Favaloro; ArgentinaFil: Arriola Benitez, Paula Constanza. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional, Trasplante y Bioingeniería. Fundación Favaloro. Instituto de Medicina Traslacional, Trasplante y Bioingeniería; ArgentinaFil: Crivelli, A.. Fundación Favaloro; ArgentinaFil: Rumbo, Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Estudios Inmunológicos y Fisiopatológicos. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Estudios Inmunológicos y Fisiopatológicos; ArgentinaFil: Solar, H.. Fundación Favaloro; ArgentinaFil: Gondolesi, Gabriel Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional, Trasplante y Bioingeniería. Fundación Favaloro. Instituto de Medicina Traslacional, Trasplante y Bioingeniería; Argentin

Article a new epigenetic model to stratify glioma patients according to their immunosuppressive state

Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Further-more, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state

Targeted whole exome sequencing and Drosophila modelling to unveil the molecular basis of primary ovarian insufficiency

STUDY QUESTION: Can a targeted whole exome sequencing (WES) on a cohort of women showing a primary ovarian insufficiency (POI) phenotype at a young age, combined with a study of copy number variations, identify variants in candidate genes confirming their deleterious effect on ovarian function? SUMMARY ANSWER: This integrated approach has proved effective in identifying novel candidate genes unveiling mechanisms involved in POI pathogenesis. WHAT IS KNOWN ALREADY: POI, a condition occurring in 1% of women under 40 years of age, affects women’s fertility leading to a premature loss of ovarian reserve. The genetic causes of POI are highly heterogeneous and several determinants contributing to its prominent oligogenic inheritance pattern still need to be elucidated. STUDY DESIGN, SIZE, DURATION: WES screening for pathogenic variants of 41 Italian women with non-syndromic primary and early secondary amenorrhoea occurring before age 25 was replicated on another 60 POI patients, including 35 French and 25 American women, to reveal statistically significant shared variants. PARTICIPANTS/MATERIALS, SETTING, METHODS: The Italian POI patients’ DNA were processed by targeted WES including 542 RefSeq genes expressed or functioning during distinct reproductive or ovarian processes (e.g. DNA repair, meiosis, oocyte maturation, folliculogenesis and menopause). Extremely rare variants were filtered and selected by means of a Fisher Exact test using several publicly available datasets. A case-control Burden test was applied to highlight the most significant genes using two ad-hoc control female cohorts. To support the obtained data, the identified genes were screened on a novel cohort of 60 Caucasian POI patients and the same case-control analysis was carried out. Comparative analysis of the human identified genes was performed on mouse and Drosophila melanogaster by analysing the orthologous genes in their ovarian phenotype, and two of the selected genes were fruit fly modelled to explore their role in fertility. MAIN RESULTS AND THE ROLE OF CHANCE: The filtering steps applied to search for extremely rare pathogenic variants in the Italian cohort revealed 64 validated single-nucleotide variants/Indels in 59 genes in 30 out of 41 screened women. Burden test analysis highlighted 13 ovarian genes as being the most enriched and significant. To validate these findings, filtering steps and Burden analysis on the second cohort of Caucasian patients yielded 11 significantly enriched genes. Among them, AFP, DMRT3, MOV10, FYN and MYC were significant in both patient cohorts and hence were considered strong candidates for POI. Mouse and Drosophila comparative analysis evaluated a conserved role through the evolution of several candidates, and functional studies using a Drosophila model, when applicable, supported the conserved role of the MOV10 armitage and DMRT3 dmrt93B orthologues in female fertility. LARGE SCALE DATA: The datasets for the Italian cohort generated during the current study are publicly available at ClinVar database (http://www.ncbi.nlm.nih.gov/clinvar/): accession numbers SCV001364312 to SCV001364375. LIMITATIONS, REASONS FOR CAUTION: This is a targeted WES analysis hunting variants in candidate genes previously identified by different genomic approaches. For most of the investigated sporadic cases, we could not track the parental inheritance, due to unavailability of the parents’ DNA samples; in addition, we might have overlooked additional rare variants in novel candidate POI genes extracted from the exome data. On the contrary, we might have considered some inherited variants whose clinical significance is uncertain and might not be causative for the patients’ phenotype. Additionally, as regards the Drosophila model, it will be extremely important in the future to have more mutants or RNAi strains available for each candidate gene in order to validate their role in POI pathogenesis. WIDER IMPLICATIONS OF THE FINDINGS: The genomic, statistical, comparative and functional approaches integrated in our study convincingly support the extremely heterogeneous oligogenic nature of POI, and confirm the maintenance across the evolution of some key genes safeguarding fertility and successful reproduction. Two principal classes of genes were identified: (i) genes primarily involved in meiosis, namely in synaptonemal complex formation, asymmetric division and oocyte maturation and (ii) genes safeguarding cell maintenance (piRNA and DNA repair pathways). STUDY FUNDING/COMPETING INTEREST(S): This work was supported by Italian Ministry of Health grants ‘Ricerca Corrente’ (08C621_2016 and 08C924_2019) provided to IRCCS Istituto Auxologico Italiano, and by ‘Piano Sostegno alla Ricerca’ (PSR2020_FINELLI_LINEA_B) provided by the University of Milan; M.P.B. was supported by Telethon-Italy (grant number GG14181). There are no conflicts of interest