Spectroscopic diagnostics of dust formation and evolution in classical nova ejecta

A fraction of classical novae form dust during the early stages of their outbursts. The classical CO nova V5668 Sgr (Nova Sgr. 2015b) underwent a deep photometric minimum about 100 days after outburst that was covered across the spectrum. A similar event was observed for an earlier CO nova, V705 Cas (Nova Cas 1993) and a less optically significant event for the more recent CO nova V339 Del (Nova Del 2013). This study provides a "compare and contrast" of these events to better understand the very dynamical event of dust formation. We show the effect of dust formation on multiwavelength high resolution line profiles in the interval 1200\AA\ - 9200\AA\ using a biconical ballistic structure that has been applied in our previous studies of the ejecta. We find that both V5668 Sgr and V339 Del can be modeled using a grey opacity for the dust, indicating fairly large grains (at least 0.1 micron) and that the persistent asymmetries of the line profiles in late time spectra, up to 650 days after the event for V5668 Sgr and 866 days for V339 Del, point to the survival of the dust well into the transparent, nebular stage of the ejecta evolution. This is a general method for assessing the properties of dust forming novae well after the infrared is completely transparent in the ejecta.Comment: 15 pages 14 figures, accepted for publication in A&A, 2018 June 2

Customer-driven design of the recharge infrastructure and Vehicle-to-Grid in urban areas: A large-scale application for electric vehicles deployment

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European type-approval test procedure for evaporative emissions from passenger cars against real-world mobility data from two Italian provinces

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A stochastic model for CD4+ T cell proliferation and dissemination network in primary immune response

The study of the initial phase of the adaptive immune response after first antigen encounter provides essential information on the magnitude and quality of the immune response. This phase is characterized by proliferation and dissemination of T cells in the lymphoid organs. Modeling and identifying the key features of this phenomenon may provide a useful tool for the analysis and prediction of the effects of immunization. This knowledge can be effectively exploited in vaccinology, where it is of interest to evaluate and compare the responses to different vaccine formulations. The objective of this paper is to construct a stochastic model based on branching process theory, for the dissemination network of antigen-specific CD4+ T cells. The devised model is validated on in vivo animal experimental data. The model presented has been applied to the vaccine immunization context making references to simple proliferation laws that take into account division, death and quiescence, but it can also be applied to any context where it is of interest to study the dynamic evolution of a population. Copyright:© 2015 Boianelli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Distribution of Primed T Cells and Antigen-Loaded Antigen Presenting Cells Following Intranasal Immunization in Mice

Priming of T cells is a key event in vaccination, since it bears a decisive influence on the type and magnitude of the immune response. T-cell priming after mucosal immunization via the nasal route was studied by investigating the distribution of antigen-loaded antigen presenting cells (APCs) and primed antigen-specific T cells. Nasal immunization studies were conducted using the model protein antigen ovalbumin (OVA) plus CpG oligodeoxynucleotide adjuvant. Trafficking of antigen-specific primed T cells was analyzed in vivo after adoptive transfer of OVA-specific transgenic T cells in the presence or absence of fingolimod, a drug that causes lymphocytes sequestration within lymph nodes. Antigen-loaded APCs were observed in mediastinal lymph nodes, draining the respiratory tract, but not in distal lymph nodes. Antigen-specific proliferating T cells were first observed within draining lymph nodes, and later in distal iliac and mesenteric lymph nodes and in the spleen. The presence at distal sites was due to migration of locally primed T cells as shown by fingolimod treatment that caused a drastic reduction of proliferated T cells in non-draining lymph nodes and an accumulation of extensively divided T cells within draining lymph nodes. Homing of nasally primed T cells in distal iliac lymph nodes was CD62L-dependent, while entry into mesenteric lymph nodes depended on both CD62L and α4β7, as shown by in vivo antibody-mediated inhibition of T-cell trafficking. These data, elucidating the trafficking of antigen-specific primed T cells to non-draining peripheral and mucosa-associated lymph nodes following nasal immunization, provide relevant insights for the design of vaccination strategies based on mucosal priming

Towards Safer Robot-Assisted Surgery: A Markerless Augmented Reality Framework

Robot-assisted surgery is rapidly developing in the medical field, and the integration of augmented reality shows the potential of improving the surgeons' operation performance by providing more visual information. In this paper, we proposed a markerless augmented reality framework to enhance safety by avoiding intra-operative bleeding which is a high risk caused by the collision between the surgical instruments and the blood vessel. Advanced stereo reconstruction and segmentation networks are compared to find out the best combination to reconstruct the intra-operative blood vessel in the 3D space for the registration of the pre-operative model, and the minimum distance detection between the instruments and the blood vessel is implemented. A robot-assisted lymphadenectomy is simulated on the da Vinci Research Kit in a dry lab, and ten human subjects performed this operation to explore the usability of the proposed framework. The result shows that the augmented reality framework can help the users to avoid the dangerous collision between the instruments and the blood vessel while not introducing an extra load. It provides a flexible framework that integrates augmented reality into the medical robot platform to enhance safety during the operation

Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared

During the COVID-19 pandemic, excess mortality has been reported worldwide, but its magnitude has varied depending on methodological differences that hinder between-study comparability. Our aim was to estimate variability attributable to different methods, focusing on specific causes of death with different pre-pandemic trends. Monthly mortality figures observed in 2020 in the Veneto Region (Italy) were compared with those forecasted using: (1) 2018–2019 monthly average number of deaths; (2) 2015–2019 monthly average age-standardized mortality rates; (3) Seasonal Autoregressive Integrated Moving Average (SARIMA) models; (4) Generalized Estimating Equations (GEE) models. We analyzed deaths due to all-causes, circulatory diseases, cancer, and neurologic/mental disorders. Excess all-cause mortality estimates in 2020 across the four approaches were: +17.2% (2018–2019 average number of deaths), +9.5% (five-year average age-standardized rates), +15.2% (SARIMA), and +15.7% (GEE). For circulatory diseases (strong pre-pandemic decreasing trend), estimates were +7.1%, −4.4%, +8.4%, and +7.2%, respectively. Cancer mortality showed no relevant variations (ranging from −1.6% to −0.1%), except for the simple comparison of age-standardized mortality rates (−5.5%). The neurologic/mental disorders (with a pre-pandemic growing trend) estimated excess corresponded to +4.0%/+5.1% based on the first two approaches, while no major change could be detected based on the SARIMA and GEE models (−1.3%/+0.3%). The magnitude of excess mortality varied largely based on the methods applied to forecast mortality figures. The comparison with average age-standardized mortality rates in the previous five years diverged from the other approaches due to the lack of control over pre-existing trends. Differences across other methods were more limited, with GEE models probably representing the most versatile option

Modulation of thymidilate synthase and p53 expression by HDAC inhibitor vorinostat resulted in synergistic antitumor effect in combination with 5FU or raltitrexed.

Despite the introduction of several novel anticancer agents almost 50% of colorectal cancer (CRC) patients die for cancer suggesting the necessity of new therapeutical approaches. In this study we demonstrated that the HDAC inhibitor vorinostat exerted potent antiproliferative effect in a panel of mut- and wt-p53 human CRC cell lines. Moreover, in combination with 5-fluorouracil modulated by folinic acid (5FU-FA) or with Raltitrexed (RTX), both commonly used in the treatment of this disease, it showed a clear schedule-dependent synergistic antiproliferative interaction as demonstrated by calculating combination indexes. Only simultaneous, or 24 h pretreatment with vorinostat followed by either agent, produced synergistic effect paralleled by evident cell cycle perturbations with major S-phase arrest. Moreover, we provided for the first time evidences that vorinostat can overcome resistance to both 5FU and RTX. Downmodulation of Thymidilate synthase (TS) protein induced by vorinostat within 24 h, represented a key factor in enhancing the effects of both drugs in sensitive as well as resistant tumor cells. Furthermore, p53, whose wild-type expression is critical for sensitivity to 5FU and RTX, was upregulated by vorinostat in wt- and downregulated in mut-p53 cells, suggesting an additional mechanism of the antiproliferative synergistic interactions observed. Overall these data add new insights in the mechanism of vorinostat antitumor effect and suggested that the association of vorinostat plus 5FU-FA and/or RTX should be clinically explored