A simplified sars-cov-2 pseudovirus neutralization assay

COVID-19 is an ongoing pandemic caused by the highly infectious coronavirus SARS-CoV-2 that is engaging worldwide scientific research to find a timely and effective eradication strategy. Great efforts have been put into anti-COVID-19 vaccine generation in an effort to protect the world population and block SARS-CoV-2 spread. To validate the protective efficacy of the vaccination campaign and effectively control the pandemic, it is necessary to quantify the induction of neutralizing antibodies by vaccination, as they have been established to be a correlate of protection. In this work, a SARS-CoV-2 pseudovirus neutralization assay, based on a replication-incompetent lentivirus expressing an adapted form of CoV-2 S protein and an ACE2/TMPRSS2 stably expressing cell line, has been minimized in terms of protocol steps without loss of accuracy. The goal of the present simplified neutralization system is to improve SARS-CoV-2 vaccination campaign by means of an easy and accessible approach to be performed in any medical laboratory, maintaining the sensitivity and quantitative reliability of classical serum neutralization assays. Further, this assay can be easily adapted to different coronavirus variants by simply modifying the pseudotyping vector

Angiogenesis modifications related with cetuximab plus irinotecan as anticancer treatment in advanced colorectal cancer patients.

Introduction: Angiogenesis has been correlated with increased invasion and metastases in a variety of human neoplasms. Inadequate inhibition of the growth of tumor microvessels by anticancer agents may result in treatment failure, rated clinically as progressive or stable disease. We designed this trial to investigate the modification of the vascular endothelial growth factor (VEGF) and interferon-c (IFN-c) in advanced colorectal cancer patients during treatment with a weekly combination of cetuximab plus irinotecan. Materials and methods: Forty-five metastatic colorectal cancer patients were prospectively evaluated for circulating levels of VEGF and IFN-c during the treatment with cetuximab (initial dose of 400 mg/m2 , followed by weekly infusions of 250 mg/m2 ) plus weekly irinotecan (90 mg/m2 ). The circulating levels of the cytokines were assessed at the following time points: just before and at 1, 21, 50 and 92 days after the start of cetuximab plus irinotecan treatment. Results: Basal serum VEGF median levels were significantly decreased just at the first day (after the first treatment infusion (P = 0.016). The VEGF persisted at the following time points reaching the highest statistical significance 92 days after the first infusion (P < 0.0001). On the contrary, IFN-c values showed a statistical significant increase one day after the first infusion (P < 0.0001). This effect persisted 21 days after the treatment start (P = 0.001), but was no more evident at the following time points. Moreover, a linear regression model with variance analysis showed a significant negative correlation between VEGF and IFN-c values 1, 21 and 50 days after the treatment beginning (P = 0.002, 0.001 and 0.047, respectively). Conclusions: This study suggests that a cetuximab may induce a modulation of VEGF circulating levels. The reduction of VEGF serum levels is a sudden and long lasting phenomenon. Moreover, in our study we identified a IFN-c increase, even if the specific role of this behavior remains to be investigated

Early magnesium reduction in advanced colorectal cancer patients treated with cetuximab plus irinotecan as predictive factor of efficacy and outcome

Introduction: Magnesium plays a role in a large number of cellular metabolic reactions. Cetuximab is able to induce hypomagnesemia by interfering with magnesium (Mg2+) transport in the kidney.We designed this trial to investigate if Mg2+ serum level modifications may be related with clinical response andoutcome in advancedcolorectal cancer patients during treatment with cetuximab plus irinotecan. Experimental Design: Sixty-eight heavily pretreatedmetastatic colorectal cancer patients were evaluatedfor Mg2+ serum levels at the following time points: before; 6 hours; and1, 7, 14, 21, 50, and92 days after the start of treatment. Results: Basal Mg2+ median levels were significantly decreased just 7 days after the first anticancer infusion and progressively decreased from the 7th day onward, reaching the highest significance at the last time point (P < 0.0001).Twenty-five patients showeda reduction in median Mg2+ circulating levels of at least 20% within the 3rdweek after the first infusion. Patients with this reduction showed a response rate of 64.0% versus 25.6% in the nonreduced Mg2+ group. The median time to progression was 6.0 versus 3.6 months in the reduced Mg2+ group andin that without reduction, respectively (P < 0.0001). Overall survival was longer in patients with Mg2+ reduction than in those without (10.7 versus 8.9 months). Conclusions: Our results confirm that cetuximab treatment may induce a reduction of Mg2+ circulating levels andoffer the first evidence that Mg2+ reduction may represent a new predictive factor of efficacy in advanced colorectal cancer patients treated with cetuximab plus irinoteca

Analysing Implicit Premises Within Children’s Argumentative Inferences

This paper presents preliminary findings of the project “Analysing children’s implicit argumentation”. We propose to reconstruct implicit premises of children’s arguments within adult-children discussions in different settings, using the Argumentum Model of Topics (AMT) for the reconstruction of the inferential configuration of arguments. We show that sources of misunderstandings are more often than not due to misalignments of implicit premises between adults and children; these misalignments concern material premises rather than the inferential-procedural level

The Butterfly Fauna Of The Italian Maritime Alps:Results Of The &#171;Edit&#187; Project

Bonelli, Simona, Barbero, Francesca, Casacci, Luca Pietro, Cerrato, Cristiana, Balletto, Emilio (2015): The butterfly fauna of the Italian Maritime Alps: results of the EDIT project. Zoosystema 37 (1): 139-167, DOI: 10.5252/z2015n1a6, URL: http://dx.doi.org/10.5252/z2015n1a

Discovering Argumentative Patterns in Energy Polylogues: A Macroscope for Argument Mining

A macroscope is proposed and tested here for the discovery of the unique argumentative footprint that characterizes how a collective (e.g., group, online community) manages differences and pursues disagreement through argument in a polylogue. The macroscope addresses broader analytic problems posed by various conceptualizations of large-scale argument, such as fields, spheres, communities, and institutions. The design incorporates a two-tier methodology for detecting argument patterns of the arguments performed in arguing by an interactive collective that produces views, or topographies, of the ways that issues are generated in the making and defending of standpoints. The design premises for the macroscope build on insights about argument patterns from pragma-dialectical theory by incorporating research and theory on disagreement management and the Argumentum Model of Topics. The design reconceptualizes prototypical and stereotypical argument patterns for characterizing large-scale argumentation. A prototype of the macroscope is tested on data drawn from six threads about oil-drilling and fracking from the subreddit Changemyview. The implementation suggests the efficacy of the macroscope’s design and potential for identifying what communities make controversial and how the disagreement space in a polylogue is managed through stereotypical argument patterns in terms of claims/premises, inferential relations, and presentational devices

Biclustering models for two-mode ordinal data

The work in this paper introduces finite mixture models that can be used to simul- taneously cluster the rows and columns of two-mode ordinal categorical response data, such as those resulting from Likert scale responses. We use the popular proportional odds parameterisation and propose models which provide insights into major patterns in the data. Model-fitting is performed using the EM algorithm and a fuzzy allocation of rows and columns to corresponding clusters is obtained. The clustering ability of the models is evaluated in a simulation study and demonstrated using two real data sets