Caracterização genética de ostras nativas do gênero Crassostrea no Brasil: base para o estabelecimento de um programa nacional de melhoramento.

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Vaccination with LAG-3Ig (IMP321) and Peptides Induces Specific CD4 and CD8 T-Cell Responses in Metastatic Melanoma Patients-Report of a Phase I/IIa Clinical Trial.

PURPOSE: Cancer vaccines aim to generate and maintain antitumor immune responses. We designed a phase I/IIa clinical trial to test a vaccine formulation composed of Montanide ISA-51 (Incomplete Freund's Adjuvant), LAG-3Ig (IMP321, a non-Toll like Receptor agonist with adjuvant properties), and five synthetic peptides derived from tumor-associated antigens (four short 9/10-mers targeting CD8 T-cells, and one longer 15-mer targeting CD4 T-cells). Primary endpoints were safety and T-cell responses. EXPERIMENTAL DESIGN: Sixteen metastatic melanoma patients received serial vaccinations. Up to nine injections were subcutaneously administered in three cycles, each with three vaccinations every 3 weeks, with 6 to 14 weeks interval between cycles. Blood samples were collected at baseline, 1-week after the third, sixth and ninth vaccination, and 6 months after the last vaccination. Circulating T-cells were monitored by tetramer staining directly ex vivo, and by combinatorial tetramer and cytokine staining on in vitro stimulated cells. RESULTS: Side effects were mild to moderate, comparable to vaccines with Montanide alone. Specific CD8 T-cell responses to at least one peptide formulated in the vaccine preparation were found in 13 of 16 patients. However, two of the four short peptides of the vaccine formulation did not elicit CD8 T-cell responses. Specific CD4 T-cell responses were found in all 16 patients. CONCLUSIONS: We conclude that vaccination with IMP321 is a promising and safe strategy for inducing sustained immune responses, encouraging further development for cancer vaccines as components of combination therapies. Clin Cancer Res; 22(6); 1330-40. ©2015 AACR

AN EXPERIMENTAL DESIGN APPROACH ON GEOREFERENCING

Georeferencing is one of the most important stages of digitizing analogue maps. It is affected by many factors such as; scales and resolutions of maps, the number of control points, etc. In this study, four of these factors were investigated using 24 factorial design in two dimensional georeferencing of cadastral maps. Factorial design determines, whether the selected factors have main and/or interaction effects on a response variable or not. Map scale, resolution of raster map, the number of control points and the coordinate transformation method were selected as experimental factors. Then, main effects and interactions between these factors were investigated. The results were statistically analyzed using analysis of variance (ANOVA), and a regression model was suggested to consider the significant main and interaction effects of factors. It was observed that the two dimensional georeferencing of maps were affected by each of the selected experimental factors and by the interaction between the map scale and coordinate transformation method

Heterogeneity assessment of functional T cell avidity.

The potency of cellular immune responses strongly depends on T cell avidity to antigen. Yet, functional avidity measurements are rarely performed in patients, mainly due to the technical challenges of characterizing heterogeneous T cells. The mean functional T cell avidity can be determined by the IFN-γ Elispot assay, with titrated amounts of peptide. Using this assay, we developed a method revealing the heterogeneity of functional avidity, represented by the steepness/hillslope of the peptide titration curve, documented by proof of principle experiments and mathematical modeling. Our data show that not only natural polyclonal CD8 T cell populations from cancer patients, but also monoclonal T cells differ strongly in their heterogeneity of functional avidity. Interestingly, clones and polyclonal cells displayed comparable ranges of heterogeneity. We conclude that besides the mean functional avidity, it is feasible and useful to determine its heterogeneity (hillslope) for characterizing T cell responses in basic research and patient investigation

OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing

SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with computational models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing, and vaccination programmes. It can simulate a population of 1 million people in seconds per day, allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 are its Python and R interfaces, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic

Research in progress: report on the ICAIL 2017 doctoral consortium

This paper arose out of the 2017 international conference on AI and law doctoral consortium. There were five students who presented their Ph.D. work, and each of them has contributed a section to this paper. The paper offers a view of what topics are currently engaging students, and shows the diversity of their interests and influences