ABSTRACT: Analysis made in 2018 with 25 samples of 15 species of Solanum taken from RFA herbarium (Biology institute - Federal University of Rio de Janeiro - UFRJ)
Project description:For the YPIC challenge 2018 contestants were invited to try to decipher two unknown English questions encoded by a synthetic protein expressed in E. coli. We present how we analyzed this unknown sample using a tryptic digest with dynamic exclusion disabled to increase the signal-to-noise ratio of the measured molecules. Subsequently, spectral clustering was used to generate high-quality consensus spectra and condense the acquired MS/MS spectral data. De novo spectrum identification was used to determine the English questions encoded by the synthetic protein, and any post-translational modifications introduced by E. coli on the synthetic protein were detected using spectral networking. Although the synthetic protein sample for the YPIC challenge 2018 is not of biological interest, the experimental and computational strategy presented here can be directly used to analyze samples for which no protein sequence information is available. All software and code to perform the bioinformatics analysis is available as open source, and a self-contained Jupyter notebook is provided to fully recreate the analysis.
Project description:A total of 97 LARC patients treated at the Institute for Oncology and Radiology of Serbia in the period of 2018-2019 were included in the study. Patients were treated with long-course chemoradiotherapy (CRT): Radiotherapy (RT) was delivered with a total dose of 50.4 Gy in 28 fractions; concomitant chemotherapy (5-FU, 350 mg/m2 daily) and Leucovorin (25 mg/m2 daily) was administered during the first and the fifth week of RT. Patients were evaluated in week 6-8 after treatment completion with pelvic MRI scan and rigid proctoscopy. Pathohistological response after surgery was assessed according to tumor regression grading (TRG) categories by Mandard. Twenty biopsy samples taken at diagnosis were used for proteomic analysis, 9 responders (R, TRG 1-2), and 11 non-responders (NR, TRG 3-5), in order to achieve the maximum range of different molecular features potentially associated with response.
Project description:Gene expression changes in the blood was studied by RNAseq; project SIG-2018 Results: Strong differential host reponse after infection with influenza virus compared to healthy controls
Project description:Transcriptomic profiling of gene expression in EA 2018 relative to that of ATCC824 revealed several key genes related to solvent formation. For example, spo0A and adhEII have higher expression level, and most of the acid formation related genes have lower expression level in EA 2018.