The Zika Virus (ZIKV) is a Flavivirus that caused a recent outbreak worldwide resulting in different neurological outcomes that are still poorly characterized and understood. Concerning this issue, in vitro and in vivo models are being applied to improve the molecular understanding of ZIKV infection. In this work, applying shotgun proteomics we revealed the differential ZIKV infection proteome in Vero cells, a non-neural cell model. A dramatic change resulting from infection was found including the differential expression of several proteins previously associated with brain diseases. The molecular alterations caused by this pathogen were further characterized through bioinformatics such as Gene Ontology and protein-protein interaction network of resulting differential proteome. Our findings identified molecular markers that were differentially expressed during ZIKV infection and had been previously linked to neurological conditions and infections caused by ZIKV and/or SARS-CoV-2. The results presented in this article highlight molecular markers associated with neurological dysfunctions, demonstrating that ZIKV infection can dysregulate neural-specific genes, even in non-neural cells.

Cryptococcosis is a serious fungal infection mainly caused by two Cryptococcus species, Cryptococcus gattii and Cryptococcus neoformans species complexes. Even though it is considered a dangerous disease, this infection is also neglected worldwide and its research is not adequately funded. The molecular understanding of the infection, which could help in the development of specific treatments and appropriate management, is hampered, as molecular data are not of easy access. With that purpose, our group developed a Cryptococcus molecular database, grouping published molecular data on gene and protein differential expression that occurred due to the infection. CRYPTOMICSDB presents a user-friendly interface, and users can search for both pathogen or host information and visualize data on experimental approaches, animal models or cell culture, Cryptococcus species and strain, genes and proteins. The database features 19,462 and 986,507 total genes related to the pathogen and host views, respectively. CRYPTOMICSDB is a powerful tool that can help health workers and microbiology researchers to better understand the molecular impact caused by cryptococcosis infection process.

The aim of this paper is to present the analysis carried out on the impact of CCNE's “Central de Tutoria” on the development of UFSM students' learning, especially on the aprovation indexes. Data were collected from May to June 2019, with 752 attendances during this period in 367 students from 47 different courses at 6 teaching centers. It was found that in all the most sought after subjects in the "Central de Tutoria", the number of students approved was higher than those who failed, with a greater emphasis on the General Statistics discipline with an 88% pass rate. Overall, it was observed that the students who sought support are mostly in the first stages of the various courses. This data reinforces the objectives of the creation of the "Central de Tutoria", since it is in the early stages of the courses that the failure rate is high, contributing to dropout. In sum, student demand for this support is expected to increase and, based on the results of the data analysis presented in this work, it is believed that continuing the "Central de Tutoria" will positively contribute to the permanence rates as well as the success of our students.