Efficacy of short-course treatment for prevention of congenital transmission of Chagas disease: A retrospective cohort study.

BACKGROUND: In regions with controlled vector transmission of T. cruzi, congenital transmission is the most frequent route of infection. Treatment with benznidazole (BZ) or nifurtimox (NF) for 60 days in girls and women of childbearing age showed to be effective in preventing mother to child transmission of this disease. Reports on short-course treatment (≤30 days) are scarce. METHODS: Retrospective cohort study. Offspring of women with Chagas disease who received short-course treatment (≤30 days) with BZ or NF, attended between 2003 and 2022, were evaluated. Parasitemia (microhaematocrit and/or PCR) was performed at <8 months of age, and serology (ELISA and IHA) at ≥8 months to rule out congenital infection. RESULTS: A total of 27 women receiving ≤30 days of treatment and their children were included in this study. NF was prescribed in 17/27 (63%) women, and BZ in 10/27 (37%). The mean duration of treatment was 29.2 days. None of the women experienced serious adverse events during treatment, and no laboratory abnormalities were observed. Forty infants born to these 27 treated women were included. All newborns were full term, with appropriate weight for their gestational age. No perinatal infectious diseases or complications were observed. DISCUSSION: Several studies have shown that treatment of infected girls and women of childbearing age for 60 days is an effective practice to prevent transplacental transmission of T. cruzi. Our study demonstrated that short-duration treatment (≤30 days) is effective and beneficial in preventing transplacental transmission of Chagas disease.

Insight into membraneless organelles and their associated proteins: Drivers, Clients and Regulators.

In recent years, attention has been devoted to proteins forming immiscible liquid phases within the liquid intracellular medium, commonly referred to as membraneless organelles (MLO). These organelles enable the spatiotemporal associations of cellular components that exchange dynamically with the cellular milieu. The dysregulation of these liquid-liquid phase separation processes (LLPS) may cause various diseases including neurodegenerative pathologies and cancer, among others. Until very recently, databases containing information on proteins forming MLOs, as well as tools and resources facilitating their analysis, were missing. This has recently changed with the publication of 4 databases that focus on different types of experiments, sets of proteins, inclusion criteria, and levels of annotation or curation. In this study we integrate and analyze the information across these databases, complement their records, and produce a consolidated set of proteins that enables the investigation of the LLPS phenomenon. To gain insight into the features that characterize different types of MLOs and the roles of their associated proteins, they were grouped into categories: High Confidence MLO associated (including Drivers and reviewed proteins), Potential Clients and Regulators, according to their annotated functions. We show that none of the databases taken alone covers the data sufficiently to enable meaningful analysis, validating our integration effort as essential for gaining better understanding of phase separation and laying the foundations for the discovery of new proteins potentially involved in this important cellular process. Lastly, we developed a server, enabling customized selections of different sets of proteins based on MLO location, database, disorder content, among other attributes (https://forti.shinyapps.io/mlos/).

ASpli: integrative analysis of splicing landscapes through RNA-Seq assays.

MOTIVATION: Genome-wide analysis of alternative splicing has been a very active field of research since the early days of next generation sequencing technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. A large number of splicing analysis methodologies exist, each of them presenting its own strengths and weaknesses. For instance, methods exclusively relying on junction information do not take advantage of the large majority of reads produced in an RNA-seq assay, isoform reconstruction methods might not detect novel intron retention events, some solutions can only handle canonical splicing events, and many existing methods can only perform pairwise comparisons. RESULTS: In this contribution, we present ASpli, a computational suite implemented in R statistical language, that allows the identification of changes in both, annotated and novel alternative-splicing events and can deal with simple, multi-factor or paired experimental designs. Our integrative computational workflow, that considers the same GLM model applied to different sets of reads and junctions, allows computation of complementary splicing signals. Analyzing simulated and real data, we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While the analysis of junctions allowed us to uncover annotated as well as non-annotated events, read coverage signals notably increased recall capabilities at a very competitive performance when compared against other state-of-the-art splicing analysis algorithms. AVAILABILITY AND IMPLEMENTATION: ASpli is freely available from the Bioconductor project site https://doi.org/doi:10.18129/B9.bioc.ASpli. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.