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Biomedical research in animal models depends heavily on nonhuman primates (NHP) (Phillips et al., Am J Primatol 76(9):801-827, 2014). In their physiology, neurobiology, and, most importantly, their susceptibility to infectious diseases and subsequent immune responses, NHPs have many parallels with humans (Rhesus Macaque Genome Sequencing and Analysis Consortium et al., Science 316(5822):222-234, 2007). Different species of NHPs have served as important animal models for numerous infectious diseases spanning a wide range of pathogens (Gardner and Luciw, ILAR J 49(2):220-255, 2008). As a result of recognizing their utility in HIV research, NHPs have contributed to groundbreaking studies of disease pathogenesis, vaccination, and curative research (London et al., Lancet 2(8355):869-873, 1983; Henrickson et al., Lancet 1 (8321):388-390, 1983). Many African NHPs are considered natural hosts for SIV in which SIV infection is usually nonprogressive and does not cause acquired immunodeficiency syndrome (AIDS) (Chahroudi et al., Science 335(6073):1188-1193, 2012; Taaffe et al., J Virol 84(11):5476-5484, 2010). However, cross-species transmission of SIV strains to other NHPs or to humans (nonnatural hosts) leads to progressive disease and AIDS (Paiardini et al., Annu Rev Med 60:485-495, 2009). In particular, SIV infection of Asian rhesus macaques recapitulates many features of HIV infection in humans and therefore has become a widely used approach for contemporary HIV research into virus persistence and cure strategies (Gardner and Luciw, FASEB J 3(14):2593-2606, 1989). There are multiple factors that should be considered in HIV/SIV studies using NHPs including the particular monkey species and geographic background, age and sex, certain genetic properties, virus strain, route and dose of infection, interventional treatments, and prespecified study outcomes. Here, we discuss consideration of these factors to address specific questions in HIV cure research., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)

Motivation: Molecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behaviour of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner., Results: We developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML-qual), that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability., Availability and Implementation: The present tool is available online: https://lifeware.inria.fr/∼soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press.)

In this work we present a systematic effort to summarize current biological pathway knowledge concerning Rheumatoid Arthritis (RA). We are constructing a detailed molecular map based on exhaustive literature scanning, strict curation criteria, re-evaluation of previously published attempts and most importantly experts' advice. The RA map will be web-published in the coming months in the form of an interactive map, using the MINERVA platform, allowing for easy access, navigation and search of all molecular pathways implicated in RA, serving thus, as an on line knowledgebase for the disease. Moreover the map could be used as a template for Omics data visualization offering a first insight about the pathways affected in different experimental datasets. The second goal of the project is a dynamical study focused on synovial fibroblasts' behavior under different initial conditions specific to RA, as recent studies have shown that synovial fibroblasts play a crucial role in driving the persistent, destructive characteristics of the disease. Leaning on the RA knowledgebase and using the web platform Cell Collective, we are currently building a Boolean large scale dynamical model for the study of RA fibroblasts' activation., Competing Interests: CONFLICT OF INTEREST The authors declare no conflict of interest.