9 research outputs found
BioSimulators: a central registry of simulation engines and services for recommending specific tools
Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations
Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer
Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.Peer reviewe
Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases
The production of peroxide and superoxide is an inevitable consequence of
aerobic metabolism, and while these particular "reactive oxygen species" (ROSs)
can exhibit a number of biological effects, they are not of themselves
excessively reactive and thus they are not especially damaging at physiological
concentrations. However, their reactions with poorly liganded iron species can
lead to the catalytic production of the very reactive and dangerous hydroxyl
radical, which is exceptionally damaging, and a major cause of chronic
inflammation. We review the considerable and wide-ranging evidence for the
involvement of this combination of (su)peroxide and poorly liganded iron in a
large number of physiological and indeed pathological processes and
inflammatory disorders, especially those involving the progressive degradation
of cellular and organismal performance. These diseases share a great many
similarities and thus might be considered to have a common cause (i.e.
iron-catalysed free radical and especially hydroxyl radical generation). The
studies reviewed include those focused on a series of cardiovascular, metabolic
and neurological diseases, where iron can be found at the sites of plaques and
lesions, as well as studies showing the significance of iron to aging and
longevity. The effective chelation of iron by natural or synthetic ligands is
thus of major physiological (and potentially therapeutic) importance. As
systems properties, we need to recognise that physiological observables have
multiple molecular causes, and studying them in isolation leads to inconsistent
patterns of apparent causality when it is the simultaneous combination of
multiple factors that is responsible. This explains, for instance, the
decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference
Practical Strategies to Circumvent and/or Surmount Six Barriers in Health Disparities Research: Observations from a Pilot Project Among Vietnamese Americans
This paper describes six practical strategies to circumvent and/or surmount barriers encountered in community-based health disparities research, as illustrated within a pilot study on Vietnamese Americans’ perceptions of the US healthcare system. Health issues, including higher rates of cancer in this group, prompted the current study. These six strategies include the following: (1) identify a population with health concerns, (2) establish the role of the community partner early, (3) recruit an investigator who understands not only the language and culture but also the research process, (4) accept the exploratory nature of a study in an understudied group, (5) put in place the groundwork for recontacting community members, and 6) assemble a motivated research team. The descriptive experience reported here might enable other investigators to undertake and complete work in the field of health disparities in minority groups
Large-scale prediction of protein ubiquitination sites using a multimodal deep architecture
Contemporary Tools and Techniques for Substrate Ablation of Ventricular Tachycardia in Structural Heart Disease
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BioSimulators: a central registry of simulation engines and services for recommending specific tools.
Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations