Modelling osteomyelitis.

BACKGROUND: This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure. RESULTS: Since both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way. CONCLUSIONS: We present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

A Brain Computer Interface that Predicts Different Hand Movements from Pre-motor EEG Activity

Every year, 50,000 Canadians will have a strokeM.A.S.2019-11-17 00:00:0

Investigating the interplay between cellular mechanics and decision-making in the C. elegans germ line

The behaviour of individual cells must be carefully coordinated across a tissue to achieve correct function. In particular, proliferation and differentiation decisions must be precisely regulated throughout development, tissue maintenance, and repair. A better understanding of how these processes are controlled would have implications for human health; cancer is, after all, dysregulated proliferation, while regenerative medicine relies on being able to influence cell decisions accurately. To investigate such fundamental biological processes, it is common practice to use an experimentally tractable model organism. Here, we focus on the germ line of the nematode worm C. elegans, which provides opportunities to study organogenesis, tissue maintenance, and ageing effects. Despite the advantages of this organism as a biological model, certain questions about germ cell behaviour and coordination remain challenging to address in the lab. There is therefore a need for computational models of the germ line to complement experimental approaches. In this thesis, we develop a new in silico model of the C. elegans germ line. Novel aspects include working in three dimensions, covering the late larval period, and integrating a logical model of germ cell behaviour into a wider cell mechanics simulation. Our model produces a reasonable fit to wild-type germline behaviour, and provides the first cell tracking and labelling predictions for the larval period. It also suggests two new biological hypotheses: 1) that âstretchingâ growth plays a significant role in gonadogenesis, and 2) that a feedback mechanism acts on the germ cell cycle to prevent overproliferation. Having introduced the full model, we address some technical questions arising from our work, namely: what is the effect of applying a more physically realistic force law?; and can simulation performance be improved by changing the numerical scheme? Finally, we use in silico modelling to compare a number of hypothesised germ line maintenance mechanisms. There, our results support a model with functionally equivalent germ cells undergoing at most infrequent, transient cell cycle arrests.</p

Maternal immunization : collaborating with Mother Nature

Maternal immunization offers much hope to substantially reduce morbidity and mortality from infectious diseases after birth. The success of tetanus, influenza and pertussis immunization during pregnancy has led to consideration of additional maternal immunization strategies to prevent Group B Streptococcus (GBS) and respiratory syncytial virus (RSV) infections, among others. However, there remain multiple gaps in our knowledge regarding the immunobiology of maternal immunization that prevent optimal design and application of this successful public health intervention. An innovative landscape analysis was therefore undertaken to identify research priorities. Key topics were delineated through review of the published literature, consultation with vaccine developers and regulatory agencies, and a collaborative workshop gathering experts across several current maternal immunization initiatives - GBS, RSV, pertussis, and influenza. Finally, a global online survey prioritized the identified knowledge gaps based on expert opinion regarding their importance and relevance. This article presents the results of this worldwide landscape analysis and discusses the identified research gaps.Medicine, Faculty ofNon UBCInfectious Diseases, Division ofMedicine, Department ofPediatrics, Department ofReviewedFacult