Granular Jamming: Stiffness vs Pressure and Organ Palpation Devices

The intent of this thesis it to find a correlation between the stiffness of granular jammed particles and the pressure of the vacuum initiating the jamming force. Currently, granular jamming is being used to create palpation simulators for physicians to practice feeling the variety of stiffnesses of organs when healthy or ill. Because granular jamming allows for variable stiffness of any shape, it is an apt phenomenon to simulate the change of rigidity organs like the liver undergoes when diseased. For physicians to correctly identify how stiff the organ must be when using these palpation simulators, there needs to be a way to know how much pressure must be applied to correctly simulate the stiffness of the organ for each specific scenario. This thesis will discuss how pressure affects stiffness by using the three-point bending test. To perform this test, a tubular balloon filled with coffee granules was used to represent the beam. An impact force as well as a hanging force was used to displace the beam. The displacement of the beam is adequate to find the Young\u27s Modulus or stiffness of the beam of granules at different pressures provided by the vacuum. It was found that there is a correlation between stiffness and pressure of a granular jammed system. This will allow for future physicians to accurately and consistently use model organs to practice palpation techniques

Towards Molecular Simulations that are Transparent, Reproducible, Usable By Others, and Extensible (TRUE)

Systems composed of soft matter (e.g., liquids, polymers, foams, gels, colloids, and most biological materials) are ubiquitous in science and engineering, but molecular simulations of such systems pose particular computational challenges, requiring time and/or ensemble-averaged data to be collected over long simulation trajectories for property evaluation. Performing a molecular simulation of a soft matter system involves multiple steps, which have traditionally been performed by researchers in a "bespoke" fashion, resulting in many published soft matter simulations not being reproducible based on the information provided in the publications. To address the issue of reproducibility and to provide tools for computational screening, we have been developing the open-source Molecular Simulation and Design Framework (MoSDeF) software suite. In this paper, we propose a set of principles to create Transparent, Reproducible, Usable by others, and Extensible (TRUE) molecular simulations. MoSDeF facilitates the publication and dissemination of TRUE simulations by automating many of the critical steps in molecular simulation, thus enhancing their reproducibility. We provide several examples of TRUE molecular simulations: All of the steps involved in creating, running and extracting properties from the simulations are distributed on open-source platforms (within MoSDeF and on GitHub), thus meeting the definition of TRUE simulations

Design and development of the Australian and New Zealand (ANZ) myeloma and related diseases registry

© 2016 The Author(s). Background: Plasma cell dyscrasias (PCD) are a spectrum of disorders resulting from the clonal expansion of plasma cells, ranging from the pre-malignant condition monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM). MM generates a significant burden of disease on the community and it is predicted that it will increase in both incidence and prevalence owing to an ageing population and longer survival secondary to new therapeutic options. Robust and comprehensive clinical data are currently lacking but are required to define current diagnostic, investigational and management patterns in Australia and New Zealand (ANZ) for comparison to both local and international guidelines for standards of care. A clinical registry can provide this information and subsequently support development of strategies to address any differences, including providing a platform for clinical trials. The Myeloma and Related Diseases Registry (MRDR) was developed to monitor and explore variations in practices, processes and outcomes in ANZ and provide benchmark outcomes nationally and internationally for PCD. This paper describes the MRDR aims, development and implementation and discusses challenges encountered in the process. Methods: The MRDR was established in 2012 as an online database for a multi-centre collaboration across ANZ, collecting prospective data on patients with a diagnosis of MGUS, MM, solitary plasmacytoma or plasma cell leukaemia. Development of the MRDR required multi-disciplinary team participation, IT and biostatistical support as well as financial resources. Results: More than 1250 patients have been enrolled at 23 sites to date. Here we describe how database development, data entry and securing ethics approval have been major challenges for participating sites and the coordinating centre, and our approaches to resolving them. Now established, the MRDR will provide clinically relevant and credible monitoring, therapy and 'real world' outcome data, to support the conduction of high quality studies. In addition, the Myeloma 1000 sub-study is establishing a repository of paired peripheral blood specimens from registry patients to study mechanisms underlying disease progression. Conclusion: Establishment of the MRDR has been challenging, but it is a valuable investment that will provide a platform for coordinated national and international collaboration for clinical research in PCD in ANZ

A comparison between the APACHE II and Charlson Index Score for predicting hospital mortality in critically ill patients

<p>Abstract</p> <p>Background</p> <p>Risk adjustment and mortality prediction in studies of critical care are usually performed using acuity of illness scores, such as Acute Physiology and Chronic Health Evaluation II (APACHE II), which emphasize physiological derangement. Common risk adjustment systems used in administrative datasets, like the Charlson index, are entirely based on the presence of co-morbid illnesses. The purpose of this study was to compare the discriminative ability of the Charlson index to the APACHE II in predicting hospital mortality in adult multisystem ICU patients.</p> <p>Methods</p> <p>This was a population-based cohort design. The study sample consisted of adult (>17 years of age) residents of the Calgary Health Region admitted to a multisystem ICU between April 2002 and March 2004. Clinical data were collected prospectively and linked to hospital outcome data. Multiple regression analyses were used to compare the performance of APACHE II and the Charlson index.</p> <p>Results</p> <p>The Charlson index was a poor predictor of mortality (C = 0.626). There was minimal difference between a baseline model containing age, sex and acute physiology score (C = 0.74) and models containing either chronic health points (C = 0.76) or Charlson index variations (C = 0.75, 0.76, 0.77). No important improvement in prediction occurred when the Charlson index was added to the full APACHE II model (C = 0.808 to C = 0.813).</p> <p>Conclusion</p> <p>The Charlson index does not perform as well as the APACHE II in predicting hospital mortality in ICU patients. However, when acuity of illness scores are unavailable or are not recorded in a standard way, the Charlson index might be considered as an alternative method of risk adjustment and therefore facilitate comparisons between intensive care units.</p

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.National Institutes of Health (U.S.) (Grant P50-GM068762)National Institutes of Health (U.S.) (Grant R24-DK090963)United States. Army Research Office (Grant W911NF-09-0001)German Research Foundation (Grant GSC 111

Ibrutinib as initial therapy for patients with chronic lymphocytic leukemia

Background: chronic lymphocytic leukemia (CLL) primarily affects older persons who often have coexisting conditions in addition to disease-related immunosuppression and myelosuppression. We conducted an international, open-label, randomized phase 3 trial to compare two oral agents, ibrutinib and chlorambucil, in previously untreated older patients with CLL or small lymphocytic lymphoma. Methods: we randomly assigned 269 previously untreated patients who were 65 years of age or older and had CLL or small lymphocytic lymphoma to receive ibrutinib or chlorambucil. The primary end point was progression-free survival as assessed by an independent review committee. Results: the median age of the patients was 73 years. During a median follow-up period of 18.4 months, ibrutinib resulted in significantly longer progression-free survival than did chlorambucil (median, not reached vs. 18.9 months), with a risk of progression or death that was 84% lower with ibrutinib than that with chlorambucil (hazard ratio, 0.16; P<0.001). Ibrutinib significantly prolonged overall survival; the estimated survival rate at 24 months was 98% with ibrutinib versus 85% with chlorambucil, with a relative risk of death that was 84% lower in the ibrutinib group than in the chlorambucil group (hazard ratio, 0.16; P=0.001). The overall response rate was higher with ibrutinib than with chlorambucil (86% vs. 35%, P<0.001). The rates of sustained increases from baseline values in the hemoglobin and platelet levels were higher with ibrutinib. Adverse events of any grade that occurred in at least 20% of the patients receiving ibrutinib included diarrhea, fatigue, cough, and nausea; adverse events occurring in at least 20% of those receiving chlorambucil included nausea, fatigue, neutropenia, anemia, and vomiting. In the ibrutinib group, four patients had a grade 3 hemorrhage and one had a grade 4 hemorrhage. A total of 87% of the patients in the ibrutinib group are continuing to take ibrutinib. Conclusions: ibrutinib was superior to chlorambucil in previously untreated patients with CLL or small lymphocytic lymphoma, as assessed by progression-free survival, overall survival, response rate, and improvement in hematologic variables. (Funded by Pharmacyclics and others; RESONATE-2 ClinicalTrials.gov number, NCT01722487.)

The role of epigenetics in renal ageing

An ability to separate natural ageing processes from processes specific to morbidities is required to understand the heterogeneity of age-related organ dysfunction. Mechanistic insight into how epigenetic factors regulate ageing throughout the life course, linked to a decline in renal function with ageing, is already proving to be of value in the analyses of clinical and epidemiological cohorts. Noncoding RNAs provide epigenetic regulatory circuits within the kidney, which reciprocally interact with DNA methylation processes, histone modification and chromatin. These interactions have been demonstrated to reflect the biological age and function of renal allografts. Epigenetic factors control gene expression and activity in response to environmental perturbations. They also have roles in highly conserved signalling pathways that modulate ageing, including the mTOR and insulin/insulin-like growth factor signalling pathways, and regulation of sirtuin activity. Nutrition, the gut microbiota, inflammation and environmental factors, including psychosocial and lifestyle stresses, provide potential mechanistic links between the epigenetic landscape of ageing and renal dysfunction. Approaches to modify the renal epigenome via nutritional intervention, targeting the methylome or targeting chromatin seem eminently feasible, although caution is merited owing to the potential for intergenerational and transgenerational effects

Search for a singly produced third-generation scalar leptoquark decaying to a tau lepton and a bottom quark in proton-proton collisions at root s=13 TeV

A search is presented for a singly produced third-generation scalar leptoquark decaying to a tau lepton and a bottom quark. Associated production of a leptoquark and a tau lepton is considered, leading to a final state with a bottom quark and two tau leptons. The search uses proton-proton collision data at a center-of-mass energy of 13 TeV recorded with the CMS detector, corresponding to an integrated luminosity of 35.9 fb(-1). Upper limits are set at 95% confidence level on the production cross section of the third-generation scalar leptoquarks as a function of their mass. From a comparison of the results with the theoretical predictions, a third-generation scalar leptoquark decaying to a tau lepton and a bottom quark, assuming unit Yukawa coupling (lambda), is excluded for masses below 740 GeV. Limits are also set on lambda of the hypothesized leptoquark as a function of its mass. Above lambda = 1.4, this result provides the best upper limit on the mass of a third-generation scalar leptoquark decaying to a tau lepton and a bottom quark.Peer reviewe