Vulnerabilities of the Artificial Pancreas System and Proposed Cryptographic Solutions

Type I Diabetes Mellitus is the most common form of diabetes in people under the age of 30. Current treatment for Type I Diabetes Mellitus includes lifelong monitoring of blood glucose levels and administration of insulin injections, but medical advances in the hybrid closed-loop artificial pancreas are a possible improvement in the maintenance of this disease. Our goal is to build a simulation of the artificial pancreas using three Raspberry Pi computers and an implementation of the OpenAPS algorithm. We will also build an artificial pancreas system using two Raspberry Pi computers, a Medtronic insulin pump, and an implementation of the OpenAPS algorithm. We are investigating the vulnerabilities of the two artificial pancreas systems by using common hacking resources such as Kali Linux equipped with Wireshark and other tools. One challenge with securing the artificial pancreas system and other implantable medical devices is the limitations of the computational power and energy storage. Through an analysis of the vulnerabilities of the system, we will design and perform experiments to propose a lightweight cryptographic algorithm that ensures the security of the data transmissions while operating with constrained resources

BioMaPS: A Roadmap for Success

The manuscript outlines the impact that our National Science Foundation Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences program, BioMaPS, has had on the students and faculty at Murray State University. This interdisciplinary program teams mathematics and biology undergraduate students with mathematics and biology faculty and has produced research insights and curriculum developments at the intersection of these two disciplines. The goals, structure, achievements, and curriculum initiatives are described in relation to the effects they have had to enhance the study of biomathematics

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations

Redox properties of the iron-sulfur clusters in activated Fe-hydrogenase from Desulfovibrio vulgaris (Hildenborough)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65750/1/j.1432-1033.1992.tb17261.x.pd

A Cell-Free Microtiter Plate Screen for Improved [FeFe] Hydrogenases

, a potential renewable fuel. Attempts to exploit these catalysts in engineered systems have been hindered by the biotechnologically inconvenient properties of the natural enzymes, including their extreme oxygen sensitivity. Directed evolution has been used to improve the characteristics of a range of natural catalysts, but has been largely unsuccessful for [FeFe] hydrogenases because of a lack of convenient screening platforms. [FeFe] hydrogenase HydA1 with a specific activity ∼4 times that of the wild-type enzyme. cell extracts, which allows unhindered access to the protein maturation and assay environment

Enhancing discovery of genetic variants for posttraumatic stress disorder through integration of quantitative phenotypes and trauma exposure information

Background Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods

Clinical use of biomarkers of survival in pulmonary fibrosis

<p>Abstract</p> <p>Background</p> <p>Biologic predictors or biomarkers of survival in pulmonary fibrosis with a worse prognosis, more specifically in idiopathic pulmonary fibrosis would help the clinician in deciding whether or not to treat since treatment carries a potential risk for adverse events. These decisions are made easier if accurate and objective measurements of the patients' clinical status can predict the risk of progression to death.</p> <p>Method</p> <p>A literature review is given on different biomarkers of survival in interstitial lung disease, mainly in IPF, since this disease has the worst prognosis.</p> <p>Conclusion</p> <p>Serum biomarkers, and markers measured by medical imaging as HRCT, pertechnegas, DTPA en FDG-PET are not ready for clinical use to predict mortality in different forms of ILD. A baseline FVC, a change of FVC of more than 10%, and change in 6MWD are clinically helpful predictors of survival.</p