Development of an R script for simple lipidomic and metabolomic data analysis

Background: Metabolomic and lipidomic studies generate vast quantities of data that are often analysed in a closed software environment with little to no access to the underlying algorithms. As a result, data processed via different software pipelines yield different results thus leading to a widespread problem of low reproducibility within these fields. To address this problem, we are developing LipidAnalyst; an R based lipidomics software pipeline. As a part of this project, we are creating a simple statistical analysis and graphing module in R to generate accurate, reproducible, high-resolution figures. Methods: R scripts were developed under version 3.5.3 with the capability to undertake statistical analyses (e.g. ANOVA) and post-hoc tests (e.g. Tukey). Additional code plotted resultant information as high resolution violin and box plots that depicted statistical significance. Thereafter, lipidomic and metabolomic data were analysed by this code and compared against commercial software and Metaboanalyst, a primary software used in metabolomic and lipidomic research. Results: Code generated in house demonstrated the same results as those generated using commercial software (e.g. JMP 14.0 Pro) but were different from results obtained by using the MetaboAnalyst pipeline. Conclusions: This study demonstrated the prevalent danger of using closed-source software pipelines for the analysis of lipidomic and metabolomic data without validating the analysis outcomes via open-source software. Open source software such as LipidAnalyst, that has also been independently validated using multiple data sets, can then be published with the results to enable transparency of data analysis and improve the replicability of results across different labs.https://scholarscompass.vcu.edu/gradposters/1092/thumbnail.jp

Free-text keystroke dynamics authentication for Arabic language

This study introduces an approach for user authentication using free-text keystroke dynamics which incorporates text in Arabic language. The Arabic language has completely different characteristics to those of English. The approach followed in this study involves the use of the keyboard's key-layout. The method extracts timing features from specific key-pairs in the typed text. Decision trees were exploited to classify each of the users' data. In parallel for comparison, support vector machines were also used for classification in association with an ant colony optimisation feature selection technique. The results obtained from this study are encouraging as low false accept rates and false reject rates were achieved in the experimentation phase. This signifies that satisfactory overall system performance was achieved by using the typing attributes in the proposed approach, while typing Arabic text

Effective catalytic deoxygenation of waste cooking oil over nanorods activated carbon supported CaO

Under nitrogen atmosphere, waste cooking oil (WCO) was deoxygenated in semi-batch experiments by using the nanorods of phosphate-activated carbon, which is derived from walnut shell and promoted by CaO as catalyst at 350 °C. The deoxygenation reaction showed high activity (> 48% hydrocarbon yield) and high selectivity towards decarboxylation/decarbonylation (deCOx) reactions via exclusive formation of green diesel C15 fraction (> 60%). The high activity and high selectivity were attributed to the good physicochemical characteristics of the catalyst, including improved metal dispersion, high surface area and high basic properties. Overall, this study demonstrates CaO/AC catalytic deoxygenation as a promising approach to produce liquid green diesel C15 from WCO under hydrogen-free atmosphere

Non-conventional keystroke dynamics for user authentication

This paper introduces an approach for user authentication using free-text keystroke dynamics which incorporates the use of non-conventional keystroke features. Semi-timing features along with editing features are extracted from the user’s typing stream. Decision trees were exploited to classify each of the user’s data. In parallel for comparison, support vector machines (SVMs) were also used for classification in association with an ant colony optimization (ACO) feature selection technique. The results obtained from this study are encouraging as low false accept rates (FAR) and false reject rates (FRR) were achieved in the experimentation phase. This signifies that satisfactory overall system performance was achieved by using the typing attributes in the proposed approach. Thus, the use of non-conventional typing features improves the understanding of human typing behavior and therefore, provides significant contribution to the authentication system

Improving the performance of free-text keystroke dynamics authentication by fusion

Free-text keystroke dynamics is invariably hampered by the huge amount of data needed to train the system. This problem has been addressed in this paper by suggesting a system that combines two methods, both of which provide a reduced training requirement for user authentication using free-text keystrokes. The two methods were fused to achieve error rates lower than those produced by each method separately. Two fusion schemes, namely: decision-level fusion and feature-level fusion, were applied. Feature-level fusion was done by concatenating two sets of features before the learning stage. The two sets of features were: a timing feature set and a non-conventional feature set. Moreover, decision-level fusion was used to merge the output of two methods using majority voting. One is Support Vector Machines (SVMs) together with Ant Colony Optimization (ACO) feature selection and the other is decision trees (DTs). Even though the classifiers using the parameters merged at feature level produced low error rates, its results were outperformed by the results achieved by the decision-level fusion scheme. Decision-level fusion was employed to achieve the best performance of 0.00% False Accept Rate (FAR) and 0.00% False Reject Rate (FRR)

High frequency of carbapenem-resistant Acinetobacter baumannii in patients with diabetes mellitus in Saudi Arabia

Carbapenem-resistant Acinetobacter baumannii is becoming increasingly prevalent in patients with diabetes mellitus in the Middle East. We examined the relationship of these bacteria and their resistance mechanisms to the diabetic disease status of patients in Saudi Arabia. Susceptibilities of 271 isolates to carbapenems, tigecycline and colistin were determined, followed by detection of carbapenemase genes. A blaVIM gene was detected in ~95 % of isolates; blaOXA-23 and blaOXA-40 genes were also prevalent. Diabetic patients were significantly more likely to carry carbapenem-resistant isolates. Carbapenem-resistant A. baumannii is a serious problem in diabetic patients, and molecular detection of resistance mechanisms in these isolates is required

Prevalence, knowledge and attitude of prohibited substances use (doping) among Saudi sport players

BACKGROUND: To estimate the lifetime prevalence and address the attitudes and knowledge of using prohibited substances (doping) among sport players in Saudi Arabia. METHODS: A cross-sectional survey carried out using systematic random sampling technique among Saudi players of variable sports attending the sport clubs, stadiums, and sport fields (70 sport clubs, 22 types of sports belong to 22 Saudi sport federations were visted in 18 cities from all regions of Saudi Arabia). RESULTS: A total of 1142 male sport players were interviewed with main age of 24. The prevalence of using prohibited substances (doping) was 4.3 %. The main reason for using prohibited substances was to improve performance (69 %). The prevalence of using food supplements (not prohibited) was 38.4 %. Among the players, 30 % of them believe that such behavior is against the spirit of sport while 70 % of the players are aware of punishment against doping. 65 % of players admitted that they received advice on prohibited substances. Higher rate of using prohibited substances (doping) among Saudi players was associated with low education, age below 20 years, previous use of food supplements and lack of punishment awareness. CONCLUSION: Using prohibited substances (doping) among Saudi sport players is common. Players believe that such use is against the spirit of the sport and they are aware about its punishment, despite this, they are still using prohibited substances

Development of an online warfarin dosing platform using R programming language to facilitate healthcare professional duties and limit medication related errors.

Development of an online warfarin dosing platform using R programming language to facilitate healthcare professional duties and limit medication related errors. Monther Alsultan, Joshua M. Morriss, Daniel Contaifer Jr, Suad Alshammari; Silas Contaifer, Rachel W Flurie, Dayanjan S. Wijesinghe# Department of Pharmacotherapy and Outcome Sciences Objective: 1) Gain experience in developing platform agnostic, fully operational and clinically relevant web applications for effective pharmacist led patient care. 2) Create a decision- support tool using open source software to facilitate evidence-based management therapy of warfarin in clinical settings where it is available for everyone to use at anytime and anywhere. Introduction: Healthcare is continuously growing and modern technologies provide opportunities for the creation of effective tools to manage multiple diseases. Mobile devices such as smartphones enable easy access to a variety of websites remotely and make data and information readily available for use. Additionally, mobile devices can offer healthcare providers with fast and easy access to essential medical information to support patient care. The profession of pharmacy is fast changing from one primarily focused on dispensing medicinal goods to one intensely focused on the delivery of patient care. This has led pharmacists to be involved in a diverse clinical service such as patient\u27s education, Medication Therapy Management (MTM) and medications dose adjustment. Implementing such services often place additional stress on the daily routine of pharmacists. Therefore, there is a high need to find efficient ways to support healthcare related clinical services. One of the widely used anticoagulant medications is warfarin. Warfarin has been available on the market as effective therapy in management of thrombotic disorders. However, warfarin is frequently associated with medications errors which may lead to serious adverse events. The purpose of this paper is to demonstrate this fact fully via warfarin dosing web application to help support healthcare professionals in clinical settings. Methods: Open-source programming language R in conjunction with RStudio version 1.2.5033 were used to develop and implement our warfarin dosing platform. Shiny packages for R with other packages were used to create our platform as a web-based app. We based our calculations and function of our platform on the UW health warfarin management- adult- ambulatory clinical practice guidelines. Results: The platform contains three tools users can use:1) Calculating the warfarin maintenance dose,2) Selecting INR goals and duration of therapy,3) Assessment of Bleeding risk. Additionally, the app has a hyperlink to direct the users to the resource used in this app. On the first page of the app, the user can select their INR target and input a patients INR and weekly dose. Then, the app will immediately display the results. On the second page of the app, there is a feature for users helps to choose the INR target recommended based on patient conditions; There is a drop down menu contains different type of antithrombotic indications. Additionally, on the third page of the app, there is a feature for users helps to calculate the bleeding risk using HAS-BLED score. The users can answer “Yes” or “No” on multiple risk factors to stratify patients’ risk into low, moderate or high. Conclusion: Our warfarin dosing platform demonstrates the feasibility of creating a free-tool for healthcare professionals to facilitate their daily practice and potential for reducing medication related errors. Additionally, we demonstrate that pharmacists can take advantage of open-sources resources available to develop any health-related application suitable to their needs. Future Directions: The skills gained in the implementation of this full stack web application development will be further improved upon to develop additional clinical support tools for pharmacists. Further implementations will also incorporate fully or partially trained machine learning models. Our ultimate goal is to allow pharmacists to utilize data driven decision making strategies to implement fast and effective patient care.https://scholarscompass.vcu.edu/gradposters/1160/thumbnail.jp

Molecular Predictors of Anakinra Treatment Success in Heart Failure Patients with Reduced Ejection Fraction

Background. Kineret (Anakinra) is an interleukin-1 antagonist that is under investigation for its novel clinical application treating patients that have heart failure with reduced (\u3c50%) ejection fraction (HFrEF). A prior study from our group indicated that Anakinra may restore heart function by addressing dysregulations in HFrEF metabolic pathways. Herein, we attempt to elicit Anakinra’s effects on both metabolome and lipidome. Methods. Lipids and metabolites that had previously been quantified by mass spectrometry (MS) from patients (n=49) who had ≥2 mg/L of high-sensitivity C-reactive protein (hs-CRP) were mTIC normalized and transformed. We conducted a stepwise Linear Discriminant Analysis (r- LDA) to test Anakinra (2 and 12 weeks) vs placebo for separation from combined baseline. Metabolic pathway analysis was performed with Fisher’s exact test algorithm for detection of over-represented and enriched analytes. Univariate analysis (one tailed t-test p\u3c0.05) compared placebo and Anakinra after 12-weeks for effect(s). Metaboanalyst 4.0, JMP Pro 14.0, and a proprietary package in R (version 3.4.4) were the software for all analyses and data wrangling. Results. Analytes such as acylcarnitines C10:0 and C16:0 and hsCRP showed significant improvements after 12 weeks of Anakinra, leading to improved mitochondrial function, reduced inflammation, and overall better health outcomes. Statistically significant (p\u3c0.05) pathways including the citrate cycle, cysteine and methionine metabolism, galactose metabolism among others were associated with treatment. Conclusions. We were able to determine significant alterations to metabolomic and lipidomic concentrations after 12 weeks of Anakinra therapy. Our biochemical analyses verifies that Anakinra did improve heart function within our HFrEF pilot cohort.https://scholarscompass.vcu.edu/gradposters/1081/thumbnail.jp