Relationship between visual prostate score (VPSS) and maximum flow rate (Qmax) in men with urinary tract symptoms

Abstract OBJECTIVE: To evaluate correlation between visual prostate score (VPSS) and maximum flow rate (Qmax) in men with lower urinary tract symptoms. MATERIAL AND METHODS: This is a cross sectional study conducted at a university Hospital. Sixty-seven adult male patients\u3e50 years of age were enrolled in the study after signing an informed consent. Qmax and voided volume recorded at uroflowmetry graph and at the same time VPSS were assessed. The education level was assessed in various defined groups. Pearson correlation coefficient was computed for VPSS and Qmax. RESULTS: Mean age was 66.1±10.1 years (median 68). The mean voided volume on uroflowmetry was 268±160mL (median 208) and the mean Qmax was 9.6±4.96mLs/sec (median 9.0). The mean VPSS score was 11.4±2.72 (11.0). In the univariate linear regression analysis there was strong negative (Pearson\u27s) correlation between VPSS and Qmax (r=-848, p\u3c0.001). In the multiple linear regression analyses there was a significant correlation between VPSS and Qmax (β-http://www.blogapaixonadosporviagens.com.br/p/caribe.html after adjusting the effect of age, voided volume (V.V) and level of education. Multiple linear regression analysis done for independent variables and results showed that there was no significant correlation between the VPSS and independent factors including age (p=0.27), LOE (p=0.941) and V.V (p=0.082). CONCLUSION: There is a significant negative correlation between VPSS and Qmax. The VPSS can be used in lieu of IPSS score. Men even with limited educational background can complete VPSS without assistance

Bacteriocin-mediated inhibition of some common pathogens by wild and mutant Lactobacillus species and in vitro amplification of bacteriocin encoding genes

Lactobacilli are the most common probiotics used in food and other industries because of their capability of producing bacteriocins. Bacteriocins are compounds that are used to kill pathogenic microorganisms. As most bacteria have become resistant to synthetic antibacterial tools, the importance of using probiotics as antibacterial agents has increased. This work was done to check the bacteriocin effect on some common pathogens and the influence of mutation on the bacteriocin activity of Lactobacilli was also investigated. Four strains were isolated, identified from meat and pickles samples via culturing methods, staining, biochemical tests, and ribotyping. Preliminary tests, including Gram staining and catalase test, were done for the confirmation of Lactobacillus species. All strains were gram-positive and catalase-negative. Antibacterial activity was checked against Pseudomonas aeruginosa, Staphylococcus aureus, Bacillus thuringiensis, Escherichia coli, and Salmonella enteritis via agar well diffusion method. The mutations were done using ethidium bromide and the influence of wild and mutants were also checked. Interestingly, mutants developed more virulence than wild ones. It was also observed that they all were sensitive to pepsin. Protein estimation was done via Bradford method. Ribotyping of GCU-W-PS1 revealed 99 % homology with Lactobacillus plantarum and GCU-W-MS1 to Lactobacillus curvatus (99 % homology). Curvacin A, sakacin P, and plantaricin A genes were also amplified using specific primers. Gene sequence showed the presence of curvacin A gene in GCU-W-MS1. It was concluded that lactic acid bacteria could be used as antibacterial tools against common pathogens

MAVERICK: An App-independent and Platform-agnostic Approach to Enforce Policies in IoT Systems at Runtime

Many solutions have been proposed to curb unexpected behavior of automation apps installed on programmable IoT platforms by enforcing safety policies at runtime. However, all prior work addresses a weaker version of the actual problem due to a simpler, unrealistic threat model. These solutions are not general enough as they are heavily dependent on the installed apps and catered to specific IoT platforms. Here, we address a stronger version of the problem via a realistic threat model, where (i) undesired cyber actions can come from not only automation platform backends (e.g., SmartThings) but also close-sourced third-party services (e.g., IFTTT), and (ii) physical actions (e.g., user interactions) on devices can move the IoT system to an undesirable state. We propose a runtime mechanism, dubbed Maverick, which employs an app-independent, platform-agnostic mediator to enforce policies against all undesired cyber actions and applies corrective-actions to bring the IoT system back to a safe state from an unsafe state transition. Maverick is equipped with a policy language capable of expressing rich temporal invariants and an automated toolchain that includes a policy synthesizer and a policy analyzer for user assistance. We implemented Maverick in a prototype and showed its efficacy in both physical and virtual testbeds, incurring minimal overhead.Comment: 13 pages, full version with material cut from version accepted at ACM WiSec 202

High-Performance Modeling and Simulation of Anchoring in Granular Media for NEO Applications

NASA is interested in designing a spacecraft capable of visiting a near-Earth object (NEO), performing experiments, and then returning safely. Certain periods of this mission would require the spacecraft to remain stationary relative to the NEO, in an environment characterized by very low gravity levels; such situations require an anchoring mechanism that is compact, easy to deploy, and upon mission completion, easy to remove. The design philosophy used in this task relies on the simulation capability of a high-performance multibody dynamics physics engine. On Earth, it is difficult to create low-gravity conditions, and testing in low-gravity environments, whether artificial or in space, can be costly and very difficult to achieve. Through simulation, the effect of gravity can be controlled with great accuracy, making it ideally suited to analyze the problem at hand. Using Chrono::Engine, a simulation pack age capable of utilizing massively parallel Graphic Processing Unit (GPU) hardware, several validation experiments were performed. Modeling of the regolith interaction has been carried out, after which the anchor penetration tests were performed and analyzed. The regolith was modeled by a granular medium composed of very large numbers of convex three-dimensional rigid bodies, subject to microgravity levels and interacting with each other with contact, friction, and cohesional forces. The multibody dynamics simulation approach used for simulating anchors penetrating a soil uses a differential variational inequality (DVI) methodology to solve the contact problem posed as a linear complementarity method (LCP). Implemented within a GPU processing environment, collision detection is greatly accelerated compared to traditional CPU (central processing unit)- based collision detection. Hence, systems of millions of particles interacting with complex dynamic systems can be efficiently analyzed, and design recommendations can be made in a much shorter time. The figure shows an example of this capability where the Brazil Nut problem is simulated: as the container full of granular material is vibrated, the large ball slowly moves upwards. This capability was expanded to account for anchors of different shapes and penetration velocities, interacting with granular soils

Correlation of red cell distribution width with inflammatory markers and its prognostic value in patients with diabetes and coronary artery disease

Background. Recent studies have shown red blood cell distribution width (RDW) as a marker for severity and prognosis in coronary artery disease patients. Other studies have also correlated RDW with diabetes mellitus and inflammation. However, such correlation and prognosis in patients with concomitant coronary artery disease and diabetes after percutaneous intervention remains unclear. Material and methods. Our study group comprised of 730 subjects including 700 patients (cases) and 30 normal subjects (control group). Patients who presented with coronary artery disease were divided into diabetic and non-diabetic groups. All patients had RDW measured at admission and percutaneous intervention was done. Follow-up for adverse events was carried out between 6 to 12 months. Results. RDW was elevated in patients as compared to control group (p < 0.05). RDW correlated well with inflammatory markers including erythrocyte sedimen­tation rate, C-reactive protein, HbA1c, white blood cells and troponin. RDW was higher with more severe atherosclerosis based on SYNTAX and Gensini scores (p < 0.05). Prognosis was found to be worse in patients with high RDW as well as in diabetics. Conclusions. RDW has positive correlation with other inflammatory marker. It may be used as a marker in determining the severity and prognosis in diabetic patients with coronary artery disease

Prognostic significance of serum potassium level for major adverse cardiac events and death in patients with coronary atherosclerotic disease

Introduction: Serum potassium levels have been shown in some animal studies to be associated with theprocess of atherosclerosis. We decided to assess the correlation of serum potassium level in ischemic heart diseasepatients with disease severity and its relationship with prognosis in terms of major acute cardiac events (MACE). Material and methods: This was a cross-sectional cohort study carried out at cardiology department of RehmanMedical Institute, from July 2016 to 31st Aug. 2018 a period of 26 months. 622 patients were included in thestudy. Clinical and angiographic characteristics were assessed based on the serum potassium level. Correlation ofserum potassium level with Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery(SYNTAX) and Gensini scores was also evaluated. Follow up for MACE was carried out after one year. Results: Mean serum potassium level was 3.93 ± 0.95 (mEq/l) in coronary artery disease patients. Serumpotassium level showed negative correlation with SYNTAX score (r = –0.60, p < 0.05) and Gensini score(r = –0.64, p < 0.05). There was also a significant difference between low and high potassium level in relationto the multi-vessel disease on coronary angiography (p < 0.05). Low potassium level was a good predictor ofadverse outcomes as shown by Kaplan-Meier analysis. Multivariate Cox regression analysis showed that serumpotassium level and diabetes were independent predictors of MACE (p < 0.05). Conclusion: Low serum potassium level is correlated with more severe coronary atherosclerosis. Low potassiumlevels are associated with significantly poor outcomes

Granular Simulation of NEO Anchoring

NASA is interested in designing a spacecraft capable of visiting a Near Earth Object (NEO), performing experiments, and then returning safely. Certain periods of this mission will require the spacecraft to remain stationary relative to the NEO. Such situations require an anchoring mechanism that is compact, easy to deploy and upon mission completion, easily removed. The design philosophy used in the project relies on the simulation capability of a multibody dynamics physics engine. On Earth it is difficult to create low gravity conditions and testing in low gravity environments, whether artificial or in space is costly and therefore not feasible. Through simulation, gravity can be controlled with great accuracy, making it ideally suited to analyze the problem at hand. Using Chrono::Engine [1], a simulation package capable of utilizing massively parallel GPU hardware, several validation experiments will be performed. Once there is sufficient confidence, modeling of the NEO regolith interaction will begin after which the anchor tests will be performed and analyzed. The outcome of this task is a study with an analysis of several different anchor designs, along with a recommendation on which anchor is better suited to the task of anchoring. With the anchors tested against a range of parameters relating to soil, environment and anchor penetration angles/velocities on a NEO