Assessing the Relationship Between Vape Use and Cardiovascular Disease Risk

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Breaking Sedentary Behavior among Faculty and Staff: Are Acoustic and/or Vibrational Stimuli Effective?

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A Machine learning Classification approach for detection of Covid 19 using CT images

Coronavirus disease 2019 popularly known as COVID 19 was first found in Wuhan, China in December 2019. World Health Organization declared Covid 19 as a transmission disease. The symptoms were cough, loss of taste, fever, tiredness, respiratory problem. These symptoms were likely to show within 11 –14 days. The RT-PCR and rapid antigen biochemical tests were done for the detection of COVID 19. In addition to biochemical tests, X-Ray and Computed Tomography (CT) images are used for the minute details of the severity of the disease. To enhance efficiency and accuracy of analysis/detection of COVID images and to reduce of doctors' time for analysis could be addressed through Artificial Intelligence. The dataset from Kaggle was utilized to analyze. The statistical and GLCM features were extracted from CT images for the classification of COVID and NON-COVID instances in this study. CT images were used to extract statistical and GLCM features for categorization. In the proposed/prototype model, we achieved the classification accuracy of 91%, and 94.5% using SVM and Random Forest respectively

Nitrogen sources on TPOMW valorization through solid state fermentation performed by Yarrowia lipolytica

This manuscript reports the valorization of two-phase olive mill waste (TPOMW) as raw material and carbon source for solid state fermentation using Yarrowia lipolytica as biocatalyst. Due to its chemical characteristics, a combination of different raw materials (TPOMW and wheat bran, WB) was evaluated and two distinct nitrogen sources were applied as supplementation for lipase production. A TPOMW/WB ratio of 1:1 and supplementation with ammonium sulfate was chosen as the best condition. The productivity in 24 h reached 7.8 U/gh and, after four days of process, only decreased about 35%. Process pH ranged from 5.5-5.9, remaining in an acid range. Thus, the successful use of TPOMW, a watery solid by-product with high content of lipids, as raw material for Yarrowia lipolytica growth and lipase production provided an environmental friendly alternative to valorize such waste.The authors kindly acknowledge the financial aid and research scholarships given by CAPES. Maria Alice Zarur Coelho thanks CNPq (Proc. 308890/ 2013-2)

Unified selective sorting approach to analyse multi-electrode extracellular data

Extracellular data analysis has become a quintessential method for understanding the neurophysiological responses to stimuli. This demands stringent techniques owing to the complicated nature of the recording environment. In this paper, we highlight the challenges in extracellular multi-electrode recording and data analysis as well as the limitations pertaining to some of the currently employed methodologies. To address some of the challenges, we present a unified algorithm in the form of selective sorting. Selective sorting is modelled around hypothesized generative model, which addresses the natural phenomena of spikes triggered by an intricate neuronal population. The algorithm incorporates Cepstrum of Bispectrum, ad hoc clustering algorithms, wavelet transforms, least square and correlation concepts which strategically tailors a sequence to characterize and form distinctive clusters. Additionally, we demonstrate the influence of noise modelled wavelets to sort overlapping spikes. The algorithm is evaluated using both raw and synthesized data sets with different levels of complexity and the performances are tabulated for comparison using widely accepted qualitative and quantitative indicators

Visit-to-visit and 24-h blood pressure variability: association with endothelial and smooth muscle function in African Americans

The purpose of this study was to investigate the association of visit-to-visit and 24-h blood pressure (BP) variability with markers of endothelial injury and vascular function. We recruited 72 African Americans who were non-diabetic, non-smoking and free of cardiovascular (CV) and renal disease. Office BP was measured at three visits and 24-h ambulatory BP monitoring was conducted to measure visit-to-visit and 24-h BP variability, respectively. The 5-min time-course of brachial artery flow-mediated dilation and nitroglycerin-mediated dilation were assessed as measures of endothelial and smooth muscle function. Fasted blood samples were analyzed for circulating endothelial microparticles (EMPs). Significantly lower CD31+CD42− EMPs were found in participants with high visit-to-visit systolic blood pressure (SBP) variability or high 24-h diastolic blood pressure (DBP) variability. Participants with high visit-to-visit DBP variability had significantly lower flow-mediated dilation and higher nitroglycerin-mediated dilation at multiple time-points. When analyzed as continuous variables, 24-h mean arterial pressure variability was inversely associated with CD62+ EMPs; visit-to-visit DBP variability was inversely associated with flow-mediated dilation normalized by smooth muscle function and was positively associated with nitroglycerin-mediated dilation; and 24-h DBP variability was positively associated with nitroglycerin-mediated dilation. All associations were independent of age, gender, body mass index and mean BP. In conclusion, in this cohort of African Americans visit-to-visit and 24-h BP variability were associated with measures of endothelial injury, endothelial function and smooth muscle function. These results suggest that BP variability may influence the pathogenesis of CV disease, in part, through influences on vascular health

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background: Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods: The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results: A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion: Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)