Unravelling the unseen ‘C’ with the cone beam computed tomography: a rare case report

Recognition of aberrant root canal configurations is critical to successfully negotiate and treat a canal and one of such aberrancies is a C shape root canal system. The fins and webs present in a C shape canal system presents a challenge to debridement and obturation. Knowledge of variations through advanced imaging modalities like CBCT, rotary and hand instruments assisted with ultrasonics and modified obturation techniques aid in effective management of C shaped root canals. This case report presents a successful endodontic management of a rare c shape canal configuration in a mandibular second premolar with the aid of the cone‑beam computed tomography (CBCT) scanning imaging technique

Associations Between High-Density Lipoprotein Particles and Ischemic Events by Vascular Domain, Sex, and Ethnicity A Pooled Cohort Analysis

Background: High-density lipoprotein (HDL) cholesterol concentration (HDL-C) is an established atheroprotective marker, in particular for coronary artery disease; however, HDL particle concentration (HDL-P) may better predict risk. The associations of HDL-C and HDL-P with ischemic stroke and myocardial infarction (MI) among women and Blacks have not been well studied. We hypothesized that HDL-P would consistently be associated with MI and stroke among women and Blacks compared with HDL-C. Methods: We analyzed individual-level participant data in a pooled cohort of 4 large population studies without baseline atherosclerotic cardiovascular disease: DHS (Dallas Heart Study; n=2535), ARIC (Atherosclerosis Risk in Communities; n=1595), MESA (Multi-Ethnic Study of Atherosclerosis; n=6632), and PREVEND (Prevention of Renal and Vascular Endstage Disease; n=5022). HDL markers were analyzed in adjusted Cox proportional hazard models for MI and ischemic stroke. Results: In the overall population (n=15 784), HDL-P was inversely associated with the combined outcome of MI and ischemic stroke, adjusted for cardiometabolic risk factors (hazard ratio [HR] for quartile 4 [Q4] versus quartile 1 [Q1], 0.64 [95% CI, 0.52-0.78]), as was HDL-C (HR for Q4 versus Q1, 0.76 [95% CI, 0.61-0.94]). Adjustment for HDL-C did not attenuate the inverse relationship between HDL-P and atherosclerotic cardiovascular disease, whereas adjustment for HDL-P attenuated all associations between HDL-C and events. HDL-P was inversely associated with the individual end points of MI and ischemic stroke in the overall population, including in women. HDL-P was inversely associated with MI among White participants but not among Black participants (HR for Q4 versus Q1 for Whites, 0.49 [95% CI, 0.35-0.69]; for Blacks, 1.22 [95% CI, 0.76-1.98];P-interaction=0.001). Similarly, HDL-C was inversely associated with MI among White participants (HR for Q4 versus Q1, 0.53 [95% CI, 0.36-0.78]) but had a weak direct association with MI among Black participants (HR for Q4 versus Q1, 1.75 [95% CI, 1.08-2.83];P-interactio

Abstract 688: Differential Associations Between Novel HDL Markers and Incident Atherosclerotic Cardiovascular Disease by Gender and Vascular Territory: A Meta-analysis of Large Population-based Cohorts

Background: There has been conflicting evidence regarding the association between high-density lipoprotein cholesterol (HDL-C) and atherosclerotic disease, especially given the failure of several therapeutic strategies aimed at raising HDL-C in demonstrating cardiovascular benefits. HDL-P may better predict atherosclerotic cardiovascular disease (ASCVD) compared to HDL-C. The relationship between novel markers of cholesterol overload such as HDL-C/HDL-P and HDL-size/HDL-P and stroke in women is also less well established. Objective: To investigate whether novel HDL markers like HDL-P, HDL size/HDL-P and HDL-C/HDL-P predict stroke better than HDL-C in both men and women. Methods: We performed an individual level meta-analyses of two large patient cohorts - Dallas Heart Study (DHS) and Multi-Ethnic Study of Atherosclerosis (MESA) with HDL marker phenotyping available for 9503 subjects from both cohorts. Cox proportional hazards models were constructed for the HDL markers of interest with adjustment for traditional cardiovascular risk factors. Results: HDL-C was not significantly associated with ASCVD, MI or stroke whereas HDL-P was inversely associated with ASCVD events in both men (n=4378, 444 events) and women (n=5125, 270 events) (Figure 1). HDL-C/HDL-P was directly associated with ASCVD in women (HR 1.39, 95% CI 1-1.93). This was largely driven by the association between HDL-C/HDL-P and stroke (HR 1.99, 95% CI 1.42-2.79). HDL-size/HDL-P was directly associated with ASCVD (HR 1.24, 95%CI 1.1-1.39) in women with similar effect sizes for both MI and stroke. In contrast, among men, both HDL-C/HDL-P and HDL size/HDL-P were directly associated with ASCVD, largely driven by MI and less so by stroke. Conclusions: Reduced HDL-P and increased indices of cholesterol overload may predict atherosclerotic risk more accurately than HDL-C alone. These relationships may vary with gender and vascular territory

Gamification and Machine Learning Inspired Approach for Classroom Engagement and Learning

Technology has enhanced the scope and span of the teaching and learning process but somehow it could not enhance the self-motivation and engagement among the students to the same scale. The lack of self-motivation and intermittent engagement is one of the prime challenges faced by educators today. Perplexing tasks for the faculty are to embroil students during the lecture. This work paves new ways to scale up the enticement using artificial intelligence and machine learning. The intelligent framework proposed here is built on yet another novel methodology used globally for user engagement and is termed gamification. The primary objective of the present research work is to negate the issue of disengagement by designing and implementing a gamified framework on 120 students from higher education that will include student engagement, enticement, and motivation. Generally, mechanisms are designed for specific courses, whereas the gamified system proposed is an open-ended method irrespective of course and the program being studied, and this framework has endeavored on multiple courses. To enhance the utility of the gamified framework, ANFIS model is utilized for smart decision-making concerning rewards distribution that is directly proportional to the number of coins gained by the students. As an outcome, better participation of a group of students under the proposed intelligent gamified system is reported as compared to the control group thus endorsing the success of the model