Atherosclerosis represents a significant cause of morbidity and mortality in both the developed and developing countries. Animal models of atherosclerosis have served as valuable tools for providing insights on its aetiology, pathophysiology and complications. They can be used for invasive interrogation of physiological function and provide a platform for testing the efficacy and safety of different pharmacological therapies. Compared to studies using human subjects, animal models have the advantages of being easier to manage, with controllable diet and environmental risk factors. Moreover, pathophysiological changes can be induced either genetically or pharmacologically to study the harmful effects of these interventions. There is no single ideal animal model, as different systems are suitable for different research objectives. A good understanding of the similarities and differences to humans enables effective extrapolation of data for translational application. In this article, we will examine the different mouse models for the study and elucidation of the pathophysiological mechanisms underlying atherosclerosis. We also review recent advances in the field, such as the role of oxidative stress in promoting endoplasmic reticulum stress, mitochondrial dysfunction and mitochondrial DNA damage, which can result in vascular inflammation and atherosclerosis. Finally, novel therapeutic approaches to reduce vascular damage caused by chronic inflammation using microRNA and nano-medicine technology, are discussed.

Background Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband. Objective This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research. Methods We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV). Results The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF. Conclusions A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening.

BackgroundModern smartphones allow measurement of heart rate (HR) by detecting pulsatile photoplethysmographic (PPG) signals with built-in cameras from the fingertips or the face, without physical contact, by extracting subtle beat-to-beat variations of skin color.ObjectiveThe objective of our study was to evaluate the accuracy of HR measurements at rest and after exercise using a smartphone-based PPG detection app.MethodsA total of 40 healthy participants (20 men; mean age 24.7, SD 5.2 years; von Luschan skin color range 14-27) underwent treadmill exercise using the Bruce protocol. We recorded simultaneous PPG signals for each participant by having them (1) facing the front camera and (2) placing their index fingertip over an iPhone’s back camera. We analyzed the PPG signals from the Cardiio-Heart Rate Monitor + 7 Minute Workout (Cardiio) smartphone app for HR measurements compared with a continuous 12-lead electrocardiogram (ECG) as the reference. Recordings of 20 seconds’ duration each were acquired at rest, and immediately after moderate- (50%-70% maximum HR) and vigorous- (70%-85% maximum HR) intensity exercise, and repeated successively until return to resting HR. We used Bland-Altman plots to examine agreement between ECG and PPG-estimated HR. The accuracy criterion was root mean square error (RMSE) ≤5 beats/min or ≤10%, whichever was greater, according to the American National Standards Institute/Association for the Advancement of Medical Instrumentation EC-13 standard.ResultsWe analyzed a total of 631 fingertip and 626 facial PPG measurements. Fingertip PPG-estimated HRs were strongly correlated with resting ECG HR (r=.997, RMSE=1.03 beats/min or 1.40%), postmoderate-intensity exercise (r=.994, RMSE=2.15 beats/min or 2.53%), and postvigorous-intensity exercise HR (r=.995, RMSE=2.01 beats/min or 1.93%). The correlation of facial PPG-estimated HR was stronger with resting ECG HR (r=.997, RMSE=1.02 beats/min or 1.44%) than with postmoderate-intensity exercise (r=.982, RMSE=3.68 beats/min or 4.11%) or with postvigorous-intensity exercise (r=.980, RMSE=3.84 beats/min or 3.73%). Bland-Altman plots showed better agreement between ECG and fingertip PPG-estimated HR than between ECG and facial PPG-estimated HR.ConclusionsWe found that HR detection by the Cardiio smartphone app was accurate at rest and after moderate- and vigorous-intensity exercise in a healthy young adult sample. Contact-free facial PPG detection is more convenient but is less accurate than finger PPG due to body motion after exercise.

Objectives The aim of this study is to determine major adverse cardiovascular events (MACE) and all-cause mortality comparing between xanthine oxidase inhibitors (XOIs) and non-XOI users, and between allopurinol and febuxostat. Methods This is a retrospective cohort study of gout patients prescribed anti-hyperuricemic medications between 2013 and 2017 using a territory-wide administrative database. XOI users were matched 1:1 to XOI non-users using propensity scores. Febuxostat users were matched 1:3 to allopurinol users. Subgroup analyses were conducted based on colchicine use. Results Of the 13 997 eligible participants, 3607 (25.8%) were XOI users and 10 390 (74.2%) were XOI non-users. After propensity score matching, compared with non-users (n = 3607), XOI users (n = 3607) showed similar incidence of MACE (hazard ratio [HR]: 0.997, 95% CI, 0.879, 1.131; P>0.05) and all-cause mortality (HR = 0.972, 95% CI 0.886, 1.065, P=0.539). Febuxostat (n = 276) users showed a similar risk of MACE compared with allopurinol users (n = 828; HR: 0.672, 95% CI, 0.416, 1.085; P=0.104) with a tendency towards a lower risk of heart failure-related hospitalizations (HR = 0.529, 95% CI 0.272, 1.029; P=0.061). Concurrent colchicine use reduced the risk for all-cause mortality amongst XOI users (HR = 0.671, 95% 0.586, 0.768; P<0.001). Conclusion In gout patients, XOI users showed similar risk of MACE and all-cause mortality compared with non-users. Compared with allopurinol users, febuxostat users showed similar MACE and all-cause mortality risks but lower heart failure-related hospitalizations.

Arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) is an inherited myocardial disease characterized by fibro‐fatty replacement of the right ventricular myocardium, and associated with paroxysmal ventricular arrhythmias and sudden cardiac death (SCD). It is currently the second most common cause of SCD after hypertrophic cardiomyopathy in young people <35 years of age, causing up to 20% of deaths in this patient population. This condition has a male preponderance and is more commonly found in individuals of Italian and Greek descent. To date, there is no single diagnostic test for ARVC/D and the diagnosis is made based on clinical, electrocardiographic, and radiological findings according to the Revised 2010 Task Force Criteria. In this review, we will discuss the mainstay treatment which includes pharmacotherapy, implantable cardioverter‐defibrillator insertion for abortion of sudden cardiac death, and in the advanced stages of the disease cardiac transplantation.