In the present study, channelrhodopsin 2 (ChR2) was specifically introduced into murine cells expressing the Phenylethanolamine n-methyltransferase (Pnmt) gene, which encodes for the enzyme responsible for conversion of noradrenaline to adrenaline. The new murine model enabled the identification of a distinctive class of Pnmt-expressing neuroendocrine cells and their descendants (i.e. Pnmt+ cell derived cells) within the heart. Here, we show that Pnmt+ cells predominantly localized to the left side of the adult heart. Remarkably, many of the Pnmt+ cells in the left atrium and ventricle appeared to be working cardiomyocytes based on their morphological appearance and functional properties. These Pnmt+ cell derived cardiomyocytes (PdCMs) are similar to conventional myocytes in morphological, electrical and contractile properties. By stimulating PdCMs selectively with blue light, we were able to control cardiac rhythm in the whole heart, isolated tissue preparations and single cardiomyocytes. Our new murine model effectively demonstrates functional dissection of cardiomyocyte subpopulations using optogenetics, and opens new frontiers of exploration into their physiological roles in normal heart function as well as their potential application for selective cardiac repair and regeneration strategies.

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the MBYC method. If this empirical correction is made, the relative standard deviation of the resulting data will be increased as a result of the uncertainty of the correction factor.Similar bias was noted for samples that contained a smaller concentration of americium.

IMPORTANCE Atrial fibrillation (AF) affects more than 6 million people in the United States; however, much AF remains undiagnosed. Given that more than 265 million people in the United States own smartphones (>80% of the population), smartphone applications have been proposed for detecting AF, but the accuracy of these applications remains unclear. OBJECTIVE To determine the accuracy of smartphone camera applications that diagnose AF. DATA SOURCES AND STUDY SELECTION MEDLINE and Embase were searched until January 2019 for studies that assessed the accuracy of any smartphone applications that use the smartphone's camera to measure the amplitude and frequency of the user's fingertip pulse to diagnose AF. DATA EXTRACTION AND SYNTHESIS Bivariate random-effects meta-analyses were constructed to synthesize data. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) of Diagnostic Test Accuracy Studies reporting guideline. MAIN OUTCOMES AND MEASURES Sensitivity and specificity were measured with bivariate random-effects meta-analysis. To simulate the use of these applications as a screening tool, the positive predictive value (PPV) and negative predictive value (NPV) for different population groups (ie, age Ն65 years and age Ն65 years with hypertension) were modeled. Lastly, the association of methodological limitations with outcomes were analyzed with sensitivity analyses and metaregressions. RESULTS A total of 10 primary diagnostic accuracy studies, with 3852 participants and 4 applications, were included. The oldest studies were published in 2016 (2 studies [20.0%]), while most studies (4 [40.0%]) were published in 2018. The applications analyzed the pulsewave signal for a mean (range) of 2 (1-5) minutes. The meta-analyzed sensitivity and specificity for all applications combined were 94.2% (95% CI, 92.2%-95.7%) and 95.8% (95% CI, 92.4%-97.7%), respectively. The PPV for smartphone camera applications detecting AF in an asymptomatic population aged 65 years and older was between 19.3% (95% CI, 19.2%-19.4%) and 37.5% (95% CI, 37.4%-37.6%), and the NPV was between 99.8% (95% CI, 99.83%-99.84%) and 99.9% (95% CI, 99.94%-99.95%). The PPV and NPV increased for individuals aged 65 years and older with hypertension (PPV, 20.5% [95% CI, 20.4%-20.6%] to 39.2% [95% CI, 39.1%-39.3%]; NPV, 99.8% [95% CI, 99.8%-99.8%] to 99.9% [95% CI, 99.9%-99.9%]). There were methodological limitations in a number of studies that did not appear to be associated with diagnostic performance, but this could not be definitively excluded given the sparsity of the data. CONCLUSIONS AND RELEVANCE In this study, all smartphone camera applications had relatively high sensitivity and specificity. The modeled NPV was high for all analyses, but the PPV was modest, (continued) Key Points Question What is the overall accuracy of smartphone camera applications that diagnose and screen for atrial fibrillation (AF)? Findings In this meta-analysis of 10 primary diagnostic accuracy studies with 3852 participants, all app...