Muscle growth occurs during embryonic development and continues in adult life as regeneration. During embryonic muscle growth and regeneration in mature muscle, singly nucleated myoblasts fuse to each other to form myotubes. In muscle growth, singly nucleated myoblasts can also fuse to existing large,syncytial myofibers as a mechanism of increasing muscle mass without increasing myofiber number. Myoblast fusion requires the alignment and fusion of two apposed lipid bilayers. The repair of muscle plasma membrane disruptions also relies on the fusion of two apposed lipid bilayers. The protein dysferlin, the product of the Limb Girdle Muscular Dystrophy type 2 locus, has been shown to be necessary for efficient, calcium-sensitive,membrane resealing. We now show that the related protein myoferlin is highly expressed in myoblasts undergoing fusion, and is expressed at the site of myoblasts fusing to myotubes. Like dysferlin, we found that myoferlin binds phospholipids in a calcium-sensitive manner that requires the first C2A domain. We generated mice with a null allele of myoferlin. Myoferlin null myoblasts undergo initial fusion events, but they form large myotubes less efficiently in vitro, consistent with a defect in a later stage of myogenesis. In vivo, myoferlin null mice have smaller muscles than controls do, and myoferlin null muscle lacks large diameter myofibers. Additionally, myoferlin null muscle does not regenerate as well as wild-type muscle does, and instead displays a dystrophic phenotype. These data support a role for myoferlin in the maturation of myotubes and the formation of large myotubes that arise from the fusion of myoblasts to multinucleate myotubes.

Background: Despite clear evidence for the efficacy of lowering cholesterol levels, there is a deficiency in its realworld application. There is a need to explore alternative strategies to address this important public health problem. This study aimed to determine the effect of a program of community pharmacist intervention on the process of cholesterol risk management in patients at high risk for cardiovascular events.

Skeletal muscle is a multinucleated syncytium that develops and is maintained by the fusion of myoblasts to the syncytium. Myoblast fusion involves the regulated coalescence of two apposed membranes. Myoferlin is a membrane-anchored, multiple C2 domain-containing protein that is highly expressed in fusing myoblasts and required for efficient myoblast fusion to myotubes. We found that myoferlin binds directly to the eps15 homology domain protein, EHD2. Members of the EHD family have been previously implicated in endocytosis as well as endocytic recycling, a process where membrane proteins internalized by endocytosis are returned to the plasma membrane. EHD2 binds directly to the second C2 domain of myoferlin, and EHD2 is reduced in myoferlin null myoblasts. In contrast to normal myoblasts, myoferlin null myoblasts accumulate labeled transferrin and have delayed recycling. Introduction of dominant negative EHD2 into myoblasts leads to the sequestration of myoferlin and inhibition of myoblast fusion. The interaction of myoferlin with EHD2 identifies molecular overlap between the endocytic recycling pathway and the machinery that regulates myoblast membrane fusion.

SCRIP (Study of Cardiovascular Risk Intervention by Pharmacists) is a unique ongoing trial that is evaluating a community pharmacist intervention designed to optimize cholesterol risk management in patients at high risk for cardiovascular events.

BackgroundIncreased spatial QRS-T angle has been shown to predict appropriate implantable cardioverter defibrilIator (ICD) therapy in patients with left ventricular systolic dysfunction (LVSD). We performed a retrospective cohort study in patients with left ventricular ejection fraction (LVEF) 31–40% to assess the relationship between the spatial QRS-T angle and other advanced ECG (A-ECG) as well as echocardiographic metadata, with all-cause mortality or ICD implantation for secondary prevention.Methods534 patients ≤75 years of age with LVEF 31–40% were identified through an echocardiography reporting database. Digital 12-lead ECGs were retrospectively matched to 295 of these patients, for whom echocardiographic and A-ECG metadata were then generated. Data mining was applied to discover novel ECG and echocardiographic markers of risk. Machine learning was used to develop a model to predict possible outcomes.Results49 patients (17%) had events, defined as either mortality (n = 16) or ICD implantation for secondary prevention (n = 33). 72 parameters (58 A-ECG, 14 echocardiographic) were univariately different (p<0.05) in those with vs. without events. After adjustment for multiplicity, 24 A-ECG parameters and 3 echocardiographic parameters remained different (p<2x10-3). These included the posterior-to-leftward QRS loop ratio from the derived vectorcardiographic horizontal plane (previously associated with pulmonary artery pressure, p = 2x10-6); spatial mean QRS-T angle (134 vs. 112°, p = 1.6x10-4); various repolarisation vectors; and a previously described 5-parameter A-ECG score for LVSD (p = 4x10-6) that also correlated with echocardiographic global longitudinal strain (R2 = - 0.51, P < 0.0001). A spatial QRS-T angle >110° had an adjusted HR of 3.4 (95% CI 1.6 to 7.4) for secondary ICD implantation or all-cause death and adjusted HR of 4.1 (95% CI 1.2 to 13.9) for future heart failure admission. There was a loss of complexity between A-ECG and echocardiographic variables with an increasing degree of disease.ConclusionSpatial QRS-T angle >110° was strongly associated with arrhythmic events and all-cause death. Deep analysis of global ECG and echocardiographic metadata revealed underlying relationships, which otherwise would not have been appreciated. Delivered at scale such techniques may prove useful in clinical decision making in the future.

SummaryDespite several clinical practice guidelines, there remains a considerable gap in prevention and management of obesity in primary care. To address the need for changing provider behaviour, a randomized controlled trial with convergent mixed method evaluation, the 5As Team (5AsT) study, was conducted. As part of the 5AsT intervention, the 5AsT tool kit was developed. This paper describes the development process and evaluation of these tools. Tools were co‐developed by the multidisciplinary research team and the 5AsT, which included registered nurses/nurse practitioners (n = 15), mental health workers (n = 7) and registered dieticians (n = 7), who were previously randomized to the 5AsT intervention group at a primary care network in Edmonton, Alberta, Canada. The 5AsT tool development occurred through a practice/implementation‐oriented, need‐based, iterative process during learning collaborative sessions of the 5AsT intervention. Feedback during tool development was received through field notes and final provider evaluation was carried out through anonymous questionnaires. Twelve tools were co‐developed with 5AsT. All tools were evaluated as either ‘most useful’ or ‘moderately useful’ in primary care practice by the 5AsT. Four key findings during 5AsT tool development were the need for: tools that were adaptive, tools to facilitate interdisciplinary practice, tools to help patients understand realistic expectations for weight loss and shared decision‐making tools for goal setting and relapse prevention. The 5AsT tools are primary care tools which extend the utility of the 5As of obesity management framework in clinical practice.

Breast cancer incidence differs by ethnicity in New Zealand (NZ) with Māori (the indigenous people) women having the highest rates followed by Pakeha (people primarily of British/European descent), Pacific and Asian women, who experience the lowest rates. The reasons for these differences are unclear. Breast density, an important risk factor for breast cancer, has not previously been studied here. We used an automated system, Volpara™, to measure breast density volume from the medio-lateral oblique view of digital mammograms, by age (≤50 years and >50 years) and ethnicity (Pakeha/Māori/Pacific/Asian) using routine data from the national screening programme: age; x-ray system and mammography details for 3,091 Pakeha, 716 Māori, 170 Pacific and 662 Asian (total n = 4,239) women. Linear regression of the natural logarithm of absolute and percent density values was used, back-transformed and expressed as the ratio of the geometric means. Covariates were age, x-ray system and, for absolute density, the natural log of the volume of non-dense tissue (a proxy for body mass index). Median age for Pakeha women was 55 years; Māori 53 years; and Pacific and Asian women, 52 years. Compared to Pakeha women (reference), Māori had higher absolute volumetric density (1.09; 95% confidence interval [95% CI] 1.03–1.15) which remained following adjustment (1.06; 95% CI 1.01–1.12) and was stronger for older compared to younger Māori women. Asian women had the greatest risk of high percentage breast density (1.35; 95% CI 1.27–1.43) while Pacific women in both the ≤50 and >50 year age groups (0.78; 95% CI 0.66–0.92 and 0.81; 95% CI 0.71–0.93 respectively) had the lowest percentage breast density compared to Pakeha. As well as expected age differences, we found differential patterns of breast density by ethnicity consistent with ethnic differences seen in breast cancer risk. Breast density may be a contributing factor to NZ’s well-known, but poorly explained, inequalities in breast cancer incidence.

Electrocardiogram (ECG)-based detection of left ventricular systolic dysfunction (LVSD) has poor specificity and positive predictive value, even when including major ECG abnormalities, such as left bundle branch block (LBBB) within the criteria for diagnosis. Although machine-read ECG algorithms do not provide information on LVSD, advanced ECG (A-ECG), using multiparameter scores, has superior diagnostic utility to strictly conventional ECG for identifying various cardiac pathologies, including LVSD. Methods: We evaluated the diagnostic utility of A-ECG in a case-control study of 40 patients with LVSD (LV ejection fraction < 50% by echocardiography), due to non-ischemic cardiomyopathy (NICM), and 39 other patients without LVSD. Diagnostic sensitivity and specificity for LVSD were determined after applying a previously validated probabilistic A-ECG score for LVSD to stored standard (10 s) clinical 12L ECGs. In 25 of the NICM patients who had serial ECGs and echocardiograms, changes in the A-ECG score versus in echocardiographic LV ejection fraction were also studied to determine the level of agreement between the two tests. Results: Analyses by A-ECG had a sensitivity of 95% for LVSD (93% if excluding N = 11 patients with LBBB) and specificity of 95%. In the 29 NICM patients without LBBB who had serial ECGs, sensitivity improved to 97% when all ECGs were considered. By comparison, human readers in a busy clinical environment had a sensitivity of 90% and specificity of 63%. A-ECG score trajectories demonstrated improvement, deterioration or no change in LVSD, which agreed with echocardiography, in 76% of cases (n = 25). Conclusion: A-ECG scoring detects LVSD due to NICM with high sensitivity and specificity. Serial A-ECG score trajectories also represent a method for inexpensively demonstrating changes in LVSD. A-ECG scoring may be of particular value in areas where echocardiography is unavailable, or as a gatekeeper for echocardiography.