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Aims: For healthy populations without comorbidities, whether prehypertension and impaired fasting glucose (IFG) are associated with new onset atrial fibrillation (AF) is not well known. Methods and results: We included 366 507 subjects (age =20 years) not diagnosed with non-valvular AF from the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC) from 2003 to 2008. In total, 139 306 subjects diagnosed with AF-related comorbidities were excluded, and a 227 102 healthy population was followed up until 2013. The body mass index (BMI), blood pressure (BP), and fasting blood glucose (BG) level were acquired during National health check-ups. Subjects with IFG [hazard ratio (HR) 1.16, P = 0.017] had a higher AF risk and the diastolic BP (HR 1.11, P = 0.045) was a stronger indicator for an AF incidence than the systolic BP. After dividing the subjects into two mutually exclusive groups, AF incidence was increased dramatically by the combination effect of both prehypertension and an IFG in BMI <25 kg/m² group, but, in BMI -25 kg/m² group, did not show this tendency. An IFG related to AF risk was more prominent in the BMI <25 kg/m² population (HR 1.18, P = 0.025) than those with a BMI =25 kg/m², and subjects with both an IFG and prehypertension had a greater AF risk (HR 1.27, P = 0.016) than those without. Conclusion: Even in a healthy Asian populations without comorbidities, prehypertension and IFG were important risk factors of AF. Specifically, when prehypertension, including systolic and diastolic BPs, was finally combined with the IFG, the risk of new onset AF was increased especially in the BMI <25 kg/m² group. [ABSTRACT FROM AUTHOR]

Aims Autophagy is essential to maintain tissue homeostasis, particularly in long-lived cells such as cardiomyocytes. Whereas many studies support the importance of autophagy in the mechanisms underlying obesity-related cardiac dysfunction, the role of autophagy in cardiac lipid metabolism remains unclear. In the heart, lipotoxicity is exacerbated by cardiac lipoprotein lipase (LPL), which mediates accumulation of fatty acids to the heart through intravascular triglyceride (TG) hydrolysis. Methods and results In both genetic and dietary models of obesity, we observed a substantial increase in cardiac LPL protein levels without any change in messenger ribonucleic acid (mRNA). This was accompanied by a dramatic down-regulation of autophagy in the heart, as revealed by reduced levels of unc-51 like kinase-1 (ULK1) protein. To further explore the relationship between cardiac LPL and autophagy, we generated cardiomyocyte-specific knockout mice for ulk1 (Myh6-cre/ulk1fl/fl), Lpl (Myh6-cre/Lplfl/fl), and mice with a combined deficiency (Myh6-cre/ulk1fl/fl Lplfl/fl). Similar to genetic and dietary models of obesity, Myh6-cre/ulk1fl/fl mice had a substantial increase in cardiac LPL levels. When these mice were fed a high-fat diet (HFD), they showed elevated cardiac TG levels and deterioration in heart function. However, with combined deletion of LPL and ULK1 in Myh6-cre/ulk1fl/fl Lplfl/fl mice, HFD feeding did not lead to alterations in levels of TG or diacylglycerol, or in cardiac function. To further elucidate the role of autophagy in cardiac lipid metabolism, we infused a peptide that enhanced autophagy (D-Tat-beclin1). This effectively lowered LPL levels at the coronary lumen by restoring autophagy in the genetic model of obesity. This decrease in cardiac luminal LPL was associated with a reduction in TG levels and recovery of cardiac function. Conclusion These results provide clear evidence of the critical role of modulating cardiac LPL activity through autophagy-mediated proteolytic clearance as a potential novel strategy to overcome obesity-related cardiomyopathy. [ABSTRACT FROM AUTHOR]

Motivation: Modulation of regulatory circuits governing the metabolic processes is a crucial step for developing microbial cell factories. Despite the prevalence of in silico strain design algorithms, most of them are not capable of predicting required modifications in regulatory networks. Although a few algorithms may predict relevant targets for transcriptional regulator (TR) manipulations, they have limited reliability and applicability due to their high dependency on the availability of integrated metabolic/regulatory models. Results: We present BeReTa (Beneficial Regulator Targeting), a new algorithm for prioritization of TR manipulation targets, which makes use of unintegrated network models. BeReTa identifies TR manipulation targets by evaluating regulatory strengths of interactions and beneficial effects of reactions, and subsequently assigning beneficial scores for the TRs. We demonstrate that BeReTa can predict both known and novel TR manipulation targets for enhanced production of various chemicals in Escherichia coli. Furthermore, through a case study of antibiotics production in Streptomyces coelicolor, we successfully demonstrate its wide applicability to even less-studied organisms. To the best of our knowledge, BeReTa is the first strain design algorithm exclusively designed for predicting TR manipulation targets. [ABSTRACT FROM AUTHOR]