Cardiac Magnetic Resonance Assessment Of Interstitial Myocardial Fibrosis And Cardiomyocyte Hypertrophy In Hypertensive Mice Treated With Spironolactone.

Nearly 50% of patients with heart failure (HF) have preserved LV ejection fraction, with interstitial fibrosis and cardiomyocyte hypertrophy as early manifestations of pressure overload. However, methods to assess both tissue characteristics dynamically and noninvasively with therapy are lacking. We measured the effects of mineralocorticoid receptor blockade on tissue phenotypes in LV pressure overload using cardiac magnetic resonance (CMR). Mice were randomized to l-nitro-ω-methyl ester (l-NAME, 3 mg/mL in water; n=22), or l-NAME with spironolactone (50 mg/kg/day in subcutaneous pellets; n=21). Myocardial extracellular volume (ECV; marker of diffuse interstitial fibrosis) and the intracellular lifetime of water (τic; marker of cardiomyocyte hypertrophy) were determined by CMR T1 imaging at baseline and after 7 weeks of therapy alongside histological assessments. Administration of l-NAME induced hypertensive heart disease in mice, with increases in mean arterial pressure, LV mass, ECV, and τic compared with placebo-treated controls, while LV ejection fraction was preserved (>50%). In comparison, animals receiving both spironolactone and l-NAME (l-NAME+S) showed less concentric remodeling, and a lower myocardial ECV and τic, indicating decreased interstitial fibrosis and cardiomyocyte hypertrophy (ECV: 0.43 ± 0.09 for l-NAME versus 0.25 ± 0.03 for l-NAME+S, P<0.001; τic: 0.42 ± 0.11 for l-NAME groups versus 0.12 ± 0.05 for l-NAME+S group). Mice treated with a combination of l-NAME and spironolactone were similar to placebo-treated controls at 7 weeks. Spironolactone attenuates interstitial fibrosis and cardiomyocyte hypertrophy in hypertensive heart disease. CMR can phenotype myocardial tissue remodeling in pressure-overload, furthering our understanding of HF progression.

Reduced Insulin Clearance And Lower Insulin-degrading Enzyme Expression In The Liver Might Contribute To The Thrifty Phenotype Of Protein-restricted Mice.

Nutrient restriction during the early stages of life usually leads to alterations in glucose homeostasis, mainly insulin secretion and sensitivity, increasing the risk of metabolic disorders in adulthood. Despite growing evidence regarding the importance of insulin clearance during glucose homeostasis in health and disease, no information exists about this process in malnourished animals. Thus, in the present study, we aimed to determine the effect of a nutrient-restricted diet on insulin clearance using a model in which 30-d-old C57BL/6 mice were exposed to a protein-restricted diet for 14 weeks. After this period, we evaluated many metabolic variables and extracted pancreatic islet, liver, gastrocnemius muscle (GCK) and white adipose tissue samples from the control (normal-protein diet) and restricted (low-protein diet, LP) mice. Insulin concentrations were determined using RIA and protein expression and phosphorylation by Western blot analysis. The LP mice exhibited lower body weight, glycaemia, and insulinaemia, increased glucose tolerance and altered insulin dynamics after the glucose challenge. The improved glucose tolerance could partially be explained by an increase in insulin sensitivity through the phosphorylation of the insulin receptor/protein kinase B and AMP-activated protein kinase/acetyl-CoA carboxylase in the liver, whereas the changes in insulin dynamics could be attributed to reduced insulin secretion coupled with reduced insulin clearance and lower insulin-degrading enzyme (IDE) expression in the liver and GCK. In summary, protein-restricted mice not only produce and secrete less insulin, but also remove and degrade less insulin. This phenomenon has the double benefit of sparing insulin while prolonging and potentiating its effects, probably due to the lower expression of IDE in the liver, possibly with long-term consequences.

Survival Extrapolation In The Presence Of Cause Specific Hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.