The erotic charisma of Alexander Hamilton

As an outsider with a mysterious childhood, Alexander Hamilton is, as psychologists say, a good "hook" for a projective identification. For his admirers Hamilton is a source of political capital. His ideas and proposals about the debt, protectionism, and an American manufacturing base are in the news in the early twenty-first century. Although the Old Left saw Hamilton as an elitist, possibly a monarchist, and a promoter of industrial capitalism, contemporary American progressives have called attention to his explicit support for habeas corpus, his efforts on behalf of banking, and his surprisingly enlightened attitudes about race and slavery. As one of the founders of a new republic, Hamilton knew he would be in the history books, but his image, representations of his physical presence, and speculation about his private life circulate on the Internet in ways that would surely astonish him. Alexander Hamilton not only has admirers in the fields of politics and history; he also has fans. © 2010 Cambridge University Press

Response to pulmonary arterial hypertension drug therapies in patients with pulmonary arterial hypertension and cardiovascular risk factors.

The age at diagnosis of pulmonary arterial hypertension (PAH) and the prevalence of cardiovascular (CV) risk factors are increasing. We sought to determine whether the response to drug therapy was influenced by CV risk factors in PAH patients. We studied consecutive incident PAH patients (n = 146) between January 1, 2008, and July 15, 2011. Patients were divided into two groups: the PAH-No CV group included patients with no CV risk factors (obesity, systemic hypertension, type 2 diabetes mellitus, permanent atrial fibrillation, mitral and/or aortic valve disease, and coronary artery disease), and the PAH-CV group included patients with at least one. The response to PAH treatment was analyzed in all the patients who received PAH drug therapy. The PAH-No CV group included 43 patients, and the PAH-CV group included 69 patients. Patients in the PAH-No CV group were younger than those in the PAH-CV group (P < 0.0001). In the PAH-No CV group, 16 patients (37%) improved on treatment and 27 (63%) did not improve, compared with 11 (16%) and 58 (84%) in the PAH-CV group, respectively (P = 0.027 after adjustment for age). There was no difference in survival at 30 months (P = 0.218). In conclusion, in addition to older age, CV risk factors may predict a reduced response to PAH drug therapy in patients with PAH

Abundance of Belugas, Delphinapterus leucas, in Cook Inlet, Alaska, 1994–2000

Annual abundance estimates of belugas, Delphinapterus leucas, in Cook Inlet were calculated from counts made by aerial observers and aerial video recordings. Whale group-size estimates were corrected for subsurface whales (availability bias) and whales that were at the surface but were missed (detection bias). Logistic regression was used to estimate the probability that entire groups were missed during the systematic surveys, and the results were used to calculate a correction to account for the whales in these missed groups (1.015, CV = 0.03 in 1994–98; 1.021, CV = 0.01 in 1999– 2000). Calculated abundances were 653 (CV = 0.43) in 1994, 491 (CV = 0.44) in 1995, 594 (CV = 0.28) in 1996, 440 (CV = 0.14) in 1997, 347 (CV = 0.29) in 1998, 367 (CV = 0.14) in 1999, and 435 (CV = 0.23, 95% CI=279–679) in 2000. For management purposes the current Nbest = 435 and Nmin = 360. These estimates replace preliminary estimates of 749 for 1994 and 357 for 1999. Monte Carlo simulations indicate a 47% probability that from June 1994 to June 1998 abundance of the Cook Inlet stock of belugas was depleted by 50%. The decline appears to have stopped in 1998

Novel diabetes drugs and the cardiovascular specialist

Recently, treatment with 2 newer classes of type 2 diabetes drugs were found to reduce events in patients with diabetes and cardiovascular (CV) disease, a group common in cardiology clinics. The sodium-glucose cotransporter 2 inhibitor, empagliflozin, markedly and rapidly reduced CV death and heart failure hospitalization, likely with hemodynamic/metabolic-driven mechanisms of action. More recently, the glucagon-like peptide–1 receptor agonists liraglutide and semaglutide also reduced CV death and/or major adverse CV events, but did so more slowly and did not influence heart failure risks, suggesting alternative mechanisms of benefit. We will discuss drug therapy for diabetes relative to CV risk, briefly summarize key findings of CV benefit from recent trials, discuss potential mechanisms for benefits of sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide–1 agonists, and suggest how such drugs might be embraced by CV specialists to reduce CV events and mortality in their patients

Effect of visit-to-visit variation of heart rate and systolic blood pressure on outcomes in chronic systolic heart failure: results from the Systolic Heart Failure Treatment With the If Inhibitor Ivabradine Trial (SHIFT) trial

Background: Elevated resting heart rate (HR) and low systolic blood pressure (SBP) are related to poor outcomes in heart failure (HF). The association between visit-to-visit variation in SBP and HR and risk in HF is unknown. Methods and Results: In Systolic Heart Failure Treatment with the If inhibitor ivabradine Trial (SHIFT) patients, we evaluated relationships between mean HR, mean SBP, and visit-to-visit variations (coefficient of variation [CV]=SD/mean×100%) in SBP and HR (SBP-CV and HR-CV, respectively) and primary composite endpoint (cardiovascular mortality or HF hospitalization), its components, all-cause mortality, and all-cause hospitalization. High HR and low SBP were closely associated with risk for primary endpoint, all-cause mortality, and HF hospitalization. The highest number of primary endpoint events occurred in the highest HR tertile (38.8% vs 16.4% lowest tertile; P&lt;0.001). For HR-CV, patients at highest risk were those in the lowest tertile. Patients in the lowest thirds of mean SBP and SBP-CV had the highest risk. The combination of high HR and low HR-CV had an additive deleterious effect on risk, as did that of low SBP and low SBP-CV. Ivabradine reduced mean HR and increased HR-CV, and increased SBP and SBP-CV slightly. Conclusions: Beyond high HR and low SBP, low HR-CV and low SBP-CV are predictors of cardiovascular outcomes with additive effects on risk in HF, but with an unknown effect size. Beyond HR reduction, ivabradine increases HR-CV. Low visit-to-visit variation of HR and SBP might signal risk of cardiovascular outcomes in systolic HF. Clinical Trial Registration: URL: http://www.isrctn.com/. Unique identifier: ISRCTN70429960

Development and Performance Evaluation of a Connected Vehicle Application Development Platform (CVDeP)

Connected vehicle (CV) application developers need a development platform to build, test and debug real-world CV applications, such as safety, mobility, and environmental applications, in edge-centric cyber-physical systems. Our study objective is to develop and evaluate a scalable and secure CV application development platform (CVDeP) that enables application developers to build, test and debug CV applications in realtime. CVDeP ensures that the functional requirements of the CV applications meet the corresponding requirements imposed by the specific applications. We evaluated the efficacy of CVDeP using two CV applications (one safety and one mobility application) and validated them through a field experiment at the Clemson University Connected Vehicle Testbed (CU-CVT). Analyses prove the efficacy of CVDeP, which satisfies the functional requirements (i.e., latency and throughput) of a CV application while maintaining scalability and security of the platform and applications

Unfolding Hidden Barriers by Active Enhanced Sampling

Collective variable (CV) or order parameter based enhanced sampling algorithms have achieved great success due to their ability to efficiently explore the rough potential energy landscapes of complex systems. However, the degeneracy of microscopic configurations, originating from the orthogonal space perpendicular to the CVs, is likely to shadow "hidden barriers" and greatly reduce the efficiency of CV-based sampling. Here we demonstrate that systematic machine learning CV, through enhanced sampling, can iteratively lift such degeneracies on the fly. We introduce an active learning scheme that consists of a parametric CV learner based on deep neural network and a CV-based enhanced sampler. Our active enhanced sampling (AES) algorithm is capable of identifying the least informative regions based on a historical sample, forming a positive feedback loop between the CV learner and sampler. This approach is able to globally preserve kinetic characteristics by incrementally enhancing both sample completeness and CV quality.Comment: 5 pages, 3 figure