InterPro in 2017-beyond protein family and domain annotations

InterPro (http://www.ebi.ac.uk/interpro/) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. InterProScan is the underlying software that allows both protein and nucleic acid sequences to be searched against InterPro's predictive models, which are provided by its member databases. Here, we report recent developments with InterPro and its associated software, including the addition of two new databases (SFLD and CDD), and the functionality to include residue-level annotation and prediction of intrinsic disorder. These developments enrich the annotations provided by InterPro, increase the overall number of residues annotated and allow more specific functional inferences

SES, Heart Failure, and N-terminal Pro-b-type Natriuretic Peptide: The Atherosclerosis Risk in Communities Study

INTRODUCTION: Compared with coronary heart disease and stroke, the association between SES and the risk of heart failure is less well understood. METHODS: In 12,646 participants of the Atherosclerosis Risk in Communities Study cohort free of heart failure history at baseline (1987-1989), the association of income, educational attainment, and area deprivation index with subsequent heart failure-related hospitalization or death was examined while accounting for cardiovascular disease risk factors and healthcare access. Because SES may affect threshold of identifying heart failure and admitting for heart failure management, secondarily the association between SES and N-terminal pro-b-type natriuretic peptide (NT-proBNP) levels, a marker reflecting cardiac overload, was investigated. Analysis was conducted in 2016. RESULTS: During a median follow-up of 24.3 years, a total of 2,249 participants developed heart failure. In a demographically adjusted model, the lowest-SES group had 2.2- to 2.5-fold higher risk of heart failure compared with the highest SES group for income, education, and area deprivation. With further adjustment for time-varying cardiovascular disease risk factors and healthcare access, these associations were attenuated but remained statistically significant (e.g., hazard ratio=1.92, 95% CI=1.69, 2.19 for the lowest versus highest income), with no racial interaction (p>0.05 for all SES measures). Similarly, compared with high SES, low SES was associated with both higher baseline level of NT-proBNP in a multivariable adjusted model (15% higher, p<0.001) and increase over time (~1% greater per year, p=0.023). CONCLUSIONS: SES was associated with clinical heart failure as well as NT-proBNP levels inversely and independently of traditional cardiovascular disease factors and healthcare access

New robust stable MPC using linear matrix inequalities

This paper addresses the stability of Model Predictive Control (MPC) with output feedback. The proposed controller uses a new state-space formulation of the system, and the control problem is presented as an LMI optimization problem. The stability condition for the closed loop is included as a Lyapunov inequality. The resulting optimization problem becomes nonlinear with the inclusion of the stabilizing condition. A suboptimal solution is developed and the problem reduces to a pair of coupled LMI problems. An iterative solution that converges to a stable output feedback gain is proposed. A polytopic set of process models can be considered. A simulation example is included in the paper and shows that the proposed strategy eliminates the usual practice of enforcing robustness by detuning the MP controller