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Generating initial configurations of polymer melts above the entanglement molecular weight is a challenge in molecular dynamics and Monte Carlo simulations. In this work, we adapt an algorithm mimicking a chemical polymerization to all-atom force fields. The principle of this algorithm is to start from a bath of monomers between which bonds are created and relaxed sequentially. Our implementation is parallel and efficient. The parallelization is that of a classical molecular dynamics code and enables the user to generate large systems, up to 7 × 106 atoms. The efficiency of the algorithm comes from the linear scaling between the simulation time and the chain length in the limit of very long chains. The implementation is able to produce long polymer chains, up to ∼2000 carbon atoms, with thermodynamic and local structural properties in good agreement with their experimental and numerical counterparts. Moreover, the chain conformations are close to being equilibrated right after the end of the polymerization process, corresponding to only a few hundred of picoseconds of simulation, despite a systematical drift from Gaussian-like behavior when the density of reactively available monomers decreases. Finally, the algorithm proposed in this work is versatile in nature because the bond creation can be easily modified to create copolymers, block copolymers, and mixtures of polymer melts with other material. [ABSTRACT FROM AUTHOR]

Objective: We sought to evaluate amniotic fluid brain natriuretic peptide (BNP) levels as a biomarker of recipient twin (RT) cardiomyopathy (RTCM) in twin-twin transfusion syndrome.Study Design: Amniotic fluid samples were obtained from 157 twin-twin transfusion syndrome RTs and from 6 singletons (controls) from 2007 through 2009. N-terminal prohormone BNP (NT-proBNP) levels were quantified by enzyme-linked immunosorbent assay. RTCM was classified as mild (IIIA), moderate (IIIB), or severe (IIIC) by fetal echocardiography. The relationship between NT-proBNP and RTCM was evaluated using analysis of variance. The ability of NT-proBNP to predict moderate or greater RTCM was evaluated by receiver operating characteristic analysis.Results: There is a significant positive correlation between NT-proBNP levels and worsening RTCM (r = 0.33; P < .001). NT-proBNP thresholds of 569 fmol/mg and 369 fmol/mg had a sensitivity of 70% and 87%, and specificity of 67% and 42%, respectively, in predicting moderate or greater RTCM.Conclusion: This is the first large case series that demonstrates a relationship between NT-proBNP and RTCM. This pathophysiologic insight supports ongoing efforts to develop screening biomarkers. [ABSTRACT FROM AUTHOR]