The solvation of Li and Na in acetonitrile from ab initio-derived many-body ion–solvent potentials

Several Li⁺- and Na⁺-acetonitrile models were derived from ab initio calculations at the counterpoise-corrected MP2/TZV++(d,p) level for distorted ion-(MeCN)_n clusters with n=1, 4 and 6. Two different many-body ion-acetonitrile models were constructed: an effective three-body potential for use with the six-site effective pair model of Böhm et al., and an effective polarizable many-body model. The polarizable acetonitrile model used in the latter model is a new empirical model which was also derived in the present paper. Mainly for comparative purposes, two ion-acetonitrile pair potentials were also constructed from the ab initio cluster calculations: one pure pair potential and one effective pair potential. Using all these potential models, MD simulations in the NPT ensemble were performed for the pure acetonitrile liquid and for Li⁺(MeCN) and Na⁺(MeCN) solutions with 1 ion in 512 solvent molecules and with a simulation time of at least 120 ps per system. Thermodynamic properties, solvation-shell structure and the self-diffusion coefficient of the ions and of the solvent molecules were calculated and compared between the different models and with experimental data, where available. The Li⁺ ion is found to be four-coordinated when the new many-body potentials are used, in contrast to the six-coordinated structure obtained for the pure pair and effective pair potentials. The coordination number of Na⁺ is close to six for all the models derived here, although the coordination number becomes slightly smaller with the many-body potentials. For both ions, the solvent molecules in the first shell point their nitrogen ends towards the cation, while in the second shell the opposite orientation is the most common.     

The phases of polymers as determined by NMR

Nuclear magnetic resonance (NMR) spectroscopy has been used to study the morphology and dynamics in semicrystalline polymers. Dynamics may be observed through NMR relaxation rates that are sensitive to motions in the 1–10⁸ Hz range, or through modulation of anisotropic magnetic interactions, such as the chemical shift and dipole-dipole interactions. Morphological structure may be inferred through NMR measurements of polymer dynamics or investigated directly through studies of the magnetic interactions. Here, we discuss the study of morphological structure in semicrystalline polymers using NMR, and review results on poly(ethylene terephthalate) that address the question of the number of phases in this semicrystalline polymer.This work was funded by the Office of Naval Research.     

Factor Xa: Simulation studies with an eye to inhibitor design

Factor Xa is a serine protease which activates thrombin and plays a key regulatory role in the blood-coagulation cascade. Factor Xa is at the crossroads of the extrinsic and intrinsic pathways of coagulation and, hence, has become an important target for the design of anti-thrombotics (inhibitors). It is not known to be involved in other processes than hemostasis and its binding site is different to that of other serine proteases, thus facilitating selective inhibition. The design of high-affinity selective inhibitors of factor Xa requires knowledge of the structural and dynamical characteristics of its active site. The three-dimensional structure of factor Xa was resolved by X-ray crystallography and refined at 2.2 Å resolution by Padmanabhan and collaborators. In this article we present results from molecular dynamics simulations of the catalytic domain of factor Xa in aqueous solution. The simulations were performed to characterise the mobility and flexibility of the residues delimiting the unoccupied binding site of the enzyme, and to determine hydrogen bonding propensities (with protein and with solvent atoms) of those residues in the active site that could interact with a substrate or a potential inhibitor. The simulation data is aimed at facilitating the design of high-affinity selective inhibitors of factor Xa.     

Operation of the quasi-optical gyrotron at harmonics of the gyrofrequency

This paper investigates the performance of a quasioptical gyrotron, when the electron beam interacts with the radiation fields at harmonics of the gyrofrequency. The nonlinear equations of motion are obtained in the slow-timescale. The expression for the linear gain is derived and the conditions for excitation are given (frequency threshold, optimal operating point, bean current and resonator quality thresholds). In the nonlinear regime, it is shown that maximum efficiencies comparable to those at the fundemental (50%) are possible, albeit at a prohitively high radiation field amplitude, while realistically feasible field amplitudes can give somewhat smaller, but nevertheless still high efficiencies (15%). Finally, the results are suplemented by empirical scaling laws, useful for experimental designs.     

The third law of thermodynamics and the degeneracy of the ground state for lattice systems

The third law of thermodynamics, in the sense that the entropy per unit volume goes to zero as the temperature goes to zero, is investigated within the framework of statistical mechanics for quantum and classical lattice models. We present two main results: (i) For all models the question of whether the third law is satisfied can be decided completely in terms of ground-state degeneracies alone, provided these are computed for all possible boundary conditions. In principle, there is no need to investigate possible entropy contributions from low-lying excited states, (ii) The third law is shown to hold for ferromagnetic models by an analysis of the ground states.Dedicated to Pierre Résibois. Work supported in part by NSF grant PHY-7825390 A01.     

Investigation Driven by Network Pharmacology on Potential Components and Mechanism of DGS,a Natural Vasoprotective Combination,for the Phytotherapy of Coronary Artery Disease

Phytotherapy offers obvious advantages in the intervention of Coronary Artery Disease (CAD), but it is difficult to clarify the working mechanisms of the medicinal materials it uses. DGS is a natural vasoprotective combination that was screened out in our previous research, yet its potential components and mechanisms are unknown. Therefore, in this study, HPLC-MS and network pharmacology were employed to identify the active components and key signaling pathways of DGS. Transgenic zebrafish and HUVECs cell assays were used to evaluate the effectiveness of DGS. A total of 37 potentially active compounds were identified that interacted with 112 potential targets of CAD. Furthermore, PI3K-Akt, MAPK, relaxin, VEGF, and other signal pathways were determined to be the most promising DGS-mediated pathways. NO kit, ELISA, and Western blot results showed that DGS significantly promoted NO and VEGFA secretion via the upregulation of VEGFR2 expression and the phosphorylation of Akt, Erk1/2, and eNOS to cause angiogenesis and vasodilation. The result of dynamics molecular docking indicated that Salvianolic acid C may be a key active component of DGS in the treatment of CAD. In conclusion, this study has shed light on the network molecular mechanism of DGS for the intervention of CAD using a network pharmacology-driven strategy for the first time to aid in the intervention of CAD.     

6σ管理和统计技术

从6σ名称,绿带、黑带的评定标准和培训内容都体现了统计技术是6σ管理的核心技术。DMAIC统计技术应用模式虽有不足,最大功绩是使应用统计技术简单化,实际应用者认识了统计技术的重要性。     

Insights into the Allosteric Effect of SENP1 Q597A Mutation on the Hydrolytic Reaction of SUMO1 via an Integrated Computational Study

Small ubiquitin-related modifier (SUMO)-specific protease 1 (SENP1) is a cysteine protease that catalyzes the cleavage of the C-terminus of SUMO1 for the processing of SUMO precursors and deSUMOylation of target proteins. SENP1 is considered to be a promising target for the treatment of hepatocellular carcinoma (HCC) and prostate cancer. SENP1 Gln597 is located at the unstructured loop connecting the helices α4 to α5. The Q597A mutation of SENP1 allosterically disrupts the hydrolytic reaction of SUMO1 through an unknown mechanism. Here, extensive multiple replicates of microsecond molecular dynamics (MD) simulations, coupled with principal component analysis, dynamic cross-correlation analysis, community network analysis, and binding free energy calculations, were performed to elucidate the detailed mechanism. Our MD simulations showed that the Q597A mutation induced marked dynamic conformational changes in SENP1, especially in the unstructured loop connecting the helices α4 to α5 which the mutation site occupies. Moreover, the Q597A mutation caused conformational changes to catalytic Cys603 and His533 at the active site, which might impair the catalytic activity of SENP1 in processing SUMO1. Moreover, binding free energy calculations revealed that the Q597A mutation had a minor effect on the binding affinity of SUMO1 to SENP1. Together, these results may broaden our understanding of the allosteric modulation of the SENP1−SUMO1 complex.     

Differential Expression Analysis of Single-Cell RNA-Seq Data: Current Statistical Approaches and Outstanding Challenges

With the advent of single-cell RNA-sequencing (scRNA-seq), it is possible to measure the expression dynamics of genes at the single-cell level. Through scRNA-seq, a huge amount of expression data for several thousand(s) of genes over million(s) of cells are generated in a single experiment. Differential expression analysis is the primary downstream analysis of such data to identify gene markers for cell type detection and also provide inputs to other secondary analyses. Many statistical approaches for differential expression analysis have been reported in the literature. Therefore, we critically discuss the underlying statistical principles of the approaches and distinctly divide them into six major classes, i.e., generalized linear, generalized additive, Hurdle, mixture models, two-class parametric, and non-parametric approaches. We also succinctly discuss the limitations that are specific to each class of approaches, and how they are addressed by other subsequent classes of approach. A number of challenges are identified in this study that must be addressed to develop the next class of innovative approaches. Furthermore, we also emphasize the methodological challenges involved in differential expression analysis of scRNA-seq data that researchers must address to draw maximum benefit from this recent single-cell technology. This study will serve as a guide to genome researchers and experimental biologists to objectively select options for their analysis.     

Mechanism Study on Nanoparticle Negative Surface Charge Modification by Ascorbyl Palmitate and Its Improvement of Tumor Targeting Ability

Surface charge polarity and density influence the immune clearance and cellular uptake of intravenously administered lipid nanoparticles (LNPs), thus determining the efficiency of their delivery to the target. Here, we modified the surface charge with ascorbyl palmitate (AsP) used as a negatively charged lipid. AsP-PC-LNPs were prepared by dispersion and ultrasonication of AsP and phosphatidylcholine (PC) composite films at various ratios. AsP inserted into the PC film with its polar head outward. The pK_a for AsP was 4.34, and its ion form conferred the LNPs with negative surface charge. Zeta potentials were correlated with the amount and distribution of AsP on the LNPs surface. DSC, Raman and FTIR spectra, and molecular dynamics simulations disclosed that AsP distributed homogeneously in PC at 1–8% (w/w), and there were strong hydrogen bonds between the polar heads of AsP and PC (PO²⁻), which favored LNPs’ stability. But at AsP:PC > 8% (w/w), the excessive AsP changed the interaction modes between AsP and PC. The AsP–PC composite films became inhomogeneous, and their phase transition behaviors and Raman and FTIR spectra were altered. Our results clarified the mechanism of surface charge modification by AsP and provided a rational use of AsP as a charged lipid to modify LNP surface properties in targeted drug delivery systems. Furthermore, AsP–PC composites were used as phospholipid-based biological membranes to prepare paclitaxel-loaded LNPs, which had stable surface negative charge, better tumor targeting and tumor inhibitory effects.