多壁碳纳米管-酰基吡唑啉酮复合膜修饰电极测定异烟肼

报道了一种修饰电极--多壁碳纳米管-酰基吡唑啉酮复合膜修饰玻碳电极(MWNTs/HPMαFP/GCE ),研究了异烟肼在此修饰电极上的电化学行为及反应机理.与裸GCE和MWNTs/GCE相比,异烟肼在MWNTs/HPMαFP/GCE上的氧化峰电流和检测灵敏度大大提高,表明多壁碳纳米管和酰基吡唑啉酮产生了协同增效作用.在...     

茶叶中多元素的微波消解等离子体发射光谱法测定

采用密闭式微波消解系统处理茶叶样品,以电感耦合等离子体发射光谱法测定茶叶样品中铜、铁、锌、锰、钡和铝6种元素.分别从消解液的选择、用酸量及样品消解量等方面进行消解条件的优化,对测定钡、铝元素存在的干扰进行了讨论.各元素的检出限范围为0.15～0.65μg·g-1,回收率为98.6%～106%,精密度为0.8%～5.3%...     

基于HEA封端聚氨酯大孔树脂颗粒的合成、表征及水声声学性能

制备了丙烯酸-β-羟乙酯（HEA）封端的聚氨酯（PUA）大分子单体,采用正庚烷作致孔剂,用悬浮聚合法合成了聚氨酯-苯乙烯（PUA-St）及聚氨酯-苯乙烯-甲基丙烯酸乙酯-二乙烯基苯（PUA-St-EMA-DVB）AB-交联共聚物大孔树脂颗粒。SEM表明：合成的PUA-St-EMA-DVB颗粒含有规整的、孔径较大的孔洞,...     

Tandem MS Analysis of Selenamide-Derivatized Peptide Ions

Our previous study showed that selenamide reagents such as ebselen and N-(phenylseleno)phthalimide (NPSP) can be used for selective and rapid derivatization of protein/peptide thiols in high conversion yield. This paper reports the systematic investigation of MS/MS dissociation behaviors of selenamide-derivatized peptide ions upon collision induced dissociation (CID) and electron transfer dissociation (ETD). In the positive ion mode, derivatized peptide ions exhibit tag-dependent CID dissociation pathways. For instance, ebselen-derivatized peptide ions preferentially undergo Se–S bond cleavage upon CID to produce a characteristic fragment ion, the protonated ebselen (m/z 276), which allows selective identification of thiol peptides from protein digest as well as selective detection of thiol proteins from protein mixture using precursor ion scan (PIS). In contrast, NPSP-derivatized peptide ions retain their phenylselenenyl tags during CID, which is useful in sequencing peptides and locating cysteine residues. In the negative ion CID mode, both types of tags are preferentially lost via the Se–S cleavage, analogous to the S–S bond cleavage during CID of disulfide-containing peptide anions. In consideration of the convenience in preparing selenamide-derivatized peptides and the similarity of Se–S of the tag to the S–S bond, we also examined ETD of the derivatized peptide ions to probe the mechanism for electron-based ion dissociation. Interestingly, facile cleavage of Se–S bond occurs to the peptide ions carrying either protons or alkali metal ions, while backbone cleavage to form c/z ions is severely inhibited. These results are in agreement with the Utah-Washington mechanism proposed for depicting electron-based ion dissociation processes.     

The potential of tetrandrine as a protective agent for ischemic stroke

Stroke is one of the leading causes of mortality, with a high incidence of severe morbidity in survivors. The treatment to minimize tissue injury after stroke is still unsatisfactory and it is mandatory to develop effective treatment strategies for stroke. The pathophysiology of ischemic stroke is complex and involves many processes including energy failure, loss of ion homeostasis, increased intracellular calcium level, platelet aggregation, production of reactive oxygen species, disruption of blood brain barrier, and inflammation and leukocyte infiltration, etc. Tetrandrine, a bisbenzylisoquinoline alkaloid, has many pharmacologic effects including anti-inflammatory and cytoprotective effects. In addition, tetrandrine has been found to protect the liver, heart, small bowel and brain from ischemia/reperfusion injury. It is a calcium channel blocker, and can inhibit lipid peroxidation, reduce generation of reactive oxygen species, suppress the production of cytokines and inflammatory mediators, inhibit neutrophil recruitment and platelet aggregation, which are all devastating factors during ischemia/reperfusion injury of the brain. Because tetrandrine can counteract these important pathophysiological processes of ischemic stroke, it has the potential to be a protective agent for ischemic stroke.     

Knowledge-based scoring functions in drug design: 2. Can the knowledge base be enriched?

Fast and accurate predicting of the binding affinities of large sets of diverse protein?ligand complexes is an important, yet extremely challenging, task in drug discovery. The development of knowledge-based scoring functions exploiting structural information of known protein?ligand complexes represents a valuable contribution to such a computational prediction. In this study, we report a scoring function named IPMF that integrates additional experimental binding affinity information into the extracted potentials, on the assumption that a scoring function with the "enriched" knowledge base may achieve increased accuracy in binding affinity prediction. In our approach, the functions and atom types of PMF04 were inherited to implicitly capture binding effects that are hard to model explicitly, and a novel iteration device was designed to gradually tailor the initial potentials. We evaluated the performance of the resultant IPMF with a diverse set of 219 protein-ligand complexes and compared it with seven scoring functions commonly used in computer-aided drug design, including GLIDE, AutoDock4, VINA, PLP, LUDI, PMF, and PMF04. While the IPMF is only moderately successful in ranking native or near native conformations, it yields the lowest mean error of 1.41 log K(i)/K(d) units from measured inhibition affinities and the highest Pearson's correlation coefficient of R(p)2 0.40 for the test set. These results corroborate our initial supposition about the role of "enriched" knowledge base. With the rapid growing volume of high-quality structural and interaction data in the public domain, this work marks a positive step toward improving the accuracy of knowledge-based scoring functions in binding affinity prediction.     

A block coordinate gradient descent method for regularized convex separable optimization and covariance selection

We consider a class of unconstrained nonsmooth convex optimization problems, in which the objective function is the sum of a convex smooth function on an open subset of matrices and a separable convex function on a set of matrices. This problem includes the covariance selection problem that can be expressed as an ℓ ₁-penalized maximum likelihood estimation problem. In this paper, we propose a block coordinate gradient descent method (abbreviated as BCGD) for solving this class of nonsmooth separable problems with the coordinate block chosen by a Gauss-Seidel rule. The method is simple, highly parallelizable, and suited for large-scale problems. We establish global convergence and, under a local Lipschizian error bound assumption, linear rate of convergence for this method. For the covariance selection problem, the method can terminate in O(n³/e){O(n^3/\epsilon)} iterations with an e{\epsilon}-optimal solution. We compare the performance of the BCGD method with the first-order methods proposed by Lu (SIAM J Optim 19:1807–1827, 2009; SIAM J Matrix Anal Appl 31:2000–2016, 2010) for solving the covariance selection problem on randomly generated instances. Our numerical experience suggests that the BCGD method can be efficient for large-scale covariance selection problems with constraints.     

Comparison results of the preconditioned AOR methods for L-matrices

In this paper, we first provide comparison results of several types of the preconditioned AOR (PAOR) methods for solving a linear system whose coefficient matrix is an L-matrix satisfying some weaker conditions than those used in the recent literature. Next, we propose an application of PAOR method to a preconditioner of Krylov subspace method. Lastly, numerical results are provided to show that Krylov subspace method with the PAOR preconditioner performs quite well as compared with the ILU (0) preconditioner.     

Shrinking Projection Methods for a Family of Quasi-φ-Strict Asymptotically Pseudo-Contractions in Banach Spaces

The purpose of this article is to propose a shrinking projection method and prove a strong convergence theorem for a family of quasi-φ-strict asymptotically pseudo-contractions. Its results hold in reflexive, strictly convex, smooth Banach spaces with the property (K). The results of this paper improve and extend the results of Matsushita and Takahashi, Marino and Xu, Zhou and Gao and others.