Data analysis in stability studies of biopharmaceutical drugs with isothermal and non-isothermal assays

Stability is a particular problem for biopharmaceutical products because the efficacy of peptides and proteins as therapeutic or diagnostic agents can be affected during preparation, shipping, and storage. A particular formulation may have no immediately apparent effect on physical or chemical stability, and the time required for these studies at ambient temperature can be very lengthy because chemical reactions proceed relatively slowly at low temperatures. Undoubtedly, accelerated and stress testing of stability can provide useful information for future product development. The many methods used to study kinetics in aqueous solution may be experimental or computational. Experimental approaches may be isothermal or non-isothermal. Non-linear and linear regression methods can be used to analyze data from these experimental approaches, and the Monte Carlo method could be useful to obtain information about uncertainties in experimental data.The purpose of this review is to describe and to discuss options for the accelerated study of peptide and protein drugs. These options are not necessarily the same as those used for regulatory testing to set expiration dates. We also review statistical techniques to estimate kinetic parameters (rate constant, activation energy, and pre-exponential factor). Further, we establish the advantages and the limitations of both thermal approaches. We analyze and discuss all aspects using the most recent examples of peptide and protein stability.     

基于小波概率估计的图像融合方法研究

在研究了已有的图像融合方法后,提出基于小波变换和最大似然概率估计(MLE)相综合的融合方法,利用概率估计融合模型,首先对不同的传感器图像进行小波分解,然后对相应的子带求解仿射变换参数,根据Bayes规则进行最大后验概率似然估计,得到估计子带系数,最后通过小波反变换得到融合图像.在仿射变换的假设条件下定义融合规则,更适合传感器图像具有局部相反对比度的情况,采用此方法对航空可见光图像和红外图像进行融合实验,其结果与采用其它方法进行了对比,表明该方法的有效性.     

Spherically Symmetric Logistic Distribution

In this paper exact formulae of the probability density function for the spherically symmetric distribution with marginal logistic are given. They are entirely different for odd and even dimensions. For an odd number of dimensions it is possible to express them by elementary functions but for an even number of dimensions, it is possible only by an infinite series of functions. These series, however, are very convenient for computations and could be useful in practice.     

关于回归模型的参数估计效率

本文讨论回归模型的参数估计效率。本文说明了现有线性回归模型的参数估计效率的下界与真实的参数估计效率在很多情况下相差较大,而且这种下界对于实测数据处理很难得到精确值。本文给出了估算参数估计效率的仿真方法。理论分析表明,该方法给出的参数估计效率的估计较现有的下界估计更合理;仿真和实算结果表明,对于一大类线性和非线性回归模型,该方法给出的回归模型的参数估计效率的估计更接近模型参数估计效率的真值。     

具无界时滞非自治Logistic模型的全局吸引性(英文)

考虑非自治Ｌｏｇｉｓｔｉｃ模型△ｘｎ ＝ ｐｎｘｎ（１ － ｘｎ－ ｋｎλ）,　　ｎ ＝ ０,１,…, （１）其中｛ｐｎ｝ｎ０为非负实数列,｛ｋｎ｝ｎ０为非负整数列且ｌｉｍｎ→∞（ｎ－ ｋｎ）＝ ∞,ｌｉｍ ｓｕｐｎ→∞ ｋｎ＝ ∞,λ为正常数．我们获得了方程（１）的平衡点λ全局吸引的新的充分条件,改进了文［５］的相应结果．     

半参数回归模型的迭代法

在补偿最小二乘法则下,采用迭代法考虑半参数回归模型Li=Ai^TX＋s（ti）＋△i（i=1,2,……n,）得到参数及非参数的估计;接着从理论上证明了该法的可行性,并给出了误差上界及确定迭代的最大次数;最后用模拟的算例说明该法的有效性．     

近红外仪测试二醋酸纤维素醋化值

本文研究了近红外仪在近红外区域（１１００－２５００ｎｍ）,多重线性回归测定二醋酸纤维素的醋化值的方法。并且就近红外仪测试二醋酸纤维素醋化值的测试结果与传统滴定结果进行了比较,对测量的重现性进行了考察,相对标准偏差为０．０７％。     

A Physical Organic Approach towards Statistical Modeling of Tetrazole and Azide Decomposition**

Nitrogen atom-rich heterocycles and organic azides have found extensive use in many sectors of modern chemistry from drug discovery to energetic materials. The prediction and understanding of their energetic properties are thus key to the safe and effective application of these compounds. In this work, we disclose the use of multivariate linear regression modeling for the prediction of the decomposition temperature and impact sensitivity of structurally diverse tetrazoles and organic azides. We report a data-driven approach for property prediction featuring a collection of quantum mechanical parameters and computational workflows. The statistical models reported herein carry predictive accuracy as well as chemical interpretability. Model validation was successfully accomplished via tetrazole test sets with parameters generated exclusively in silico. Mechanistic analysis of the statistical models indicated distinct divergent pathways of thermal and impact-initiated decomposition.     

Close-Shell Reductive Elimination versus Open-Shell Radical Coupling for Site-Selective Ruthenium-Catalyzed C−H Activations by Computation and Experiments

Ruthenium-catalyzed σ-bond activation-assisted meta-C−H functionalization has emerged as a useful tool to forge distal C−C bonds. However, given the limited number of mechanistic studies, a clear understanding of the origin of the site-selectivity and the complete reaction pattern is not available. Here, we present systematic computational studies on ruthenium-catalyzed C−H functionalization with primary, secondary, tertiary alkyl bromides and aryl bromides. The C−H scission and the C−C formation were carefully examined. Monocyclometalated ruthenium(II) complexes were identified as the active species, which then underwent inner-sphere single electron transfer (ISET) to activate the organic bromides. The site-selectivity results from the competition between the close-shell reductive elimination and the open-shell radical coupling. Based on this mechanistic understanding, a multilinear regression model was built to predict the site-selectivity, which was further validated by experiments.