Voltammetry coupled to mass spectrometry in the presence of isotope O labeled water for the prediction of oxidative transformation pathways of activated aromatic ethers: Acebutolol

The coupling between an electrochemical cell (EC) and a mass spectrometer (MS) is a useful screening tool (EC-MS) to study the oxidative transformation pathways of various electroactive species. For that purpose, we showed that the EC-MS method, carried out in the presence and absence of isotope ¹⁸O labeled water leads not only to a fast identification of oxidation products but also leads to a fast elucidation of the mechanism pathway reaction. We examined herein the case of the electrochemical hydrolysis of activated aromatic ether. Acebutolol (β-blockers) was selected herein as model of activated aromatic ether, and its electrochemical oxidation was examined in both the presence and absence of isotope ¹⁸O labeled water. To elucidate electrochemical hydrolysis pathway reaction: O-dealkylation or O-dealkoxylation, our approach was used to prove its applicability. The electrochemical oxidation mechanism was then elucidated showing an O-dealkoxylation reaction. In addition, density functional theory (DFT) calculations fully support the experimental conclusions.     

Identification of bioactive peptides in hypoallergenic infant milk formulas by CE‐TOF‐MS assisted by semiempirical model of electromigration behavior

Biologically active peptides derived from complex bovine milk protein hydrolysates are of particular interest in food science and nutrition because they have been shown to play different physiological roles, providing benefits in human health. In this study, we used CE‐TOF‐MS for separation and identification of bioactive peptides in three hypoallergenic infant milk formulas. An appropriate sample cleanup using a citrate buffer with DTT and urea followed by SPE with Sep‐Pack® C18 and StrataX^TM cartridges allowed the detection of a large number of low molecular mass bioactive peptides. This preliminary identification was solely based on the measured experimental monoisotopic molecular mass values (M_exp). Later, we evaluated the classical semiempirical relationships between electrophoretic mobility and charge‐to‐mass ratio (m_e vs. q/M^α, α = 1/2 for the classical polymer model) to describe their migration behavior. The assistance of migration prediction proved to be useful to improve reliability of the identification, avoiding misinterpretations and solving some identity conflicts. After revision, the identity of 24, 30, and 38 bioactive peptides was confirmed in each of the three infant milk formulas. A significant number of these peptides were reported as inhibitors of angiotensin‐converting enzyme, however, the presence of sequences with other biological activities such as antihypertensive, antithrombotic, hypocholesterolemic, immunomodulation, cytotoxicity, antioxidant, antimicrobial, antigenic, or opioid was also confirmed.     

多种类表面活性剂临界胶束浓度定量构效关系

表面活性剂的临界胶束浓度(CMC)是个非常重要的物质特性参数, CMC在研究表面活性剂的工业应用和生物利用方面发挥着关键作用. 本工作提出了一个新的拓扑指数—扩展距离矩阵, 建立了一个稳定的构效关系模型, 并对175种表面活性剂的临界胶束浓度进行了计算预测. 结果表明, 基于新的拓扑指数建立的构效关系模型计算临界胶束浓度能给出稳定可靠的预测结果, 其预测结果相关性系数R²(training set)=0.9295, 相对标准偏差ARD(training set)=8.20%, R²(testing set)=0.9257, ARD(testing set)=6.76%. 与文献中模型预测结果的对比表明, 本工作在稳定性和可靠性上均有显著改善.     

基于层次分析法的隧道综合地质预报优化

隧道综合地质预报是解决隧道施工期地质问题、降低施工风险的一项重要技术手段。鉴于目前综合预报多为简单的数量上的综合,为更加有效地利用综合预报技术,首先归纳地质分析辨识常见不良地质体的方法,通过地质分析法初步判定隧道掌子面前方可能存在的地质异常,并结合层次分析法的基本思路,将影响预报手段的指标量化,即赋予预报方法权重,建立二级综合评价指标体系,研究不同预报方法对特定工程地质条件的适用性,以选择几种最优预报方法。主要研究结论如下:利用地质分析法定性、层次分析法定量的方法优选预报手段,减少了综合超前地质预报中物探手段选择的随意性,并据此建立综合预报体系。最后将该体系应用于紫荆山隧道F2断层的预报中,成功预报了ZK221+960处地下暗河,避免了施工事故的发生,取得了一定的经济效益,证明了通过层次分析法来优化综合预报方法的可行性。     

概率神经网络及FAAS在植物药分类研究中的应用

用火焰原子吸收法（FAAS）测定了植物药中Fe、Mg、Mn、Cu、Zn和Ca元素的含量,采用主成分分析法对所测数据进行预处理,结合概率神经网络模型对中药功效类别进行识别预测研究,取得了较满意的结果。     

A simplified prediction of entropy of melting for energetic compounds

A new widely applicable model for the prediction of the entropy of melting of organic compounds is presented. The use of three simple geometry based parameters: rotational symmetry, flexibility, and eccentricity enables the simple and accurate prediction of this important property. This paper demonstrates the use of the model for energetic compounds.     

Extension of polar GC-SAFT to systems containing some oxygenated compounds: Application to ethers, aldehydes and ketones

The GC-SAFT equation of state proposed by Tamouza et al. (2004) [51], extended to polar molecular fluids NguyenHuynh et al. (2008) [32], is here applied to model vapor-liquid phase equilibria of various binary mixtures containing at least one oxygenated compound belonging to ethers, ketones or aldehydes chemical families.These systems are modeled using a polar version of the three different versions of SAFT-EOS (original, VR-SAFT and PC-SAFT) in a predictive manner: binary interaction parameters k_ij and l_ij are all set to zero.In the case of alcohol + ether, +ketone, +aldehyde systems, a cross-association interaction between an oxygenated compound (non self-associating compound) and an alcohol is necessary to model/predict accurately the mixture VLE. The corresponding association parameters are assumed to be equal to the self-association parameters of pure 1-alkanols.The above-cited systems have been treated in a comprehensive manner. The general agreement between polar GC-SAFT and experimental data is good (within 4-5% deviation on pressure), similar to the one obtained on previously investigated systems using GC-SAFT.     

基于定量构效关系设计自乳化系统

将定量构效关系引入到自乳化系统中, 采用HF/6-31G^*方法优化分子结构, 在此基础上计算出组分的量子化学参数, 考察组分含量、立体效应、疏水效应、静电效应对自乳化体系的微乳区域面积和粒径的影响, 通过多元线性回归建立了分子结构参数和组分比例与体系的微乳区域面积/粒径间的定量函数模型, 并对模型外的组分组成的测试集进行了预测. 研究结果表明: 乳化剂与助乳化剂的用量比是影响自乳化体系相行为的主要因素, 油相和助乳化剂含量增大, 粒径增加, 乳化剂含量增大, 粒径减小; 而组分间的相互作用力对系统性质影响较小. 除以肉豆蔻酸异丙酯(IPM)为油相建立的模型外, 其余模型均具有较好的预测效果, 利用这些规律可为自乳化系统的组分筛选提供理论指导, 提高实验效率.     

大数据时代下的化学经验2.0：基于键能的大规模反应途径预测

报道了一个基于键能数据预测反应途径的可编程算法．运用该算法,成功预测了F₂+CH₃Cl气相反应的最优产物(CF₄)和对应的反应途径．提供了一个启示性的化学经验2.0 的例子,并可能开启大数据时代下的大规模反应途径预测的大门．