Serum pharmacochemistry combined with multiple data processing approach to screen the bioactive components and their metabolites in Mutan Cortex by ultra‐performance liquid chromatography tandem mass spectrometry

Root cortex of Paeonia suffruticosa Andrews (Paeoniaceae), known as Moutan Cortex (MC), is known to have anti‐allergic and anti‐inflammatory properties. However, the constituents absorbed into blood after oral administration of MC remain unknown. A sensitive and rapid method by ultra‐high‐pressure liquid chromatography–electrospray ionization–quadrupole‐time‐of‐flight mass spectrometry (UPLC‐ESI‐Q‐TOF‐MS) technology and the MetaboLynx^TM software combined with multiple data processing approach (Mdpa) was established to investigate the absorbed constituents in rats after oral administration of MC, providing unique high‐throughput capabilities for drug metabolism study. A hyphenated electrospray ionization and quadrupole‐time‐of‐flight analyzer was used for the determination of accurate mass of the fragment ion in negative mode, with excellent MS mass accuracy and enhanced data acquisition. This rapid automated analysis method was successfully applied for screening and identification of the constituents absorbed and metabolized studies of MC after oral administration to rats. A total of 46 peaks were obtained from MC, 41 of which were tentatively characterized. In the VIP‐plot of orthogonal partial least‐squares discriminant analysis, 23 interesting ions in serum samples were extracted, and 16 parent components and seven metabolites were detected in vivo. The integrative serum pharmacochemistry technique, UPLC‐ESI‐Q‐TOF‐MS, and Mdpa method were successfully applied for rapid discovery of multiple components from MC. Copyright © 2013 John Wiley & Sons, Ltd.     

SMART: A data reporting standard for mass spectrometry imaging By Ying Xi,Alexandria L. Sohn,Alena N. Joignant,Stephanie M. Cologna,Boone M. Prentice and David C. Muddiman

Mass spectrometry imaging (MSI) is an important analytical technique that simultaneously reports the spatial location and abundance of detected ions in biological, chemical, clinical, and pharmaceutical studies. As MSI grows in popularity, it has become evident that data reporting varies among different research groups and between techniques. The lack of consistency in data reporting inherently creates additional challenges in comparing intra- and inter-laboratory MSI data. In this tutorial, we propose a unified data reporting system, SMART, based on the common features shared between techniques. While there are limitations to any reporting system, SMART was decided upon after significant discussion to more easily understand and benchmark MSI data. SMART is not intended to be comprehensive but rather capture essential baseline information for a given MSI study; this could be within a study (e.g., effect of spot size on the measured ion signals) or between two studies (e.g., different MSI platform technologies applied to the same tissue type). This tutorial does not attempt to address the confidence with which annotations are made nor does it deny the importance of other parameters that are not included in the current SMART format. Ultimately, the goal of this tutorial is to discuss the necessity of establishing a uniform reporting system to communicate MSI data in publications and presentations in a simple format to readily interpret the parameters and baseline outcomes of the data.     

Advances in Targeting Drug Biological Carriers for Enhancing Tumor Therapy Efficacy

Chemotherapy drugs continue to be the main component of oncology treatment research and have been proven to be the main treatment modality in tumor therapy. However, the poor delivery efficiency of cancer therapeutic drugs and their potential off-target toxicity significantly limit their effectiveness and extensive application. The recent integration of biological carriers and functional agents is expected to camouflage synthetic biomimetic nanoparticles for targeted delivery. The promising candidates, including but not limited to red blood cells and their membranes, platelets, tumor cell membrane, bacteria, immune cell membrane, and hybrid membrane are typical representatives of biological carriers because of their excellent biocompatibility and biodegradability. Biological carriers are widely used to deliver chemotherapy drugs to improve the effectiveness of drug delivery and therapeutic efficacy in vivo, and tremendous progress is made in this field. This review summarizes recent developments in biological vectors as targeted drug delivery systems based on microenvironmental stimuli-responsive release, thus highlighting the potential applications of target drug biological carriers. The review also discusses the possibility of clinical translation, as well as the exploitation trend of these target drug biological carriers.     

基于LSTM的浮选钼精矿品位软测量模型

战略性稀有金属钼矿品位低,组分复杂、嵌布粒度细等特点,其有价金属分离回收难。浮选作为微细粒钼矿分离回收的主要选矿方法之一,其浮选钼精矿品位一直是选厂的关键性产品指标。国内大多数选厂采取轮班制采样,人工化验得到精矿品位结果,但此方式严重滞后于浮选工艺,难以满足对生产过程进行实时监测和操作指导。LSTM是一种特殊的循环神经网络,引入门机制有效的传递或选择性遗忘长时间序列中的信息,解决RNN中的长期依赖、梯度消失和爆炸问题。本文分析整理东坡选厂中各平台源数据,结合选厂浮选工艺及机理,筛选出多个影响浮选钼精矿品位的变量作为模型输入;将输入变量进行异常值判定,缺失值填充和数据降噪等数据预处理,建立高质量浮选钼精矿品位数据库;软测量模型采用PyCharm软件编码,使用BatchNorm批量规范化处理样本数据,加入Dropout正则化防止过拟合,建立基于LSTM的浮选钼精矿品位软测量模型,通过前向传播算法更新神经网络结构参数,并于Linear模型和CNN模型的预测性能指标结果比较。结果表明：基于LSTM的浮选钼精矿品位软测量模型预测准确度高,样本数据误差波动平稳,浮动范围小,模型泛化能力强,模型平均绝对百分比误差MAPE为1.13%,均方根误差RMSE为0.7049%,决定系数R2为0.8763,实现了浮选钼精矿品位的在线预测。     

AEIV结合AHSI用于饱和脂肪酮类物质的13C NMR谱模拟

应用一种反映分子局部微环境描述子--原子电性相互作用矢量（vector of atomic electronegative interaction,AEIV）和原子杂化状态指数（Atomic Hybridation State Index, AHSI）对饱和脂肪酮类化合物的55种分子中的153个¹³C NMR谱建模模拟,应用多元线性回归方法得到定量结构波谱关系(QSSR)模型的复相关系数R_MM=0.997, 标准偏差为SD_MM=7.155. 采用留一法交互检验的结果是R_CV=0.993,SD_CV=10.195. 并随机抽出三部分分子进行检验,得到的相关系数分别是R_MM1=0.996,R_MM2=0.996,R_MM3=0.999. 研究结果表明使用AEIV和AHSI所建模型预测能力是相当稳定的.     

Lorentz-Minkowski空间中旋转W超曲面

1841年,D elaunay获得如下定理:如果在一平面上沿定直线滚动一条二次圆锥直线,然后将其焦点的轨迹绕定直线旋转,则所得到的曲面具有常数平均曲率,反之,所有旋转常数平均曲率曲面(除球面外)都有如此构造.本文将以上的D elaunay定理推广到Lorentz-M inkow sk i空间Rn1 1中类空的Sm型旋转W超曲面.     

污染数据半参数回归模型中估计的相合性

利用最小二乘估计方法和权函数法给出了半参数模型Y=βX g(T) ε在某种污染方式下,,βg和污染系数的估计,并在适当条件下证明了它们具有相合性.     

Classification of nasopharyngeal cell lines (C666-1, CNE2, NP69) via Raman spectroscopy and decision tree

Researchers have demonstrated that Raman spectroscopy can be used for characterization of tumor cells with excellent spatial resolution. However, performance evaluation of different algorithms in classifying multiclass of Raman spectra has not been reported yet. In this work, we present Raman spectra of nasopharyngeal carcinoma and nasopharyngeal normal cell lines. Combined with student’s t-test and several multivariate approaches, including decision tree, support vector classification, and linear discriminant analysis, our work shows that the relative content of two histological abnormality sensitive bands at 1449 and 1658 cm⁻¹ in tumor cells is significantly different from that of normal cells (p = 0.0132), and can be a biomarker to classify these cells. This difference is confirmed by importance analyses in the decision tree model. Furthermore, performances of statistical methods are compared with one another to explore the ability in classification. Results show that the decision tree can be more capable for classification between tumorous and normal cell lines with sensitivity and specificity of 99.0% and 96.9%, respectively. Findings of this work further support our previous work and indicate that the decision tree performs more robustly in cell classification. Our work will prove helpful to the early diagnosis of nasopharyngeal carcinoma, and will indicate the decision tree to be the primary algorithm in tumor-cell classification.     

催化剂筛选：火山型曲线成因理论解析及其在多相催化中的应用

多相催化对于现代社会来说具有极其重要的意义,催化剂的理性设计/筛选是现代催化化学研究者的一个重要的目标。其中,火山型曲线是一个的重要工具。它指出对于一个催化反应来说,其催化活性针对关键物种吸附能来说呈一条先上升后下降的曲线,要求最佳催化剂对中间体的吸附能不能太高也不能太低。近几十年来,密度泛函理论等第一性原理计算方法的发展让许多催化剂表面反应微观物理量的计算成为了可能,这极大地拓展了火山型曲线的应用范围。 然而,对于火山型曲线根源的解释,人们却并非了解得十分清楚;一些基本科学概念的理解很多还是基于经验性的Sabatier原理：吸附太弱不利于吸附、太强不利于脱附。针对该问题的科学解析,本文进行了详细的动力学探究,试图以完全数学解析的方式回答催化反应中火山型曲线的必然存在性、产生根源及在催化活性预测中的内涵。本文采用了两步催化模型以及微动力学来进行速率方程的推导,并考虑BEP关系(基元反应的能垒与其反应焓存在线性关系)的应用,最终将整体反应速率转化为中间体吸附能相关的单值函数。基于对该函数的系列推导和分析,得到如下基本结论：(1)从数学上以一个完全的解析形式证明了催化反应中火山型曲线的存在。(2)通过对比催化反应与与之对应的气相反应,我们证明了：若无催化剂参与反应,则火山型曲线不会产生;由于催化剂表面的参与,随着催化剂吸附能力的增强,其表面会因为吸附作用而被占据毒化,导致反应速率存在一个最大值,即形成火山型曲线。从概念上讲,火山型曲线的根源是由“吸附过程引发表面活性位占据”这一自毒化效应造成的,它的存在可能体现为多相催化的基本属性。(3)数值模拟解析展示了表面反应与气相反应的区别,印证了我们的数学解析结论。同时,通过一定的简化,我们对火山型曲线中各部分的斜率进行了研究。结果发现,对于吸附决速过程,催化反应和气相反应斜率相同,其差别主要出现在脱附决速过程。在此阶段由于吸附能过大,表面被毒化,表面反应速率开始下降;而气相反应的速率依然上升。(4)表面反应速率方程的分解和简化结果表明,最佳催化剂在反应中的空活性位点覆盖度和其BEP关系的斜率存在内在关联关系(θ*opt=1–α),据此讨论了其在催化剂寻优过程中的意义。尝试解释了(a)合成氨反应中正逆反应所需最佳催化剂不同的现象;(b)合成氨或CO甲烷化反应最佳催化剂为前过渡金属、而CO/NO氧化等为后过渡金属这一典型催化现象的物理图像。最后,针对火山型曲线理论框架在实际催化剂理论筛选寻优中的应用,我们简要综述了本课题组近年来在光解水制氢Pt基助催化剂和染料敏化太阳能电池的对电极材料设计方面的理论进展。