合成二苄基二硒醚的新方法

苯骈三氮唑和胺(伯、仲胺: 芳胺、杂环胺或杂环芳胺)、苯甲醛发生Mannich反应, 生成N-取代-1-苯骈三氮唑基苄胺, 它与硒氢化钠反应生成二苄基二硒醚, 反应条件温和, 产率高, 胺和苯骈三氮唑均可回收再利用。     

苯骈三氮唑的胺烷基化: 二级胺的合成

在干苯溶液中, 用4-N, N-二甲胺基苯甲醛, 苯骈三氮唑和芳胺或杂环芳胺回流,生成N-取代-1-苯骈三氮唑基-P-1N,N-二甲胺基)苄胺, 然后利用NaBH~4还原, 结果得到N-取代-4-N,N-二甲胺基苄胺, 反应条件温和、产率高、后处理方便, 一般只需一次重结晶, 即可得到纯产物。因此, 是合成二级胺的较好方法。     

血吸虫病化学治疗的研究Ⅸ.——酚类化合物的Mannich硷

对位有氯、溴、硝基、甲氧基、甲巯基、甲基、苯基等取代基的苯酚与甲醛及仲胺共热,或与双(二烃氨基)甲烷作用,生成预期的2-二烃氨甲基-4-取代基苯酚.以1,4-二氮六圜作为仲胺作用,酚、醛、胺的用量比虽为1∶1∶1,反应却以2∶2∶1的比例进行,获得N,N'-双(2-羟基芳甲基)-1,4-二氮六圜.3,4-二巯基甲苯与甲醛及仲胺作用时,氨甲基引进在硫原子上,生成3,4-双(二烃氨甲巯基)甲苯.     

α, α'-二胺基二苄基硒醚的合成

本文以苯骈三氮唑、胺和苯甲基醛为原料,发现Mannich反应,生成胺烷基化的苯骈三氮唑衍生物。在此衍生物中,苯骈三氮唑基是亲核取代反应的良好离去基团,易被强亲核试剂的硒负离子取代,生成对称α,α'-二胺基二苄基硒醚。反应易进行,产率较高,产物均为固体,易提纯。这是合成含氮原子的对称硒醚的较好方法。     

氨基硫醚及氨基砜化合物的制备

苄基β-氯乙基硫醚、苯基β-溴乙基硫醚、苄基β-氯乙基砜、苯基β-溴乙基砜分别与各种仲胺作用,制成一系列氨基上有各种不同取代基的β-氨基硫醚及β-氨基砜.有的β-氨基砜则由相应硫醚以过氧化氢氧化制成. 二苯甲磺酰乙酸与苯甲醛及醋酸铵共热,除获得预期产物二苯甲基β-氨基-β-苯基乙基砜外,并得副产品二苯甲基β-苯乙烯基砜及二苯甲基甲基砜.苄磺酰乙酸反应时也生成类似产物.二苯甲硫醇与甲醛及仲胺进行Mannich反应,生成预期的氨甲基化产物.     

N,N′-双(1H-苯骈三氮唑基-1-甲基)-硫脲的合成和晶体结构

参照文献报道的合成方法,以苯骈三氮唑和硫脲为原料,以冰醋酸为溶剂,制备了双苯骈三氮唑取代的化合物N,N′-双(1H-苯骈三氮唑基-1-甲基)-硫脲;经进一步培养得到其单晶;利用元素分析和红外光谱初步分析了产物的组成和结构,利用X射线单晶衍射分析了其分子结构.     

苯并[de]蒽-7-酮类叔芳胺的合成及其发光性能的研究

芳基伯胺与芳基溴在Pd(dba)2/P(t-Bu)3催化下于80 ℃甲苯溶液中反应生成芳基仲胺, 芳基仲胺再与3-溴苯并[de]蒽-7-酮在Pd(OAc)2/P(t-Bu)3催化下于120 ℃邻二甲苯溶液中反应生成苯并[de]蒽-7-酮类叔芳胺有机电致发光材料; 3-二苯基氨基苯并[de]蒽-7-酮与丙二腈反应生成2-(3-二苯基氨基)苯并[de]蒽-7-基亚基丙二腈. 产物的结构经1H NMR, 13C NMR, 13C (DEPT), HRMS光谱所证实. 用UV-Vis, PL, DSC测定了化合物的发光性能.     

B_2pin_2参与的含硼酸酯的芳香胺和醛的一锅两步还原胺化反应（英文）

官能团化的仲胺广泛存在于生物和天然产物,在有机化学中具有重要的地位.此外,含硼酸频哪醇酯的芳香仲胺是一种重要的有机合成中间体.研究了在氢氧化钠和乙醇的存在下,联硼酸频哪醇酯作为还原剂,含硼酸频哪醇酯的芳香伯胺和醛的一锅两步还原胺化反应.通过对碱、温度、溶剂、时间、醛的用量等进行筛选,在较优的反应条件下以中等到较好的收率得到了一系列相应的含硼酸频哪醇酯的芳香仲胺.该方法产率较高,具有良好的官能团容忍性,并且合成的芳香仲胺中硼酸频哪醇酯取代基还可以进一步官能团化.     

Pd2dba3高效催化碘代芳烃的双羰化反应合成α-酮酰胺

以高效、廉价易得的Pd2dba3作为催化剂,成功实现了碘代芳烃的双羰化反应,得到的α-酮酰胺最高分离收率达90%.该催化体系对于不同取代基的碘代芳烃和仲胺都具有广泛的底物适应性.     

多聚磷酸存在下取代6-苄硫基嘧啶与羧酸的环合反应研究

以多聚磷酸(PPA)为催化剂, 对取代6-苄硫基嘧啶与羧酸的反应进行了研究. 当羧酸为脂肪酸时, 在60-80 ℃下反应, 可选择性地得到6-苄硫基嘌呤衍生物; 改用芳香酸时, 则得到硫上的苄基被脱除的6-巯基嘌呤和嘧啶并[5,4-d]噻唑; 如果将嘧啶4-位上伯胺取代基变成仲胺取代基, 只得到嘧啶并[5,4-d]噻唑. 通过双途径反应机理对上述现象进行了解释.     

A semi-supervised learning approach for RNA secondary structure prediction

RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited.     

Recent developments in non-enzymatic catalytic oxidative kinetic resolution of secondary alcohols

The goal of this review is to collect the recent developments in non-enzymatic catalytic oxidative kinetic resolutions of secondary alcohols reported since the beginning of 2011. It is divided into four sections, dealing successively with manganese-catalysed oxidative kinetic resolutions of secondary alcohols, palladium-catalysed oxidative kinetic resolutions of secondary alcohols, oxidative kinetic resolutions of secondary alcohols catalysed by other metals and organocatalysed oxidative kinetic resolutions of secondary alcohols.     

Additive property of secondary relaxation processes in di-n-octyl and di-isooctyl phthalates: signature of non-Johari-Goldstein relaxation

Broadband dielectric spectroscopy was used to study relaxation dynamics of supercooled di-n-octyl phthalate, di-isooctyl phthalate, and their mixtures. Additionally, low temperature measurements were performed to investigate the nature of the secondary relaxation processes in both glass formers. The authors found that the secondary relaxation observed in the mixture is the additive sum of the secondary relaxations of the two components. This experimental evidence indicates that these secondary relaxation processes are intramolecular in origin, and they are non-Johari-Goldstein secondary relaxations.     

Construction of global and robust near-infrared calibration models based on hybrid calibration sets using Partial Least Squares (PLS) regression

Near-infrared spectroscopy (NIR) models built on a particular instrument are often invalid on other instruments due to spectral inconsistencies between the instruments. In the present work, global and robust NIR calibration models were constructed by partial least square (PLS) regression based on hybrid calibration sets, which are composed of both primary and secondary spectra. Three datasets were used as case studies. The first consisted of 72 radix scutellaria samples measured on two NIR spectrometers with known baicalin content. The second was composed of 80 corn samples measured on two instruments with known moisture, oil, and protein concentrations. The third dataset included 279 primary samples of tobacco with known nicotine content and 78 secondary samples of tobacco with known nicotine concentrations. The effect of the number of secondary spectra in the hybrid calibration sets and the methods for selecting secondary spectra on the PLS model performance were investigated by comparing the results obtained from different calibration sets. This study shows that the global and robust calibration models accurately predicted both primary and secondary samples as long as the ratios of the number of primary spectra to the number of secondary spectra were less than 22. The models performance was not influenced by the selection method of the secondary spectra. The hybrid calibration sets included the primary spectral information and also the secondary spectra; information, rendering the constructed global and robust models applicable to both primary and secondary instruments.     

A new mapping rule for RNA secondary structures with its applications

According to the characterization of RNA secondary structures, the RNA secondary structures are transformed into elementary sequences, namely characteristic sequences of RNA secondary structures, by representing A, U, G, C in A-U/ G-C pairs, as A′, U′, G′, C′. Based on the representation, three recurrences for mapping RNA secondary structures into 1-D graph, 2-D graph and 3-D graph are given, respectively. Furthermore, a frequency-based method for RNA secondary structures is given in terms of 1-D graph.     

钯催化带有酮或醛的芳基三氟甲磺酸酯与胺或酰胺的取代反应

各种含有酮或醛的芳基三氟甲磺酸酯在催化量的钯和膦配体的存在下与胺或酰胺发生取代反应。BINAP为配体对仲胺效果最好,MOP-型配体对伯胺和少量仲胺效果较好,Xantphos 对伯酰胺和环状仲酰胺效果好。脂肪族的仲酰胺作为亲核试剂没有得到好的结果。     

Dynamics of glassy and liquid m-toluidine investigated by high-resolution dielectric spectroscopy

The glass-former m-toluidine displays the characteristic properties of a fragile supercooled liquid, which suggest the existence of a slow secondary relaxation process. In view of the recently realized importance of such a secondary relaxation feature, we have conducted a dielectric search for the secondary process in viscous and glassy m-toluidine. Based on high-resolution experiments on the distilled liquid, a secondary process can be identified which has the properties typical of a Johari-Goldstein beta relaxation. As a result, the previous hypothesis that the methyl group might be responsible for suppressing the secondary dynamics in glassy m-toluidine no longer holds.     

三氯乙酸酯与二级胺反应的研究

三氯乙酸酯与二级胺反应,在不同条件下得到不同的产物。当三氯乙酸酯与环状二级胺反应时,碳碳键断裂并生成胺基甲酸酯;而与链状二级胺反应时则发生碳氧键断裂并生成叔胺。     

Liquid chromatographic resolution of secondary amino alcohols on a chiral stationary phase based on (+)-(18-crown-6)-2,3,11,12-tetracarboxylic acid Dependence of temperature effect on analyte structure

Two types of secondary amino alcohols were successfully resolved on a liquid chromatographic chiral stationary phase based on (+)-(18-crown-6)-2,3,11,12-tetracarboxylic acid. The secondary amino alcohols containing a secondary amino group connected directly to the stereogenic center were resolved much better than those containing a hydroxyl group attached directly to the stereogenic center. In addition, the dependence of the separation factor (alpha) on column temperature was exactly opposite for the two different types of secondary amino alcohols. From the thermodynamic calculations based on Van't Hoff plots, we conclude that the enantioselectivity for the resolution of the secondary amino alcohols containing a secondary amino group connected directly to the stereogenic center is enthalpically controlled while that for the resolution of the secondary amino alcohols containing a hydroxyl group attached directly to the stereogenic center is entropically controlled.     

Integrating protein secondary structure prediction and multiple sequence alignment

Modern protein secondary structure prediction methods are based on exploiting evolutionary information contained in multiple sequence alignments. Critical steps in the secondary structure prediction process are (i) the selection of a set of sequences that are homologous to a given query sequence, (ii) the choice of the multiple sequence alignment method, and (iii) the choice of the secondary structure prediction method. Because of the close relationship between these three steps and their critical influence on the prediction results, secondary structure prediction has received increased attention from the bioinformatics community over the last few years. In this treatise, we discuss recent developments in computational methods for protein secondary structure prediction and multiple sequence alignment, focus on the integration of these methods, and provide some recommendations for state-of-the-art secondary structure prediction in practice.