Studies on metabolites and metabolic pathways of bulleyaconitine A in rat liver microsomes using LC‐MSn combined with specific inhibitors

Bulleyaconitine A (BLA) from Aconitum bulleyanum plants is usually used as anti‐inflammatory drug in some Asian countries. It has a variety of bioactivities, and at the same time some toxicities. Since the bioactivities and toxicities of BLA are closely related to its metabolism, the metabolites and the metabolic pathways of BLA in rat liver microsomes were investigated by HPLC–MSⁿ. In this research, the 12 metabolites of BLA were identified according to the results of HPLC‐MSⁿ data and the relevant literature. The results showed that there are multiple metabolites of BLA in rat liver microsomes, including demethylation, deacetylation, dehydrogenation deacetylation and hydroxylation. The major metabolic pathways of BLA in rat liver microsomes were clarified by HPLC‐MS combined with specific inhibitors of CYP450 isoforms. As a result, CYP3A and 2C were found to be the principal CYP isoforms contributing to the metabolism of BLA. Moreover, CYP2D6 and 2E1 are also more important CYP isoforms for the metabolism of BLA. While CYP1A2 only affected the formation rate of M11, its effect on the metabolism of BLA is very small. Copyright © 2014 John Wiley & Sons, Ltd.     

Selective Catalytic Isomerization of β-Pinene Oxide to Perillyl Alcohol Enhanced by Protic Tetraimidazolium Nitrate

A series of tetraimidazolium salts with different anions was prepared and applied in the isomerization of β-pinene oxide. After examining the activity of different catalysts, a remarkable enhancement of the selectivity of perillyl alcohol (47 %) was obtained over [PEimi][HNO₃]₄ under mild reaction conditions and using DMSO as the solvent. Furthermore, noncovalent interactions between solvent molecules and the catalyst were found by FT-IR spectroscopy and confirmed by computational chemistry. The homogeneous catalyst showed excellent stability and was reused up to six times without significant loss.     

Quantization for an evolution equation with critical exponential growth on a closed Riemann surface

In this paper, we analyze the concentration behavior of a positive solution to an evolution equation with critical exponential growth on a closed Riemann surface, and particularly derive an energy identity for such a solution. This extends a result of Lamm-Robert-Struwe and complements that of Yang.     

Electrochemiluminescence Enhanced by the Synergetic Effect of Porphyrin and Multi-walled Carbon Nanotubes for Uric Acid Detection

The design and exploration of efficient, stable and environmentally compatible organic emitters for an electrochemiluminescence (ECL) sensor is a promising topic. Herein, a novel environmentally-friendly luminophore, ZnBCBTP@MWCNTs, were fabricated via self-assembly of porphyrin molecules (ZnBCBTP) onto multi-walled carbon nanotubes (MWCNTs). The resulting luminophore ZnBCBTP@MWCNTs displayed not only the highly ECL property and but also the good accelerated electron mobility. Then, a label-free ECL biosensor based ZnBCBTP@MWCNTs was constructed for the ultrasensitive detection of uric acid. Excitingly, this proposed ECL biosensor performed a good linear relationship in the range of 0–300 μM with a low detection limit of 1.4 μM, thus offering another reliable and feasible sensing platform for clinical bioanalysis with good selectivity, stability, and repeatability.     

Photodegradation mechanisms of acyclovir in water and the toxicity of photoproducts

Journal of Radioanalytical and Nuclear Chemistry - In the present work the final products of coumarin radiation chemical transformation are investigated by chromatography. During radiolysis of...     

Sentinel-2卫星的多光谱轻量级船舶目标检测算法

近年来深度卷积神经网络在可见光船舶检测方面取得了显著的进展，然而，大多数相关研究是通过改进大型的网络结构来提高检测性能，因此加大了对更高计算机性能的需求。此外，可见光图像难以在云、雾、海杂波、黑夜等复杂场景检测到船舶。针对以上问题，提出了一种融合红（red, R）、绿（green, G）、蓝（blue, B）和近红外（NIR）4个波段光谱信息的由粗到精细的轻量型船舶检测算法。与现有的方法中根据光谱特性利用水体检测算法提取水体区域不同之处是该算法是利用改进的水体检测算法来提取船舶候选区域。为获取更准确的候选区域，对船舶、厚云、薄云、平静海面、杂波海面5种场景中4个波段的像素值进行了统计分析，选取近红外大于阈值作为辅助判断，并以其中心点获取候选区域32×32大小的切片，并对切片进行非极大值抑制，由此获得了船舶粗检测结果。随后构建了轻量级LSGFNet网络对船舶候选区域切片进行精细识别。构建的网络融合了1×1卷积提取的波谱特征与3×3的提取几何特征，为防止光谱特征与几何特征的信息在融合时“信息不流通”，在LSGFNet网络中引入了ShuffleNet中的通道打乱机制，并减小了模型结构，与典型的轻量级网络相比具有更好的效果且模型较小。最后，利用Sentinel-2卫星多光谱10 m分辨率数据构建了512×512大小的1 120组数据进行粗检测，以及32×32大小的6 014组数据进行精细网络训练，其中候选区域粗提取的查全率为98.99%，精细识别网络精确度为96.04%，不同场景下的平均精确度为92.98%。实验表明该算法在抑制云层、海浪杂波等干扰的复杂背景下具有较高的检测效率，且训练时间短、计算机性能需求低。