Computational Insight into Biotransformation Profiles of Organophosphorus Flame Retardants to Their Diester Metabolites by Cytochrome P450

Biotransformation of organophosphorus flame retardants (OPFRs) mediated by cytochrome P450 enzymes (CYPs) has a potential correlation with their toxicological effects on humans. In this work, we employed five typical OPFRs including tris(1,3-dichloro-2-propyl) phosphate (TDCIPP), tris(1-chloro-2-propyl) phosphate (TCIPP), tri(2-chloroethyl) phosphate (TCEP), triethyl phosphate (TEP), and 2-ethylhexyl diphenyl phosphate (EHDPHP), and performed density functional theory (DFT) calculations to clarify the CYP-catalyzed biotransformation of five OPFRs to their diester metabolites. The DFT results show that the reaction mechanism consists of Cα-hydroxylation and O-dealkylation steps, and the biotransformation activities of five OPFRs may follow the order of TCEP ≈ TEP ≈ EHDPHP > TCIPP > TDCIPP. We further performed molecular dynamics (MD) simulations to unravel the binding interactions of five OPFRs in the CYP3A4 isoform. Binding mode analyses demonstrate that CYP3A4-mediated metabolism of TDCIPP, TCIPP, TCEP, and TEP can produce the diester metabolites, while EHDPHP metabolism may generate para-hydroxyEHDPHP as the primary metabolite. Moreover, the EHDPHP and TDCIPP have higher binding potential to CYP3A4 than TCIPP, TCEP, and TEP. This work reports the biotransformation profiles and binding features of five OPFRs in CYP, which can provide meaningful clues for the further studies of the metabolic fates of OPFRs and toxicological effects associated with the relevant metabolites.     

Bioavailability Enhancement of Cepharanthine via Pulmonary Administration in Rats and Its Therapeutic Potential for Pulmonary Fibrosis Associated with COVID-19 Infection

Cepharanthine (CEP) has excellent anti-SARS-CoV-2 properties, indicating its favorable potential for COVID-19 treatment. However, its application is challenged by its poor dissolubility and oral bioavailability. The present study aimed to improve the bioavailability of CEP by optimizing its solubility and through a pulmonary delivery method, which improved its bioavailability by five times when compared to that through the oral delivery method (68.07% vs. 13.15%). An ultra-performance liquid chromatography tandem-mass spectrometry (UPLC-MS/MS) method for quantification of CEP in rat plasma was developed and validated to support the bioavailability and pharmacokinetic studies. In addition, pulmonary fibrosis was recognized as a sequela of COVID-19 infection, warranting further evaluation of the therapeutic potential of CEP on a rat lung fibrosis model. The antifibrotic effect was assessed by analysis of lung index and histopathological examination, detection of transforming growth factor (TGF)-β1, interleukin-6 (IL-6), α-smooth muscle actin (α-SMA), and hydroxyproline level in serum or lung tissues. Our data demonstrated that CEP could significantly alleviate bleomycin (BLM)-induced collagen accumulation and inflammation, thereby exerting protective effects against pulmonary fibrosis. Our results provide evidence supporting the hypothesis that pulmonary delivery CEP may be a promising therapy for pulmonary fibrosis associated with COVID-19 infection.     

MIT袋模型的一种束缚能跑动形式修正

最近,文献[1]在MIT袋模型的基础上引入了一种强耦合常数跑动形式和重夸克束缚能,较好地计算了所有已确认的基态强子谱。考虑到束缚能的贡献之一为重夸克间的短程束缚作用,即色电相互作用,其跑动形式将会取代之前的拟合参数。此跑动形式为类库仑势,随着袋半径R变化,并且在质量公式中参与变分。结果表明,色电相互作用的引入同样会将基态强子质量计算误差控制在大致40 MeV以内,且与拟合参数的方法相比得到了较为准确的结果。这为重夸克色电相互作用的研究提供了参考依据。     

一种基于PCI Express总线的DMA高速传输系统

介绍了DMA高速传输系统的结构以及DMA的设计,搭建了×8通道的PCIE系统.在整个系统的板卡终端,连接了两个FIFO,提供标准的FIFO接口,能连接光纤数据、CT图像采集数据、A/D采样数据等.实验验证了DMA读和DMA写两种传输方式的可靠性,测试了DMA读写的传输速度.实验表明,在单次DMA传输大小达到1MB时,×8通道的PCIE系统DMA读和写速度均能达到1 000 MB/s,可满足大部分高速数据传输的要求.     

基于二阶混合注意力的行人重识别

基于注意力机制的行人重识别方法更多利用图像中 一阶信息,忽略了特征中二阶信息 ,不能挖掘特征图之间的相关性和细粒度信息。提出一种基于二阶混合注意力的行人重 识别算法(second-order mixed attention module,SMAN)。二阶混合注意力模块(second-order mixed attention module,SOMA)由二阶通道注意力(second-order channel attention,SOCA)和二阶空间注意力模 块(second-order information,SOSA)组成,该方法将全局协方差池函数嵌入到SOCA和SOSA模块中,学习特征中二阶信息 。SOCA模块学习特征图之间相关性,SOSA模块则重新为特征图分配权重,关注特征图空间域 的细粒度信息。SMAN算法在Market-1501和 DukeMTMC-ReID数据集上的首位准确率分别 为 94.3%和87.1%,mAP分别达到85.7%和74.5%,同时使用类激活图验证SOMA模块的影响 ,实验表 明SMAN算法充分利用特征图的通道域和空间域中二阶信息。算法的性能优于现有的一些基于 注意力机制行人重识别方法,甚至接近某些优秀的方法。     

面向语义的解释型测试程序集

通过对国内外研究工作的分析,提出了面向语义的解释型测试程序集描述方法。该方法采用具有完备性、独立性和灵活性的语义集合对具体的测试需求进行抽象,构建通用性较强的测试程序集,并为可扩展性提供了相应的接口。     

表面活化处理在激光局部键合中的应用

为了研究低热应力键合工艺,提出了一种将表面活化直接键合与激光局部键合相结合的键合技术。首先采用RCA溶液对键合片进行表面亲水活化处理,并在室温下成功地完成了预键合。然后在不使用任何夹具施加外力辅助的情况下,利用波长1064nm、光斑直径500μm、功率70W的Nd:YAG连续式激光器,实现了激光局部键合,并取得了6.3MPa~6.8MPa的键合强度。结果表明,这种以表面活化预键合代替加压的激光局部键合技术克服了传统激光键合存在的激光对焦困难,以及压力不匀易损害键合片和玻璃盖板等缺点,同时缩短了表面活化直接键合的退火时间,提高了键合效率。     

雷达目标特征提取的一种方法

针对雷达高分辨率距离像（HRRP）方位敏感性和平移敏感性的问题,在对一维距离像进行预处理的基础上,提取两个平移不变特征：中心矩和熵,并将二者形成组合特征,采用Karhunen—Loeve变换进一步进行特征压缩,运用并比较了最大最小距离判别法和SVM分类器的识别性能．实验结果表明中心矩一熵组合特征提取方法能够显著增强目标的可分性,大大提高识别率。     

粗糙集和支持向量机在复杂电路系统诊断中的应用

为了解决复杂电路系统故障样本少、特征信息冗杂的问题,提出了一种基于粗糙集属性约简理论和支持向量机分类方法相结合的故障诊断方法.首先采用粗糙集约简故障模式库中的冗余特征属性和矛盾样本,然后提取最简故障特征模式作为支持向量机的学习样本,通过样本训练使构建的支持向量机多分类器能够快速实现故障诊断的目的.最后,通过仿真算例验证了该方法在小样本故障识别上的有效性和可行性.     

基于ASP模式下UD_RBAC模型的研究与实现

随着应用服务提供商(ASP)模式的发展,为解决集成了越来越多应用服务的ASP平台与用户之间复杂的管理需求,提出了一种ASP模式下用户授权代理机制的角色访问控制(UD-RBAc)模型.文中对UD_RBAC模型形式化描述,细致地分析了其构成要素、用户授权代理管理模式和实施策略.采用LDAP目录访问协议统一存储用户身份和权限信息,通过代理策略保护应用服务资源,实现对用户的访问进行分级授权和控制.