The application of high-resolution mass spectrometry-based data-mining tools in tandem to metabolite profiling of a triple drug combination in humans

Patients are usually exposed to multiple drugs, and metabolite profiling of each drug in complex biological matrices is a big challenge. This study presented a new application of an improved high resolution mass spectrometry (HRMS)-based data-mining tools in tandem to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was metronidazole-pantoprazole-clarithromycin (MET-PAN-CLAR), which is widely used in clinic to treat ulcers caused by Helicobacter pylori. First, mass defect filter (MDF), as a targeted data processing tool, was able to recover all relevant metabolites of MET-PAN-CLAR in human plasma and urine from the full-scan MS dataset when appropriate MDF templates for each drug were defined. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, worked effectively except for several trace metabolites, which were buried in the remaining background signals. Third, an integrated strategy, i.e., untargeted BS followed by improved MDF, was effective for metabolite identification of MET-PAN-CLAR. Most metabolites except for trace ones were found in the first step of BS-processed datasets, and the results led to the setup of appropriate metabolite MDF template for the subsequent MDF data processing. Trace metabolites were further recovered by MDF, which used both common MDF templates and the novel metabolite-based MDF templates. As a result, a total of 44 metabolites or related components were found for MET-PAN-CLAR in human plasma and urine using the integrated strategy. New metabolic pathways such as N-glucuronidation of PAN and dehydrogenation of CLAR were found. This study demonstrated that the combination of accurate mass-based multiple data-mining techniques in tandem, i.e., untargeted background subtraction followed by targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drugs in vivo.     

Circular dichroism sensor based on cadmium sulfide quantum dots for chiral identification and detection of penicillamine

A new chemical sensor based on the measuring of circular dichroism signal (CD) was fabricated from cysteamine capped cadmium sulfide quantum dots (Cys-CdS QDs). The chiral-thiol molecules, d-penicillamine (DPA) and l-penicillamine (LPA), were used to evaluate potentials of this sensor. Basically, DPA and LPA provide very low CD signals. However, the CD signals of DPA and LPA can be enhanced in the presence of Cys-CdS QDs. The CD spectra of DPA and LPA exhibited a mirror image profile. Parameters affecting the determination of DPA and LPA were thoroughly investigated in details. Under the optimized condition, the CD signals of DPA and LPA displayed a linear relationship with the concentrations of both enantiomers, ranging from 1 to 35 μM. Detection limits of this sensor were 0.49 and 0.74 μM for DPA and LPA, respectively. To demonstrate a potential application of this sensor, the proposed sensor was used to determine DPA and LPA in real urine samples. It was confirmed that the proposed detection technique was reliable and could be utilized in a broad range of applications.     

Diversity‐Oriented Approach for Chemical Biology

Synthetic molecules that modulate and probe biological events are critical tools in chemical biology. Utilizing combinatorial and diversity‐oriented synthetic strategies, access to large numbers of small molecules is becoming more and more feasible, and research groups in this field can take advantage of the power of chemical diversity. Since the majority of early studies were focused on the discovery of compounds that perturb protein functions, diversity‐based approaches are often considered as therapeutic lead discovery tactics. However, the diversity‐oriented approach can also be applied to advance distinct aims, such as target protein identification, or the development of imaging probes and sensors. This review provides a personal perspective of the chemical‐diversity‐based approach and how this principle can be adapted to various chemical biology studies.     

Unsupervised LoS/NLoS identification in mmWave communication using two-stage machine learning framework

Identification of line-of-sight (LoS)/ non-LoS (NLoS) condition in millimeter wave (mmWave) communication is important for localization and unobstructed transmission between a base station (BS) and a user. A sudden obstruction in a link between a BS and a user can result in poorly received signal strength or termination of communication. Channel features obtained by the estimation of channel state information (CSI) of a user at the BS can be used for identifying LoS/NLoS condition. With the assumption of labeled CSI, existing machine learning (ML) methods have achieved satisfactory performance for LoS/NLoS identification. However, in a real communication environment, labeled CSI is not available. In this paper, we propose a two-stage unsupervised ML based LoS/NLoS identification framework to address the lack of labeled data. We conduct experiments for the outdoor scenario by generating data from the NYUSIM simulator. We compare the performance of our method with the supervised deep neural network (SDNN) in terms of accuracy and receiver characteristic curves. The proposed framework can achieve an accuracy of 87.4% and it outperforms SDNN. Further, we compare the performance of our method with other state-of-the-art LoS/NLoS identification schemes in terms of accuracy, recall, precision, and F1-score.     

初中化学“酸和碱的性质”创意教学*——探析食品发热包

以食品发热包为主题情境,通过探析发热包成分、解密发热原理、计算原料配比、配制发热包等环节梳理酸和碱的性质、用途。从元素观、转化观的视角认识物质转化规律,体现物质研究的一般思路,凸显科学探究的基本过程。通过设计方案测定发热包中碳酸钠的含量,总结混合物成分鉴定及定量测定的方法;归纳气体定量测定的影响因素。呈现一堂学科观念、学科方法教学具体课例,凸显物质研究、定性检验、定量测定的基本方法。     

“宏观辨识与微观探析”视域下的初中化学教学*——中和反应

在“宏观辨识与微观探析”视域下进行中和反应教学,首先以常规实验为载体,从宏观视角认识中和反应的外在表现,然后以模型、动画为载体,从微观视角了解中和反应的微观过程,再以数字化实验为载体,从宏观与微观相结合的视角理解中和反应的内在本质,最后联系生产生活实际,体验中和反应的应用价值。这样设计,学生能深刻理解中和反应的本质,增进化学学科理解,培养化学学科核心素养。     

基质辅助激光解析/电离飞行时间质谱(MALDI-TOF MS)在微生物鉴定中的应用*

基质辅助激光解析/电离飞行时间质谱(MALDI-TOF MS)是一种新型软电离生物质谱,具有检测速度快、操作简便、结果准确等优点,目前已成为可靠的微生物快速鉴定技术。就工作流程而言,与常规生化方法相比,MALDI-TOF MS可以将微生物鉴定的时间缩短为一天甚至更短。对于具有抗生素耐药性的微生物,使用MALDI-TOF MS鉴定也有很好的准确性。在病毒鉴定中,MALDI-TOF MS也可以发挥作用,已有报道将MALDI-TOF MS和机器学习(ML)分析方法结合来检测鼻拭子中SARS-CoV-2。此外,MALDI-TOF MS还可用于细菌的无光谱库鉴定。目前,MALDI-TOF MS正通过与其他技术(例如傅里叶红外光谱FTIR)相结合进一步扩大微生物鉴定范围。     

色谱在药物-机体复杂巨系统研究中的应用进展

色谱是一门以分离分析为主,旨在追求复杂事物纯而净的分析化学的重要分支学科。其经过百余年的发展,理论与技术日臻完善,集科学、技术与艺术于一体。近年来,色谱及其与质谱、核磁共振波谱、原子发射光谱等联用技术极大推动了环境、食品、石油化工、生物医药等领域中所涉及复杂体系的研究进展。作为我国传统文化的核心代表,中医药为中国乃至世界人民的健康服务逾千年,从古至今历经上千年临床考验,疗效经久不衰。近年来,中国政府强调继承与创新,加大推进中医药的现代化与国际化。然而中药自身的多成分协同起效复杂性及其与机体时刻新陈代谢变化的复杂性往往相互作用,由此形成了药物-机体复杂巨系统。该复杂巨系统的分析研究是中医药现代化进程的关键瓶颈。色谱的优势在于复杂成分的分离与分析,此恰能为上述复杂巨系统提供技术支撑,色谱及其联用技术已成为推动中医药分子化、数字化、信息化乃至现代化的主流技术。该文综述了色谱及其联用技术在中药复杂体系、复杂生命过程及药物-机体复杂巨系统中的应用进展,介绍了笔者研究团队对中医药现代化的认识、研究思路和研究工作,最后笔者结合对于百年色谱与千年中医药文化之现代化交织的感悟,对色谱技术在此领域的前景做出了展望。     

Large scale synthesis of red emissive carbon dots powder by solid state reaction for fingerprint identification

Red emissive carbon dots(CDs) powder was synthesized on a large scale from phloroglucinol and boric acid by a novel solid state reaction with yield up to 75%. This method is safe and convenient, for it needs neither high pressure reactors nor complicated post-treatment procedures. The as-prepared carbon dots powder exhibited strong red fluorescence with excitation-independent behavior. XPS measurement and PL spectra suggest that such red fluorescence arise from boron-doped structures in CDs, which increases along with the boron concentration on CDs surface but decreases when the concentration quenching effect takes place. To overcome the aggregation induced fluorescence quenching of the solid CDs powder,the conventional methods are dispersing CDs into a large amount of inert substrates. But our present work provides a new strategy to realize strong red fluorescence of CDs in solid state. As a result, such carbon dots powder works well for latent fingerprint identification on various material surfaces.