• <nav id="ikqyo"><strong id="ikqyo"></strong></nav><menu id="ikqyo"></menu>
  • <nav id="ikqyo"></nav>
  • <nav id="ikqyo"><nav id="ikqyo"></nav></nav>
    <nav id="ikqyo"><nav id="ikqyo"></nav></nav>


    The interrelationships and synergistic regulations of bioactive molecules play pivotal roles in physiological and pathological processes involved in the initiation and development of some diseases, such as cancer and neurodegenerative and cardiovascular diseases. Therefore, the simultaneous, accurate and timely detection of two bioactive molecules is crucial to explore their roles and pathological mechanisms in related diseases. Fluorescence imaging associated with small molecular probes has been widely used in the imaging of bioactive molecules in living cells and due to its excellent performances, including high sensitivity and selectivity, noninvasive properties, real-time and high spatial temporal resolution. Single organic molecule fluorescent probes have been successively developed to simultaneously monitor two biomolecules to uncover their synergistic relationships in living systems. Hence, in this review, we focus on summarizing the design strategies, classifications, and bioimaging applications of dual-response fluorescent probes over the past decade. Furthermore, future research directions in this field are proposed.

    Yongqing Zhou ,   Xin Wang   et al.
    Modeling and optimization is crucial to smart chemical process operations. However, a large number of nonlinearities must be considered in a typical chemical process according to complex unit operations, chemical reactions and separations. This leads to a great challenge of implementing mechanistic models into industrial-scale problems due to the resulting computational complexity. Thus, this paper presents an efficient hybrid framework of integrating machine learning and particle swarm optimization to overcome the aforementioned difficulties. An industrial propane dehydrogenation process was carried out to demonstrate the validity and efficiency of our method. Firstly, a data set was generated based on process mechanistic simulation validated by industrial data, which provides sufficient and reasonable samples for model training and testing. Secondly, four well-known machine learning methods, namely, K-nearest neighbors, decision tree, support vector machine, and artificial neural network, were compared and used to obtain the prediction models of the processes operation. All of these methods achieved highly accurate model by adjusting model parameters on the basis of high-coverage data and properly features. Finally, optimal process operations were obtained by using the particle swarm optimization approach.

    Haoqin Fang ,   Jianzhao Zhou   et al.
    Heterocyclic compound quinoline and its derivatives exist in natural compounds and have a broad spectrum of biological activity. They play an important role in the design of new structural entities for medical applications. Similarly, indoles and their derivatives are found widely in nature. Amino acids, alkaloids and auxin are all derivatives of indoles, as are dyes, and their condensation with aldehydes makes it easy to construct reaction sites for nucleophilic addition agents. In this work, we combine these two groups organically to construct a rapid response site (within 30 s) for H S, and at the same time, a ratiometric fluorescence response is presented throughout the process of H S detection. As such, the lower detection limit can reach 55.7 nmol/L for H S. In addition, cell imaging shows that this probe can be used for the mitochondrial targeted detection of endogenous and exogenous H S. Finally, this probe application was verified by imaging H S in nude mice.

    Yan Shi ,   Fangjun Huo   et al.
    Lysine lipoylation plays vital roles in cell metabolism and redox processes. For example, removal of lipoylation will decrease pyruvate dehydrogenase activity and affect the citric acid cycle. Despite the important functions of lysine lipoylation, the mechanisms for the addition and removal of this modification remain largely unexplored. Very few useful chemical tools are available to study the interactions of lysine lipoylation with its regulatory delipoylation proteins. For example, immunoaffinity purification-mass spectrometry is one of such tools, which highly relies on antibody efficiency and purification techniques. Single-step activity based fluorogenic probes developed by our groups and others is also an efficient method to study the deacylation activity. Affinity-based labeling probe using photo-cross-linker is a powerful platform to study the transient and dynamic interactions of peptide ligands with the interacting proteins. Herein, we have designed and synthesized a dual-function probe KTLlip for studying enzymatic delipoylation (eraser) activity and interaction of lysine lipoylation with the eraser at the same time. We show that KTLlip can be used as a useful tool to detect delipoylation as demonstrated by its ability to fluorescently label the eraser activity of recombinant Sirt2. We envision that the probe will help delineate the roles of delipoylation enzyme in biology.

    Yusheng Xie ,   Jie Zhang   et al.

    Most Popular