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Due to the large mismatch in the timescale investigated by the atomistically detailed simulations and experiments, the glass transition temperature predicted in simulations shifts to higher values. When this timescale mismatch is accounted for by using appropriate shift factors, the master curves of the dynamic moduli obtained in simulations closely match those obtained in experiments. This result demonstrates the exciting ability of TTS to overcome the large timescale disparity between simulations and experiments which will enable the use of molecular simulations for quantitatively predicting the rheological property values at frequencies of practical interest.Metal oxides are widely used in the fields of chemistry, physics and materials science. Oxygen vacancy formation energy is a key parameter to describe the chemical, mechanical, and thermodynamic properties of metal oxides. How to acquire quickly and accurately oxygen vacancy formation energy remains a challenge for both experimental and theoretical researchers. Herein, we propose a machine learning model for the prediction of oxygen vacancy formation energy via data-driven analysis and the definition of simple descriptors. Starting with the database containing oxygen vacancy formation energies for 1750 metal oxides with enough structural diversity, new descriptors that effectively avoid the defects of molecular fingerprints, molecular graphic descriptors and site descriptors are defined. The descriptors have obvious physical meanings and wide practicability. Multiple linear regression analysis is then used to screen important features for machine learning model development, and two strongly associated features are obtained. The selected descriptors are used as input for the training of 21 machine learning models to select and develop the most accurate machine learning model. Finally, it is shown that the least squares support vector regression method exhibits the best performance for accurate prediction of the targeted oxygen vacancy formation energy through systematic error analysis, and the prediction accuracy is also verified by the external dataset. Our work establishes a novel and simple computational approach for accurate prediction of the oxygen vacancy formation energy of metal oxides and highlights the availability of data-driven analysis for metal oxide material research.Capillary electrophoresis (CE) presents a promising possibility for analyzing traditional Chinese medicine (TCM) due to its low reagent consumption, high analysis speed, and enhanced efficiency. Herein we review the employment of CE for analyzing the effective components in TCM and identifying TCM via a fingerprint. Furthermore, we discuss the application of state-of-the-art capillary electrophoresis modes for screening enzyme inhibitors and investigating the interactions between TCM and plasma proteins. The review concludes with recommendations for future studies and improvements in this field of research. The general development trend identified in this review indicates that the application of CE has significantly improved TCM assay performance.As a common feature of the tumor microenvironment (TME), hypoxia significantly impedes the effects of photodynamic therapy. Moreover, for tumor combination therapy, smart responsive and well-designed nanocarriers are highlighted to co-deliver different therapeutics, enhance drug delivery into target sites, and realize stimuli-responsive drug release. Herein, oxygen- and bubble-generating polymersomes (FIMPs) were developed for tumor-targeted and enhanced photothermal-photodynamic combination therapy. FIMPs efficiently co-encapsulated manganese dioxide (MnO2) and the hydrophobic photosensitizer indocyanine green (ICG) within the hydrophobic membrane as well as the bubble-generating reagent NH4HCO3 in the internal cavity of the vesicles, and achieved pH/temperature/reduction multiple responsiveness. The CO2 bubbles generated from the decomposition of NH4HCO3via laser irradiation or acidic environment and the cleavage of the copolymer disulfide bond in the reducing TME would destroy the vesicle structure for triggering drug release. In addition, oxygen can be produced to overcome tumor hypoxia through the high reaction activity of MnO2 with endogenous H2O2. this website In vitro studies have shown that FIMPs achieved good photothermal conversion efficiency, promoted the generation of oxygen and reactive oxygen species (ROS), and thus effectively killed tumor cells. In vivo studies indicated that FIMPs effectively overcome the hypoxic microenvironment within tumors and significantly inhibit tumor growth with good biocompatibility. The rationally designed oxygen- and bubble-generating polymersomes have great potential to overcome the tumor hypoxia limitations for enhancing the photothermal-photodynamic combination therapeutic effect.Nitric oxide (NO) gas treatment offers a promising strategy for tumor therapy; however, its practical application is still limited due to its poor efficacy and biotoxicity which were caused by gas leakage during blood delivery. Herein, a nano-platform (CMH-OBN) composed of chlorin e6-melanin-hyaluronic acid nanoparticles (Ce6-MNP-HA, CMH) and oxidized bletilla striata polysaccharide microcapsules (Oxi-BSP) carrying NO donors was prepared for responsive and cascaded release of NO, reactive oxygen species (ROS) and its secondary metabolite reactive nitrogen species (RNS) in tumor sites. Melanin not only endowed CMH with good photothermal properties, but also helped Ce6 to produce a large number of ROS under near-infrared (NIR) irradiation. OBN microcapsules, which were sensitive to ROS, can release NO donors under the stimulation of ROS released by CMH nanoparticles under NIR irradiation and can further release NO in the tumor microenvironment (TME) with high expression of glutathione (GSH). NO could further up-regulate soluble guanylate cyclase-cyclic guanosine monophosphate (sGC-cGMP) signal pathways to relieve hypoxia, thus further enhancing the photodynamic therapy (PDT). Moreover, the cascaded release of ROS and NO could produce RNS with higher lethality, which could sequentially initiate the cellular apoptotic procedure and promote immunotherapy by activating T cells at the tumor sites. More interestingly, the CMH-OBN nano-platform could supply magnetic resonance imaging (MRI) and infrared photothermal imaging guidance for tumor therapy. In conclusion, the development of a CMH-OBN nano-platform provides a satisfactory demonstration by combining NO therapy with photothermal therapy (PTT), PDT and immunotherapy for the treatment of cancer.