A Hierarchical Metal-Organic Framework Composite Aerogel Catalyst Containing Integrated Acid, Base, and Metal Sites for the One-Pot Catalytic Synthesis of Cyclic Carbonates.

Catalysis has played a decisive role in the development of unique chemical reactions to produce important chemicals. However, conventional stepwise synthetic routes that rely on individual catalysts to promote each step often suffer from ponderous processes for the isolation of intermediates that result in massive material losses and large economic expenditures. In addition, traditional powder forms of these catalysts suffer from poor processability and recoverability. Herein, we designed and prepared a hierarchical metal-organic framework (MOF) composite monolithic catalyst IL-Au@UiO-66-NH2/CMC that contains integrated acid (Zr4+), base (ionic liquid (IL)), and metal sites (Au nanoparticles (NPs)) to promote the one-pot preparation of cyclic carbonates from styrene derivatives and CO2. Highly dispersed Au NPs, IL 1-aminoethyl-3-methylimidazolium bromide ([C2NH2 MIM] [Br]), and MOF-positioned Lewis acid sites within this composite aerogel are separately responsible for catalyzing selective epoxidation of the styrene derivatives and the subsequent cycloaddition reaction of CO2 with intermediate styrene oxides. Importantly, inclusion of the imidazolium-based IL effectively modulates the size and chemical microenvironment of the Au NPs via electrostatic protection, leading to catalyst stability and its selective oxidation of styrene. Benefiting from the rapid mass transfer and high exposure of active sites within the pore-rich hierarchical nanostructure, IL-Au@UiO-66-NH2/CMC promotes high conversion (90.5%) of the styrene and selectivity (80.5%) for styrene carbonate (SC) formation in the one-pot process, a performance level that far exceeds those of related catalysts containing only Au NPs or IL (the selectivity of SC < 42%). Furthermore, the composite aerogel catalyst can be readily separated and recycled at least five times without a remarkable loss of activity and selectivity. The controllable integration of various active components in the hierarchical MOF composite aerogel herein should serve as the foundation for the design of multifunctional monolithic catalysts for other valuable tandem processes.

An injectable PC10ARGD/Cu2+/DOX hydrogel for combined chemodynamic and chemotherapy of tumors.

Nowadays, chemotherapy is a common clinical treatment for cancer, but it still faces many limitations and challenges. Therefore, the combination of chemotherapy and other treatments often enhances the effectiveness of treatments. Herein, an injectable hydrogel of PC10ARGD/Cu2+/DOX based on Cu2+, hydrophilic doxorubicin (DOX), and genetically engineered polypeptide PC10ARGD was prepared. First, Cu2+ was attached to the histidines in the PC10ARGD polypeptide by the coordination reaction to form PC10ARGD/Cu2+ hydrogel, then the PC10ARGD/Cu2+/DOX hydrogel was prepared by encapsulating the DOX into the PC10ARGD/Cu2+ hydrogel. The results of scanning electron microscopy showed that the PC10ARGD/Cu2+/DOX hydrogel displayed loose porous morphology. In vitro, reactive oxygen species production results showed that the PC10ARGD/Cu2+/DOX hydrogel could continuously produce ·OH in the presence of H2O2. In vitro MTT results showed that the PC10ARGD/Cu2+/DOX hydrogel had a good inhibitory effect on cell activity. Flow cytometry further confirmed the antitumor effect of the PC10ARGD/Cu2+/DOX hydrogel. In vivo experiment results showed that the tumor volume of mice treated with the PC10ARGD/Cu2+/DOX hydrogel was significantly inhibited compared with control groups, which was due to the combination of chemodynamic and chemotherapy. The results of body weight and blood analysis of mice showed that the PC10ARGD/Cu2+/DOX hydrogel possessed good biocompatibility.

Hierarchical Amino-Functionalized Ionic Liquids@MOF Composite Gel for Catalytic Conversion of CO2.

Hybridization of metal-organic frameworks (MOFs) and homogeneous ionic liquids (ILs) endows the heterogeneous composite with high porosity and accessible multiple active sites (e.g., acidic or basic sites), which exhibits great potential in CO2 capture and conversion. Nevertheless, the majority of MOF composites are synthesized as powders, significantly restricting their practical applications due to inherent problems such as poor handling properties, high pressure drops, and mechanical instability. Thus, it is crucial to shape MOF composites into various monoliths that allow efficient processing, especially for industrial purposes. In this work, a hierarchical ILs@nanoMOF composite gel (H-IL@UiO-66-gel) featuring both intraparticle micropores and interparticle mesopores and multiple active sites was successfully fabricated by a two-step approach. Benefiting from the integrated advantages of the hierarchically porous MOF for enhanced mass transfer and affinity of ILs for activating CO2 molecules, the resultant H-IL@UiO-66-gel exhibits excellent uptake of macromolecules and catalytic activity toward CO2 cycloaddition with epoxides under moderate conditions, far beyond the traditional microporous IL@UiO-66-gel and unfunctionalized H-UiO-66-gel. Furthermore, the H-IL@UiO-66 composite monolith can be effortlessly separated and reused at least three times without depletion of catalytic activity. It is believed that this fabrication method for the shaping of MOF composites is highly versatile and can be extended to other types of MOFs for various application fields.

MXene-based Materials for Water Splitting: Synthesis and Modification.

With abundant metal site and tunable electronic structure, MXene is considered as a promising electrocatalyst for the conversion of energy molecules. In this review, the latest research progress on inexpensive MXene-based catalysts for water electrolysis is summarized. Typical preparation and modification methods and their advantages and disadvantages are briefly discussed, with a focus on the regulation and design of the surface interface electronic states, which improve the electrocatalytic performance of MXene-based materials. The main strategies for the electronic state modification include end-group modification, heteroatom doping, and heterostructure construction. Some limitations of MXene-based materials, which should be considered in the rational design of advanced MXene-based electrocatalyst, are also discussed. Finally, prospects for the rational design of Mxene-based electrocatalysts is proposed.

Diagnosis of endometrium hyperplasia and screening of endometrial intraepithelial neoplasia in histopathological images using a global-to-local multi-scale convolutional neural network.

BACKGROUND AND OBJECTIVE: Endometrial hyperplasia (EH), a uterine pathology characterized by an increased gland-to-stroma ratio compared to normal endometrium (NE), may precede the development of endometrial cancer (EC). Particularly, atypical EH also known as endometrial intraepithelial neoplasia (EIN), has been proven to be a precursor of EC. Thus, diagnosing different EH (EIN, hyperplasia without atypia (HwA) and NE) and screening EIN from non-EIN are crucial for the health of female reproductive system. Computer-aided-diagnosis (CAD) was used to diagnose endometrial histological images based on machine learning and deep learning. However, these studies perform single-scale image analysis and thus can only characterize partial endometrial features. Empirically, both global (cytological changes relative to background) and local features (gland-to-stromal ratio and lesion dimension) are helpful in identifying endometrial lesions. METHODS: We proposed a global-to-local multi-scale convolutional neural network (G2LNet) to diagnose different EH and to screen EIN in endometrial histological images stained by hematoxylin and eosin (H&E). The G2LNet first used a supervised model in the global part to extract contextual features of endometrial lesions, and simultaneously deployed multi-instance learning in the local part to obtain textural features from multiple image patches. The contextual and textural features were used together to diagnose different endometrial lesions after fusion by a convolutional block attention module. In addition, we visualized the salient regions on both the global image and local images to investigate the interpretability of the model in endometrial diagnosis. RESULTS: In the five-fold cross validation on 7812 H&E images from 467 endometrial specimens, G2LNet achieved an accuracy of 97.01% for EH diagnosis and an area-under-the-curve (AUC) of 0.9902 for EIN screening, significantly higher than state-of-the-arts. In external validation on 1631 H&E images from 135 specimens, G2LNet achieved an accuracy of 95.34% for EH diagnosis, which was comparable to that of a mid-level pathologist (95.71%). Specifically, G2LNet had advantages in diagnosing EIN, while humans performed better in identifying NE and HwA. CONCLUSIONS: The developed G2LNet that integrated both the global (contextual) and local (textural) features may help pathologists diagnose endometrial lesions in clinical practices, especially to improve the accuracy and efficiency of screening for precancerous lesions.