Latest ArticlesThe escalation in the incidence of multidrug-resistant Gram-negative bacteria is becoming a pressing global concern. Polymyxin B (PMB), a conventional antibiotic with notable therapeutic efficacy against Gram-negative bacterial infections, serves as a crucial final recourse against carbapenem-resistant Klebsiella pneumoniae (CRKP) infections. Nevertheless, the clinical usage of PMB is impeded by its pronounced nephrotoxicity and poor infection site targeting. This investigation is geared to construct a nanoparticle formulation (named HA-PMB@H) comprising hyaluronic acid (HA) and PMB via a simple Schiff base reaction and further coating HA by electrostatic action. HA-PMB@H shows an average size of (153.8 ± 24.3) nm, and a mean zeta potential of (−25.6 ± 5.2) mV. Additionally, PMB can be released from HA-PMB@H more thoroughly and efficiently at pH 5.5 compared to pH 7.4, which demonstrates the Schiff base modification of PMB paves the way for its release at focus of infection. The uptake ratio of HA-PMB@H by alveolar epithelial cells (RLE-6TN) surpassed that of free PMB devoid of HA, which facilitates to the intracellular sterilization of PMB. Furthermore, the employment of HA-PMB@H ameliorated the toxicity of PMB towards human embryonic kidney cells (HEK 293) and pulmonary microvascular endothelial cells (HULEC-5a). What is more, HA-PMB@H effectively managed severe pneumonia induced by CRKP samples from clinical patients diagnosed with CRKP infection in vivo, substantially enhancing the survival rate of mice. Consequently, this nano-delivery system holds promising clinical significance in the combat against drug-resistant bacterial infections.
In the realm of drug discovery, recent advancements have paved the way for innovative approaches and methodologies. This comprehensive review encapsulates six distinct yet interrelated mini-reviews, each shedding light on novel strategies in drug development. (a) The resurgence of covalent drugs is highlighted, focusing on the targeted covalent inhibitors (TCIs) and their role in enhancing selectivity and affinity. (b) The potential of the quantum mechanics-based computational aid drug design (CADD) tool, Cov_DOX, is introduced for predicting protein-covalent ligand binding structures and affinities. (c) The scaffolding function of proteins is proposed as a new avenue for drug design, with a focus on modulating protein-protein interactions through small molecules and proteolysis targeting chimeras (PROTACs). (d) The concept of pro-PROTACs is explored as a promising strategy for cancer therapy, combining the principles of prodrugs and PROTACs to enhance specificity and reduce toxicity. (e) The design of prodrugs through carbon-carbon bond cleavage is discussed, offering a new perspective for the activation of drugs with limited modifiable functional groups. (f) The targeting of programmed cell death pathways in cancer therapies with small molecules is reviewed, emphasizing the induction of autophagy-dependent cell death, ferroptosis, and cuproptosis. These insights collectively contribute to a deeper understanding of the dynamic landscape of drug discovery.
Charge-neutral method (CNM) is extensively used in investigating the performance of catalysts and the mechanism of N2 electrochemical reduction (NRR). However, disparities remain between the predicted potentials required for NRR by the CNM methods and those observed experimentally, as the CNM method neglects the charge effect from the electrode potential. To address this issue, we employed the constant electrode potential (CEP) method to screen atomic transition metal-N-graphene (M1/N-graphene) as NRR electrocatalysts and systematically investigated the underlying catalytic mechanism. Among eight types of M1/N-graphene (M1 = Mo, W, Fe, Re, Ni, Co, V, Cr), W1/N-graphene emerges as the most promising NRR electrocatalyst with a limiting potential as low as −0.13 V. Additionally, the W1/N-graphene system consistently maintains a positive charge during the reaction due to its Fermi level being higher than that of the electrode. These results better match with the actual circumstances compared to those calculated by conventional CNM method. Thus, our work not only develops a promising electrocatalyst for NRR but also deepens the understanding of the intrinsic electrocatalytic mechanism.
Histopathological analysis of chronic wounds is crucial for clinicians to accurately assess wound healing progress and detect potential malignancy. However, traditional pathological tissue sections require specific staining procedures involving carcinogenic chemicals. This study proposes an interdisciplinary approach merging materials science, medicine, and artificial intelligence (AI) to develop a virtual staining technique and intelligent evaluation model based on deep learning for chronic wound tissue pathology. This innovation aims to enhance clinical diagnosis and treatment by offering personalized AI-driven therapeutic strategies. By establishing a mouse model of chronic wounds and using a series of hydrogel wound dressings, tissue pathology sections were periodically collected for manual staining and healing assessment. We focused on leveraging the pix2pix image translation framework within deep learning networks. Through CNN models implemented in Python using PyTorch, our study involves learning and feature extraction for region segmentation of pathological slides. Comparative analysis between virtual staining and manual staining results, along with healing diagnosis conclusions, aims to optimize AI models. Ultimately, this approach integrates new metrics such as image recognition, quantitative analysis, and digital diagnostics to formulate an intelligent wound assessment model, facilitating smart monitoring and personalized treatment of wounds. In blind evaluation by pathologists, minimal disparities were found between virtual and conventional histologically stained images of murine wound tissue. The evaluation used pathologists' average scores on real stained images as a benchmark. The scores for virtual stained images were 71.1% for cellular features, 75.4% for tissue structures, and 77.8% for overall assessment. Metrics such as PSNR (20.265) and SSIM (0.634) demonstrated our algorithms' superior performance over existing networks. Eight pathological features such as epidermis, hair follicles, and granulation tissue can be accurately identified, and the images were found to be more faithful to the actual tissue feature distribution when compared to manually annotated data.
Thermally activated delayed fluorescence (TADF) materials driven by a through-space charge transfer (TSCT) mechanism have garnered wide interest. However, access of TSCT-TADF molecules with long-wavelength emission remains a formidable challenge. In this study, we introduce a novel V-type D-A-D-A' emitter, Trz-mCzCbCz, by using a carborane scaffold. This design strategically incorporates carbazole (Cz) and 2,4,6-triphenyl-1,3,5-triazine (Trz) as donor and acceptor moieties, respectively. Theoretical calculations alongside experimental validations affirm the typical TSCT-TADF characteristics of this luminogen. Owing to the unique structural and electronic attributes of carboranes, Trz-mCzCbCz exhibits an orange-red emission, markedly diverging from the traditional blue-to-green emissions observed in classical Cz and Trz-based TADF molecules. Moreover, bright emission in aggregates was observed for Trz-mCzCbCz with absolute photoluminescence quantum yield (PLQY) of up to 88.8%. As such, we have successfully fabricated five organic light-emitting diodes (OLEDs) by utilizing Trz-mCzCbCz as the emitting layer. It is important to note that both the reverse intersystem crossing process and the TADF properties are profoundly influenced by host materials. The fabricated OLED devices reached a maximum external quantum efficiency (EQE) of 12.7%, with an emission peak at 592 nm. This represents the highest recorded efficiency for TSCT-TADF OLEDs employing carborane derivatives as emitting layers.
The realization of high-efficiency photocatalysis is greatly meaningful to overcome the issues of current energy and environment, in which the core factor is the exploration of photocatalysts with promising semiconductor properties. The Cu-based metal sulfide photocatalysts of CuSbS2 and its derivative of bournonite CuPbSbS3 possess the features of earth-abundant elements, strong photostability, visible-light range bandgap, and high absorption coefficient, possessing great potential for the realization of efficient photocatalytic applications. Although the photocatalysts of CuSbS2 and CuPbSbS3 have been investigated in photocatalysis application of hydrogen production and degradation, the exploration process is still in the early-development stage. In this review, the design concept and semiconductor properties of CuSbS2 and CuPbSbS3 are firstly introduced. Subsequently, the photocatalytic applications of CuSbS2 and CuPbSbS3 photocatalysts, mainly including hydrogen production and degradation, are systematically reviewed. Finally, the challenges and prospects for the further exploration of CuSbS2 and CuPbSbS3 photocatalysts are provided.
The development of high-performance carbon-based composite hosts plays decisive roles in the electrochemistry of lithium sulfur batteries. Herein, a novel metal-ion induced gelation self-assembly technology is reported to construct sodium alginate carbon (SAC) based polar hierarchical carbon composites with cross-linked network architecture and in-situ co-grown cross-linked polar nanoparticles. Interestingly, it shows high versatility to an extensive array of materials including metals, alloys, and metallic oxides. As a representative, NiCo alloy nanoparticles are chosen to obtain the SAC/NiCo composite host for sulfur in LSBs, which possess superior physical/chemical adsorption capabilities and catalytic conversion kinetics to polysulfide in virtue of synergistic interaction between the hierarchical pore structures and NiCo catalyst. The designed SAC/NiCo-S cathode shows superior electrochemical performance with excellent rate capacity (2 C: 693.5 mAh/g) and enhanced cycling stability (764.3 mAh/g at 0.1 C after 240 cycles). This work provides a straightforward approach for fabricating multifunctional carbon composites with adjustable component for advanced energy storage system.
The bicarbonate-formate (HCO3− – HCO2−) interconversion provides a promising cycle for a conveniently accessible hydrogen storage system via reversible dehydrogenation and hydrogenation processes. Existing catalytic systems often use organic solvents, tedious optimization as well as manipulation of pH values, solvent, pressure and various additives. Herein, we present an operational, robust, safe and cost-effective catalytic system for hydrogen storage and liberation. We have established a unique catalytic system with two different solid organometallic assemblies (NHC-Ru and NHC-Ir) that facilitate the reversible transformation between sodium formate and bicarbonate in aqueous solutions collaboratively and efficiently. Notably, the NHC-Ru catalyst is privileged for the hydrogenation of sodium bicarbonate, whereas the NHC-Ir component enables the dehydrogenation of sodium formate, all in a single reaction vessel. What sets this system apart is its simplicity. The H2 discharging and recharging is simply regulated by heating the mixture with or without H2. Remarkably, this process requires no extra additives or supplementary treatments. Moreover, the reversible hydrogen storage system is durable and can be reused for over 30 cycles without a discernible decline in activity and selectivity. The strategic paradigm in this study shows significant practical potential in hydrogen fuel cell applications.
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