Latest ArticlesMaintaining high metal dispersion of supported metal catalysts to achieve superior reactivity under harsh conditions poses one of the main challenges for their practical applications. Constructing and regulating the strong metal-support interactions (SMSI) by diverse methodologies has emerged as one of the promising approaches to fabricating robust supported metal catalysts. In this study, we report an L-ascorbic acid (AA)-inducing strategy to generate SMSI on a titania-supported gold (Au) catalyst after high-temperature treatment in an inert atmosphere (600 ℃, N2). The AA-induced SMSI can efficiently stabilize Au nanoparticles (NPs) and preserve their catalytic performance. The detailed study reveals that the key to realizing this SMSI is the generation of oxygen vacancies within the TiO2 support induced by the adsorbed AA, which drives the formation of the TiOx permeable layer onto the Au NPs. The strategy could be extended to TiO2-supported Au catalysts with different crystal phases and platinum group metals, such as Pt, Pd, and Rh. This work offers a promising novel route to design stable and efficient supported noble metal catalysts by constructing SMSI using simple reducing organic adsorbent.
Mo2N has been identified as a highly promising carrier for electrocatalysis. However, its complex synthesis method, use of toxic gases, and serious effects on supported noble metals catalyst during high-temperature sintering processes have seriously affected its hydrogen evolution reaction (HER) activity and stability. Here, we report an efficient strategy for synthesizing Mo2N using the high temperature shock (HTS) method in just 1.67 s, while also uniformly loading Ru onto Mo2N nanosheets. The HTS enables the homogeneous dispersion of the noble metal Ru, leading to an increased electrocatalytic activity, along with a strong charge transfer between Mo2N and Ru. Ru/Mo2N exhibited an overpotential of 66 mV at 10 mA/cm2 in 1 mol/L KOH. In the evaluation of catalytic activity, Ru/Mo2N demonstrates superiority over commercial Pt/C catalysts in terms of mass activity (1.71 A/mgRu vs. 0.91 A/mgPt at 200 mV) and turnover frequency (1.41 s−1 vs. 0.18 s−1 at 100 mV). This result provides a rational and effective pathway for the preparation of efficient electrocatalysts.
Prostaglandin E2 (PGE2) serves as the ultimate mediator of fever induced by inflammatory factors. In contrast to cyclooxygenase inhibitors that suppress arachidonic acid metabolism, antipyretic herbs possess a well-established clinical history in effectively managing fever. However, the specific mechanisms underlying their efficacy remain unclear. Following the screening for lead compounds that inhibit PGE2 from antipyretic herbs, alkynylated active molecule probes were designed and synthesized to track and identify potential targets. The target investigation revealed that three antipyretic compounds, namely cinnamaldehyde, 2,4-decadienal, and perillaldehyde, containing α,β-unsaturated aldehyde groups irreversibly targeted the microsomal PGES1-TM4 helix (mPGES1-TM4) at Ser139. This specific interaction effectually inhibited PGE2 production in the cerebral vasculature, leading to exert potent antipyretic effects. α,β-Unsaturated aldehydes targeting mPGES1-TM4 offer a new approach for antipyretic effects with significant potential for various applications.
Established evidence has unveiled two strategies for treating cancer: depleting tumor-associated macrophages (TAMs) and reprogramming M2-like TAMs into an antitumor M1 phenotype. Here, we designed novel pH-sensitive biomimetic hybrid nanovesicles (EDHPA) loaded with doxorubicin (DOX). DOX@EDHPA can specifically target TAMs by activating macrophage-derived exosomes (M1-Exos) and anisamide (AA) as cancer-specific targeting ligands. In vitro and in vivo studies demonstrated that DOX@EDHPA could efficiently be delivered to the tumor site and taken up by cells. Meanwhile, it synergistically enhanced immunogenic cell death (ICD) and induced a subsequent antigen-specific T cell immune response. The tumor inhibitory rate of the DOX@EDHPA group was 1.42 times that of the free DOX group. Further analysis showed that the excellent antitumor effects of DOX@EDHPA should ascribe to the homing effect of M1-Exos on macrophages and the repolarization to antitumor M1 TAMs, which induced the elevated secretion of pro-inflammatory factors. Therefore, the hybrid EDHPA targeting TAMs to reshape the tumor microenvironment constituted a novel immunochemotherapy strategy to inhibit tumor growth.
Acute lung injury (ALI) is a critical respiratory disorder with a high mortality rate and is caused by several factors. Addressing oxidative stress and inflammation is a pivotal strategy for ALI treatment. In this study, we introduced a novel nanotherapeutic approach involving a curcumin-loaded ceria nanoenzyme delivery system tailored to counteract the multifaceted aspects of ALI. This system leverages the individual and combined effects of the components to provide a comprehensive therapeutic solution. The dual-action capability of this nanosystem was manifested by mitigating mitochondrial oxidative stress in lung epithelial cells and inhibiting the transient receptor potential melanosome-associated protein 2 (TRPM2)-NOD-like receptor thermal protein domain associated protein 3 (NLRP3) signaling pathway, offering a highly effective therapeutic approach to ALI. Our findings reveal the underlying mechanisms of this innovative nanodelivery system, showcasing its potential as a versatile strategy for ALI treatment and encouraging further exploration of nanoenzyme-based therapies for ALI.
Sulfates are always promising short-wave ultraviolet (UV) nonlinear optical (NLO) candidates, if their birefringence could be greatly improved. Here, in terms of the insufficient birefringence, the unity of heteroleptic tetrahedral groups and triangular ones was proposed and implemented. Thus, a new semi-organic crystal, [C(NH2)3]S3O6 (G2S3O6), was obtained, which is composed of [S3O6]2− and [C(NH2)3]+ groups. It exhibits excellent optical properties with a short absorption cutoff edge of 218 nm, a strong NLO response of 1.4 × KH2PO4, and more especially, a large birefringence of 0.097@546 nm. This birefringence leap makes the G2S3O6 crystal achieve a phase-matching behavior under a 532 nm laser. Thus, the synergy of [S3O6]2− and [C(NH2)3]+ groups results in excellent optical performances. This finding opens a new horizon for exploring novel UV NLO crystals.
Chitin is an abundant aminopolysaccharide found in insect pests and phytopathogenic microorganisms but absent in higher plants and vertebrates. It is crucial for mitigating threats posed by chitin-containing organisms to human health, food safety, and agriculture. Therefore, targeting the chitin biosynthesis-associated bioprocess holds a promise for developing human-safe and eco-friendly antifungal agents or pesticides. Chitin biosynthesis requires chitin synthase and associated factors, which are involved in the modification, regulation, organization or turnover of chitin during its biosynthesis. A number of enzymes such as chitinases, hexosaminidases, chitin deacetylases are closely related and therefore are promising targets for designing novel agrochemicals that target at chitin biosynthesis. This review summarizes the advances in understanding chitin biology over the past decade by our research group and collaborates, specifically regarding essential proteins linked to chitin biosynthesis that can be exploited as promising pesticide targets. Examples of small bioactive molecules that against the activity of these targets are given.
Gel-based sensors have provided unprecedented opportunities for bioelectric monitoring. Until now, sensors for underwater applicants have remained a notable challenge, as most sensors work effectively in air but swell underwater leading to functional failure. Herein, we introduce an innovative amphibian-inspired high-performance ionogel, where multiple supramolecular interactions in the ionogel's network confer good stretchability, elasticity, conductivity, and the hydrophobic C-F bonds play a key role in diminishing water molecule hydration and provide outstanding environmental stability. These unique properties of ionogels make them suitable as wearable amphibious flexible sensors, and the sensors are capable of highly sensitive and stable human motion monitoring in air and underwater. Integration of the designed sensor into an artificial intelligence drowning alarm system, which recognizes the swimmer's movement status by monitoring the amplitude and frequency, especially in the drowning status for real-time alarms. This work provides novel strategies for motion recognition and hazard monitoring in amphibious environments, meeting the new generation of wearable sensors.
Two dimensional (2D) materials based on boron and carbon have attracted wide attention due to their unique properties. BC compounds have rich active sites and diverse chemical coordination, showing great potential in optoelectronic applications. However, due to the limitation of calculation and experimental conditions, it is still a challenging task to predict new 2D BC monolayer materials. Specifically, we utilized Crystal Diffusion Variational Autoencoder (CDVAE) and pre-trained Materials Graph Neural Network with 3-Body Interactions (M3GNet) model to generate novel and stable BCP materials. Each crystal structure was treated as a high-dimensional vector, where the encoder extracted lattice information and element coordinates, mapping the high-dimensional data into a low-dimensional latent space. The decoder then reconstructed the latent representation back into the original data space. Additionally, our designed attribute predictor network combined the advantages of dilated convolutions and residual connections, effectively increasing the model's receptive field and learning capacity while maintaining relatively low parameter count and computational complexity. By progressively increasing the dilation rate, the model can capture features at different scales. We used the DFT data set of about 1600 BCP monolayer materials to train the diffusion model, and combined with the pre-trained M3GNet model to screen the best candidate structure. Finally, we used DFT calculations to confirm the stability of the candidate structure. The results show that the combination of generative deep learning model and attribute prediction model can help accelerate the discovery and research of new 2D materials, and provide effective methods for exploring the inverse design of new two-dimensional materials.
Diabetes mellitus (DM) is a serious health problem in the world, and infections are common complications in diabetic patients, particularly methicillin-resistant Staphylococcus aureus (MRSA) infections, which substantially increases mortality in patients. In clinical practice, the treatment of diabetic complication-related infections involves multiple issues such as drug resistance when combining antidiabetic drugs with antibiotics. In this study, a series of derivatives were synthesized with alkyl radicals with different chain lengths substituted at the C8 and C12 positions of berberine, with compounds CY1 and CY3 with good antidiabetic and antibacterial activities screened out after identification. Then, oral liposomes (CY1-Lip and CY3-Lip) were prepared, and their particle sizes, stability, and pharmacokinetics were investigated. In acquired mouse models of diabetes, induced with an acute MRSA lung infection, we demonstrate that CY1-Lip and CY3-Lip can effectively reduce levels of fasting blood glucose (FBG), fasting insulin (FINS), and insulin resistance index among diabetic mice with pneumonia, thus exerting their multi-targets effects. Furthermore, both preparations significantly reduced lung MRSA loads and improved lung tissue lesions, reduced high infiltration of M1 macrophages in lung, and suppressed the expression levels of pro-inflammatory factors such as necrosis factor-α (TNF-α) and interleukin-6 (IL-6). This provides new insights into the clinical treatment of diabetes complicated with pulmonary infections.
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