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The strong metal-support interaction (SMSI) has long been studied in heterogonous catalysis on account of its importance in stabilizing active metals and tuning catalytic performance. As a dynamic process taking place at the metal-support interface, the SMSI is closely related to the metal surface properties which are usually affected by the size of metal nanoparticles (NPs). In this work we report the discovery of a size effect on classical SMSI in Au/TiO 2 catalyst where larger Au particles are more prone to be encapsulated than smaller ones. A thermodynamic equilibrium model was established to describe this phenomenon. According to this finding, the catalytic performance of Au/TiO 2 catalyst with uneven size distribution can be improved by selectively encapsulating the large Au NPs in a hydrogenation reaction. This work not only brings in-depth understanding of the SMSI phenomenon and its formation mechanism, but also provides an alternative approach to refine catalyst performance. Strong metal-support interaction (SMSI) is critical in determining the catalytic performance of supported metal catalysts. Here the authors report a phenomenon of size-dependent classical SMSI in Au/TiO 2 catalyst where larger Au particles are more prone to be encapsulated than smaller ones.

Semi-hydrogenation of acetylene in excess ethylene is a key industrial process for ethylene purification. Supported Pd catalysts have attracted most attention due to their superior intrinsic activity but often suffer from low selectivity. Pd single-atom catalysts (SACs) are promising to significantly improve the selectivity, but the activity needs to be improved and the feasible preparation of Pd SACs remains a grand challenge. Here, we report a simple strategy to construct Pd 1 /TiO 2 SACs by selectively encapsulating the co-existed small amount of Pd nanoclusters/nanoparticles based on their different strong metal-support interaction (SMSI) occurrence conditions. In addition, photo-thermo catalysis has been applied to this process where a much-improved catalytic activity was obtained. Detailed characterization combined with DFT calculation suggests that photo-induced electrons transferred from TiO 2 to the adjacent Pd atoms facilitate the activation of acetylene. This work offers an opportunity to develop highly stable Pd SACs for efficient catalytic semi-hydrogenation process. Semi-hydrogenation of acetylene in excess ethylene is a key industrial process for ethylene purification. Here the authors develop highly stable Pd1/TiO2 single-atom catalyst for photo-thermo semi-hydrogenation of acetylene.

Metal-support interaction predominately determines the electronic structure of metal atoms in single-atom catalysts (SACs), largely affecting their catalytic performance. However, directly tuning the metal-support interaction in oxide supported SACs remains challenging. Here, we report a new strategy to subtly regulate the strong covalent metal-support interaction (CMSI) of Pt/CoFe 2 O 4 SACs by a simple water soaking treatment. Detailed studies reveal that the CMSI is weakened by the bonding of H + , generated from water dissociation, onto the interface of Pt-O-Fe, resulting in reduced charge transfer from metal to support and leading to an increase of C-H bond activation in CH 4 combustion by more than 50 folds. This strategy is general and can be extended to other CMSI-existed metal-supported catalysts, providing a powerful tool to modulating the catalytic performance of SACs. A simple water soaking treatment significantly weakened the strong covalent metal-support interaction between the atomically dispersed Pt and CoFe 2 O 4 , which leads to an enhanced activity towards methane combustions by 55 times. This work highlights the critical role of altering the coordination structure of single-atom active sites and provides a new strategy to modulate metal-support interaction regulation.

In this paper, we establish an energy conservation criterion via a combination of the velocity and the gradient of velocity for both the Cauchy and Dirichlet problems of 3D incompressible Navier–Stokes equations, which covers the classical result of Lions (Rend Semin Mat Univ Padova 30:16–23, 1960) and Shinbrot (SIAM J Math Anal 5:948–954, 1974) and recent results in Berselli and Chiodaroli (Nonlinear Anal 192:111704, 2020) and Zhang (J Math Anal Appl 480:9, 2019). The parallel result also holds for the weak solutions of the generalized Newtonian equations, which immediately entails the latest corresponding progress in Beirao da Veiga and Yang (Nonlinear Anal 185:388–402, 2019), Yang (Appl Math Lett 88:216–221, 2019) and Berselli and Chiodaroli (2020) and particularly derives several new sufficient conditions keeping energy equality.

Molecular imprinting technology is widely used for the specific identification of compounds, but the selective recognition mechanisms of the same compounds still need to be further studied. Based on differences in hydrogen bond size and orientation, molecularly imprinted polymers (MIPs) were designed to adsorb flavonols with the same parent core and different hydroxyl groups. A surface-imprinted material was designed with silicon dioxide as the carrier, myricetin as the template molecule, and methacrylic acid (MAA) as the functional monomer. Scanning electron microscopy (SEM), Brunauer–Emmett–Teller surface area (BET) analyses, Fourier-transform infrared spectroscopy (FT-IR), and other characterization experiments were carried out. The intrinsic mechanism of the MIPs was also explored. The MIPs showed good adsorption of myricetin and other flavonoids through hydrogen bonding and steric hindrance. The adsorption capacity was 3.12–9.04 mg/g, and the imprinting factor was 1.78–3.37. Flavonoids with different hydroxyl groups in different numbers and directions had different hydrogen bond strengths with functional monomers. R2, R4, and R1 on 2-phenylchromogenone had stronger electronegativity, and the hydroxyl group was also more likely to form and have stronger hydrogen bonds. The hydroxyl negativity and the degree of steric hindrance of flavonoids played a major role in the recognition of molecularly imprinted materials. This study is of great significance for the synthesis of and selection of templates for analogous molecular imprinting materials.

Bovine alphaherpesvirus 1 (BoAHV-1) is a promising oncolytic virus that can infect the human lung carcinoma cell line A549. In an effort to adapt the virus to grow more rapidly in these cells through the serial passaging of viral progeny, we were unsuccessful. Here, we found that extracellular vesicles (EVs) secreted by BoAHV-1-infected A549 cells (referred to as EDVs) contain 59 viral proteins, including both viral structure proteins (such as gC and gD) and viral regulatory proteins (such as bICP4 and bICP22), as identified via a proteomic analysis. These EDVs can bind to and enter target cells, inhibit viral particles binding to cells, and stimulate the production of IFN-α and IFN-β in A549 cells. When EDVs are inoculated into rabbits via either the conjunctival sacs or intravenously, they can be readily detected in neurons within the trigeminal ganglia (TG), where they reduce viral replication and promote the transcription of IFN-γ. Furthermore, incorporation of the known anti-herpesvirus drug Acyclovir (ACY) into the EDVs leads to synergistically enhanced antiviral efficacy. Collectively, the EDVs exhibit antiviral effects by blocking viral binding to target cells and stimulating the innate immune response, thereby leading to the failure of the serial passaging of viral progeny in these cells, and these EDVs may serve as a promising vector for delivering drugs targeting TG tissues for antiviral purposes.

The main objective of this study was to develop novel BSA nanoparticles (BSA NPs) for improving the bioavailability of curcumin as an anticancer drug, and those BSA NPs were galactosylated for forming the curcumin-loaded galactosylated BSA nanoparticles (Gal-BSA-Cur NPs), thus enhancing their ability to target asialoglycoprotein receptor (ASGPR) overexpressed on hepatocellular carcinoma (HCC) cells. Gal-BSA-Cur NPs were prepared by the desolvation method and showed a spherical shape and well distribution with the average particle size of 116.24 nm. In vitro drug release assay exhibited that Gal-BSA-Cur NPs had higher release rates and improved the curcumin solubility. Cell uptake studies confirmed that Gal-BSA-Cur NPs could selectively recognize receptors on the surface of HCC (HepG2) cells and improve internalization ability of drug compared with BSA NPs-loaded curcumin (BSA-Cur NPs), which might be due to high affinity to galactose. Further, the effects of Gal-BSA-Cur NPs were evaluated by cytotoxicity assay, crystal violet assay, cell apoptosis assay, and wound healing assay, respectively, which revealed that Gal-BSA-Cur NPs could inhibit HepG2 cells proliferation, induce cell apoptosis, and inhibit cell migration. Immunofluorescence staining has proved that the effects of Gal-BSA-Cur NPs related to the suppression of the nuclear factor κB-p65 (NF-κB-p65) expression in HepG2 cell nucleus. Therefore, these results indicate that novel Gal-BSA-Cur NPs are potential candidates for targeted curcumin delivery to HCC cells.

Enhancing drug accumulation in target organs while minimizing adverse effects is critical for pharmacological therapies. Therefore, the development of advanced drug-targeting platforms is essential for clinical application. These systems must not only enable precise organ-specific targeting but also improve drug bioavailability and extend systemic circulation. In recent years, significant progress has been made in blood cell-inspired drug delivery strategies, with red blood cells-based (RBCs-based) platforms showing particular promise due to their inherent physiological advantages. Nevertheless, the development of organ-specific RBCs-mediated delivery systems remains challenging. We categorize and summarize various drug loading methods for existing RBCs, along with their advantages, disadvantages, and treated disease types. We then focus on describing various design strategies of RBCs-based delivery systems targeting specific organs and review their current applications. Additionally, we discuss current challenges and future perspectives regarding RBCs-based targeted delivery platforms.

Chronic obstructive pulmonary disease (COPD) is a complex respiratory disorder driven by genetic, environmental, and metabolic factors. This study aims to elucidate the causal role of metabolites in COPD pathogenesis and identify novel therapeutic targets through a multi-omics approach coupled with experimental validation. We performed two-sample Mendelian randomization (MR) on 1,400 metabolites using genetic data from European-ancestry cohorts. Causal candidates were refined using stringent conditional colocalization (SuSiE, PP4 > 0.8) to exclude pleiotropic confounders. Pathway enrichment and protein-protein interaction (PPI) analyses were conducted to identify key mechanisms. Findings were validated in external transcriptomic datasets (GEO) and an in vitro COPD model using cigarette smoke extract (CSE)-induced human bronchial epithelial cells (BEAS-2B/16HBE). The regulatory effects of the COPD drug Salbutamol on the identified metabolic targets were assessed via qRT-PCR and Western Blot. Initial MR identified six COPD-associated metabolites, but stringent colocalization confirmed a shared causal etiology for only two: Carnitine C14 and 3-hydroxyoleoylcarnitine. The remaining candidates were excluded due to confounding (high PP3). Pathway analysis highlighted fatty acid metabolism, implicating the rate-limiting enzymes ACACA and ACACB. Transcriptomic validation in human tissues confirmed the upregulation of ACACA/ACACB and downregulation of ADRB2 in COPD. In in vitro experiments, CSE exposure inhibited the phosphorylation of ACACA, promoting metabolic dysregulation. Crucially, Salbutamol treatment restored ACACA phosphorylation via the ADRB2 signaling axis, reversing the lipid metabolic dysregulation. This study identifies Carnitine C14 and 3-hydroxyoleoylcarnitine as robust causal biomarkers for COPD. We experimentally demonstrated that the bronchodilator Salbutamol exerts a non-canonical therapeutic effect by restoring fatty acid metabolic homeostasis through the ADRB2-ACACA axis. These findings propose a novel metabolic mechanism for existing therapies and highlight lipid metabolism as a promising target for intervention.

Neurosyphilis presents significant diagnostic and therapeutic challenges due to its heterogeneous clinical manifestations, absence of a gold-standard diagnostic criterion, and variable treatment responses. This study aims to identify clinically homogeneous subtypes of suspected neurosyphilis patients and develop a machine learning-based subtyping model to support clinical decision-making. Data from 451 suspected neurosyphilis patients were retrospectively collected from West China Hospital of Sichuan University. Patients were divided into a model development cohort (n=369) and an external validation cohort (n=82) by time. Latent class analysis (LCA) was performed to identify subtypes, with the optimal class number determined by model fit indicators. Key predictive variables were selected using LASSO regression and Boruta algorithm. Six machine learning algorithms were employed to build LCA subtype prediction models. Feature importance was interpreted via SHAP analysis, and model generalizability was assessed using the external cohort. LCA classified patients into three homogeneous subtypes: \"typical neurosyphilis\" (43.7%; predominantly male, high serum TRUST titer, significant CSF abnormalities, and robust intrathecal immune activation), \"atypical neurosyphilis\" (17.9%; absence of elevated CSF protein, mild intrathecal IgG synthesis), \"non-neurosyphilis\" (38.5%; normal CSF parameters). Six variables (age, serum TRUST titer, CSF protein, CSF nucleated cells, IgG index, CSF TTs) were used for model construction. The XGBoost model demonstrated optimal performance, achieving an AUC of 0.966 (accuracy: 87.3%) on the internal test set and 0.970 (accuracy: 91.5%) on the external validation set. Key predictors included CSF nucleated cells, CSF TTs, and IgG index. This study defines three clinically meaningful latent subtypes of neurosyphilis. The developed XGBoost model effectively discriminates between these subtypes of neurosyphilis and non-neurosyphilis in clinical settings, facilitating timely diagnosis and treatment.