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Aims The present study aims to develop a nano-delivery system that encapsulates berberine (BBR) into PLGA-based nanoparticles (BPL-NPs), to treat ulcerative colitis (UC). Furthermore, the therapeutic efficacy and molecular targeting mechanisms of BPL-NPs in the management of UC are thoroughly examined. Methods Emulsion solvent-driven methods were used to self-assemble BBR and PLGA into nanoparticles, resulting in the development of the nano-delivery system (BPL-NPs). The therapeutic effectiveness of BPL-NPs was evaluated using a dextran sulfate sodium (DSS)-induced model of ulcerative colitis in mice and a lipopolysaccharide (LPS)-induced model of inflammation in THP-1 macrophages. The interaction between Mφs and NCM-460 cells was investigated using a co-culture system. The molecular targeting ability of BPL-NPs in the treatment of UC was validated through in vitro as well as in vivo experiments. Results The BPL-NPs demonstrated a particle size of 184 ± 22.4 nm, enhanced dispersibility in deionized water, and a notable encapsulation efficiency of 31.1 ± 0.2%. The use of BPL-NPs clearly improved the clinical symptoms and pathological changes associated with UC in mice while also ensuring minimal toxicity. In addition, BPL-NPs improved intestinal epithelial cell apoptosis and enhanced the function of the intestinal barrier by inhibiting M1 Mφs infiltration and IL-6 signaling pathway in mice with UC. Furthermore, the BPL-NPs were found to selectively target the IL-6/IL-6R axis during the M1 Mφs-induced apoptosis of NCM460 cells. Conclusion The BPL-NPs were confirmed to harbor anti-inflammatory effects both in vitro and in vivo, along with enhanced water solubility and bioactivity. In addition, the precise targeting of the IL-6/IL-6R axis was confirmed as the mechanism by which the BPL-NPs exerted therapeutic effects in UC, as demonstrated in both in vitro as well as in vivo studies. Graphical Abstract

Anomaly detection in the Controller Area Network (CAN) bus is critical for ensuring the security and reliability of intelligent connected vehicles, which are increasingly prevalent. While existing anomaly detection strategies offer some benefits, they often face challenges such as limited feature extraction and data imbalance, which reduce their effectiveness. To address these issues, in this paper, we propose an unsupervised intrusion detection method based on CAN message graph named CGTS. Specifically, we first construct a message graph based on CAN message sequences. A Graph Transformer is then employed to extract complex structural information, accurately capturing the intrinsic connections between messages. Furthermore, to address the data imbalance problem, we integrate the Support Vector Data Description algorithm after the Graph Transformer model. This algorithm identifies anomalous behaviors efficiently without relying on a priori labels. Experiments conducted on public datasets, including Car-Hacking and CAN-Train-and-Test, demonstrate the efficacy of CGTS. The model achieves an average accuracy exceeding 0.990, precision above 0.995, and an F1-score nearing 0.993. These results highlight CGTS can effectively detect multiple injection attacks and significantly improve the CAN bus intrusion detection performance.

Highlights A catalyst desolvation strategy via phosphorus-modulated Ce single-atom catalysts is proposed to reduce the Li + desolvation barrier and accelerate reaction kinetics. The Ce- f orbital achieves a maximized overlap with the S- p orbital, and this strengthened f - d - p orbital hybridization effectively inhibits the diffusion of polysulfide anions through the interlayer. Synergizing accelerated Li + desolvation with suppressed polysulfide shuttling, the batteries demonstrate ultrastable cycling with an ultralow decay rate of 0.036% per cycle over 1700 cycles. The practical deployment of lithium–sulfur batteries (LSBs) is fundamentally limited by the sluggish stepwise sulfur redox kinetics. However, current design philosophies remain heavily constrained by the conventional “adsorption-catalysis” strategy, often overlooking the crucial rate-limiting kinetic obstacle of the high Li + desolvation energy barrier. This sluggish Li + desolvation process imposes a severe kinetic penalty on polysulfide conversion, thereby depressing electrochemical stability. Herein, we propose a catalyst desolvation strategy utilizing a Ce single-atom catalyst to promote the Li + desolvation process, thereby enhancing the redox conversion of polysulfides. Results indicate that the catalyst desolvation strategy increases the proportion of contact ion pairs and aggregates, reduces the Li + desolvation energy barrier, and stabilizes the lithium anode/electrolyte interface. Consequently, the accelerated Li + desolvation facilitates rapid sulfur redox kinetics, thereby realizing stable cycling in LSBs with a low decay rate of 0.036% per cycle over 1700 cycles at 1 C. This work confirms the significant impact of Li + desolvation and provides a new solution for achieving efficient conversion of polysulfides in LSBs.

Cellular senescence plays a complex, dual role in cancer. Senescent cells induce tumor suppression through cell cycle arrest and immune response activation but also secrete pro‐inflammatory factors via the senescence‐associated secretory phenotype (SASP), which can foster tumor growth, metastasis, and immune evasion. However, the therapeutic potential of targeting senescence mechanisms remains underexplored. This review examines the dual functions of senescent cells in cancer, emphasizing the paradoxical role of the SASP in both promoting tumor progression and modulating immune responses. We explore how SASP factors contribute to tumor growth, metastasis, and immune evasion by reshaping the tumor microenvironment. We then discuss emerging strategies aimed at targeting senescent cells, focusing on approaches for their selective clearance and the modulation of SASP components. These strategies have the potential to enhance the effectiveness of conventional cancer therapies, such as chemotherapy and radiation, by reducing immune‐suppression and improving immune surveillance. Additionally, we delve into the growing interest in SASP‐targeted immunotherapies, which aim to overcome the immunosuppressive effects of senescent cells and boost antitumor immunity. This review emphasizes the importance of targeting senescence and SASP for developing precision‐based cancer therapies, offering new opportunities for next‐generation immunotherapy. Cellular senescence shapes tumor progression through both antitumor and protumor mechanisms. Senescence triggered by telomere shortening restricts malignant transformation and limits tumor cell proliferation, while the senescence‐associated secretory phenotype (SASP) secretion enhances antitumor immunity by activating cytotoxic T cells. Conversely, senescence‐associated epigenetic remodeling can endow normal cells with tumor‐promoting features, and SASP‐driven chronic inflammation remodels the tumor microenvironment to facilitate tumor cell colonization and growth.

Selecting crop varieties with high and stable yields, as well as improving quality and economic benefits, has become a long-term topic while facing the continuous increasing population and the adverse effects of environmental changes [...]

This paper mainly investigates the energy-efficient and secure offloading problem in air-to-ground Mobile Edge Computing (MEC) networks. The proposed efficient offloading mechanism is as per the requirements of the heterogeneous tasks of ground users. Further, the optimizing offloading rate, offloading object, and channel access jointly formulate system energy consumption and eavesdropping rate minimization. A distributed two-stage offloading scheme is proposed for achieving the sub-optimal solution for the Mixed-integer Nonlinear Programming (MINLP) problem. Finally, simulation results demonstrate that the proposed scheme is superior to several benchmark schemes.

Establishing the protein–protein interaction network sheds light on functional genomics studies by providing insights from known counterparts. However, the rice interactome has barely been studied due to the lack of massive, reliable, and cost‐effective methodologies. Here, the development of a barcode‐indexed PCR coupled with HiFi long‐read sequencing pipeline (BIP‐seq) is reported for high throughput Protein Protein Interaction (PPI)identification. BIP‐seq is essentially built on the integration of library versus library Y2H mating strategy to facilitate the efficient acquisition of random PPI colonies, semi‐mechanized dual barcode‐indexed yeast colony PCR for the large‐scale indexed amplification of bait and prey cDNAs, and massive pac‐bio sequencing of PCR amplicon pools. It is demonstrated that BIP‐seq could map over 15 000 high‐confidence (≈62.5% could be verified by Bimolecular fluorescence Complementation (BiFC)) rice PPIs within 2 months, outperforming the other reported methods. In addition, the obtained 23 032 rice PPIs, including 22,665 newly identified PPIs, greatly expanded the current rice PPI dataset, provided a comprehensive overview of the rice PPIs networks, and could be a valuable asset in facilitating functional genomics research in rice. BIP‐seq is developed, a cost‐effective pipeline for high‐throughput protein–protein interaction (PPI) identification using yeast two‐hybrid system. BIP‐seq successfully map over 15 000 high‐confidence rice PPIs (≈62.5% could be verified by BiFC) within 2 months. A rice PPI database (RiPPID) containing 23032 PPIs is established, which greatly enhances the understanding of the interactome in rice.

With the rapid development of automotive technology, the security of in-vehicle networks (IVN) has received increasing attention. The controller area network (CAN), widely used for in-vehicle communication, faces significant security risks due to its inherent vulnerabilities. These risks can lead to attacks, data leakage, and abnormal functioning of vehicle systems. Currently, the mainstream security approach is the intrusion detection system (IDS). Graph-based IDSs have been widely studied for their ability to represent the relationships between CAN messages through nodes and edges, providing an intuitive and structured analysis that enables effective detection of various types of attacks. However, existing graph-based methods rely on basic features, such as the number of nodes, edges, and the maximum degree, which are insufficient for capturing the complex characteristics of spoofing and replay attacks, resulting in suboptimal detection accuracy. To address this, we propose a graph-based decision tree IDS, named GDT-IDS, specifically tailored to the characteristics of spoofing and replay attacks. By analyzing these attack types, we introduce three novel graph-based features—time difference, betweenness centrality, and graph density—that significantly enhance detection accuracy. Moreover, our method can perform multi-class classification, effectively handling mixed attack scenarios. The use of a decision tree model ensures the process remains lightweight and interpretable, making it suitable for resource-constrained systems like vehicles.

CF4 has a global warming potential of 6500 and possesses a lifetime of 50,000 years. In this study, we modified the HZSM-5 catalyst with Ce and sulfuric acid treatment. The S/Ce/HZSM-5 catalyst achieves 41% of CF4 conversion at 500 °C, which is four times higher than that over Ce/HZSM-5, while the HZSM-5 exhibits no catalytic activity. The effects of modification were studied by using NH3-TPD, FT-IR of pyridine adsorption, and XPS methods. The results indicated that the modification, especially the sulfuric acid treatment, strongly increased the Lewis acidic sites, strong acidic sites, and moderate acidic sites on catalysts, which are the main active centers for CF4 decomposition. The mechanism of acidic sites increases by modification and CF4 decomposition is clarified. The results of this work will help the development of more effective catalysts for CF4 decomposition.

Gibberellins (GAs) are diterpenoid phytohormones regulating various aspects of plant growth and development, such as internode elongation and seed germination. Although the GA biosynthesis pathways have been identified, the transcriptional regulatory network of GA homeostasis still remains elusive. Here, we report the functional characterization of a GA-inducible OsABF1 in GA biosynthesis underpinning plant height and seed germination. Overexpression of OsABF1 produced a typical GA-deficient phenotype with semi-dwarf and retarded seed germination. Meanwhile, the phenotypes could be rescued by exogenous GA3, suggesting that OsABF1 is a key regulator of GA homeostasis. OsABF1 could directly suppress the transcription of green revolution gene SD1, thus reducing the endogenous GA level in rice. Moreover, OsABF1 interacts with and transcriptionally antagonizes to the polycomb repression complex component OsEMF2b, whose mutant showed as similar but more severe phenotype to OsABF1 overexpression lines. It is suggested that OsABF1 recruits RRC2-mediated H3K27me3 deposition on the SD1 promoter, thus epigenetically silencing SD1 to maintain the GA homeostasis for growth and seed germination. These findings shed new insight into the functions of OsABF1 and regulatory mechanism underlying GA homeostasis in rice.