The presence of Hg²⁺ causes substantial stress to plants, adversely affecting growth and health by disrupting cell cycle divisions, photosynthesis, and ionic homeostasis. Accurate visualization of the spatiotemporal distribution of Hg²⁺ in plant tissues is crucial for the management of Hg pollution; however, the related research is still at its early stage. Herein, a small-molecule amphiphilic fluorescent probe (termed LJTP2) was developed for the specific detection of Hg²⁺ with a high sensitivity ~(16 nM). Fluorescent imaging applications with LJTP2 not only detected the dynamic distribution of Hg²⁺ within plant cells at the subcellular level but also enabled the understanding of cell membrane health under Hg²⁺ stress. This study introduces a valuable imaging tool for elucidating the molecular mechanism of Hg²⁺ stress in plants, demonstrating the potential of the application of small-molecule fluorescent probes in plant science.

After years of research and development, flexible sensors are gradually evolving from the traditional “electronic” paradigm to the “ionic” dimension. Smart flexible sensors derived from the concept of ion transport are gradually emerging in the flexible electronics. In particular, ionic hydrogels have increasingly become the focus of research on flexible sensors as a result of their tunable conductivity, flexibility, biocompatibility, and self-healable capabilities. Nevertheless, the majority of existing sensors based on ionic hydrogels still mainly rely on external power sources, which greatly restrict the dexterity and convenience of their applications. Advances in energy harvesting technologies offer substantial potential toward engineering self-powered sensors. This article reviews in detail the self-powered mechanisms of ionic hydrogel self-powered sensors (IHSSs), including piezoelectric, triboelectric, ionic diode, moist-electric, thermoelectric, potentiometric transduction, and hybrid modes. At the same time, structural engineering related to device and material characteristics is discussed. Additionally, the relevant applications of IHSS toward wearable electronics, human–machine interaction, environmental monitoring, and medical diagnostics are further reviewed. Lastly, the challenges and prospective advancement of IHSS are outlined.

Allergen-specific immunotherapy (AIT) is the only treatment that addresses the root cause of immunoglobulin E (IgE)-mediated allergies, but conventional methods face challenges with treatment duration, patient compliance, and adverse effects. In this study, we propose intratonsillar immunotherapy (ITIT) as a new effective and safer route for AIT. Prior to clinical trials, we analyzed tonsil samples from human subjects to assess immune responses, measuring interleukin-4 (IL-4), IL-21, total IgE (tIgE), and allergen-specific IgE concentrations using ELISA and BioIC. Our results indicated that tonsils contained higher levels of allergen-specific IgE compared to peripheral blood. In the clinical phase, 120 allergic rhinitis (AR) patients were treated with either 3 intratonsillar allergen injections over 2 months or conventional subcutaneous immunotherapy (SCIT) over 1 year. ITIT demonstrated superior and faster symptom relief, especially in younger patients, while requiring markedly fewer doses and injections than SCIT. Immunological analysis revealed reduced eosinophil counts, increased regulatory T (T_reg) and follicular regulatory T (T_FR) cell levels, and a favorable shift in cytokine profiles. Adverse events were minimal, and the treatment showed high patient compliance. These findings suggest that ITIT could provide an effective, safer, and more convenient alternative to AIT.

Transfer RNA-derived small RNAs, a recently identified class of small noncoding RNAs, play a crucial role in regulating gene expression and are implicated in cerebrovascular diseases. However, the specific biological roles and mechanisms of transfer RNA-derived small RNAs in intracranial aneurysms (IAs) remain unclear. In this study, we identified that the transfer RNA-Asp-GTC derived fragment (tRF-AspGTC) is highly expressed in the IA tissues of both humans and mice. tRF-AspGTC promotes IA formation by facilitating the phenotypic switching of vascular smooth muscle cells, increasing of matrix metalloproteinase 9 expression, and inducing of oxidative stress and inflammatory responses. Mechanistically, tRF-AspGTC binds to galectin-3, inhibiting tripartite motif 29-mediated ubiquitination and stabilizing galectin-3. This stabilization activates the toll-like receptor 4/MyD88/nuclear factor kappa B pathway, further driving phenotypic switching and inflammation. Clinically, circulating exosomal tRF-AspGTC demonstrates strong diagnostic efficacy for IAs and is identified as an independent risk factor for IA occurrence. These findings highlight the potential of tRF-AspGTC as a promising diagnostic biomarker and therapeutic target for IAs.

Autonomous vehicles with self-evolution capabilities are expected to improve their performance through learning algorithms, to automatically adapt to the external environment. However, due to the infinity, complexity, and variability of the actual traffic environment, it is necessary to develop quantitative representation indicators of scenario difficulty and generate targeted scenarios to ensure the evolution gradually, so as to quickly approach the performance limit of the algorithm. Therefore, this paper proposes a data-driven quantitative representation method of scenario difficulty. Specifically, the concept of environment agent is proposed, and a reinforcement learning method combined with mechanism knowledge is constructed for policy search to obtain an agent with an adversarial behavior. The model parameters of the environment agent at different stages in the training process are extracted to construct a policy group, and then agents with different adversarial intensities are obtained, which are used to realize data generation in different difficulty scenarios through the simulation environment. Finally, a data-driven scenario difficulty quantitative representation model is constructed, which is used to output the environment agent policy under different difficulties. Experimental results show the effectiveness of the proposed method. The result analysis shows that the proposed algorithm can generate reasonable and interpretable scenarios with high discrimination and can provide quantifiable difficulty representation without any expert logic rule design. Compared with the rule-based discrete scenario difficulty representation method, the proposed algorithm can achieve continuous difficulty representation. The video link is https://www.youtube.com/watch?v=GceGdqAm9Ys.

Drug resistance to a single agent is common in cancer-targeted therapies, and rational drug combinations are a promising approach to overcome this challenge. Many Food and Drug Administration-approved drugs can induce cellular senescence, which possesses unique vulnerabilities and molecular signatures. However, there is limited analysis on the effect of the combination of cellular-senescence-inducing drugs and targeted therapy drugs. Here, we conducted a comprehensive evaluation of cellular senescence using 7 senescence-associated gene sets. We quantified the cellular senescence states of ~10,000 tumor samples from The Cancer Genome Atlas and examined their associations with targeted drug responses. Our analysis revealed that tumors with higher cellular senescence scores exhibited increased sensitivity to targeted drugs. As a proof of concept, we experimentally confirmed that etoposide-induced senescence sensitized lung cancer cells to 2 widely used targeted drugs, erlotinib and dasatinib. Furthermore, we identified multiple genes whose dependencies were associated with senescence status across ~1,000 cancer cell lines, suggesting that cellular senescence generates unique vulnerabilities for therapeutic exploitation. Our study provides a comprehensive overview of drug response related to cellular senescence and highlights the potential of combining senescence-inducing agents with targeted therapies to improve treatment outcomes in lung cancer, revealing novel applications of cellular senescence in targeted cancer therapies.

Immune recognition and activation by the peptide-laden major histocompatibility complex–T cell receptor (TCR)–CD3 complex is essential for anti-tumor immunity. Tumors may escape immune surveillance by dissembling the complex. Here, we report that transferrin, which is overexpressed in patients with liver metastasis, disassociates TCR from the CD3 signaling apparatus by targeting the constant domain (CD) of T cell receptor α (TCRα), consequently suppresses T cell activation, and inhibits anti-metastatic and anti-tumor immunity. In mouse models of melanoma and lymphoma, transferrin overexpression exacerbates liver metastasis, while its knockdown, antibody, designed peptides, and CD mutation interfering with transferrin–TCRα interaction inhibit metastasis. This work reveals a novel strategy of tumor evasion of immune surveillance by blocking the coupling between TCRs and the CD3 signaling apparatus to suppress TCR activation. Given the conservation of CD and transferrin up-regulation in metastatic tumors, the strategy might be a common metastatic mechanism. Targeting transferrin–TCRα holds promise for anti-metastatic treatment.

The engineering design and construction of active interfaces represents a promising approach amidst numerous initiatives aimed at augmenting catalytic activity. Herein, we present a novel approach to incorporate interconnected pores within bulk single crystals for the synthesis of macroscopic porous single-crystalline rutile titanium oxide (R-TiO₂). The porous single crystal (PSC) R-TiO₂ couples a nanocrystalline framework as the solid phase with pores as the fluid phase within its structure, providing unique advantages in localized structure construction and in the field of catalysis. We successfully construct well-defined Ni cluster/TiO₂ active interfaces by directly confining Ni clusters on the continuous lattice surface of PSC R-TiO₂. We confirm that the lattice oxygen connected to the Ni clusters exhibits exceptional activation capability at temperatures close to room temperature compared to the pure phase PSC R-TiO₂ monoliths. The PSC Ni/TiO₂ catalyst demonstrates complete CO oxidation and stable catalytic performance during continuous operation in air at ~80 °C for 200 h.

The optoelectronic memristor integrates the multifunctionalities of image sensing, storage, and processing, which has been considered as the leading candidate to construct novel neuromorphic visual system. In particular, memristive materials with all-optical modulation and complementary metal oxide semiconductor (CMOS) compatibility are highly desired for energy-efficient image perception. As a p-type oxide material, Cu₂O exhibits outstanding theoretical photoelectric conversion efficiency and broadband photoresponse. In this work, an all-optically controlled memristor based on the Cu₂O/TiO₂/sodium alginate nanocomposite film is developed. Optical potentiation and depression behaviors have been implemented by utilizing visible (680 nm) and ultraviolet (350 nm) light. Furthermore, a 7 × 9 optoelectronic memristive array with satisfactory device variation and environment stability is constructed to emulate the image preprocessing function in biological retina. The random noise can be reduced effectively by utilizing bidirectional optical input. Beneficial from the image preprocessing function, the accuracy of handwritten digit classification increases more than 60%. Our work presents a pathway toward high-efficient neuromorphic visual system and promotes the development of artificial intelligence technology.

Hyperglycemia and bacterial colonization in diabetic wounds aberrantly activate Nod-like receptor protein 3 (NLRP3) in macrophages, resulting in extensive inflammatory infiltration and impaired wound healing. Targeted suppression of the NLRP3 inflammasome shows promise in reducing macrophage inflammatory disruptions. However, challenges such as drug off-target effects and degradation via lysosomal capture remain during treatment. In this study, engineered apoptotic bodies (BHB-dABs) derived from adipose stem cells loaded with β-hydroxybutyric acid (BHB) were synthesized via biosynthesis. These vesicles target M1-type macrophages, which highly express the folic acid receptor in the inflammatory microenvironment, and facilitate lysosomal escape through 1,2-distearoyl-sn-propyltriyl-3-phosphatidylethanolamine–polyethylene glycol functionalization, which may enhance the efficacy of NLRP3 inhibition for managing diabetic wounds. In vitro studies demonstrated the biocompatibility of BHB-dABs, their selective targeting of M1-type macrophages, and their ability to release BHB within the inflammatory microenvironment via folic acid and folic acid receptor signaling. These nanovesicles exhibited lysosomal escape, anti-inflammatory, mitochondrial protection, and endothelial cell vascularization properties. In vivo experiments demonstrated that BHB-dABs enhance the recovery of diabetic wound inflammation and angiogenesis, accelerating wound healing. These functionalized apoptotic bodies efficiently deliver NLRP3 inflammasome inhibitors using a dual strategy of targeting macrophages and promoting lysosomal escape. This approach represents a novel therapeutic strategy for effectively treating chronic diabetic wounds.