The interaction between organic and inorganic components in metal hybrid perovskites fundamentally determines the intrinsic optoelectronic performance. However, the underlying interaction sites have still remained elusive, especially for those non-hydrogen-bonded hybrid perovskites, thus largely impeding materials precise design with targeted properties. Herein, high pressure is utilized to elucidate the interaction mechanism between organic and inorganic components in the as-synthesized one-dimensional hybrid metal halide (DBU)PbBr₃ (DBU = 1,8-diazabicyclo [5.4.0] undec-7-ene). The interaction sites are identified to be the N from DBU and the Br from inorganic framework by the indicative of enhanced Raman mode under high pressure. The change in interaction strength is indeed derived from the pressure modulation on both distance and spatial arrangement of the nearest Br and N, rather than traditional hydrogen-bonding effect. Furthermore, the enhanced interaction increased charge transfer, resulting in a cyan emission with photoluminescence quantum yields (PLQYs) of 86.6%. The enhanced cyan emission is particularly important for underwater communication due to the much less attenuation in water than at other wavelength emissions. This study provides deep insights into the underlying photophysical mechanism of non-hydrogen-bonded hybrid metal halides and is expected to impart innovative construction with superior performance.

Rheumatoid arthritis (RA) is an autoimmune disease with features of synovial inflammation, cartilage erosion, bone destruction, and pain and is currently lacking a satisfactory treatment strategy. Dihydroartemisinin (DHA), the active metabolite of artemisinin, has exhibited outstanding suppressive effects on RA without obvious side effects. However, the underlying mechanisms remain unclear, which limits its further clinical application. The purpose of this study is to reveal the pharmacodynamic mechanism of DHA against RA by means of a combination of single-cell RNA sequencing (RNA-seq), proteomics, as well as transcriptomics both in vivo and in vitro. In our results, DHA effectively reduced the degree of redness, swelling, and pain in RA rats and dramatically changed the synovial tissue microenvironment under the pathological state. Within this microenvironment, fibroblasts, macrophages, B cells, and endothelial cells were the major affected cell types, primarily through DHA targeting the extracellular matrix (ECM) structural constituent signaling pathway. In addition, we confirmed that DHA regulated the ECM by modulating matrix metalloproteinase 2 (MMP2) and MMP3 in the synovial tissue of RA rats. Moreover, DHA induced apoptosis in MH7A cells, further validating the bioinformatics data. In conclusion, DHA effectively reduced the inflammatory response and improved the immune microenvironment in synovial tissue by inhibiting MMP2 and MMP3. Our findings provide a basis for the application of DHA in the treatment of RA.

Layered structure oxides have emerged as highly promising cathode materials for lithium-ion batteries. In these cathode materials, volume variation related to anisotropic lattice strain during Li⁺ insertion/extraction, however, can induce critical structural instability and electrochemical degradation upon cycling. Despite extensive research efforts, solving the issues of lattice strain and mechanical fatigue remains a challenge. This perspective aims to establish the “structure–property relationship” between the degradation mechanism of the layered oxide cathode due to lattice strain and the structural evolution during cycling. By addressing these issues, we aim to guide the improvement of electrochemical performance, thereby facilitating the widespread adoption of these materials in future high-energy density lithium-ion batteries.

Deep learning relies on learning from extensive data to generate prediction results. This approach may inadvertently capture spurious correlations within the data, leading to models that lack interpretability and robustness. Researchers have developed more profound and stable causal inference methods based on cognitive neuroscience. By replacing the correlation model with a stable and interpretable causal model, it is possible to mitigate the misleading nature of spurious correlations and overcome the limitations of model calculations. In this survey, we provide a comprehensive and structured review of causal inference methods in deep learning. Brain-like inference ideas are discussed from a brain-inspired perspective, and the basic concepts of causal learning are introduced. The article describes the integration of causal inference with traditional deep learning algorithms and illustrates its application to large model tasks as well as specific modalities in deep learning. The current limitations of causal inference and future research directions are discussed. Moreover, the commonly used benchmark datasets and the corresponding download links are summarized.

Dental, oral, and craniofacial diseases can substantially impact the quality of human life, thereby posing a serious public health concern. Although conventional therapies such as surgery have solved these problems largely, the prognosis of patients is not always satisfactory. Cell membrane-coated nanoparticles (CMCNPs) carry nanodrugs with the help of natural cell membranes, therefore utilizing their remarkable ability to interface and interact with their surrounding environment. These nanoparticles have demonstrated substantial advantages in drug targeting, prolonging blood circulation time, penetrating biofilms, and immune escape. With the assistance of CMCNPs, the therapeutic effects of dental, oral, and craniofacial diseases can reach a higher level. CMCNPs have been applied for dental, oral, and craniofacial diseases for various conditions such as head and neck cancer, periodontal disease, and oral biosignal detection. For the therapies of head and neck cancer, CMCNPs have been widely utilized as a tool of chemotherapy, phototherapy, and immunotherapy, while yet to be exploited in imaging technique. In the end, we summarized the challenges and prospectives of CMCNPs for dental, oral, and craniofacial diseases: large-scale production with uniform standards and high quantity, extensive application directions in dental, oral, and craniofacial regions (implant, endodontics), and the promotion of its clinical application.

Rational regulation of reactive oxygen species (ROS) plays a vital importance in maintaining homeostasis of living biological systems. For ROS-related pathologies, chemotherapy technology derived from metal nanomaterials currently occupies a pivotal position. However, they suffer from inherent issues such as complicated synthesis, batch-to-batch variability, high cost, and potential biological toxicity caused by metal elements. Here, we reported for the first time that dual-action 3,5-dihydroxy-1-ketonaphthalene-structured small-molecule enzyme imitator (DHKNase) exhibited 2-edged ROS regulation, catering to the execution of physiology-beneficial ROS destiny among diverse pathologies in living systems. Based on this, DHKNase is validated to enable remarkable therapeutic effects in 2 classic disease models, including the pathogen-infected wound-healing model and the dextran sulfate sodium (DSS)-caused inflammatory bowel disease (IBD). This work provides a guiding landmark for developing novel natural small-molecule enzyme imitator and significantly expands their application potential in the biomedical field.

Microneedles have shown considerable potential in treating ocular diseases, yet enhancing their architecture and functionality to improve therapeutic efficacy poses marked challenges. Here, inspired by the antioxidant strategy of blueberries and the wet adhesive mechanism of clingfish, we construct hierarchical and multifunctional microneedles. These microneedles possess both wet adhesive and antioxidant properties, making them highly effective for ocular wound healing. Constructed using polyacrylic acid-N-hydroxysuccinimide-based hydrogel with hexagonal structures, these generated microneedles ensure strong adhesion in wet environments. Furthermore, by incorporating proanthocyanidins (pAc) into the tips, the microneedle is imparted with excellent competence to scavenge reactive oxygen species (ROS). In the rat model of ocular alkali burns, the designed microneedle not only exhibited robust adhesion and desirable antioxidant properties in the moist ocular environment but also facilitated sustained drug release and effective treatment. These results suggest that our bioinspired microneedles with multifunctional properties offer substantial advancement over conventional approaches, positioning them as promising candidates for versatile wound healing applications.

Hydrogels have emerged as appealing prospects for wound healing due to their superior biocompatible qualities. However, the integration of antibacterial active substances into hydrogels for effective wound repair remains challenging. Here, we present a novel double-network hydrogel for nasal mucosal injury repair with antibacterial and self-healing capabilities. This hydrogel is the result of mixing aldehyde polyethylene glycol (PEG) and a carboxymethyl chitosan (CMCS)-based hydrogel with a photocured methylacrylate gelatin (GelMA) hydrogel to envelop mesenchymal stem cell exosomes (MSC-Exos). CMCS is rich in amino groups and facilitates antibacterial repair. Given the dynamically reversible Schiff base connections between the amino group of chitosan and the aldehyde group of modified PEG, the hydrogel can be easily injected into the lesion site because of its excellent injection and shear thinning properties. GelMA introduces an additional network layer for the hydrogel, which enhances its strength and extends the duration of stem cell exosomes on the wound surface. On the basis of these characteristics, we provide evidence that this compound hydrogel can substantially increase cell proliferation and regeneration, inhibit scar hyperplasia, and stimulate angiogenesis in rabbit nasal septum mucosa trauma models. These results suggest that MSC exosome-loaded hydrogels (ME-Gel) have substantial clinical potential for the repair and regeneration of nasal mucosa after surgery or trauma.

Understanding protein corona composition is essential for evaluating their potential applications in biomedicine. Relative protein abundance (RPA), accounting for the total proteins in the corona, is an important parameter for describing the protein corona. For the first time, we comprehensively predicted the RPA of multiple proteins on the protein corona. First, we used multiple machine learning algorithms to predict whether a protein adsorbs to a nanoparticle, which is dichotomous prediction. Then, we selected the top 3 performing machine learning algorithms in dichotomous prediction to predict the specific value of RPA, which is regression prediction. Meanwhile, we analyzed the advantages and disadvantages of different machine learning algorithms for RPA prediction through interpretable analysis. Finally, we mined important features about the RPA prediction, which provided effective suggestions for the preliminary design of protein corona. The service for the prediction of RPA is available at http://www.bioai-lab.com/PC_ML.

This review comprehensively covers recent developments of cyclodextrin-mediated chemical transformations for green chemistry. These cyclic oligomers of glucose are nontoxic, eco-friendly, and recyclable to accomplish eminent functions in water. Their most important feature is to form inclusion complexes with reactants, intermediates, and/or catalysts. As a result, their cavities serve as sterically restricted and apolar reaction fields to promote the efficiency and selectivity of reactions. Furthermore, unstable reagents and intermediates are protected from undesired side reactions. The scope of their applications has been further widened through covalent or noncovalent modifications. Combinations of them with metal catalysis are especially successful. In terms of these effects, various chemical reactions are achieved with high selectivity and yield so that valuable chemicals are synthesized from multiple components in one-pot reactions. Furthermore, cyclodextrin units are orderly assembled in oligomers and polymers to show their cooperation for advanced properties. Recently, cyclodextrin-based metal–organic frameworks and polyoxometalate–cyclodextrin frameworks have been fabricated and employed for unique applications. Cyclodextrins fulfill many requirements for green chemistry and should make enormous contributions to this growing field.