Photodynamic therapy (PDT) is a clinically approved therapeutic modality that uses photosensitizers (PSs) to generate reactive oxygen species (ROS) upon light irradiation, enabling disease treatment with minimal invasiveness and excellent spatiotemporal precision. Despite these advantages, conventional PDT is fundamentally constrained by the mismatch between its oxygen dependence and the intrinsically hypoxic tumor microenvironment, which markedly compromises therapeutic outcomes. In this context, type I PSs offer a promising solution because they can produce cytotoxic radicals through electron transfer pathways, thereby reducing dependence on oxygen (O₂) and improving efficacy under hypoxic conditions. Organic framework materials have recently emerged as powerful and versatile platforms for constructing type I PSs, owing to their programmable structures, high porosity, and efficient photoinduced charge separation and electron transfer. Importantly, the modular nature of these frameworks enables rational tuning of both structural motifs and compositional building blocks, allowing systematic regulation of light absorption, redox properties, and ROS generation pathways to maximize type I PDT performance. Moreover, organic frameworks can simultaneously function as nanocarriers for therapeutics, facilitating co-delivery and synergistic combinations (e.g., chemotherapy, immunotherapy, or catalytic therapies) that may achieve more durable and comprehensive tumor control. However, current studies remain fragmented, and there is still a lack of an integrated and mechanistically grounded overview that connects framework design principles with type I ROS generation mechanisms and performance optimization strategies. To address this unmet need, this review provides a comprehensive summary of the design strategies, mechanistic insights, and recent progress in organic framework-based type I PSs. We first outline the fundamental principles of type I photochemistry and the key physical and chemical processes underlying type I PDT. We then highlight rational design and modulation strategies to enhance optical properties, promote charge separation, and strengthen oxygen independence. Next, we summarize representative in vivo/in vitro disease models to demonstrate emerging diagnostic and therapeutic applications. Finally, we discuss current challenges and future opportunities for clinical translation, offering practical guidance for the development of next-generation phototherapeutic agents based on these innovative framework systems.

Chemotherapy-induced gastrointestinal toxicity, particularly intestinal barrier disruption and diarrhea, is a major dose-limiting adverse effect with unclear mechanisms. Here, we identify magnesium isoglycyrrhizinate (MIG) as a novel therapeutic agent that ameliorates 5-fluorouracil (5-FU)- and irinotecan-induced intestinal injury by enhancing epithelial barrier integrity. Using MIG as a molecular probe, we revealed a pathogenic mechanism underlying chemotherapy-induced barrier damage. Integrated chemoproteomics (limited proteolysis–mass spectrometry and thermal proteome profiling) analyses revealed direct binding of MIG to the RNA helicase DDX5 (DEAD-box helicase 5), whose expression is markedly increased upon 5-FU-induced injury. Mechanistically, DDX5 destabilizes the G-quadruplex (G4) structure in the CTNNB1 (β-catenin) 5′ untranslated region, suppressing β-catenin production and compromising barrier function. Crucially, MIG acts as a novel DDX5 inhibitor that blocks G4 unwinding, thereby restoring β-catenin expression and barrier integrity in a dose-dependent manner. In vivo, MIG outperforms the canonical DDX5 inhibitor supinoxin in mitigating intestinal damage. Taken together, the results of our study not only establish MIG as a promising therapeutic candidate but also delineate the DDX5/CTNNB1 axis as a targetable pathway for treating chemotherapy-induced barrier dysfunction.

Biomolecular self-assembly presents a convenient and promising approach for fabricating functional nanomaterials. The inherent structural and functional diversity of biomolecules facilitates the creation of a wide spectrum of biological nanomaterials through this intricate process. These versatile materials have demonstrated extensive utility in multidisciplinary domains, encompassing materials science, biomedical engineering, tissue engineering, nanotechnology, and analytical science. This review focuses on self-assembled biomolecular materials for energy harvesting applications, organized into 4 main aspects. Firstly, we introduce the self-assembly methods and key factors involved in biomolecular self-assembly mechanism, including hydrogen bonding, covalent bonds, π–π interactions, electrostatic interactions, and hydrophobic/hydrophilic interactions. Secondly, we discussed the structural characteristics of different types of self-assembled biomolecular materials and introduced their mechanical, piezoelectric, ferroelectric, semiconductor, and biocompatibility properties. Next, the application of self-assembled biomolecular materials in energy harvesting was studied, mainly focusing on piezoelectric nanogenerators, triboelectric nanogenerators, water-enabled electricity generation, and other types of energy harvesting devices. Finally, we emphasized challenges in the area encompassing not only the design of the materials and assembly regulation but also probable efforts in improving performance and application fields. We believe that this review will elucidate diverse functions of self-assembled biomaterials, paving the way for the innovative design of biomaterials not only for energy harvesting systems but also for biomaterial-based microelectronic devices.

The integration of wearable technology and smart textiles has substantially advanced the development of radio-frequency (RF) electronics embedded in textile substrates, opening new opportunities across health monitoring, environmental sensing, and wireless communication. Despite their established performance, conventional rigid RF systems face inherent limitations in conformability and seamless integration within wearable platforms. This review comprehensively summarizes recent progress in textile-based RF active devices, encompassing reconfigurable antennas, tunable metasurfaces, and multifunctional RF systems. We emphasize the transition from isolated components to fully integrated, intelligent platforms capable of energy harvesting, low-power communication, and distributed sensing while proposing solution strategies and future development directions for enriched and systematic performance. Critical technical challenges such as high-precision fabrication, tunable RF response, and architecture design for complex systems are thoroughly discussed. Ultimately, this review outlines promising pathways toward autonomous, adaptive, and intelligently networked textile RF systems, highlighting the convergence of wireless functionality and system-level co-design for the next generation of wearable electronics.

Clear cell renal cell carcinoma (ccRCC) is a lethal urologic malignancy with limited biomarkers for prognosis and therapeutic stratification. Interferon-induced protein 44 (IFI44) has been implicated in immune regulation, but its role in ccRCC is unclear. To address this gap, we comprehensively investigated the clinical significance, biological roles, and molecular mechanisms of IFI44 in ccRCC pathogenesis. Using integrative transcriptomic analysis of the Gene Expression Omnibus and the Cancer Genome Atlas-Kidney Clear Cell Carcinoma cohorts, we first identified IFI44 as a key candidate gene. Bioinformatic enrichment analyses and immune infiltration profiling were conducted to investigate potential mechanisms. In parallel, we established ccRCC cell lines with stable IFI44 knockdown and evaluated phenotypic changes using Cell Counting Kit-8, Transwell assays, wound-healing assays, and flow cytometry, thereby examining cell proliferation, apoptosis, migration, and invasion. We observed that IFI44 was markedly elevated in ccRCC tissues, and its increased level was closely associated with advanced tumor stage and poorer patient survival. Enrichment analyses indicated that IFI44 participates in pathways related to viral response, RNA splicing, and mRNA processing. Moreover, elevated IFI44 expression may be associated with an immunosuppressive tumor microenvironment, as suggested by increased infiltration of effector T cells and M1 macrophages, along with decreased infiltration of activated dendritic cells. In mechanistic studies, IFI44 knockdown markedly suppressed cell proliferation, triggered apoptosis, and reduced both migratory and invasive capacities, whereas PRDX1 overexpression rescued these phenotypes and PRDX1 was shown to interact with IFI44. In summary, the data show that IFI44 acts as an oncogene in ccRCC, promoting tumor progression through its interaction with PRDX1 while also shaping an immunosuppressive microenvironment, and suggest that IFI44 is a promising biomarker of prognosis and candidate therapeutic target for ccRCC.

Hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR⁺/HER2⁻) early breast cancer (EBC) patients face long-term recurrence risk despite standard treatment. Current prognostic tools relying on clinicopathological factors or multigene assays have limited accuracy or accessibility. In this study, we developed a multimodal recurrence risk prediction (MRRP) model integrating routinely available clinical data, including whole-slide images (WISs), ultrasound (US) imaging and diagnostic reports, and structured clinical parameters. The MRRP model employs a hierarchical transformer-based fusion framework with innovative intra- and intermodality cross-attention mechanisms to dynamically integrate diverse feature representations. Using a well-curated cohort of 768 HR⁺/HER2⁻ EBC patients with long-term follow-up, MRRP demonstrated superior prognostic performance (C-index = 0.840) compared to single-modality models, with robust time-dependent AUCs exceeding 0.85 at 3, 5, and 7 years. Ablation studies highlighted the central role of pathology features and the complementary value of US and clinical data. We further validated the optimal query selection strategies and evaluated different pretrained encoders, revealing complex modality interactions. To address real-world challenges of missing modality data, a learnable compensation mechanism was implemented, improving model robustness. Our study provides a clinically practical, AI-driven tool for precise risk stratification in HR⁺/HER2⁻ EBC patients, facilitating individualized treatment and surveillance decisions without reliance on costly multi-omics data.

The modulation of thermal radiation is essential for advanced photonic applications, offering a novel perspective for information carriers. However, current carriers are limited to a few discrete radiation states at isolated time points and cannot capture the entire dynamic process along the full temporal axis, resulting in substantial information loss. Here, we propose and experimentally validate a novel spatiotemporal modulation strategy that dynamically tailors emissivity across the entire temporal domain, where gentle and uniform modulation of atomic configurations enables the creation of entirely novel permittivity libraries. To realize flexible thermal radiation tailoring, we utilize an Ag–In₃SbTe₂ (IST) interface atomic rearrangement metamaterial (ARM). As a dynamic optical control platform, ARM exhibits continuous spectral modulation with remarkably high amplitudes (64.74% in the 3- to 5-μm band and 73.94% in the 8- to 14-μm band), together with rich variations across the temporal domain to realize tailored infrared emissivity and infrared information encryption. This work establishes a unified framework for continuous, atomic-scale spatiotemporal control of thermal radiation, opening new pathways for spectral modulation and photonic information regulation in the time domain.

Major psychiatric disorders are characterized by substantial clinical heterogeneity and high comorbidity, yet their underlying biological mechanisms are not fully uncovered. The microbiota–gut–brain axis (MGBA) offers a cross-system perspective for elucidating the pathophysiology of major psychiatric disorders. The Brain–Gut Health Initiative (BIGHI) was established as the first prospective longitudinal cohort in China dedicated to investigating major psychiatric disorders guided by the framework of MGBA, enabling large-scale, transdiagnostic, and longitudinal analyses of brain–gut interactions. To date, the BIGHI has enrolled over 1,200 participants with schizophrenia, major depressive disorder, bipolar disorder, and healthy controls, with multidimensional data collected including clinical symptomatology, neurocognitive performance, electroencephalography, magnetic resonance imaging, peripheral blood biomarkers, and gut microbiome profiles. The studies within the BIGHI reveal (a) brain–gut physiological alterations in psychiatric disorders; (b) systematic relationships among brain function, peripheral physiological markers, and gut microbiome; and (c) brain–gut network patterns with marked interindividual heterogeneity. In future studies, we will expand the BIGHI into a collaborative network and promote data harmonization and interdisciplinary collaboration to advance computational psychiatry as well as its clinical translation.

Understanding the variation of functional architecture across individuals and populations is fundamental to advancing our knowledge of human health and behavior. Yet, while functional organization differences related to ethnicity/race are consistently reported, their underlying mechanisms remain poorly understood. Here, we apply precision individualized functional mapping to systematically investigate ethnicity/race-related differences between African American (AA) and white American (WA) cohorts in the brain’s intrinsic organization and their associations with lifestyle and transcriptional signatures. We show that variations in network topography and functional connectivity across these ethnic/racial groups follow a hierarchical sensorimotor–association axis and are constrained by brain morphology. Importantly, we identify lifestyle factors—particularly education and substance use—that significantly mediate these associations between ethnicity/race and functional connectivity. Leveraging human brain gene expression data, we further demonstrate that cortical transcriptional patterns are spatially aligned with ethnicity/race-related variability in functional connectivity. Gene ontology analyses of associated genes reveal significant enrichment in biological processes such as synaptic signaling and neuronal system development. Together, these findings uncover a multi-layered framework linking ethnicity/race-related differences in brain function to structural constraints, lifestyle influences, and molecular signatures, and point to the need for a more comprehensive and equitable understanding of human brain diversity.

Conventional second near-infrared (NIR-II; 1,000 to 1,700 nm) fluorescence imaging cannot simultaneously achieve a high signal-to-noise ratio and motion-artifact-free capture of rapid physiological dynamics. Here, we introduce NIR-II compressive fluorescence imaging (COFI), a high-speed, pixel-super-resolved compressive imaging technique that encodes dynamics into single frames using a high-speed spatial light modulator and a low-frame-rate NIR-II camera. A hybrid reconstruction algorithm integrating a denoising convolutional neural network with an enhanced super-resolution generative adversarial network subsequently restores high-fidelity videos. The system achieves 3.3 kiloframes per second with a space–bandwidth–time product of 4.22 × 10⁸ pixels/s without compromising intrinsic sensitivity. Compared to conventional short-exposure imaging with the same duration of 500 μs, NIR-II COFI achieves a 36% improvement in signal-to-noise ratio. Furthermore, using bright 1,525-nm nanoparticle probes, we demonstrate multicomponent phosphorescence lifetime imaging, high-speed motion tracking, and real-time visualization of murine intestinal peristalsis in both awake and anesthetized states. This work facilitates deep-tissue, high-speed in vivo imaging of fast biological processes.