中国人民解放军军事医学科学院

Sepsis, characterized by its complex pathophysiology, presents significant challenges for clinical treatment. An integrative approach combining highly effective antibacterial measures, immunomodulation, and organ protection is urgently needed to enhance the therapeutic efficacy. Here, we construct hybrid cerium-baicalein nanozymes (Ce-BE NZs), which exhibit broad-spectrum non-antibiotic antibacterial and redox enzyme-mimicking activities, effectively scavenging reactive oxygen species and reducing inflammatory mediators in lipopolysaccharide-stimulated macrophages. Ce-BE NZs also correct immune dysregulation, reduce liver injury, and extend survival in both cecal ligation and puncture and "two-hit" sepsis models. Mechanistically, Ce-BE NZs inhibit ferroptosis and mitigate mitochondrial dysfunction by promoting ferritin heavy chain-1 expression, thereby enhancing multi-target sepsis therapy. Additionally, they mitigate ferroptosis and cell damage in a macrophage-incorporating human liver-derived organoid model. Overall, Ce-BE NZs represent a promising multi-target therapy for sepsis and may pave the way for an antibiotic-free and transnational approach to treating other infectious diseases.

Flow electrode capacitive deionization (FCDI) has emerged as a sustainable and promising technology for water desalination, yet its efficiency remains hindered by the intrinsic limitations of conventional flow electrode materials. Herein, a novel CNTs@ZIF-67 composite was synthesized via in situ crystal growth and employed as the active component of the flow electrode. The integration of CNTs into the ZIF-67 framework constructs a unique three-dimensional dot-line conductive network with abundant porosity, large specific surface area, nitrogen-rich functionalities, and enhanced wettability, thereby facilitating efficient ion transport and storage. Electrochemical analysis reveals that capacitance contributions are dominated by Faradaic processes, with pseudo-capacitance (31.84%) and diffusive redox capacitance (19.37%) surpassing the electric double-layer contribution (48.79%). At an optimal loading of 5 wt%, the CNTs@ZIF-67 flow electrode achieves outstanding desalination performance (ASRR = 4.77 mu g center dot cm-2 center dot min-1, CE = 119%, SEC = 0.314 kWh center dot m-3, ENRS = 12.3 mu mol center dot J-1) and superior long-term stability under SC mode, significantly outperforming ICC mode. Multiscale density functional theory (DFT) calculations further reveal that CNTs induce electronic hybridization with the Co-N coordination framework of ZIF-67, strengthen Na+/Cl-adsorption, and generate delocalized electronic states that facilitate charge transfer and ion migration. These results demonstrate the potential of CNTs@ZIF-67 for advancing FCDI technology.

Vesicant mustards are a class of highly toxic chemical warfare agents, posing a serious societal and environmental threat. Early and accurate diagnosis of exposure is essential to guide effective medical countermeasures and minimize bodily injuries. However, developing specific, rapid and on-site diagnostic methods remains challenging owing to complex matrix interference and low analyte abundance. Herein, we designed a label-free, non-invasive and sensitive method combining capillary-driven surface-enhanced Raman spectroscopy (SERS) with reversed-phase thin-layer chromatography (RP-TLC) for detecting mustard-DNA adducts as exposure biomarkers. In this strategy, trace acetonitrile (ACN) and perfluoropolyether (PFPE) lubricant were employed to optimize interfacial kinetics for efficient analyte extraction and confine droplet diffusion for high reproducibility, respectively. Target molecules were further trapped in plasmonic nanogaps during evaporation, yielding strong SERS enhancement. Subsequently, 24 kinds of DNA adduct from 10 different mustards were distinguished assisted by machine learning, and the lowest absolute detection limit of 12.5 pg was achieved. Compared to conventional TLC-SERS, the detection sensitivity was improved by four orders of magnitude (similar to 10(4)). Finally, trace adducts were successfully identified from the urine of individuals exposed to sulfur mustard HD. To our knowledge, this is the first systematic study on rapid diagnosis of vesicant exposure via DNA adduct profiling.

INTRODUCTION:Sepsis is a life-threatening condition characterized by organ dysfunction due to a dysregulated immune response to infection. Despite extensive research into its complex pathogenesis, effective clinical treatments remain limited, necessitating novel therapeutic strategies. OBJECTIVES:This study aims to develop a multifunctional nanozyme-based therapy for severe sepsis, combining broad-spectrum antimicrobial activity and reactive oxygen species (ROS) scavenging to counteract organ injury, immune dysregulation, and high mortality. METHODS:We designed biocompatible resveratrol-Ag + -Prussian blue nanozymes (ARPB NZs) and evaluated their therapeutic effects in two murine sepsis models: E. coli-induced abdominal infection and cecal ligation puncture (CLP). Mechanistic studies focused on oxidative stress attenuation, cytokine storm suppression, lymphocyte function, and dendritic cell pyroptosis via the NLRP3/caspase-1/GSDMD pathway. RESULTS:ARPB NZs effectively alleviated organ damage, maintained immune homeostasis by reducing inflammation and oxidative stress, and significantly improved survival rates in both sepsis models. They also inhibited lymphocyte apoptosis and dampened dendritic cell pyroptosis. CONCLUSION:ARPB NZs represent a promising synergistic strategy for severe sepsis by simultaneously targeting infection and immune dysregulation. This approach may translate into broader applications for infectious diseases.

Emerging DNA language models provide powerful tools to address the challenge of accurately predicting chromatin loops, fundamental structures governing 3D genome organization and gene regulation. Here we present CLAMP, which utilizes a deep language model pre-trained on broad cross-species chromatin accessibility data. CLAMP achieves superior performance compared to existing methods in predicting specific protein-mediated loops across 10 species, 18 proteins, and 24 cell types. CLAMP incorporates a novel CoVE explainer that reveals context-dependent genomic feature contributions, providing insights into the features driving predictions. CLAMP predictions effectively identify functionally significant chromatin loops and associated biological pathways.