Acute kidney injury (AKI) is a critical clinical condition characterized by rapid renal function decline, with high morbidity, mortality, and healthcare costs. Traditional Chinese medicine (TCM) has shown potential effects on mitigating oxidative stress and programmed cell death in AKI models. Scutellaria barbata D. Don (SB) and Scleromitrion diffusum (Willd.) R. J. Wang (SD), a classic TCM herbal pair exhibited anti-inflammatory and antioxidant activities. Using advanced chromatographic separation technology, we enriched the effective fractions of water extracts from SB-SD, obtaining self-assembled herbal nanoparticles (SB and SD nanoparticles, SSNPs) rich in flavonoids and terpenoids. These SSNPs demonstrated robust antioxidant properties in vitro and mitigated AKI progression in vivo by activating the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway. Oral administration of SSNPs in mice resulted in absorption into the bloodstream, formation of a protein corona, reduced macrophage phagocytosis, and enhanced bioavailability and renal targeting. Furthermore, we investigated the self-assembly principle of SSNPs using representative flavonoids and terpenoids. Kinetic studies and in situ transmission electron microscopy (in situ TEM) revealed that these compounds self-assemble via supramolecular forces like hydrogen bonding and π-π interactions, forming stable nanostructures. This study elucidates the renoprotective effects and mechanisms of SB and SD, and provides a novel approach for the development of TCM-based nanomedicines, highlighting the potential of nano-TCM in AKI treatment.

Section Background The early diagnosis and prognosis of head and neck tumors are crucial for enhancing patients’ quality of life. This study focuses on angiogenic genes to develop prognostic and diagnostic models, offering a novel strategy to improve patient outcomes and increase the early diagnosis rate of HNSCC. AbstractSection Methods Samples were clustered based on MSI, SCNA, and mTMB. A vascularization-related diagnostic and prognostic scoring model was constructed through the analysis of differentially expressed genes (DEGs). The model was validated using univariate and multivariate Cox proportional hazards analyses with data from the International Cancer Genome Consortium (ICGC). Subsequently, samples were grouped according to model scores, and immune infiltration analysis was conducted. Immune profiling, combined with narrow band imaging (NBI), was employed to verify the diagnostic model. AbstractSection Results Cluster analysis based on MSI, SCNA, and mTMB burden values effectively stratified HNSCC into three distinct types. An angiogenesis-related prognostic model was developed from differential gene analysis to assess patient outcomes. Validation using an external database (ICGC dataset) confirmed the model’s robust performance. Following the stratification of TCGA samples into high-risk and low-risk groups based on risk scores, significant differences were observed in expression data and immune cell infiltration between the two cohorts. Furthermore, after adjustments using both univariate and multivariate Cox regression analyses, the risk score index emerged as an independent prognostic factor. Subsequent validation using Narrow Band Imaging (NBI) combined with immunohistochemistry confirmed the model’s utility in diagnosing early-stage head and neck tumors. AbstractSection Conclusion The model holds potential for application in the diagnostic and prognostic evaluation of early-stage head and neck tumors.

Radiation-induced intestinal injury (RIII) represents a significant dose-limiting complication of radiotherapy, characterized by substantial loss of intest