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麦醇溶蛋白
PHYTOMEDICINE · 2026 · IF 11.3

Rehmannia glutinosa extract inhibits Henoch-Schönlein Purpura (IgA Vasculitis) by restoring regulatory T cell and T helper 17 cell balance via the PI3K/Akt/mTOR signaling pathway

Linyan Lang,Yiping Fu,Jinxin Miao,Yagang Song,Xiaolei Zhang,Quanyou Zhao,Yuting Liu,Yu Zhang,Mingsan Miao,Xingyi Liu,Yueyang Zhang,Xiaoran Wang,Zhanzhan Li

In this study, we report that Fresh Rehmannia glutinosa extract (RGE), effectively prevents and treats Henoch-Schönlein Purpura (HSP) by regulating the PI3K-AKT-mTOR signaling pathway to restore the Treg/Th17 balance. • RGE, a traditional "medicinal and edible homology" herb recently added to China's 2024 list, demonstrates therapeutic potential for HSP by aligning with the TCM principle of "clearing descending fire and nourishing yin" to treat blood syndromes. • RGE and its core active component catalpol significantly alleviate HSP symptoms, reducing skin and renal purpura, pathological damage, and IgA deposition in mouse models. • RGE and its core active component catalpol restore Treg/Th17 balance and suppresses inflammatory cytokines by inhibiting the PI3K-AKT-mTOR/NF-κB signaling pathway, as confirmed by network pharmacology, molecular docking, and in vivo/in vitro experiments. • Multi-omics analysis reveals that RGE intervention reshapes gut microbiota structure and regulates metabolic homeostasis, suggesting a protective "gut-microbiota-immune" mechanism in HSP treatment. Background Therapeutic choices remain limited for Henoch-Schönlein purpura (HSP), an IgA-associated vasculitis. Rehmannia glutinosa , a medicinal and edible herb traditionally used to "clear heat and cool blood," shows clinical promise, yet its precise pathogenesis remains elusive. Purpose This study was designed to examine the therapeutic impact of Rehmannia glutinosa extract (RGE) on HSP, characterize its primary active components, and explore the mechanistic basis of its activity. Study design An integrative approach encompassing in vivo and in vitro HSP models, network pharmacology, LC-MS, molecular docking, dynamics simulations, microbiomics, and metabolomics was utilized to systematically identify the anti-HSP material basis and underlying mechanisms of RGE. Methods Forty-one active components in RGE were identified via LC-MS. A multi-level computational strategy-encompassing network pharmacology, docking studies, and molecular dynamics was applied to screen and identify Catalpol (Cat) as the key active candidate. ICR mouse HSP models and cell cultures were treated with RGE or Cat. Pathological injuries, IgA deposition, and immune cell proportion changes were evaluated using RT-qPCR, Western blot, flow cytometry, and multiplex immunofluorescence. Furthermore, microbiomics and metabolomics were utilized to decipher the mechanism by which RGE exerts its effects through gut microbiota regulation. Results RGE and Cat significantly alleviated skin and kidney injuries and reduced abnormal IgA deposition. By suppressing the PI3K-AKT-mTOR/NF-κB pathway, they successfully rectified the Treg/Th17 imbalance and mitigated inflammatory cytokine production. Additionally, RGE effectively reshaped the gut microbiota ecology and regulated the metabolome. Molecular simulations further confirmed Cat as a key active compound. Conclusion RGE exerts therapeutic effects on HSP through multi-target immunomodulation and gut microbiota remodeling, with Cat identified as a critical active component. These data support the herapeutic prospects of RGE and Cat in the prophylaxis and management of HSP. Download: Download high-res image (351KB) Download: Download full-size image

CAS / MDL: 9007-90-3 158966-92-8
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SENSORS AND ACTUATORS B-CHEMICAL · 2025 · IF 7.7

Ultrasensitive and rapid screening of food allergy risk via aptamer-engineered AuMBA@AgNPs core-shell nanoparticle SERS tags-based lateral flow immunoassay

Huan Li,Keyu Tao,Hongbo Chen,Shuifeng Zhang,Huadong Sheng,Linglin Fu

Trace allergens hidden in food products, particularly those arising from cross-contamination during manufacturing, can elicit severe and potentially life-threatening allergic reactions. This underscores critical demand for rapid and ultrasensitive detection technologies to identify trace-level allergens in food matrices, thereby enabling proactive prevention of food allergy risks. In this study, a surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-LFA) based on the Au MBA @AgNPs-Apt SERS tag was developed for rapid and ultrasensitive screening of the allergenic risks in food. With the competitive detection principle, the SERS-LFA achieved detection of target allergenic proteins with a limit of detection (LOD) of 2.2   ng/mL within 8   min. Notably, by integrating additional test line on the nitrocellulose (NC) membrane, the method was adapted for multi-target detection. Under the optimized conditions, the SERS-LFA could simultaneously detect milk allergenic β-lactoglobulin (β-Lg) and fish allergenic parvalbumin (PV) with LODs of 40   ng/mL and 1.1   ng/mL, respectively. The proposed method demonstrated excellent specificity, reproducibility, and comparable performance to commercial ELISA kits in real-sample analysis, establishing a robust on-site methodology for rapid allergy risk screening in complex food matrices.

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BMC BIOLOGY · 2025 ·Vol. 23 ·期 1 ·1-17 · IF 4.5

Deep learning-based dipeptidyl peptidase IV inhibitor screening, experimental validation, and GaMD/LiGaMD analysis

He Yi,Zhang Yan,Liu Minghao,Li Jiaying,Li Wannan,Han Weiwei

Background Dipeptidyl peptidase-4 (DPP4) is considered a crucial enzyme in type 2 diabetes (T2D) treatment, targeted by inhibitors due to its role in cleaving glucagon-like peptide-1 (GLP-1). In this study, a novel DPP4 inhibitor screening strategy was developed, which significantly improved screening accuracy. Results In this study, a DPP4 inhibitor screening method was developed, integrating receptor-based ConPLex, ligand-based KPGT, and molecular docking to enhance screening accuracy. Using this approach, four potential drugs were identified from the FDA database, achieving a 100% hit rate. Among these, Isavuconazonium demonstrated the highest inhibitory activity (IC 50  = 6.60 µM). Furthermore, a user-friendly server, DPP4META, was established to predict IC 50 values for DPP4 inhibitors. The binding and dissociation mechanisms of these drugs with DPP4 were further examined through Gaussian accelerated Molecular Dynamics (GaMD) and ligand Gaussian accelerated Molecular Dynamics (LiGaMD), revealing strong correlations with IC 50 values. Additionally, a Python-based toolkit, pymd, was developed to facilitate protein-compound binding analysis. Conclusions Our study offers a robust approach and valuable insights for the development of DPP4 inhibitors, providing an effective means to investigate the binding and dissociation mechanisms between proteins and compounds.

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