ObjectiveTo study the tumor inhibition and T helper cell （Th）1/Th2 balance regulation effect of modified Wenyang Sanjie prescription on lung cancer tumor-bearing mice and to elaborate its mechanism. MethodsA mouse model bearing a lung cancer tumor was established by subcutaneous injection of Lewis lung cancer cells into the armpit and was randomly divided into lung cancer model group， low-dose， medium-dose， and high-dose groups of modified Wenyang Sanjie prescription， and positive control group， with 12 mice per group. The low-dose， medium-dose， and high-dose groups of modified Wenyang Sanjie prescription were given modified Wenyang Sanjie prescription by dosing at 2.5， 5， 10 g·kg^-1， once a day， respectively. The positive control group was intraperitoneally injected with cisplatin （2 mg·kg^-1）， once every other day， for a total of 30 days. Serum interferon （IFN）-γ， interleukin （IL）-2， IL-4， IL-6， and IL-10 were determined by enzyme-linked immunosorbent assay （ELISA）， and spleen index， thymus index， and tumor growth inhibition rate were calculated. Tumor microvascular density was determined by immunohistochemistry， and tumor hypoxia inducible-factor （HIF）-1α， epidermal growth factor receptor （EGFR）， and vascular endothelial growth factor （VEGF） mRNA were determined by Real-time quantitative polymerase chain reaction （PCR）. The protein levels of HIF-1α， EGFR， and VEGF were determined by Western blot. ResultsCompared with lung cancer model group， IFN-γ and IL-2 were increased in the modified Wenyang Sanjie prescription groups and positive control group， while IL-4， IL-6， IL-10， spleen index， thymus index， tumor weight， and tumor microvascular density were decreased， as well as HIF-1α， EGFR， and VEGF mRNA and protein levels （P<0.05）. Compared to the low-dose group of modified Wenyang Sanjie prescription， IFN-γ and IL-2 were increased in the medium-dose and high-dose groups of modified Wenyang Sanjie prescription， while IL-4， IL-6， IL-10， spleen index， thymus index， tumor weight， and tumor microvascular density were decreased， as well as HIF-1α， EGFR， and VEGF mRNA and protein levels （P<0.05）. IFN-γ and IL-2 were increased in the high-dose group of modified Wenyang Sanjie prescription compared to the medium-dose group of modified Wenyang Sanjie prescription， and IL-4， IL-6， IL-10， spleen index， thymus index， tumor weight， and tumor microvascular density were decreased， as well as HIF-1α， EGFR， and VEGF mRNA and protein levels （P<0.05）. ConclusionModified Wenyang Sanjie prescription can significantly inhibit microangiogenesis， regulate Th1/Th2 balance， inhibit tumor growth， and significantly inhibit the progression of lung cancer in mice.

Objective: To investigate the protective effects and underlying mechanisms of sodium pyruvate (SP) on RBC storage lesions using an oxidative damage model. Methods: Six units of leukocyte-depleted suspended RBCs (discarded for non-infectious reasons within three days post-collection) were randomly assigned to four groups: negative control (NS), positive control (PS), experimental group 1 (SP1), and experimental group 2 (SP2). Oxidative stress was induced in the PS group by the addition of hydrogen peroxide (H O ), while SP1 and SP2 received SP supplementation at different concentrations (25 mM and 50 mM, respectively) in the presence of H O . After 1 hour of incubation, RBC morphology was assessed microscopically, and biochemical indicators including glutathione (GSH), malondialdehyde (MDA), methemoglobin (MetHb), adenosine triphosphate (ATP), and Na /K -ATPase activity were measured. Results: RBCs in the PS group exhibited pronounced morphological damage, including cell shrinkage and echinocyte formation, whereas both SP-treated groups showed significantly reduced structural injury. SP treatment led to elevated GSH levels and decreased concentrations of MDA and MetHb, suggesting attenuation of oxidative stress. Additionally, SP enhanced intracellular ATP levels and Na /K -ATPase activity, thereby contributing to membrane stability. Notably, the SP2 group (50 mM) demonstrated superior protective effects compared to SP1 (25 mM). Conclusion: Sodium pyruvate effectively attenuates oxidative storage lesions in RBCs, primarily through its antioxidant properties, energy metabolism supporting ability, and celluar membrane stabilizing function. These findings suggest SP as a promising additive for enhancing the quality and safety of stored RBCs.

Antibody-drug conjugate (ADC), a novel class of antineoplastic agents, combines tumor-specific targeting with potent cytotoxic activity. In recent years, ADC has achieved notable advances in the treatment of non-small cell lung cancer (NSCLC), particularly within therapeutic sequencing after failure of first-line therapy or the emergence of resistance. This paper will systematically review the efficacy and safety evidence of representative ADC in NSCLC, and further to discuss progress and challenges in ADC structural optimization, toxicity management, biomarker identification, and combination strategies, aiming to provide a comprehensive theoretical foundation and practical reference for clinical practice and future research.
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Humans ; Carcinoma, Non-Small-Cell Lung/drug therapy* ; Immunoconjugates/chemistry* ; Lung Neoplasms/drug therapy* ; Drug Resistance, Neoplasm/drug effects* ; Antineoplastic Agents/chemistry*

ObjectiveTo study the tumor inhibition and T helper cell （Th）1/Th2 balance regulation effect of modified Wenyang Sanjie prescription on lung cancer tumor-bearing mice and to elaborate its mechanism. MethodsA mouse model bearing a lung cancer tumor was established by subcutaneous injection of Lewis lung cancer cells into the armpit and was randomly divided into lung cancer model group， low-dose， medium-dose， and high-dose groups of modified Wenyang Sanjie prescription， and positive control group， with 12 mice per group. The low-dose， medium-dose， and high-dose groups of modified Wenyang Sanjie prescription were given modified Wenyang Sanjie prescription by dosing at 2.5， 5， 10 g·kg^-1， once a day， respectively. The positive control group was intraperitoneally injected with cisplatin （2 mg·kg^-1）， once every other day， for a total of 30 days. Serum interferon （IFN）-γ， interleukin （IL）-2， IL-4， IL-6， and IL-10 were determined by enzyme-linked immunosorbent assay （ELISA）， and spleen index， thymus index， and tumor growth inhibition rate were calculated. Tumor microvascular density was determined by immunohistochemistry， and tumor hypoxia inducible-factor （HIF）-1α， epidermal growth factor receptor （EGFR）， and vascular endothelial growth factor （VEGF） mRNA were determined by Real-time quantitative polymerase chain reaction （PCR）. The protein levels of HIF-1α， EGFR， and VEGF were determined by Western blot. ResultsCompared with lung cancer model group， IFN-γ and IL-2 were increased in the modified Wenyang Sanjie prescription groups and positive control group， while IL-4， IL-6， IL-10， spleen index， thymus index， tumor weight， and tumor microvascular density were decreased， as well as HIF-1α， EGFR， and VEGF mRNA and protein levels （P<0.05）. Compared to the low-dose group of modified Wenyang Sanjie prescription， IFN-γ and IL-2 were increased in the medium-dose and high-dose groups of modified Wenyang Sanjie prescription， while IL-4， IL-6， IL-10， spleen index， thymus index， tumor weight， and tumor microvascular density were decreased， as well as HIF-1α， EGFR， and VEGF mRNA and protein levels （P<0.05）. IFN-γ and IL-2 were increased in the high-dose group of modified Wenyang Sanjie prescription compared to the medium-dose group of modified Wenyang Sanjie prescription， and IL-4， IL-6， IL-10， spleen index， thymus index， tumor weight， and tumor microvascular density were decreased， as well as HIF-1α， EGFR， and VEGF mRNA and protein levels （P<0.05）. ConclusionModified Wenyang Sanjie prescription can significantly inhibit microangiogenesis， regulate Th1/Th2 balance， inhibit tumor growth， and significantly inhibit the progression of lung cancer in mice.

Organoids,as a three-dimensional structural model that has been rapidly developed and widely concerned in recent years,enable the key functions and microenvironment of internal organs to be simulated in the real world,and closely reflect the physiological and pathological characteristics of the natural occurrence and metastasis of tumors,providing a new platform for disease modeling,drug research and precision medicine.This paper briefly summarizes the limitations and development prospects of organoid models,analyzes the current construction and development of organoid models of lung cancer and its applicability compared with traditional models under the holistic concept of traditional Chinese medicine and the basic theory of syndrome differentiation and treatment,and discusses the application of organoid technology in the basic research of lung cancer treatment.The advantages in screening anti-tumor Chinese medicine and drug resistance research and precision medicine provide new ideas for realizing innovative breakthroughs in traditional Chinese medicine research combined with modern science and technology.

With the rapid advancements in minimally invasive spine surgery and the increasingly sophisti-cated concept of visualization,transforaminal endoscopic lumbar discectomy(TELD)has become a primary treatment for lumbar disc herniation.Among the critical preoperative steps in TELD,foraminalplasty plays a pivotal role,as its quality directly impacts surgical outcomes and postoperative recurrence rates.This article systemati-cally reviews the evolution of foraminalplasty techniques,evaluates the selection and application of plasty sites,examines factors influencing stability after lumbar foraminalplasty,and highlights recent advancements in computer-assisted navigation.The goal is to serve as a comprehensive reference for clinicians.

OBJECTIVE: This study investigates the efficacy and mechanisms of Qingjie Fuzheng Granules (QFG) in inhibiting colitis-associated colorectal cancer (CAC) development via RNA sequencing (RNA-seq) and 16S ribosomal RNA (rRNA) correlation analysis. METHODS: CAC was induced in BALB/c mice using azoxymethane (AOM) and dextran sulfate sodium (DSS), and QFG was administered orally to the treatment group. The effects of QFG on CAC were evaluated using disease index, histology, and serum T-cell ratios. RNA-seq and 16S rRNA analysis assessed the transcriptome and microbiome change. Key pharmacodynamic pathways were identified by integrating these data and confirmed via Western blotting and immunofluorescence. The link between microbiota and CAC-related markers was explored using linear discriminant analysis effect size and Spearman correlation analysis. RESULTS: Long-term treatment with QFG prevented AOM/DSS-induced CAC formation, reduced levels of interleukin (IL)-1β, tumor necrosis factor-alpha (TNF-α), IL-6, and interferon γ (IFN-γ), and increased CD3⁺ and CD4⁺/CD8⁺ T cells ratio, without causing hepatic or renal toxicity. A 16S rRNA analysis revealed that QFG rebalanced the Firmicutes/Bacteroidetes ratio and mitigated AOM/DSS-induced microbiota disturbances. Transcriptomics and Western blotting analysis identified the nucleotide-binding oligomerization domain-containing protein 2 (NOD2)/nuclear factor kappa-B (NF-κB) pathway as key for QFG's treatment against CAC. Furthermore, QFG decreased the abundance of Bacilli, Bacillales, Staphylococcaceae, Staphylococcus, Lactobacillales, Aerococcus, Alloprevotella, and Akkermansia, while increasing Clostridiales, Lachnospiraceae, Lachnospiraceae_NK4A136_group, Ruminococcaceae, and Muribaculaceae, which were highly correlated with CAC-related markers or NOD2/NF-κB pathway. CONCLUSION By mapping the relationships between CAC, immune responses, microbiota, and key pathways, this study clarifies the mechanism of QFG in inhibiting CAC, highlighting its potential for clinical use as preventive therapy.

The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Understanding the metabolism of endogenous and exogenous substances in the human body is essential for elucidating disease mechanisms and evaluating the safety and efficacy of drug candidates during the drug development process. Recent advancements in artificial intelligence (AI), particularly in machine learning (ML) and deep learning (DL) techniques, have introduced innovative approaches to metabolism research, enabling more accurate predictions and insights. This paper emphasizes computational and AI-driven methodologies, highlighting how ML enhances predictive modeling for human metabolism at the molecular level and facilitates integration into genome-scale metabolic models (GEMs) at the omics level. Challenges still remain, including data heterogeneity and model interpretability. This work aims to provide valuable insights and references for researchers in drug discovery and development, ultimately contributing to the advancement of precision medicine.