Objective:To apply bioinformatics methods to screen and analyze differentially expressed genes and biological processes specific to peripheral blood mononuclear cells in postmenopausal women with osteoporosis.Methods:From the Gene Expression Omnibus database, GSE56814, GSE56815, and GSE2208 datasets were screened as the research objects. The limma package in R language was used to screen differentially expressed genes, and the multigene Meta-analysis function in Metascape platform was utilized to perform enrichment analysis of gene ontology and pathway. Protein-protein interaction network construction, module analysis, core gene, and enrichment analysis will be carried out.Results:In the GSE56814 dataset, there were 84 significantly up-regulated genes and 73 significantly down-regulated genes. In the GSE56815 dataset, there were 8 significantly up-regulated genes and 33 significantly down-regulated genes. In the GSE2208 dataset, there were 21 significantly up-regulated genes and 10 significantly down-regulated genes. The multigene Meta-analysis identified 3 modules and 19 core genes in the Metascape platform. The core genes of MCODE1 included STXBP2, EIF2S2, EIF3J, PTPN6, FLNA, HLA- DQA1, CTSD, HSPA6, HLA- DPB1, EIF3E, PLEC. They mainly enriched formation of cytoplasmic translation initiation complex, antigen processing and presentation of exogenous peptide antigen via major histocompatibility complex Ⅱ, cytoplasmic translational initiation, nsp1 from SARS-CoV-2 inhibits translation initiation in the host cell, programmed cell death 1 signaling pathway, allograft rejection reaction. The core genes of MCODE2 included FOS, FOSB, EGR1, EGR2, JUNB. They mainly enriched RNA polymerase Ⅱ-specific, DNA-binding transcription activator activity, cellular response to salt, nerve growth factor-stimulated transcriptional pathways, nuclear kinase and transcription factor activation activation pathways, neurotrophic receptor tyrosine kinase 1 signaling pathway. The core genes of MCODE3 included CEBPA, H2AC6, SPI1. They mainly enriched transcriptional regulation of granulopoiesis. Conclusion:This study obtained a total of 3 modules, 19 core genes, and enriched them in the biological processes related to postmenopausal osteoporosis, providing new ideas and biological targets for exploring its occurrence pathogenesis and drug treatment.

In the past, aortic dissection, aortic aneurysm, and other aortic diseases, primarily rely on surgical intervention. In recent years, due to breakthroughs in materials science, endovascular therapy has become the first choice for the surgical treatment of most aortic diseases. However, traditional endovascular repair cannot fully meet the clinical needs for certain complex lesions involving the aortic arch and the originations of visceral arteries. The emergence of physician-modified stent technology has brought new hope for the treatment of complex aortic diseases. This article provides a detailed introduction to the concept, development, technical characteristics, and applications of physician-modified stents in the treatment of aortic diseases, analyzing their advantages and limitations. Physician-modified stents serve as a powerful complement to traditional endovascular interventions and commercial branched stents, yet further research and refinement are still required.

Objective:To compare the efficacy and safety of Rotarex mechanical thrombectomy (Rotarex) combined with drug-coated balloon (DCB) versus percutaneous transluminal angioplasty (PTA) combined with DCB in the treatment of femoropopliteal artery in-stent restenosis (ISR).Methods:A multicenter, prospective, randomized controlled trial was conducted. 46 patients with femoropopliteal artery ISR admitted to five hospitals (Beijing Friendship Hospital, Capital Medical University; Beijing Chaoyang Hospital, Capital Medical University; Beijing Jishuitan Hospital, Capital Medical University; Xuanwu Hospital, Capital Medical University; Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University) from July 2020 to June 2024 were enrolled. Patients were randomly divided into the Rotarex+ DCB group ( n=24) and the PTA+ DCB group ( n=22) using a random number table. The clinical data of the two groups were collected, including clinical characteristics, Fontaine classification, stent placement location, stent duration, and lesion length. The primary endpoint was the target blood vessel patency rate at 6 and 12 months postoperatively; the secondary endpoints included improvement in clinical symptoms (Fontaine classification), rate of reintervention, and safety indicators. Measurement data were expressed as mean±standard deviation ( ± s), and the t-test was used for comparison between groups; count data were expressed as the number of cases and percentages, and intergroup comparisons were performed using the Chi-test or Fisher exact probability method. Results:At 12 months postoperatively, the target blood vessel patency rate in the Rotarex+ DCB group was significantly higher than that in the PTA+ DCB group (81.8% vs 45.5%, P=0.012), and the proportion of patients in Fontaine classification stage I was also higher (86.4% vs 45.5%, P=0.004). The results at the 6-month follow-up were consistent (target blood vessel patency rate: 87.0% vs 59.1%, P=0.035). In terms of safety, no severe complications such as arterial rupture, amputation, or procedure-related death occurred during the perioperative period in either group. During the postoperative follow-up, no amputation or procedure-related deaths occurred in either group. Conclusion:For the treatment of femoropopliteal artery ISR, Rotarex mechanical thrombectomy combined with DCB is significantly superior to PTA+ DCB in terms of 12-month target blood vessel patency rate and improvement of clinical symptoms, with comparable safety.

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

Structural optimization of lead compounds is a crucial step in drug discovery. One optimization strategy is to modify the molecular structure of a scaffold to improve both its biological activities and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. One of the deep molecular generative model approaches preserves the scaffold while generating drug-like molecules, thereby accelerating the molecular optimization process. Deep molecular diffusion generative models simulate a gradual process that creates novel, chemically feasible molecules from noise. However, the existing models lack direct interatomic constraint features and struggle with capturing long-range dependencies in macromolecules, leading to challenges in modifying the scaffold-based molecular structures, and creates limitations in the stability and diversity of the generated molecules. To address these challenges, we propose a deep molecular diffusion generative model, the three-dimensional (3D) equivariant diffusion-driven molecular generation (3D-EDiffMG) model. The dual strong and weak atomic interaction force-based long-range dependency capturing equivariant encoder (dual-SWLEE) is introduced to encode both the bonding and non-bonding information based on strong and weak atomic interactions. Additionally, a gate multilayer perceptron (gMLP) block with tiny attention is incorporated to explicitly model complex long-sequence feature interactions and long-range dependencies. The experimental results show that 3D-EDiffMG effectively generates unique, novel, stable, and diverse drug-like molecules, highlighting its potential for lead optimization and accelerating drug discovery.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index