ObjectiveThis paper aims to investigate the potential molecular biological mechanism of Buyang Huanwu Tongfeng decoction in treating hyperuricemia and gouty arthritis by network pharmacology and molecular docking technology and preliminarily verify the mechanism through animal experiments. MethodsThe active ingredients and targets in the Buyang Huanwu Tongfeng decoction were obtained by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP） and ETCM databases. The DisGeNET and GeneCards databases were utilized to acquire disease targets associated with hyperuricemia and gouty arthritis. These disease targets were then intersected with drug targets to identify key targets. The R language ClusterProfiler package and Python were employed for conducting gene ontology（GO） enrichment analysis and Kyoto encyclopedia of genes and genomes（KEGG） enrichment analysis. The regulatory network diagram of the drug-key target-function-pathway was visualized using Cytoscape 3.9.1 software， and the protein-protein interaction （PPI） network for key targets was depicted. Finally， the hub gene was determined through topological analysis. Auto Dock， PyMOL， and other software were used for molecular docking to explore the possible therapeutic mechanism of Buyang Huanwu Tongfeng decoction for hyperuricemia and gouty arthritis. In animal experiments， a composite rat model of hyperuricemia induced by intraperitoneal injection of oteracil potassium combined with gouty arthritis induced by the modified Coderre method was established. Through hematoxylin-eosin（HE） staining， uric acid test， enzyme linked immunosorbent assay（ELISA）， Western blot， and real-time polymerase chain reaction（Real-time PCR）， the molecular mechanism and key targets of Buyang Huanwu Tongfeng decoction for treating hyperuricemia and gouty arthritis were observed. ResultsAfter screening and removing duplicate values， 76 active ingredients and 15 key targets were finally obtained. GO enrichment analysis yielded that the treatment of hyperuricemia and gouty arthritis with Buyang Huanwu Tongfeng decoction was significantly associated with acute inflammatory response， astrocyte activation， regulation of interleukin （IL）-8 production， nuclear receptor activity， and binding of growth factor receptor. KEGG pathway enrichment analysis obtained that the key target genes were significantly associated with the IL-17 signaling pathway， advanced glycosylation end/receptor of advanced glycation endproducts（AGE/RAGE） signaling pathway， anti-inflammatory， and other pathways. PPI network indicated that albumin（ALB）， peroxisome proliferator-activated receptor-γ （PPAR-γ）， IL-6， IL-1β， and C-reactive protein（CRP） were the key protein targets. The molecular docking results showed that ALB had the strongest binding force with beta-carotene （β-carotene）. Biochemical results showed that blood uric acid decreased in the Buyang Huanwu Tongfeng decoction groups. HE staining results showed that the low-dose （7.76 g·kg^-1·d^-1）， medium-dose （15.53 g·kg^-1·d^-1）， and high-dose （31.05 g·kg^-1·d^-1） groups of Buyang Huanwu Tongfeng decoction had different degrees of remission， and the remission of the high-dose group was the most obvious. Fibroblastic tissue hyperplasia in synovial joints accompanied with inflammatory cell infiltration， as well as inflammatory cell infiltration in renal tissue of the high-dose group was significantly reduced， followed by the medium-dose and low-dose groups， and the expression of ALB， PPAR-γ， IL-6， IL-1β， and CRP was down-regulated to different degrees. ConclusionBy regulating the targets such as ALB， PPAR-γ， IL-6， IL-1β， and CRP， inhibiting the PPAR-γ/nuclear transcription factor （NF）-κB pathway， and reducing AGEs/RAGE-mediated inflammation， Buyang Huanwu Tongfeng decoction exerts anti-inflammatory and analgesic effects and activates blood circulation and diuresis in the treatment of hyperuricemia and gouty arthritis.

OBJECTIVE To provide reference for improving the pre-prescription review system and reducing the occurrence of medication error by analyzing the drug-related problems （DRPs） in the pre-prescription review orders of pediatric outpatient clinics using the Pharmaceutical Care Network Europe （PCNE） classification system. METHODS The data of pre-prescription review orders were retrospectively collected from outpatient department of Shanghai Children’s Medical Center， Shanghai Jiao Tong University School of Medicine from July 2022 to June 2023； DRPs in the pre-prescription review orders were classified and summarized by using the PCNE classification system （version 9.1）， and then analyzed in terms of types and causes of issues， and the acceptance of interventions. RESULTS A total of 66 017 DRPs orders were included， involving 41 165 patients. The proportion of DRPs orders in children aged ≤5 years old was the highest （58.25%）， followed by children aged 6-12 years old （33.52%）； the department with the highest proportion of DRPs was internal medicine of pediatrics department （71.41%）； the department with the highest incidence of DRPs was thoracic surgery department （9.73%）； top three drug categories of DRPs orders were systemic anti- infective drugs （25.26%）， Chinese patent medicines （24.74%） and respiratory drugs （22.38%）. Referring to PCNE classification system， the types of DRPs mainly focused on treatment safety （64.86%）； the reasons of DRPs orders mainly focused on dose selection （82.09%）， of which 41.26% were due to excessive drug dosage； 92.13% of interventions could be accepted and fully executed by doctors. CONCLUSIONS DRPs orders identified by the pre-prescription review system can be effectively analyzed by using PCNE classification system. Pharmacists should focus on medication use in children aged ≤5 years old， update and develop personalized prescription review rules timely， and meet the rational needs of clinical medication for children.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

Two new coumarin glycosides were isolated and purified from the dichloromethane fraction of Angelica biserrata 75% ethanol extract using silica gel, Sephadex LH-20 column chromatography, and semi-preparative high-performance liquid chromatography. Through the comprehensive use of modern spectroscopic methods, their structures were identified as angelmanetin A (1) and angelmanetin B (2), respectively.

ObjectiveNeuroinflammation plays a crucial role in both the onset and progression of ischemic stroke, exerting a significant impact on the recovery of the central nervous system. Excessive neuroinflammation can lead to secondary neuronal damage, further exacerbating brain injury and impairing functional recovery. As a result, effectively modulating and reducing neuroinflammation in the brain has become a key therapeutic strategy for improving outcomes in ischemic stroke patients. Among various approaches, targeting immune regulation to control inflammation has gained increasing attention. This study aims to investigate the role of in vitro induced regulatory T cells (Treg cells) in suppressing neuroinflammation after ischemic stroke, as well as their potential therapeutic effects. By exploring the mechanisms through which Tregs exert their immunomodulatory functions, this research is expected to provide new insights into stroke treatment strategies. MethodsNaive CD4⁺ T cells were isolated from mouse spleens using a negative selection method to ensure high purity, and then they were induced in vitro to differentiate into Treg cells by adding specific cytokines. The anti-inflammatory effects and therapeutic potential of Treg cells transplantation in a mouse model of ischemic stroke was evaluated. In the middle cerebral artery occlusion (MCAO) model, after Treg cells transplantation, their ability to successfully migrate to the infarcted brain region and their impact on neuroinflammation levels were examined. To further investigate the role of Treg cells in stroke recovery, the changes in cytokine expression and their effects on immune cell interactions was analyzed. Additionally, infarct size and behavioral scores were measured to assess the neuroprotective effects of Treg cells. By integrating multiple indicators, the comprehensive evaluation of potential benefits of Treg cells in the treatment of ischemic stroke was performed. ResultsTreg cells significantly regulated the expression levels of both pro-inflammatory and anti-inflammatory cytokines in vitro and in vivo, effectively balancing the immune response and suppressing excessive inflammation. Additionally, Treg cells inhibited the activation and activity of inflammatory cells, thereby reducing neuroinflammation. In the MCAO mouse model, Treg cells were observed to accumulate in the infarcted brain region, where they significantly reduced the infarct size, demonstrating their neuroprotective effects. Furthermore, Treg cell therapy notably improved behavioral scores, suggesting its role in promoting functional recovery, and increased the survival rate of ischemic stroke mice, highlighting its potential as a promising therapeutic strategy for stroke treatment. ConclusionIn vitro induced Treg cells can effectively suppress neuroinflammation caused by ischemic stroke, demonstrating promising clinical application potential. By regulating the balance between pro-inflammatory and anti-inflammatory cytokines, Treg cells can inhibit immune responses in the nervous system, thereby reducing neuronal damage. Additionally, they can modulate the immune microenvironment, suppress the activation of inflammatory cells, and promote tissue repair. The therapeutic effects of Treg cells also include enhancing post-stroke recovery, improving behavioral outcomes, and increasing the survival rate of ischemic stroke mice. With their ability to suppress neuroinflammation, Treg cell therapy provides a novel and effective strategy for the treatment of ischemic stroke, offering broad application prospects in clinical immunotherapy and regenerative medicine.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

BackgroundNon-suicidal self-injury （NSSI） in adolescents is a serious global public health issue. Self-stigma is identified as a key factor hindering adolescents from seeking professional psychological help， while only a few studies have dealt with the self-stigma in adolescents with mood disorder exhibiting NSSI behavior. ObjectiveTo investigate the influencing factors of self-stigma among adolescents with mood disorder who exhibit NSSI behavior， and to examine the chained mediation role of self-esteem and social avoidance/distress in the relationship between NSSI behavior and self-stigma， with the aim of providing references for the detection and intervention of self-stigma in such patients. MethodsA total of 220 consecutive adolescent patients with mood disorder who met "the International Classification of Diseases， Tenth Edition"（ICD-10） diagnostic criteria for depressive disorder or depressive episode of bipolar disorder and attended the Fourth People's Hospital of Wuhu from November 2022 to November 2023 were recruited. The Adolescent Non-suicidal Self-injury Assessment Questionnaire （ANSAQ）， Internalized Stigma of Mental Illness （ISMI） Scale， Self-Esteem Scale （SES）， and Social Avoidance/Distress Scale （SADS） were employed to assess the participants. Correlation among variables was evaluated using Pearson's correlation coefficient. Multivariate linear regression analysis was utilized to identify the factors influencing self-stigma among adolescent patients with mood disorder exhibiting NSSI. The proposed mediating hypotheses were tested using Model 6 in the SPSS Process macro （version 3.0）. ResultsValid responses were received from 204/220 （92.73%） participants， including 153 cases with NSSI and 51 cases without NSSI. The NSSI （vs. no NSSI） group reported significantly higher scores on ISMI and SADS （t=-5.187， -4.564， P<0.01）， and lower scores on SES （t=4.478， P<0.01）. In the NSSI group， the total score of ISMI demonstrated a positive correlation with the total score of SADS and the behavioral questionnaire score in ANSAQ （r=0.644， 0.316， P<0.01）， and a negative correlation with the total score of SES （r=-0.724， P<0.01）. Multivariate linear regression analysis revealed that NSSI severity （β=0.132， P<0.05） and social avoidance/distress （β=0.309， P<0.01） were found to be positive predictors of the self-stigma， whereas self-esteem （β=-0.493， P<0.01） was a significant negative predictor of the self-stigma. Additionally， self-esteem and social avoidance/distress partially mediated the relationship between NSSI and self-stigma， with a mediating effect of 0.237 （95% CI： 0.103~0.374）， which constituted 55.89% of the total effect. The mediating effect included two paths： NSSI behavior→self-esteem→self-stigma （effect size was 0.163， 95% CI： 0.069~0.273） and NSSI behavior→self-esteem→social avoidance/distress→self-stigma （effect size was 0.063， 95% CI： 0.020~0.119）. ConclusionThe severity of NSSI can affect self-stigma in adolescents with mood disorders either directly through mediating self-esteem or indirectly through the chained mediation path of self-esteem and social avoidance/distress.［Funded by Scientific Research Projects of Wuhu Fourth People's Hospital in 2000（number，kjxm202203）］

OBJECTIVE To evaluate the effectiveness and safety of warfarin anticoagulation therapy guided by gene test in patients undergoing left ventricular assist device （LVAD） implantation， and to analyze the influencing factors of warfarin anticoagulation efficacy. METHODS Patients who underwent LVAD implantation at the Heart and Vascular Center of Northern Jiangsu People’s Hospital from January 2023 to October 2024 and required warfarin anticoagulant therapy were selected as the study subjects. They were divided into genetic testing group （n＝51） and empirical treatment group （n＝17） based on whether they underwent CYP2C9 and VKORC1 gene test. The gene test group was given warfarin based on the predicted dose calculated by gene test， while the empirical treatment group was given warfarin by clinical doctors based on international normalized ratio （INR） experience， all patients were given warfarin once a day. Follow-up observation was conducted for 6 months to compare the effectiveness [time in therapeutic range（TTR）， the time required to reach INR for the first time， the incidence of embolic events， the incidence of INR＜1.5 events] and safety （the incidence of major and minor bleeding events，the incidence of INR＞3.5 events） of warfarin treatment between two groups of patients. According to whether the patient’s TTR was ≥60%， they were divided into TTR≥60% group （n＝20） and TTR＜60% group （n＝48）. Univariate and multivariate binary Logistic regression analysis were used to determine the factors affecting the anticoagulant effect of warfarin in patients. RESULTS The TTR of patients in the gene test group was significantly higher than that in the empirical treatment group （P＜0.05）. The incidence of INR＜1.5 events in the gene test group was significantly lower than in the empirical treatment group （P＜0.05）. The incidence of minor bleeding events and INR＞3.5 events in the gene test group were lower than in the empirical treatment group， but the difference was not statistically significant （P＞0.05）. The results of multivariate binary Logistic regression analysis showed that gene test was an independent protective factor for warfarin anticoagulant therapy [odds ratio （OR）＝10.842， 95% confidence interval （CI）： 1.211-27.037， P＝0.033]， and the combination of statins was an independent risk factor for warfarin anticoagulant therapy [OR＝0.196， 95%CI： 0.045-0.861， P＝0.031]. CONCLUSIONS Under the guidance of gene test， warfarin anticoagulation therapy for LVAD patients after implantation can improve TTR， shorten the anticoagulation target time， and has good safety； meanwhile， it should be noted that the combination of statins may enhance the anticoagulant effect of warfarin， thereby increasing the risk of bleeding in patients.

Based on the principle of molecular hybridization, fifteen compounds were designed and synthesized through the combination of aminothiazoloxime and phosphonate fragment. The results showed that these compounds had better inhibitory effects on the tested bacteria. In particular, the activities of compounds Ⅲf and Ⅲi against S. aureus, E. coli, methicillin-resistant S. aureus (MRSA) and fluoroquinolone-resistant E. coli (FREC) were the most significant, the minimal inhibitory concentration (MIC) of Ⅲf was 1, 8, 4, 16 μg·mL^-1 respectively, and the MIC of Ⅲi was 4, 4, 16, 8 μg·mL^-1 respectively, which were slightly lower than that of the control drug oxacillin, and their anti-E. coli, MRSA and FREC activities were superior to that of the control drug oxacillin. Their activities to S. aureus were close to that of oxacillin, and to E. coli, MRSA and FREC were superior to that of oxacillin, which is worthy of further study.

Sulfur dioxide(SO2)is involved in regulating various physiological processes of blood vessels,such as maintaining normal vascular structure,regulating vascular tension,controlling blood pressure,inhibiting vascular cell proliferation,regulating apoptosis and autophagy.In pathophysiological conditions such as hypertension,pulmonary hypertension and atherosclerosis,SO2 plays a protective role in pathological changes through different molecular mechanisms.In this paper,we will review the endogenous SO2 production and metabolism,vascular biological effects and its regulation on blood vessels.