ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.

ObjectiveThis study aims to investigate the effects of different sizes of seedlings and melatonin treatment on physiological and biochemical indicators and bolting-related gene expression in Angelica sinensis， find substances related to early bolting， and elucidate the inhibitory mechanism of melatonin on bolting. MethodsSpectrophotometry was used to detect the related enzyme activities of A. sinensis leaves. The contents of endogenous hormones and polyamines were detected using ultra-high performance liquid chromatography-tandem mass spectrometry. Real-time polymerase chain reaction （Real-time PCR） was used to detect the expression levels of bolting-related genes. Inter-group differential indicator analysis， orthogonal partial least squares discriminant analysis， and principal component analysis were comprehensively applied to identify factors related to early bolting. ResultsEndogenous jasmonic acid and melatonin were identified as the most important factors affecting early bolting. Secondly， the activity of antioxidant enzymes， abscisic acid content， gibberellin content， and the expression levels of CO3， HD3A， and FD genes had important effects on the bolting process. Compared with small seedlings， exogenous melatonin treatment mainly inhibited early bolting by increasing endogenous melatonin content， reducing gibberellin content， and decreasing the expression levels of SOC1 and FD genes. ConclusionExogenous melatonin can inhibit early bolting in A. sinensis by regulating its physiological， biochemical， and gene expression levels.

With the continuous development of society, a large number of new chemicals are continuously emerging, which presents a challenge to current risk assessment and safety management of chemicals. Traditional toxicology research methods have certain limitations in quickly, efficiently, and accurately assessing the toxicity of many chemicals, and cannot meet the actual needs. In response to this challenge, computational toxicology that use mathematical and computer models to achieve the prediction of chemical toxicity has emerged. In the meantime, as researchers increasingly pay attention to understanding the interaction mechanisms between exogenous chemical substances and the body from the system level, and multiomics technologies develop rapidly such as genomics, transcriptomics, proteomics, and metabolomics, huge amounts of data have been generated, providing rich information resources for studying the interactions between chemical substances and biological molecules. System toxicology and network toxicology have also developed accordingly. Of these, network toxicology can integrate these multiomics data to construct biomolecular networks, and then quickly predict the key toxicological targets and pathways of chemicals at the molecular level. This paper outlined the concept and development of network toxicology, summarized the main methods and supporting tools of network toxicology research, expounded the application status of network toxicology in studying potential toxicity of exogenous chemicals such as agricultural chemicals, environmental pollutants, industrial chemicals, and foodborne chemicals, and analyzed the development prospects and limitations of network toxicology research. This paper aimed to provide a reference for the application of network toxicology in other fields.

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 establish a interview outline design process and quality control evaluation method based on grounded theory， providing ideas for qualitative research interview outline design in medical fields. METHODS A literature review was conducted to understand the current research status； a preliminary interview outline was developed around the research content. The triangulation method， group evaluation， expert review and pre-interview were adopted to execute the interview outline and conduct quality control. The evaluation indicators and target values were formulated （an average score for the overall quality evaluation of all indicators ≥4.5， and an average score for individual indicators ≥4.00） to evaluate the effect of the interview outline. Taking the research on the mechanism of physicians’ prescribing behavior under the background of Diagnosis Related Groups （DRGs） payment as an example， the methodological contents of above interview outline were applied in practical research. RESULTS The interview outline included basic information and interview questions. The interview questions were divided into three parts：influencing factors survey， promoting and hindering factors of standardizing physician prescription behavior， and communication， with a total of 12 questions. After being reviewed by members of the research group， experts review and pre- interview， a total of 9 people participated in the quality control evaluation of the interview outline. The overall evaluation score was 4.94 （＞4.50）， and the average score of each indicator was greater than 4.00， indicating that the quality of the outline met the requirements for the interview and could be used for the formal interview. CONCLUSIONS The established interview outline design and quality control method based on grounded theory provides ideas for the qualitative research interview outline design in the medical field， and lays the foundation for further using grounded theory to study the influencing factors and mechanisms of physician prescription behavior under the DRG background.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Objective To campare biomechanical effects of different postural compression techniques on three-dimensional model of lumbar disc herniation(LDH)by finite element analysis.Methods Lumbar CT image of a 48-year-old female patient with LDH(heighted 163 cm,weighted 53 kg)was collected.Mimics 20.0,Geomagic Studio,Solidwords and other software were used to establish three-dimensional finite element model of LDH on L4,5 segments.Compression techniques under horizon-tal position,30° forward bending and 10° backward extension were simulated respectively.After applying the pressure,the ef-fects of compression techniques under different positions on stress,strain and displacement of various tissues of intervertebral disc and nerve root were observed.Results L4,5 segment finite element model was successfully established,and the model was validated.When compression manipulation was performed on the horizontal position,30° flexion and 10° extension,the annular stress were 0.732,5.929,1.286 MPa,the nucleus pulposus stress were 0.190,1.527,0.295 MPa,and the annular strain were 0.097,0.922 and 0.424,the strain sizes of nucleus pulposus were 0.153,1.222 and 0.282,respectively.The overall displace-ment distance of intervertebral disc on Y direction were-3.707,-18.990,-4.171 mm,and displacement distance of nerve root on Y direction were+7.836,+5.341,+3.859 mm,respectively.The relative displacement distances of nerve root and interverte-bral disc on Y direction were 11.543,24.331 and 8.030 mm,respectively.Conclusion Compression manipulation could make herniated intervertebral disc produce contraction and retraction trend,by increasing the distance between herniated interverte-bral disc and nerve root,to reduce symptoms of nerve compression,to achieve purpose of treatment for patients with LDH,in which the compression manipulation is more effective when the forward flexion is 30°.

Objective To investigate the efficacy and safety of hybrid surgery for the recanalization of carotid artery occlusion after stenting.Methods Clinical data and results of 17 patients with occlusion after carotid artery stenting and treated with hybrid surgery from June 2016 to April 2023 at the Department of Neurosurgery Cerebral Blood Flow Reconstruction Center of Xuanwu Hospital,Capital Medical University were retrospectively analyzed.According to whether the recanalization was successful,17 patients were divided into the the successful recanalization group and the failed recanalization group.Successful recanalization was defined as achieving modified thrombolysis in cerebral infarction(mTICI)grade ≥2b and residual stenosis＜50％.Baseline data(age,sex,body mass index,smoking history,alcohol consumption history,hypertension history,diabetes history,hyperlipidemia history,coronary heart disease history),clinical data(National Institutes of Health Stroke Scale[NIHSS]score at admission,fasting blood glucose,low density lipoprotein,high density lipoprotein,total cholesterol,triglyceride,occlusion side and segment,combination with severe stenosis or occlusion of the contralateral carotid artery,opening of the anterior communicating artery,opening of the posterior communicating artery,compensation of the external and internal carotid artery,compensation of the pia artery,stump morphology,and time from imaging diagnosis of occlusion to recanalization)were documented and compared between groups.The recanalization of occlusive vessels and perioperative complications were recorded.Imaging and clinical follow-up were performed 3,6 months and≥1 year after surgery.Results Among the 17 patients,the ratio of successful recanalization was 13/17.One patient had re-occlusion after operation,which was re-opened after thrombolysis,but neck hematoma with dyspnea occurred,and recovered after emergency operation.There was no postoperative stroke or death.The incidence of perioperative complications was 1/17.Compared with the successful recanalization group,the levels of high density lipoprotein and total cholesterol in the failed recanalization group were higher,and the differences between the groups were statistically significant(high density lipoprotein[1.3±0.3]mmol/L vs.[0.9±0.3]mmol/L,t=-2.139;total cholesterol:[4.2±0.8]mmol/L vs.[3.1±0.7]mmol/L,t=-2.649;both P＜0.05);There were no significant differences in other baseline data and clinical data(all P＞0.05).Imaging follow-up was completed in 9 of the 13 patients in the successful recanalization group,and the follow-up time was 3.8-36.9 months,with a median follow-up time of 22.8(12.8,34.7)months.Among them,1 patient(1/9)developed restenosis of recanalization vessels at 33.0 months after surgery and underwent stent implantation again.Conclusions The preliminary analysis showed that the occlusion after carotid artery stenting had better recanalization success and lower perioperative complications.In patients with chronic occlusion after carotid stenting,the application of a hybrid surgery for opening may be attempted under multimodal imaging assessment.

Objective:To investigate the safety and efficacy of mitoxantrone liposome in the treatment of children with high-risk acute myeloid leukemia(AML).Methods:The children with high-risk AML who received the mitoxantrone liposome regimen at Wuhan Children's Hospital from January 2022 to February 2023 were collected as the observation group,and the children with high-risk AML who received idarubicin regimen were enrolled as controls,and their clinical data were analyzed.Time to bone marrow recovery,the complete remission rate of bone marrow cytology,the clearance rate of minimal residual disease,and treatment-related adverse reactions were compared between the two groups.Results:The patients treated with mitoxantrone liposome showed shorter time to recovery of leukocytes(17 vs 21 day),granulocytes(18 vs 24 day),platelets(17 vs 24 day),and hemoglobin(20 vs 26 day)compared with those treated with idarubicin,there were statistical differences(P＜0.05).The effective rate and MRD turning negative rate in the observation group were 90.9％and 72.7％,respectively,while those in the control group were 94.1％and 76.4％,with no statistical difference(P＞0.05).The overall response rate of the two groups of patients was similar.Conclusion:The efficacy of mitoxantrone liposome is not inferior to that of idarubicin in children with high-risk AML,but mitoxantrone liposome allows a significantly shorter duration of bone marrow suppression and the safety is better.

Objective:To investigate the expression and clinical significance of CD30 in patients with diffuse large B-cell lymphoma(DLBCL).Methods:A retrospective analysis was conducted on 124 cases of primary DLBCL diagnosed at Changzhou Second People's Hospital Affiliated with Nanjing Medical University from January 2018 to July 2020.The expression of CD30 in patients with DLBCL was detected by immunohistochemical method,and the clinicopathological characteristics were analyzed and compared between CD30+and CD30-groups.Kaplan-Meier analysis was used for survival analysis.The relationship between CD30 expression and clinical features and prognosis were analyzed.Results:Among the 124 patients with DLBCL,19 patients expressed CD30,and the positive rate is 15.32％.The clinico-pathological characteristics of CD30+in patients with DLBCL were characterized by low age,more common in males,fewer extranodal lesions,lower international prognostic index(IPI),GCB type being more common in Hans subtype,and achieving better therapeutic effects(P＜0.05).However,there were no significant statistical differences in B-symptoms(P=0.323),Ann Arbor staging(P=0.197),Eastern Cooperative Oncology Group(ECOG)score(P=0.479),lactate dehydrogenase(LDH)(P=0.477),and the involvement of bone marrow(P=0.222).There were significant differences in OS and PFS between the CD30+and CD30-groups(x2=5.653,P=0.017;x2=4.109,P=0.043),the CD30+group had a better prognosis than that of the CD30-group.The results of subgroup analysis showed that the CD30+group in the IPI score=1-2,LDH elevated group had a better prognosis(P＜0.05).In the subgroups of Ann Arbor staging Ⅲ-Ⅳ(P=0.055)and non GCB type(P=0.053),the CD30+group had a good prognosis trend,but the difference was not statistically significant.The results of univariate analysis showed that the good prognosis of DLBCL patients was closely related to CD30+expression,no B-symptoms,early Ann Arbor staging,low ECOG score,normal LDH,low IPI score,fewer extranodal involvement,and obtaining the best therapeutic effect as CR(all P＜0.05).COX multivariate regression analysis showed that the presence of B-symptoms and achieving the best therapeutic effect as Non-CR were independent risk factors affecting the prognosis of DLBCL patients(P＜0.05).Conclusion:The CD30+expression in DLBCL patients indicates a good prognosis and has certain diagnostic value in evaluating the prognosis of DLBCL patients.