Objective:To analyze the clinical features and long-term prognosis of ANCA-associated vasculitis (AAV) patients with different onset ages.Methods:A total of 243 patients diagnosed with AAV at the First Affiliated Hospital to Nanjing Medical University from May 2009 to January 2025 were retrospectively analyzed. The patients were divided into the elderly group (age≥60 years old) and middle-aged and young patient group (age<60 years old) according to the age of onset. The baseline clinical characteristics and long-term prognosis of the two groups were compared, and the risk factors for progression to end-stage renal disease (ESRD) in elderly AVV patients were analyzed. The clinical characteristics and long-term prognosis of the two groups of patients were compared. The measurement data were analyzed by t-test or rank sum test, and the count data were analyzed by chi-square test. The risk factors for the progression of ESRD in elderly patients with AAV were analyzed by binary multivariate logistic regression. Results:A total of 243 AAV patients were included, among which 174 cases were microscopic polyangiitis (MPA) and 69 cases were granulomatosis with polyangiitis (GPA). In 157 elderly patients, with 72 cases female, 84.1%(132 cases) had MPA. Compared with young and middle-aged patients, renal involvement is more common in elderly patients with AAV [(eldrly group 133 cases, 84.7%) vs. middle-aged and young patient group: 61 cases(70.9%), χ2=6.557, P=0.010]. The proportion of patients with hypertension, thrombosis, stroke, coronary heart disease, and COPD was higher compared to non-elder patients ( P<0.05). Elderly patients with AAV have higher levels of IgA and serum creatinine. Kaplan-Meier survival analysis showed that compared with young and middle-aged patients, elderly AAV patients had a higher all-cause mortality rate within 1 year after disease onset and a higher risk of progressing to ESRD within 1 year ( P<0.05), while the levels of IgM, C3, C4, albumin, and hemoglobin were lower ( P<0.05). 86 patients were middle-aged and young patients, with 54 cases were female and 51.2%(44 cases) had GPA. Ear, nose, and throat involvement was more common than elder patients[elderly group: 26 cases(16.2%) vs. middle-aged and young patient group: 31 cases(36.0%), χ2=10.864, P=0.001]. The median follow-up duration was 18 (7, 60) months. Kaplan-Meier survival analysis showed that compared with middle-aged and young patients, elderly AVV patients had a higher all-cause mortality rate within 1 year after disease onset and a higher risk of progression to ESRD within 1 year ( P<0.05). Multivariate logistic regression analysis revealed that baseline serum creatinine level [ OR(95% CI)=1.008(1.003, 1.012), P<0.001] was an independent risk factor for progression to ESRD in elderly patients. Conclusion:Elderly patients with AAV have more severe organ damage, higher all-cause mortality within one year, and a higher risk of progression to ESRD within one year after disease onset close monitoring of high-risk elderly patients should be strengthened.

OBJECTIVE: To explore the feasibility of establishing a temporary trauma team led by trauma experts in primary hospitals for disaster medical rescue. METHODS: In the coal mine flooding accident in Xiaoyi City, Shanxi Province on December 15, 2021, according to the local emergency plan and the characteristics of the accident, the trauma experts trained the medical staff from the local primary hospital on advanced trauma life support (ATLS) and damage control surgery (DCS) in the short time interval between the occurrence of the mine disaster and the admission of medical staff to the disaster scene. A temporary trauma team composed of trauma experts, ATLS team, and DCS team was formed to provide early diagnosis and treatment for survivors before and in the hospital. RESULTS: The miners were found on the 36th hour of the disaster. All 22 miners were male, and 2 died underground. Another 20 people were rescued 39－43 hours after the disaster, with a median age of 48 years (34-57 years). All the survivors suffered from hypothermia, dehydration, maceration of feet and other injuries. There were 18 cases of acute inhalation tracheobronchitis, 14 cases of electrolyte acid-base disturbance, 6 cases of trunk contusion, 1 case of psoas major hematoma, and 1 case of lower extremity hematoma. Deep vein thrombosis was in 4 cases. The ATLS team focused on injury assessment, rewarming and rehydration within 50－60 minutes before admission, and completed auxiliary examinations within 2 hours after admission to clarify the diagnosis. The DCS team evaluated 6 patients with mechanical blunt trunk injury and excluded the indication of emergency surgery. The trauma experts conducted the whole process of supervision and quality control of disaster rescue. The positive rate of capillary refill test in the all survivors at the third hour of admission was significantly lower than that immediately after being rescued (75.0% vs. 15.0%, P=0.000 3), and they were discharged 4－7 days after admission. CONCLUSION Under the leadership of trauma experts and relying on the medical staff of primary hospitals, it is feasible to establish and train a temporary trauma team with ATLS and DCS functions to participate in the medical rescue of disasters, which is in line with the current national conditions of China.
Humans ; Adult ; Middle Aged ; Male ; Rescue Work/organization & administration* ; China ; Disasters ; Patient Care Team/organization & administration* ; Wounds and Injuries/therapy* ; Advanced Trauma Life Support Care/organization & administration* ; Disaster Planning/organization & administration* ; Emergency Medical Services/organization & administration*

"Weibing" is a fundamental concept in traditional Chinese medicine (TCM), representing a transitional state characterized by diminished self-regulatory abilities without overt physiological or social dysfunction. This perspective delves into the biological foundations and quantifiable markers of Weibing, aiming to establish a research framework for early disease intervention. Here, we propose the "Health Quadrant Classification" system, which divides the state of human body into health, sub-health, disease-susceptible state, and disease. We suggest the disease-susceptible stage emerges as a pivotal point for TCM interventions. To understand the intrinsic dynamics of this state, we propose laboratory and clinical studies utilizing time-series experiments and stress-induced disease susceptibility models. At the molecular level, bio-omics technologies and bioinformatics approaches are highlighted for uncovering intricate changes during disease progression. Furthermore, we discuss the application of mathematical models and artificial intelligence in developing early warning systems to anticipate and avert the transition from health to disease. This approach resonates with TCM's preventive philosophy, emphasizing proactive health maintenance and disease prevention. Ultimately, our perspective underscores the significance of integrating modern scientific methodologies with TCM principles to propel Weibing research and early intervention strategies forward.

Computational approaches for predicting drug-target interactions (DTIs) are pivotal in advancing drug discovery. Current methodologies leveraging heterogeneous networks often fall short in fully integrating both local and global network information. To comprehensively consider network information, we propose DHGT-DTI, a novel deep learning-based approach for DTI prediction. Specifically, we capture the local and global structural information of the network from both neighborhood and meta-path perspectives. In the neighborhood perspective, we employ a heterogeneous graph neural network (HGNN), which extends Graph Sample and Aggregate (GraphSAGE) to handle diverse node and edge types, effectively learning local network structures. In the meta-path perspective, we introduce a Graph Transformer with residual connections to model higher-order relationships defined by meta-paths, such as "drug-disease-drug", and use an attention mechanism to fuse information across multiple meta-paths. The learned features from these dual perspectives are synergistically integrated for DTI prediction via a matrix decomposition method. Furthermore, DHGT-DTI reconstructs not only the DTI network but also auxiliary networks to bolster prediction accuracy. Comprehensive experiments on two benchmark datasets validate the superiority of DHGT-DTI over existing baseline methods. Additionally, case studies on six drugs used to treat Parkinson's disease not only validate the practical utility of DHGT-DTI but also highlight its broader potential in accelerating drug discovery for other diseases.

Objective:To investigate the risk of hospital death in patients with traumatic hemorrhagic shock combined with multiple organ dysfunction syndrome(MODS)predicted by discriminant analysis.Methods:This study was a single-center retrospective study. From January 2013 to May 2023, patients with traumatic hemorrhagic shock complicated with MODS admitted to Peking University People's Hospital were selected as the research objects. According to the in-hospital survival, the patients were divided into survival group (205 cases) and death group (29 cases). The general condition, injury assessment, laboratory indexes, complications and clinical scores of the two groups were compared. Wilks's Lambda stepwise discriminant analysis was used to establish a discriminant model for in-hospital death in patients with traumatic hemorrhagic shock combined with MODS. the Receiver operating characteristic curve (ROC) was drawn and the Area under the curve (AUC) was calculated. The cross-validation method was used to evaluate the accuracy of the prediction results of the established model.Results:There was a statistical difference between the survival group and the death group in terms of the main bleeding site (limbs), the time from injury to hospital admission, temperature, platelet count, prothrombin time, activated partial thrombin time, fibrinogen, albumin, serum creatinine, estimated glomerular filtration rate, uric acid, cardiac troponin I, procalcitonin, base excess, lactate to albumin ratio, glucose to albumin ratio, acute respiratory distress syndrome, acute kidney injury, acute myocardial injury, traumatic induced coagulopathy, ISS, APACHEⅡ score and SOFA scores. There are four indicators entering the final discrimination model: Prothrombin time, ISS score, estimated glomerular filtration rate, lactate to albumin ratio. The AUC for predicting the risk of death in patients with traumatic hemorrhagic shock combined with MODS was 0.791, and the 95% CI was 0.671 to 0.911. Conclusions:The established discriminant model is highly accurate in predicting the risk of hospital death in patients with traumatic hemorrhagic shock complicated with MODS. Prothrombin time, ISS score, estimated glomerular filtration rate and lactate to albumin ratio were associated with an increased risk of death from traumatic hemorrhagic shock with MODS.

AIM:To investigate the potential mechanism of licorice on liver injury induced by Se-men Strychni based on network pharmacology,mo-lecular docking combined with animal experiments,providing an effective strategy for prevention and treatment of liver injury induced by Semen Strych-ni.METHODS:Firstly,the active ingredients of Se-men Strychni and licorice were obtained through the ETCM,TCMSP database and analysis platform,CTD database and literature supplementation.Then,the potential toxic ingredients of Semen Strychni were further screened based on the Swis-sADME platform,and the targets corresponding to the active ingredients were predicted through the SwissTargetPrediction platform.By using the Gene-Cards and OMIM databases to collect DILI-related targets,the potential targets for licorice to alleviate liver injury caused by Semen Strychni were ob-tained.By constructing the active ingredient-target network,the core ingredients of licorice in alleviat-ing liver injury caused by Semen Strychni were screened.The key targets obtained were used to construct and analyze the protein-protein interac-tion networks(PPI)through the STRING database and Cytoscape 3.9.0 software.The potential targets were subjected to GO and KEGG pathway enrich-ment analysis with the aid of the DAVID database,and constructed a network of active ingredient-tar-get-pathway.Molecular docking study was ap-proved for the core targets and the active ingredi-ents by using Schrodinger 2023-1 software,and the visualization operation was conducted through Py-mol.Finally,the regulatory effect of licorice on the key pathway of liver injury caused by Semen Strych-ni was validated by establishing a rat model of liver injury induced by Semen Strychni.RESULTS:After screening,6 potential toxic components of Semen Strychni and 104 corresponding targets,89 active components of licorice and 347 corresponding tar-gets,and 3 200 DILI targets were obtained.A total of 23 intersection targets were obtained through Venn analysis.By constructing the active ingredi-ent-target network,it was found that the main core ingredients were 7-methoxy-2-methyl isofla-vone,medicarpin,shinpterocarpin,quercetin,for-mononetin and isoliquiritigenin.The PPI network indicated that the core targets were protein kinase B1(AKT1),epidermal growth factor receptor(EG-FR),human epidermal growth factor receptor 2(ERBB2),glycogen synthase kinase 3 beta(GSK3B),kinase insert domain receptor(KDR)and Janus ki-nase 2(JAK2).A total of 39 relevant pathways were enriched in KEGG(P＜0.01),among which the phos-phatidylinositol 3-kinase(PI3K)-protein kinase B(AKT)(PI3K-AKT)signaling pathway,which has been confirmed and ranks first in enrichment,and was closely related to liver injury.Molecular docking re-sults showed that the core components have good binding ability with the core targets.In vivo animal experiments demonstrated that,compared to the model group,licorice significantly reduced the liver index(P＜0.01),serum levels of alkaline phospha-tase(ALP),alanine aminotransferase(ALT),aspar-tate aminotransferase(AST),indirect bilirubin(IBIL),and total bilirubin(TBIL)in rats with liver in-jury,while increasing total protein(TP)levels(P＜0.05 or P＜0.01).Additionally,licorice alleviated con-gestion in the central veins and hepatic sinusoids,improved the alignment of hepatocytes,and re-duced inflammatory cell infiltration.Furthermore,licorice significantly decreased the levels of malo-ndialdehyde(MDA),tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),and interleukin-6(IL-6)in the liver tissue of injured rats,while elevating the levels of superoxide dismutase(SOD)and glutathi-one peroxidase(GSH-Px)(P＜0.01).It also markedly downregulated the phosphorylation levels of PI3K and AKT(P＜0.01).CONCLUSION:Licorice has multi-component and multi-target properties in the treat-ment of liver injury induced by Semen Strychni,which may play a hepatoprotective role by inhibit-ing the activation of PI3K-AKT signaling pathway.

Objective To investigate the expression levels and clinical significance of type Ⅰ innate lymphoid cells(ILC1s),T-box transcription factor(T-bet),interleukin(IL)-12,IL-18 and interferon-gamma(IFN-γ)in peripheral blood of patients with primary immune thrombocytopenia(ITP).Methods Thirty-five ITP patients with their first episode were selected as the initial treatment group.Thirteen of these patients were followed up after receiving treatment.Additionally,20 healthy individuals underwent routine physical examinations during the same period were recruited as the control group.Peripheral blood samples were collected for analysis.The proportion of ILC1s was determined by flow cytometry.T-bet mRNA expression was measured using quantitative real-time PCR(qRT-PCR).Serum levels of IL-18,IL-12 and IFN-γ were quantified by enzyme-linked immunosorbent assay(ELISA).The differences in ILC1s proportion,T-bet mRNA expression and cytokine levels were compared between groups.Correlations between ILC1s proportion,T-bet mRNA,cytokine levels and platelet(PLT)counts were also analyzed.Results Compared with the control group,the initial treatment group exhibited significantly elevated levels of peripheral ILC1s,T-bet mRNA and serum IL-18,IL-12 and IFN-γ(P＜0.05).Among the 13 patients who were followed up,all these indices decreased significantly after treatment(P＜0.05).Correlation analysis revealed that the proportion of ILC1s in the initial treatment group was positively correlated with IL-12,IL-18,IFN-γ and T-bet mRNA levels(rs=0.666,0.647,0.677,and 0.750,respectively,P＜0.01),and negatively correlated with PLT count(rs=-0.637,P＜0.01).Conclusion Innate immunity may play a role in the pathogenesis and progression of ITP by regulating the expression levels of ILC1s,T-bet,IL-12,IL-18 and IFN-γ.

Objective To explore and address the issue of insufficient segmentation accuracy in liver tumor segmentation using the traditional U-Net algorithm,which is caused by the lack of contextual information for both the liver and tumor,as well as the large morphological variability of tumors.Methods A cascaded liver tumor segmentation algorithm,DDR-UNet++,which integrated dilated convolutions and residual modules was proposed.Firstly,CT images from the LiTS-2017 dataset were preprocessed through window width/level adjustment,histogram equalization and Gaussian filtering to reduce noise and smooth edges.Then,a cascaded liver segmentation model was employed to enhance the liver region proportion,mitigate interference from surrounding tissues and address data imbalance issue.For liver tumor segmentation,deformable dilated convolutions and residual networks were introduced to expand the receptive field and improve feature extraction capability.Results DDR-UNet++outperformed the traditional U-Net on the LiTS-2017 dataset,achieving improvements of 4.7%,1.7%,and 8.5%in Dice similarity coefficient,relative volume difference,and Jaccard index,respectively.These enhancements contribute to overcoming the inefficiency and low accuracy issues in conventional tumor segmentation,thereby improving early tumor detection rates,enhancing patient survival outcomes,and alleviating the diagnostic burden on clinicians.Conclusion The proposed method improves the feature extraction capability to some extent by enhancing the model structure and segmentation strategy,effectively increases the accuracy and robustness of liver tumor segmentation,and provides a reliable technical reference for clinical auxiliary diagnosis.

Objective To investigate the effects of Jiawei Ditan Decoction on neurological function,pentraxin-3(PTX-3),and vascular endothelial growth factor(VEGF)in patients with post-ischemic stroke cognitive impairment(PSCI).Methods A total of 97 patients with PSCI who were admitted to Xuzhou Central Hospital from March 2022 to March 2024 were enrolled and randomly assigned to control group(n=48)or decoction group(n=49)using the envelope drawing method.The control group received conventional treatment,while the decoction group was additionally treated with Jiawei Ditan Decoction.Clinical efficacy,Traditional Chinese Medicine(TCM)syndrome scores,cognitive and functional assessments,laboratory markers,and oxidative stress levels were compared between the two groups.Results The total effective rate in the decoction group was significantly higher than that in the control group(P<0.05).At 3 and 6 months after treatment,TCM syndrome scores in the decoction group were lower than those in the control group(P<0.05).The scores of the Montreal cognitive assessment(MoCA),mini-mental state examination(MMSE),and Barthel index(BI)in the decoction group were higher than those in the control group at 3 months after treatment,while the National Institutes of Health stroke scale(NIHSS)score in the decoction group was lower than that in the control group(P<0.05).At 1 month after treatment,PTX-3 and hypersensitive C-reactive protein(hs-CRP)levels in the decoction group were lower than those in the control group,while VEGF,superoxide dismutase(SOD),glutathione peroxidase(GSH-Px),and nitric oxide(NO)levels in the decoction group were higher than those in the control group(P<0.05).Conclusion Jiawei Ditan Decoction exhibits significant effects on improving neurological function and modulating PTX-3 and VEGF levels in patients with PSCI.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.
Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Deep Learning ; Diagnostic Imaging/methods*