Objective To investigate the correlation between dual-energy computed tomography angiography(CTA)parameters of carotid plaques and acute stroke events.Methods A retrospective analysis was conducted on the clinical and imaging data of patients who underwent dual-energy head and neck CTA and brain MRI scans.Utilizing the Siemens workstation(Syngo.Via VB40B),region of interest(ROI)were placed on the thickest slice of the carotid plaque in the axial plane to obtain parameters such as fat fraction(FF),virtual non-contrast(VNC)value,iodine concentration(IC),electron density(Rho),effective atomic number(Zeff),dual energy index(DEI),spectral curve,and corresponding CT values at 40 keV(40 keVHU)and 90 keV(90 keVHU).The slope of the energy spectrum curve(λ)was calculated within the 40 keV-90 keV range.Patients with acute cerebral infarction(ACI)in the ipsilateral anterior circulation territory were classified into the ACI group,while those without were classified into the non-acute cerebral infarction(NACI)(NACI group).Qualitative data were analyzed using the x2 test,and quantitative data were analyzed using the t-test.The predictive performance was assessed using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve,and the differences between different ROC curves were compared using the DeLong test.Results A total of 72 patients were included,with 21 in the ACI group and 51 in the NACI group.The mean values of FF,Zeff,and 40 keVHU in the ACI group were greater than those in the NACI group.Statistically significant differences were observed between the groups for Zeff,DEI,40 keVHU,and λ(P＜0.05).40 keVHU demonstrated the highest predictive performance,and the AUC,sensitivity,and specificity was 0.789,81.0％,and 74.5％,respectively.A combined variable constructed through logistic regression analysis yielded an AUC,sensitivity,and specificity of 0.796,85.7％,and 70.6％,respectively,with no significant statistical differences compared to single factor variables.Conclusion Dual-energy CTA parameters of carotid plaques may aid in predicting intraplaque hemorrhage(IPH)and the occurrence of acute stroke events.

This paper aims to discuss the application value and progress of artificial intelligence (AI) in the diagnosis and treatment of gastrointestinal tumors and teaching practice of gastrointestinal oncology. Through a comprehensive analysis of the current clinical research status and literature, this paper summarizes the application practice and exploratory thinking of AI and deep learning technologies in gastrointestinal oncology. In diagnosis, AI technologies have improved the early detection and diagnosis efficiency for gastrointestinal tumors by optimizing medical image analysis, especially in the recognition of liver metastases. Applications of AI in pathological diagnosis include automatic recognition of tumor cells and tissue structure, as well as improving diagnostic sensitivity and specificity through feature extraction and pattern recognition. In treatment, the application scenarios of AI include rapid diagnosis, accurate staging, personalized treatment plan formulation, drug development, and surgical assistance. In surgical assistance, AI technology improves the safety and effectiveness of surgery through preoperative evaluation, surgical navigation, and postoperative evaluation. In teaching, AI technology facilitates knowledge acquisition and clinical skill enhancement of medical students by providing a multidisciplinary learning platform, simulating clinical environment and case details, and establishing a remote learning platform. The application of AI technology in teaching also includes deep learning and assessment feedback, providing personalized teaching and real-time assessment for students. This paper discusses the application prospects for AI technology in the teaching practice of gastrointestinal oncology. Although AI technology shows great potential in the diagnosis and treatment of gastrointestinal tumors and teaching gastrointestinal oncology, it also has limitations and needs to be combined with traditional teaching methods to achieve the best teaching results.

The chemical components of Carthami Flos were investigated by using macroporous resin, silica gel column chromatography, reversed-phase octadecylsilane(ODS) column chromatography, Sephadex LH-20, and semi-preparative high-performance liquid chromatography(HPLC). The planar structures of the compounds were established based on their physicochemical properties and ultraviolet-visible(UV-Vis), infrared(IR), high-resolution electrospray ionization mass spectrometry(HR-ESI-MS), and nuclear magnetic resonance(NMR) spectroscopic technology. The absolute configurations were determined by comparing the calculated and experimental electronic circular dichroism(ECD). Six flavonoid C-glycosides were isolated from the 30% ethanol elution fraction of macroporous resin obtained from the 95% ethanol extract of Carthami Flos, and identified as saffloquinoside F(1), 5-hydroxysaffloneoside(2), iso-5-hydroxysaffloneoside(3), isosafflomin C(4), safflomin C(5), and vicenin 2(6). Among these, the compounds 1 to 3 were new chalcone C-glycosides. The compounds 1, 2, 4, and 5 could significantly increase the viability of H9c2 cardiomyocytes damaged by oxygen-glucose deprivation/reoxygenation(OGD/R) at a concentration of 50 μmol·L~(-1), showing their good cardioprotective activity.
Glycosides/pharmacology* ; Flowers/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Carthamus tinctorius/chemistry* ; Chalcones/pharmacology* ; Animals

Objective:To describes the probability and rate of native liver survival (NLS) in biliary atresia (BA) patients after Kasai portoenterostomy (KPE)over various time periods and analyzes the perioperative factors associated with liver transplantation or death.Methods:A retrospective case-summary.BA patients administrated at the Department of Fetal and Neonatal Surgery in Hunan Children′s Hospital between January 2015 and December 2021.Probability and rate of NLS were calculated by life table.Cox proportional hazards regression model and Logistic model was applied to explore the perioperative factors related to post-Kasai liver transplantation/death.Results:The median age at Kasai surgery was 62 days.The rate of jaundice clearance (JC) was 64.5% within 3 months after Kasai, and 58.3% of the patients had cholangitis.The probability of NLS reached its lowest point in the first 1 year after Kasai (76.2%) and ranged from 93.2% to 98.0% in years 2-8 after Kasai.The rates of NLS in 2 years, 5 years and 8 years were 71.1%, 62.8% and 56.0%, respectively.Cytomegalovirus (CMV) infection before or on the day of Kasai without antiviral treatment can increase the risk of liver transplantation or death[ HR(95% CI): 1.628 (1.081-2.452), P=0.020].Preoperative gamma-glutamyl transferase increased the risk of liver transplantation/death within 1 year after Kasai[ OR(95% CI): 1.001 (1.000-1.001), P=0.021], and early cholangitis was a risk factor for liver transplantation/death within 5 years after Kasai[ OR(95% CI): 1.934 (1.004-3.726), P=0.048].JC within 3 months post-KPE was a protective factor of NLS. Conclusions:The first year after Kasai was the highest risk period for liver transplantation/death, which should be the focus of follow-up management.JC within 3 months after surgery is the protective factor for overall NLS, 1-year NLS and 5-year NLS.

This paper aims to discuss the application value and progress of artificial intelligence (AI) in the diagnosis and treatment of gastrointestinal tumors and teaching practice of gastrointestinal oncology. Through a comprehensive analysis of the current clinical research status and literature, this paper summarizes the application practice and exploratory thinking of AI and deep learning technologies in gastrointestinal oncology. In diagnosis, AI technologies have improved the early detection and diagnosis efficiency for gastrointestinal tumors by optimizing medical image analysis, especially in the recognition of liver metastases. Applications of AI in pathological diagnosis include automatic recognition of tumor cells and tissue structure, as well as improving diagnostic sensitivity and specificity through feature extraction and pattern recognition. In treatment, the application scenarios of AI include rapid diagnosis, accurate staging, personalized treatment plan formulation, drug development, and surgical assistance. In surgical assistance, AI technology improves the safety and effectiveness of surgery through preoperative evaluation, surgical navigation, and postoperative evaluation. In teaching, AI technology facilitates knowledge acquisition and clinical skill enhancement of medical students by providing a multidisciplinary learning platform, simulating clinical environment and case details, and establishing a remote learning platform. The application of AI technology in teaching also includes deep learning and assessment feedback, providing personalized teaching and real-time assessment for students. This paper discusses the application prospects for AI technology in the teaching practice of gastrointestinal oncology. Although AI technology shows great potential in the diagnosis and treatment of gastrointestinal tumors and teaching gastrointestinal oncology, it also has limitations and needs to be combined with traditional teaching methods to achieve the best teaching results.

Objective:Based on the best evidence, formulate the review indicators to promote the initiation and establishment of maternal lactation and carry out clinical review, analyze the barriers and promoting factors of the clinical application of evidence, and formulate countermeasures.Methods:Evidence-based nursing research was used to identify clinical problems, build evidence-based group, systematically search, evaluate and synthesize evidence. On September 1,2023 to December 31 in Affiliated Hospital of Jiangsu University document and delivery of maternal investigation, in Ottawa research application mode as a guide, based on the evidence to review indicators and review method, clear clinical status and evidence gap, combined with the stakeholders interview, using content analysis to analyze barriers and promoting factors, to formulate action countermeasures.Results:In this study, 140 pregnant women were finally included for clinical review, aged from 22 to 42 (30.13 ± 3.69) years. A total of 23 pieces of best evidence were incorporated, leading to the establishment of 29 review indicators. Among these, 20 review indicators showed compliance rates below 60%. The main obstacles based on the results of review and interviews with stakeholders: the evidence content covered perinatal stages but lacked specificity and practical applicability; nurses had insufficient knowledge and faced increased workloads; pregnant/postpartum women lacked essential knowledge and skills, with delayed resolution of lactation issues; the practice environment lacked evidence-based implementation protocols, specialized assessment tools, and professional lactation consultant teams, etc. Promoting factors: the project team had rich experience in evidence transformation; the reform aligned with national policies, high engagement from departmental leaders, and standardized management systems for evidence-based projects in the nursing department; strong motivation among pregnant/postpartum women; the hospital was an infant-friendly hospital with talents needed for evidence transformation.Conclusions:There is a big gap between the clinical status and the evidence of promoting the initiation and establishment of lactation, so nursing staff should make full use of the promoting factors and formulate countermeasures according to the obstacle factors, so as to provide reference for promoting the initiation of lactation and the establishment of relevant evidence to clinical transformation.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

The Guidelines for Occupational Hazard Assessment and Control of Active Pharmaceutical Ingredient in the Pharmaceutical Industry (T/WSJD 60—2024) is the first guiding standard in the field of health in China that focuses on occupational health protection for active pharmaceutical ingredient (API). It covers the general principles, work procedures, assessment methods, and control strategies for API occupational hazard assessment, providing practical guidance and recommendations for pharmaceutical enterprises to eliminate or reduce occupational health risks associated with API, improve working environment, and enhance refined management practices. This article interpreted and analyzed the background of standard establishment, formulation process, fundamental basis, and main content, to provide scientific and comprehensive technical support for occupational health managers in the pharmaceutical industry to better apply this standard.