Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective:To analyze the epidemiological, etiological characteristics and transmission of an imported D8 genotype measles case in a child in Shandong Province, August 2023.Methods:A study was conducted on a measles case and 16 contacts in Shandong Province in August 2023. Field epidemiological surveys, including recent exposure and immunization history, were conducted. Serum and throat swab samples were collected from all 16 subjects. Measles IgM and IgG antibody levels and avidity were measured by ELISA, while virus detection and genotyping were performed using fluorescence quantitative PCR and RT-PCR. Genetic evolutionary analysis of the obtained sequences was conducted using MEGA and Beast software.Results:The case was an 11-year-old boy, a fifth-grade student, who developed symptoms on August 28, 2023. A total of five close contacts were investigated, including three family members (grandfather, father and sister) and two playmates. Additionally, 11 classmates who had close contact with the case′s sister during the infectious period (within five days after the rash onset) were also investigated. Among the 16 serum samples tested, only one case was positive for IgM, while the other 15 samples were negative for IgM. The results of the serum antibody avidity test showed that among the 16 serum samples, 14 were positive for IgG. Of these, eight had a relative avidity index >55%, indicating high-avidity antibodies; one had a relative avidity index <45%, indicating low-avidity antibodies; and five had an avidity index between 45% and 55%. The IgG detection OD values for the case′s sister and grandfather were higher than those of the other contacts. Based on the vaccination history of the subjects and the results of IgM and IgG tests, it was preliminarily determined that the case had a recent wild-type measles virus infection. The case′s sister and grandfather had a history of measles wild-type virus infection, while the high-avidity antibodies in the other contacts were likely induced by the measles vaccine. The results of the pharyngeal swab tests showed that only the case was positive for measles virus nucleic acid, while the remaining 15 samples were negative for measles virus. The genetic evolutionary analysis revealed that the viral sequence of this case (Mvs/Shandong.CHN/38.23) had a 100% homology with the Hong Kong strain sequence from August 2023. It belonged to a different transmission chain from the D8 genotype strains that appeared in Shandong Province between 2018 and 2019, with sequence homology ranging from 98.0% to 98.8%. The sequence homology within the transmission chain of this case was between 99.1% and 100%. The evolutionary rate of this transmission chain was approximately 8.38×10 -3 sub/site/year, and the most recent common ancestor was estimated to have emerged around the year 2011. Conclusion:This case is the first imported D8 genotype measles case in Shandong Province. There is no spatio-temporal correlation between this case and adult cases of D8 genotype imported from Shandong Province in 2018-2019, indicating a new D8 genotype imported epidemic.

Objective To observe the value of conventional MRI and diffusion weighted imaging(DWI)for differentiating soft tissue lymphoma(STL)and soft tissue sarcoma(STS).Methods Conventional MRI and DWI data of 25 cases of STL(STL group)and 38 cases of STS(STS group)were retrospectively analyzed.MRI features being statistically different between groups were included in logistic regression analysis to screen the independent risk factors of STL and to evaluate the sensitivity,specificity and accuracy of their combination for predicting STL.Receiver operating characteristic curve was generated,the area under the curve(AUC)was calculated to assess the diagnostic efficacy of the mean apparent diffusion coefficient(ADCmean),the minimum apparent diffusion coefficient(ADCmin),the maximum apparent diffusion coefficient(ADCmax)values for distinguishing STL from STS.Results Slightly hyperintensity on T1WI,non-necrosis,involvement of multiple muscle groups and homogeneous enhancement were all independent risk factors of STL(all P＜0.05).The sensitivity,specificity and accuracy of their combination for predicting STL was 72.00％(18/25),89.47％(34/38)and 82.54％(52/63),respectively.ADCmean,ADCmin and ADCmax values of STL was(1.06±0.18)× 10-3,(0.77±0.14)×10-3 and(1.47±0.31)× 10-3mm2/s,respectively,all lower than those of STS([1.31±0.17]× 10-3,[1.02±0.23]× 10-3 and[1.64±0.16]× 10-3 mm2/s;t=-4.829--2.498,all P＜0.05).The AUC of ADCmean,ADCmin and ADCmax values and their combination for differential diagnosis of STL and STS was 0.845,0.844,0.683 and 0.877,respectively.Conclusion Conventional MRI features,including T1WI signal intensity,necrosis,involvement of multiple muscle groups and enhancement pattern,along with ADCmean and ADCmin values derived from DWI contributed to differentiating STL and STS.

Objective Pharmacovigilance,as an essential component of post-marketing drug regulation,plays a crucial role in ensuring the safety of public medication use.In recent years,Artificial intelligence(AI)technology,with its powerful data processing and analysis capabilities,has shown tremendous potential in the field of Pharmacovigilance.This article introduced and analyzed the application background of AI technology in Pharmacovigilance,its exploration and current status both internationally and within China,highlighted its application in the country,as well as the associated problems and challenges from the perspective of post-marketing regulation.It aims to provide reference for post-marketing regulation in China.Currently,China's exploration and application of AI in pharmacovigilance have just begun,and efforts should be intensified and the pace accelerated.Regulatory agencies should actively develop and implement regulatory standards or relevant guidelines for AI technologies throughout the product lifecycle,strengthen personnel training,talent cultivation,and introduction,actively promote close cooperation among regulatory agencies,pharmaceutical companies,research institutes,and universities,and jointly promote the innovative application of AI technology in the field of drug regulation.

Objective In view of the potential threat of adverse drug reaction(ADR)to patients'health and the limitations of traditional monitoring methods,this study investigates the construction method of an ADR knowledge graph based on a knowledge-driven technology path to promote the intelligent upgrading of pharmacovigilance field.Methods In this study,an adverse drug reaction knowledge base was established,and the data within the knowledge base were preprocessed.The BERT-CRF model was utilized to identify and extract the relevant entities,relationships and attribute information,and knowledge alignment was carried out by combining the rule method and statistical method.The knowledge fusion data was stored in the Neo4j graph database to construct the knowledge graph.Results Based on the established knowledge base,this study explored the method of constructing knowledge graph of adverse drug reaction by knowledge-driven technology,laying the groundwork for data mining and the development of intelligent auxiliary system tools based on knowledge graph.Conclusions The study on the construction method of an ADR knowledge graph based on a knowledge-driven technology path provides a new perspective and technical path for the intelligent upgrading of pharmacovigilance field.It holds important theoretical and practical significance for improving drug safety,protecting patients'health,and promoting the healthy development of pharmaceutical industry.

Medical ultrasound technology is widely used for diagnosis and therapy in clinical practice.Ultrasound probes,which are directly contact with patients,pose a potential risk of pathogen transmission.This expert consen-sus was developed by a multidisciplinary team based on international guidelines,standards in China,and the results of a national survey,aiming to reduce the risk of healthcare-associated infection through standardizing reprocessing of medical ultrasound probes,and formulating consensus recommendations with the Delphi method.The consensus clarifies the reprocessing principles for three types of ultrasound probes of different infection risks:external-use ul-trasound probes,interventional percutaneous ultrasound probes,and internal-use ultrasound probes,puts forward systematic suggestions on the reprocessing standards and disinfection levels of ultrasound probe isolation covers and coupling agents,the reprocessing procedures and methods of ultrasound probes,as well as architectural layout and management of reprocessing,so as to provide a scientific prevention and control framework for ensuring ultrasound diagnosis and therapy safety.

Purpose To analyze the expression of SNAP23 in esophageal squamous cell carcinoma(ESCC)and its influence on invasion of ESCC cells.Methods A total of 41 cases of ESCC and paired normal adjacent tissue(NAT)were collected.The expression and localization of SNAP23 were detected by immunohistochemical EnVision method.The differences of SNAP23 expression levels between ESCC tissues and NAT tissues were compared to analyze the relationship between SNAP23 expression and clinicopathological characteristics.The expression level of SNAP23 in human immortalized esophageal epithelial cells SHEE and ESCC cell lines TE-1,TE-13 and KYSE150 were detected by Western blot.Lentiviral vector transfection technique was used to construct stable transfection cell lines with knock-down and overexpression of SNAP23 gene.The effect of SNAP23 on invasion of ESCC cell line TE-13 was evaluated by cell invasion experiment.Results The expression of SNAP23 in ESCC was significantly higher(53.7％,22/41)than that in the NAT group(19.5％,8/41),the difference was statistically significant(x2=10.303,P＜0.01).The expression level of SNAP23 in ESCC tissues was significantly correlated with maximum tumor diameter(x2=4.193,P＜0.05)and invasion depth(x2=7.264,P＜0.05),but was not correlated with patient gender,age,tumor site,tumor type,pathologic grade,vascular embolus,nerve invasion and lymph node metastasis(P＞0.05).Compared with human immortalized esophageal epithelial cells SHEE,SNAP23 was highly expressed in ESCC cell lines(P＜0.000 1).Compared with the sh-NT group,the invasion of ESCC cell line TE-13 was inhibited when SNAP23 expression was knocked down(P＜0.000 1);compared with the Vector group,the invasion of ESCC cell line TE-13 was enhanced after overexpression of SNAP23(P＜0.000 1).Conclusion SNAP23 is highly expressed in ESCC tis-sue and cell lines,and its expression level in ESCC tissues is positively correlated with tumor maximum diameter and invasion depth;SNAP23 promotes the invasion of ESCC cells.

Heatstroke,especially in high-temperature and high-humidity environments,is a life-threatening acute heat-injury disease that seriously endangers human health.Timely and effective on-site treatment is crucial for patients'survival and prognosis.Early recognition,rapid assessment,and on-site cooling are the core of pre-hospital treatment of heatstroke.Currently,there is a lack of standardized application procedures for pre-hospital emergency care of heatstroke.Therefore,the"Expert Consensus on Pre-hospital Emergency Management of Heatstroke(2024 edition)"was initiated by the Expert Group on Heatstroke Prevention of the People's Liberation Army and developed in collaboration with experts from local pre-hospital emergency care,emergency departments,and intensive care units.This consensus focuses on heatstroke prevention,on-site and ambulance-based treatment,and early emergency room interventions,and puts forward 10 evidence-based recommendations,aiming to provide a reference for scientific and standardized pre-hospital emergency care of heatstroke.

Objective:To explore the potential categories and influencing factors of medication compliance in patients with cardiometabolic multimorbidity, and provide a reference for formulating targeted intervention measures.Methods:A cross-sectional study design was adopted. From March to October 2024, the patients with cardiometabolic multimorbidity in the First Hospital Affiliated with Hunan Normal University (Hunan Provincial People′s Hospital) were selected by convenience sampling method as research objects. Data were collected using a general information questionnaire, Medication Adherence Rating Scale (MARS), Perceived Social Support Scale (PSSS), and Medication Literacy Questionnaire. The latent class analysis was used to explore the characteristics and classifications of medication compliance in cardiometabolic multimorbidity, and unordered multivariate Logistic regression was used to analyze the influencing factors of different latent classes.Results:A total of 421 subjects were included, consisting of 291 males and 130 females, aged (64.28±9.74) years old. The overall medication adherence score was 6.00 (5.00, 8.00) points, which could be divided into four categories: overall good adherence group (24.47%, 103/421), subjective perception-poor adherence group (15.91%, 67/421), forgetfulness-poor adherence group (37.53%, 158/421), and overall poor adherence group (22.09%, 93/421). The results showed that when taking the overall good adherence group as a reference, the inability to obtain pharmaceutical information from social media, medication literacy scores, social support scores were the influencing factors for the subjective perception-poor adherence group ( OR=4.210, 0.516, 0.733, all P<0.05). Occupational characteristics (employees in public institutions or government-affiliated institutions), age, social support scores were the influencing factors for the forgetfulness-poor adherence group( OR=0.173, 1.155, 0.781, all P<0.05). Occupational characteristics (employees in public institutions or government-affiliated institutions), failure to receive medication guidance from medical staff, medication literacy scores and social support scores were the influencing factors for the overall poor adherence group( OR values were 0.136-5.275, all P<0.05). When taking the overall poor adherence group as a reference, failure to receive medication guidance from medical staff and medication literacy scores were the influencing factors for the subjective perception-poor adherence group ( OR=0.310, 1.752, both P<0.05). Failure to receive medication guidance from medical staff, age, medication literacy scores and social support scores were the influencing factors for the forgetfulness-poor adherence group ( OR values were 0.315-2.554, all P<0.05). Conclusions:There is significant heterogeneity in medication adherence among patients with cardiometabolic multimorbidity. Healthcare professionals should consider individual characteristics in clinical practice and provide targeted, precise interventions to improve adherence in different patient categories.

Objective Pharmacovigilance,as an essential component of post-marketing drug regulation,plays a crucial role in ensuring the safety of public medication use.In recent years,Artificial intelligence(AI)technology,with its powerful data processing and analysis capabilities,has shown tremendous potential in the field of Pharmacovigilance.This article introduced and analyzed the application background of AI technology in Pharmacovigilance,its exploration and current status both internationally and within China,highlighted its application in the country,as well as the associated problems and challenges from the perspective of post-marketing regulation.It aims to provide reference for post-marketing regulation in China.Currently,China's exploration and application of AI in pharmacovigilance have just begun,and efforts should be intensified and the pace accelerated.Regulatory agencies should actively develop and implement regulatory standards or relevant guidelines for AI technologies throughout the product lifecycle,strengthen personnel training,talent cultivation,and introduction,actively promote close cooperation among regulatory agencies,pharmaceutical companies,research institutes,and universities,and jointly promote the innovative application of AI technology in the field of drug regulation.