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 explore the risk factors of cognitive dysfunction in patients with sepsis and constructing a predictive model.Methods A total of 102 patients treated in the Department of this hospital from April 2021 to April 2024 were selected as the research subjects.According to the scores of the Mini-Men-tal State Examination(MMSE)three months after discharge,the patients were divided into the cognitive im-pairment group and the non-cognitive impairment group.Demographic data,critical illness-related scores and laboratory indicators of the patients were collected.Univariate analysis and multivariate logistic regression were used to analyze the risk factors for cognitive impairment in patients with sepsis.A nomogram model was constructed and its performance was verified through internal data.Results According to the MMSE scores,there were 60 patients were divided into the cognitive impairment group and 42 patients into the non-cognitive impairment group.The results of logistic regression analysis showed that age,educational level,the time of hospital stay,total hospitalization cost,chronic diseases,APACHEⅡ score,SOFA score,WBC,use of vasoac-tive drugs,indwelling urinary catheter,opening of artificial airway,medical devices,and clinical conditions were influencing factors for the occurrence of cognitive impairment(P＜0.05).The area under the receiver operating characteristic curve of the nomogram model for predicting the occurrence of cognitive dysfunction was 0.883.The predicted probability of the occurrence of cognitive impairment was highly similar to the actu-al situation,indicating that the predictive model had good discrimination and accuracy.Conclusion The nomo-gram risk model can predict the incidence of cognitive impairment in sepsis patients relatively well,which is beneficial to the early identification,early evaluation,early intervention and treatment of high-risk groups.

Objective To explore the acceptability of routine biochemical test results for serum samples with varying degrees of chylous high triglyceride(TG).Methods Blood samples of 69 patients with different degrees of lipids were collected,including 33 patients with mild to moderate lipids(1.7 mmol/L≤TG<5.6 mmol/L)and 36 patients with severe lipids(TG≥5.6 mmol/L).Twenty-nine biochemical tests were detected before and after high-speed centrifugation.The result acceptability before high speed centrifugation of serum was compared with the results after high speed centrifugation as the gold standard[TG and total cholesterol(TC)before centrifugation].The acceptable criteria were subject to the following three conditions at the same time.Firstly,correlation coefficient(R2)was greater than or equal to 0.95.Secondly,the slope of linear re-gression equation was 1.00±0.05.Thirdly,for the same index,the number of samples whose result bias be-fore and after centrifugation was less than 1/2 total allowable error(TEa)in more than 90%of the total sam-ple numbers.Results Firstly,in the mild to moderate lipemia group,22 tests met the criteria,7 tests did not,including total protein(TP),albumin(ALB),TG,aspartate aminotransferase(AST),carbon dioxide(CO2),α-L-fucosidase(AFU),lactate dehydrogenase(LDH)(bias<10%),and the coincidence rate was 75.9%.In the severe lipemia group,12 tests met the criteria,17 tests did not,including pre-albumin(PA),AFU,γ-glu-tamyltransferase(γ-GT),LDH,AST,TC,direct bilirubin(DBIL),CO2,5'-nucleotidase(5'-NT),small and low-density lipoprotein cholesterol(sd-LDL-C),high density lipoprotein cholesterol(HDL-C),low-density lipoprotein cholesterol(LDL-C),adenosine deaminase(ADA),cystatin C(CysC),glycosylated albumin(GA),total bilirubin(TBIL)(bias>10%),the coincidence rate was 41.4%,and there was a statistically sig-nificant difference in the coincidence rate between the two groups(P<0.05).Secondly,there was no statisti-cally significant difference in the acceptability of results between continuous monitoring method and endpoint method detection methods(P>0.05).Conclusion Most test results of direct determination with mild or moderate lipemia samples are acceptable,and the bias of unacceptable tests is small(<10%),so it is recom-mended to issue a test report without further sample treatment.However,due to the large number of unacceptable tests and larger bias(>10%),severe lipemia samples should be determined after high-speed centrifugation.

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.

Aim To investigate the effect of metformin on epithelial-mesenchymal transition(EMT)of lung cancer A549 cells and its underlying mechanism.Methods Lung cancer A549 cells were cultured in vitro and treated with metformin.Cell morphology was observed by fluorescence staining.The mRNA expres-sion levels of E-cadherin,N-cadherin,SMA and Vimen-tin were detected by RT-PCR.The regulatory effects of metformin on EMT in A549 cellswere examined by high-throughput sequencing.An EMT model was estab-lished through TGF-β1 induction.Following metformin treatment,the morphology of A549 cells was observed.Western blot was employed to determine the expression levels of NGF,E-cadherin,N-cadherin,SMA and Vim-entin.Additionally,si-NGF transfection was performed to evaluate the protein expressions of E-cadherin,N-cadherin,SMA and Vimentin in A549 cells,and a cell scratch assay was conducted to assess cell migration.Results After metformin treatment,A549 cells exhibi-ted a loss of mesenchymal-like morphology,character-ized by a transition to a round shape,a reduction in colony formation,and decreased adherence.RT-PCR and high-throughput sequencing revealed a down-regu-lation in the expression of genes associated with mesen-chymal transition,including N-cadherin,SMA,and Vim-entin,and an up-regulation in the expression of genes associated with epithelial transformation,such as ZO-1 and E-cadherin.Additionally,the expression of nerve growth factor(NGF)was significantly up-regulated.Following transfection with si-NGF,A549 cells treated with metformin exhibited a down-regulation in the ex-pression of the epithelial marker E-cadherin,concomi-tant with an up-regulation in the expression of stromal markers N-cadherin,Vimentin,and SMA.Conclusions Metformin can up-regulate the expression of E-cad-herin and down-regulate the expression of N-cadherin,Vimentin and SMA in lung cancer A549 cells,thereby inhibiting EMT.Additionally,NGF signaling molecules may play a significant role in this process.

Objective To develop dynamic prediction models based on multiple postnatal time points to support early diagnosis and individualized intervention for bronchopulmonary dysplasia(BPD)in preterm infants with gestational age<32 weeks.Methods Clinical data of 472 preterm infants with gestational age<32 weeks admitted to the Second Xiangya Hospital of Central South University between January 2016 and November 2020 were retrospectively analyzed.Multivariable logistic regression was applied to develop five independent prediction models at postnatal days 1,7,14,21,and 28.The performance of the models was assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Results Baseline characteristics such as gestational age and birth weight differed significantly between the BPD group(n=147)and the non-BPD group(n=325)(P<0.05).Predictors of BPD evolved across time points:on day 1,key predictors included gestational age,birth weight,Score for Neonatal Acute Physiology II(SNAP-II),invasive mechanical ventilation,and fraction of inspired oxygen>30%;by day 7,additional variables emerged,including fasting duration>2 days,mean feeding advancement rate<8.5 mL/(kg·d),neonatal respiratory distress syndrome,apnea of prematurity,and positive sputum culture;from day 14 onward,nutrition-and treatment-related indicators were incorporated additionally.The models demonstrated good discrimination at postnatal days 1,7,14,21,and 28,with AUCs of 0.917,0.927,0.939,0.944,and 0.968,respectively,and good calibration(Hosmer-Lemeshow P>0.05).Internal validation showed AUCs ranging from 0.899 to 0.958,indicating robust performance.Conclusions Dynamic postnatal prediction models incorporating indicators spanning perinatal factors,respiratory support,nutritional management,and therapeutic interventions demonstrate high predictive performance and facilitate dynamic risk assessment for BPD in preterm infants with gestational age<32 weeks.

Objective To analyze the serum metabolomic changes of preterm infants with bronchopulmonary dysplasia(BPD)at postmenstrual age(PMA)36 weeks,screen potential biomarkers and associated metabolic pathways,and assess their relationship with short-term respiratory outcomes.Methods A retrospective case-control study was conducted.Infants with gestational age 28-32 weeks admitted to the Children's Hospital Affiliated to Zhengzhou University from January to December 2024 were included.Twenty infants with BPD and 20 gestational age-,birth weight-,and sex-matched non-BPD preterm infants were included.Serum collected at PMA 36 weeks was subjected to untargeted metabolomics analysis,and associations with short-term respiratory outcomes were analyzed.Results Thirteen potential biomarkers distinguishing BPD were identified(area under the curve>0.75,P<0.05).Eight biomarkers—including terephthalic acid,phosphatidylinositol,fumarate,and lysophosphatidic acid—were significantly upregulated(FC≥1.5),while five biomarkers,such as 7α-hydroxy-3-oxo-4-cholestenoate ester and phosphatidylcholine,were significantly downregulated(FC≤1/1.5).Pathway analysis indicated five pathways associated with BPD,including glycerophospholipid metabolism and phenylalanine metabolism.Dysregulation of glycerophospholipid and bile acid metabolism may affect adverse short-term respiratory outcomes in infants with BPD.Conclusions The 13 significantly different metabolites may serve as biomarkers for the diagnosis of BPD.Glycerophospholipid metabolism is associated with the occurrence of BPD and with adverse short-term respiratory outcomes.