Objective To provide a scientific basis for vector prevention and control in port areas, vector monitoring has been conducted continuously to characterize the composition, density, and seasonal fluctuations of vectors across 21 port-areas of Shandong province from 2017 to 2023. Methods In accordance with the Regional Vector Monitoring Plan for Frontier Ports, vector surveillance of mosquitoes, flies, cockroaches, rodents, and other disease vectors was performed. Data were analyzed to describe vector community composition and identify seasonal fluctuations. Results A total of 601 rodents belonging to 1 family, 4 genera, and 4 species were captured. Three dominant rodent species inhabit port areas. In addition, 88 104 mosquitoes were captured and classified into 3 subfamilies, 4 genera, and 12 species; 38 959 flies were trapped and classified into 8 families,31 genera, and 51 species, including 9 dominant fly species in port-areas; and 54 672 captured cockroaches were classified into 2 families,4 genera, and 4 species, with Blattella germanica as the dominant species. Conclusions Significant vector community changes(P＜0.005)have been identified after the epidemic. To improve the pertinence and efficacy of port health quarantine work, continuous and strong attention should be paid to vector compositions and population densities at Shandong ports.

Objective:To explore the feasibility of modifying hemerythrin molecules with natural cross-linker genipin,and evaluate its efficacy and safety.Methods:Hemerythrin was isolated and purified from sipunculid worms using tangential flow ultrafiltration.Subsequently,genipin cross-linked hemerythrin nanoparticles(GHrNPs)were constructed by adding 20％w/w genipin under mildly acidic conditions,and glutaraldehyde cross-linked hemerythrin nanoparticles(GAHrNPs)were constructed by adding 10％w/w glutaraldehyde under mildly alkaline conditions.The diameter,dispersity index,zeta potential,functional group structure,P50,and Hill coefficient of the two nanoparticle groups were measured.The two nanoparticle groups at different concentrations were co-cultured with vascular endothelial cells for 24 hours,then the cell viability and NO concentration in the culture medium were measured.Results:After glutaraldehyde/genipin molecular cross-linking,infrared spectra showed the continuous presence of amide bands Ⅰ and Ⅱ.The hydrated particle sizes of hemerythrin,GHrNP and GAHrNP were(93.14±2.11),(109.53±3.54),and(115.65±2.65)nm,dispersity indexes were 0.30±0.06,0.27±0.05,and 0.25±0.03,zeta potentials were(-24.00±1.54),(-19.52±1.31),and(-18.90±1.25)mV,P50 values were(9.28±0.22),(8.50±0.54),and(5.75±0.90)mmHg,and Hill coefficients were 1.61±0.14,1.58±0.17,and 1.41±0.22,respectively.The average hydrated particle size increased after cross-linking with hemerythrin,the negative value of the zeta potential decreased(both P＜0.05).The P50 value of GAHrNP was significantly decreased than that of hemerythrin and GHrNP(P＜0.05).The viability of vascular endothelial cells in the GHrNP group was higher than that in the GAHrNP group at different mass concentrations(P＜0.05).The NO concentration in the culture medium of vascular endothelial cells in the GHrNP group was higher than that in the GAHrNP group only at 2.0 mg/ml(P＜0.05).Conclusion:Hemerythrin molecules cross-linked by genipin can form stable nanoparticles with good oxygen-carrying activity and lower cytotoxicity compared to glutaraldehyde.

Objective:To evaluate the efficacy and safety of blinatumomab in adult patients with relapsed/refractory(R/R)or measurable residual disease(MRD)positive B-cell acute lymphoblastic leukemia(B-ALL)in the real world.Methods:The clinical data of 30 B-ALL patients received at least 1 course of blinatumomab therapy in the Chinese PLA General Hospital from January 1st,2021 to December 31st,2023 were retrospectively analyzed,including pre-treatment baseline clinical feature,post-treatment complete response(CR),CR with partial hematologic recovery(CRh),CR with incomplete hematologic recovery(CRi),complete MRD response rate,MRD response rate(MRD＜10-4),overall survival(OS),and disease-free survival(DFS),as well as drug-related adverse reactions.Results:Among 5 patients who were not assessed 4 were MRD negative and 1 did not receive bone marrow biopsy.In the R/R B-ALL group(13 cases),11 patients achieved CR/CRh/CRi and 10 patients achieved complete MRD response.In MRD+group(12 cases),9 patients achieved overall MRD response and 7 patients achieved complete MRD response.The median follow-up time was 8.4(95％CI:6.3-10.4)months.The median OS was 15.5(95％CI:0.7-30.3)months in the R/R group,while not reached in the MRD+group.The median DFS of the two groups were not reached.Drug-related adverse reactions occurred in 22 patients,and pyrexia was the most common(13 cases).Grade ≥3 adverse reactions occurred in 15 patients,and neutropenia was the most common(9 cases).Cytokine release syndrome occurred in 6 patients,including 5 cases with grade 1 and 1 case with grade 3.No patients interrupted therapy or died due to drug-related adverse reactions.Conclusion:Blinatumomab is effective in the treatment of R/R or continuous MRD+B-ALL with acceptable adverse reactions.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To evaluate the effectiveness of health education and health promotion for coal-burning pollution-induced endemic fluorosis (coal-burning fluorosis) in Ankang City, Shaanxi Province, and provide reference for further developing health education and health promotion measures.Methods:From 2020 to 2023, one county (district) was selected as the project county in coal-burning fluorosis area of Ankang City each year, and 3 to 5 towns of each project county were selected as the project town. Health education and health promotion activities on coal-burning fluorosis were carried out for department heads, endemic disease propaganda workers of project county, and students in grades 4 to 6 from center primary schools, local residents and migrant workers of all affected villages of project county. Before and after the implementation of health education and health promotion projects, 30 to 45 primary school students and 30 local residents from each project town were selected to conduct a questionnaire survey on the prevention and control knowledge of coal-burning fluorosis every year, and a household survey was conducted to investigate the prevalence and changes of specific behaviors of local residents who open their stoves.Results:From 2020 to 2023, the coverage rate of intervention activities for department heads, endemic disease propaganda workers, and primary school students in the project county was 100%; the coverage rate of intervention activities for local residents in the project county was 94.44% (18 271/19 346), and for migrant workers was 97.86% (8 683/8 873). The awareness rate of prevention and control knowledge of coal-burning fluorosis among primary school students and local residents after health education and health promotion in each year was significantly higher than those before health education and health promotion ( P < 0.001), and showed an increasing trend year by year (χ 2trend = 36.73, 38.47, P < 0.001). From 2020 to 2023, a total of 420 local residents were surveyed, and 110 people used open stoves. The prevalence rate of specific behaviors was 26.19%, and it showed a decreasing trend year by year (χ 2trend = 0.29, P < 0.001). After health education and health promotion, the number of people who changed their behavior during a certain period was 106, and the specific behavior change rate was 96.36% (106/110). Conclusions:The health education and health promotion on coal-burning fluorosis in Ankang City has achieved significant results. In the future, we should continue to increase investment in health education and health promotion, continuously improve the long-term mechanism of endemic disease health education and health promotion, innovate health education models, further improve the effectiveness of health promotion, and consolidate the achievements of prevention and control.

Objective To explore the correlation between fasting blood glucose(FBG)level and fractional flow reserve(FFR)in patients with borderline coronary artery disease,and to clarify its potential influence on FFR measurement.Methods From August 2020 to August 2023,the data of 135 patients with coronary atherosclerotic heart disease who received coronary angiography and FFR evaluation in the Fourth Affiliated Hospital of Harbin Medical University were retrospectively collected.According to the exclusion and inclusion criteria,85 cases of borderline diseased vessels of single coronary artery with stenosis degree of 50％-80％were screened out,and they were divided into FBG≥6.1 mmol/L group(47 cases)and FBG＜6.1 mmol/L group(38 cases).The baseline data,angiographic and functional indexes of the two groups were compared,and the correlation between FBG and FFR was analyzed.Results Compared with the FBG＜6.1 mmol/L group,the FBG≥6.1 mmol/L group had a higher proportion of FFR negative results(72.3％vs.23.7％,P＜0.001),and the FFR measurement values were generally increased[0.84(0.80,0.90)vs.0.75(0.68,0.80),P＜0.001],with statistically significant differences.Pearson correlation analysis was performed on all lesions,and FFR＞0.80(negative result)was positively correlated with FBG≥6.1 mmol/L(r=0.484,P＜0.001).Conclusions Among the patients with borderline coronary artery disease(50％-80％stenosis)included in this study,FBG≥6.1 mmol/L is significantly correlated with FFR＞0.80.For patients with borderline coronary lesions with elevated FBG,the influence of blood glucose factors should be carefully considered in clinical interpretation of FFR results.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To explore the correlation between fasting blood glucose(FBG)level and fractional flow reserve(FFR)in patients with borderline coronary artery disease,and to clarify its potential influence on FFR measurement.Methods From August 2020 to August 2023,the data of 135 patients with coronary atherosclerotic heart disease who received coronary angiography and FFR evaluation in the Fourth Affiliated Hospital of Harbin Medical University were retrospectively collected.According to the exclusion and inclusion criteria,85 cases of borderline diseased vessels of single coronary artery with stenosis degree of 50％-80％were screened out,and they were divided into FBG≥6.1 mmol/L group(47 cases)and FBG＜6.1 mmol/L group(38 cases).The baseline data,angiographic and functional indexes of the two groups were compared,and the correlation between FBG and FFR was analyzed.Results Compared with the FBG＜6.1 mmol/L group,the FBG≥6.1 mmol/L group had a higher proportion of FFR negative results(72.3％vs.23.7％,P＜0.001),and the FFR measurement values were generally increased[0.84(0.80,0.90)vs.0.75(0.68,0.80),P＜0.001],with statistically significant differences.Pearson correlation analysis was performed on all lesions,and FFR＞0.80(negative result)was positively correlated with FBG≥6.1 mmol/L(r=0.484,P＜0.001).Conclusions Among the patients with borderline coronary artery disease(50％-80％stenosis)included in this study,FBG≥6.1 mmol/L is significantly correlated with FFR＞0.80.For patients with borderline coronary lesions with elevated FBG,the influence of blood glucose factors should be carefully considered in clinical interpretation of FFR results.

Aim To examine the pathogenesis of disul-fide death gene in vascular dementia(VD)by bioin-formatics analysis of disulfide death differentially ex-pressed genes(DEGs)combined with experimental verification.Methods The death DEGs of disulfide were screened and their correlation was analyzed.The VD patients data in the data set were analyzed by clus-tering and typing and gene set variation.The clustering risk of DEGs was tested with a nomogram model,and the optimal learning model was predicted.After the es-tablishment of VD rat model,water maze test,HE stai-ning and RT-qPCR detection were performed to verify the results of health information.Results Four DEGs including SLC7A11 were obtained,which had antago-nistic or synergistic interaction with each other.The genetic data could be divided into two subtypes with significant differences.After typing,VD disulfide DEGs were mainly concentrated in GnRH signaling pathways.The accuracy of the nomogram prediction model was high.Generalized linear was the best ma-chine learning model.Compared with the sham opera-tion group,the escape latency of rats in the model group was prolonged,the number of crossing platforms decreased,the relative mRNA expression levels of Slc3a2 and Slc7a11 decreased,and LRPPRC in-creased.Conclusions SLC7A11 and other disulfide death DEGs and its related GnRH signaling pathway may be an important part of the pathogenesis of VD di-sulfide death.SLC3A2,LRPPRC and SLC7A11 can be used as characteristic genes in the regulation of VD by disulfide death,which may affect VD progression through the regulation of disulfide death.

Objective:To explore the expression regulation of lipid metabolism gene ABHD5 in testes.Methods:Differential gene analysis was performed by integrating databases of TCGA and GTEx to identify the target gene ABHD5.The expression trends of ABHD5 gene in testicular carcinoma tissue were analyzed.Human testis single-cell atlases were obtained from the Human Protein Atlas and Male Health Atlas databases to determine the expression distribution of ABHD5 across different testicular cell types.Additionally,the GTEx database was utilized to visualize the expression pattern of ABHD5 in the testis,thereby enhancing the understanding of its transcriptional profile.The relationship between ABHD5 expression and age was assessed through integrated database analysis.Western blotting and immunofluorescence were performed to detect differential expressions of ABHD5 in testicular tissues of young and aged mice respectively.Results:The TCGA database indicated that the expression of ABHD5 in human testicular carcinoma tissue was significantly lower than that in normal testicular tissue which showed a negative correlation with patient survival.ABHD5 was highly ex-pressed in germ cells of the testis reveaked from Human Protein Atlas and Male Health Atlas databases.The stability of ABHD5 protein was crucial for testicular tissue,and its expression decreased with age.Furthermore,Western blot and immunofluorescence staining demonstrated that ABHD5 expression in the testicular tissue of aged mice was significantly lower than that in young mice.Conclu-sion:ABHD5 plays an important role in testicular tissue,and may be inseparable from testicular tumors and reproductive aging.How-ever,its mechanism of action remains to be further studied.