Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.

AIM:To investigate the current status of astigmatism and its associated factors among children and adolescents from kindergarten through senior high school in Yangpu District, Shanghai, and to provide scientific evidence for the prevention and control of refractive errors.METHODS:A cluster sampling method was employed. From September to November 2024, students from 14 randomly selected schools in Yangpu District, Shanghai, were enrolled as study subjects. Autorefraction and ocular biometry were performed under non-cycloplegic conditions, and questionnaire surveys were administered. Comparisons of astigmatism degree, detection rate, and axis were made across age groups, educational stages, and sexes. Multiple linear and logistic regression analyses were conducted to identify factors associated with astigmatism.RESULTS:A total of 7 233 students aged 4-18 y were enrolled including 3 731 males, 3 502 females, with the mean age 10.13±4.18 y, astigmatism -0.76±0.82 D, and the detection rate(≤-1.00 D)was 29.23%. Both the degree and detection rate of astigmatism were correlated with age and educational stage, peaking in senior high school, with the most pronounced changes observed during primary school. Besides age, astigmatic refractive power was influenced by spherical equivalent(β=0.105, P<0.001), mean keratometry(β=-0.118, P<0.001), sex(with boys as the reference, girls: β=0.054, P<0.001), frequent sustained near work for 30-40 min(with “almost never” as the reference, β=-0.030, P=0.038), preterm birth(β=-0.023, P=0.044), maternal myopia(β=-0.028, P=0.020), and homework completion time on rest days(β=-0.035, P=0.041). The detection rate of astigmatism was associated with maternal myopia(OR=1.130, P=0.039), male sex(OR=0.773, P<0.001), shorter sleep duration on school days(OR=0.909, P=0.028), shorter sleep duration on rest days(OR=0.937, P=0.046), preterm birth(OR=1.382, P=0.012), frequent excessive head lowering(OR=1.216, P=0.045), homework completion time on rest days(OR=1.043, P=0.046), higher spherical equivalent(OR=0.891, P<0.001), and higher mean keratometry(OR=1.188, P<0.001).CONCLUSION:The degree and detection rate of astigmatism among children and adolescents from kindergarten to senior high school in Yangpu District, Shanghai are correlated with educational stage, and primary school may represent a critical period for astigmatism prevention and control. Male sex, maternal myopia, preterm birth, high-intensity near work, and insufficient sleep and other factors may be associated with the onset and progression of astigmatism. It is recommended that education and health departments strengthen visual health screening during primary school, while promoting behavioral interventions such as scientific eye-use habits and adequate sleep across different educational stages to delay the onset and progression of astigmatism.

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.

Aim To investigate the effect of total fla-vones of Coreopsis tinctoria Nutt(CF)on cognitive im-pairment in vascular dementia(VD).Methods The VD rat models were established by modified bilateral common carotid arteries ligation method.SD rats were divided into the sham operation group,model group,positive control group(nicergoline),and low,medium,and high dose CF groups.After eight weeks of admin-istration,the short term memory and spatial learning and memory abilities were evaluated by the platform jumping test,dark avoidance test and Morris water maze test.The pathological changes of the hippocam-pal tissues were inspected by HE and Nissl staining.The contents of TNF-α and IL-1β in the hippocampal were examined by ELISA.The protein expression lev-els of TLR4,MyD88,NF-κB p65,and p-NF-κB p65 in the hippocampal were detected by Western blot.The mRNA expression levels of miR-93,TLR4,MyD88,and NF-κB p65 in the hippocampal were determined by qRT-PCR.Results CF obviously improved the short term memory and spatial learning and memory abilities of VD rats,and alleviated the pathological damage of the hippocampus.CF also obviously decreased the lev-els of TNF-α and IL-1β,declined the protein expres-sion levels of TLR4,MyD88,and p-NF-κB p65,and re-duced the miR-93,TLR4,and MyD88 mRNA expres-sion in the hippocampus.Conclusion CF has a nota-ble protective effect on the neuroinflammation and cog-nitive impairments in VD rats by inhibiting the miR-93-mediated TLR4 signaling pathway.

Objective:To evaluate the efficacy of early bronchoalveolar lavage using electronic bronchoscopy in pediatric drowning cases.Methods:A retrospective analysis of clinical data from 81 pediatric drowning cases treated in the intensive care unit of Hunan Children's Hospital from January 2017 to September 2023 was conducted.Among these,43 cases underwent bronchoalveolar lavage with electronic bronchoscopy within 24 hours of drowning,constituting the treatment group,while 38 cases either did not receive treatment within 24 hours or underwent the procedure after 24 hours,forming the control group.We compared the two groups regarding pre-admission observations,admission observations,and disease progression or prognosis indicators to assess the clinical efficacy of early bronchoalveolar lavage with electronic bronchoscopy in pediatric drowning cases.Results:Compared to the control group,children in the treatment group exhibited a significant reduction in invasive ventilation time [(73.33±13.33) h vs.(94.82±15.77) h] and a significant decrease in pediatric intensive care unit stay [105.00 (94.00,121.00) h vs.123.5 (109.75,149.00) h],with both differences being statistically significant( P<0.05).No significant differences in white blood cell count and neutrophil percentage were observed between the treatment group and control group at admission and on the first day( P>0.05).However,by the third day,there was a significant improvement in white blood cell count in both groups,with statistical significance( P<0.05).There was a significant decrease in C-reactive protein and procalcitonin levels between the treatment group and control group on the 1st and 3rd days,with the differences being significant( P<0.05).Six hours after electronic bronchoalveolar lavage,the P/F ratio in the treatment group was lower than that in the control group (177.09±41.27 vs. 233.50±48.23),but it increased more significantly at 24 hours (286.00±34.32 vs.256.34±44.22),with a significant difference between two groups.The positive rate of lavage fluid culture in the treatment group was significantly higher than that in the control group,and the difference was statistically significant( P<0.05).There was no significant difference in the number of organ function damage between two groups( P>0.05).However,regarding prognosis,the treatment group showed significantly better outcomes than the control group( P<0.05). Conclusion:For pediatric patients with wilderness drowning,early electronic bronchoscopy with alveolar lavage may shorten the duration of invasive mechanical ventilation and pediatric intensive care unit stay,improving prognosis,and is worth promoting.

An assay was established for detection of toxigenic Clostridioides difficile by combining microfluidic chip analysis with immunochromatography,and its performance was evaluated and compared with those of the Xpert C.difficile/Epi and VIDAS CD AB tests.Primer pairs were designed according to the tcdB and tpi genes in C.difficile.The specificity,limit of detection,reproducibility,and stability were evaluated.A total of 215 stool samples from patients with diarrhea were collected and tested in parallel with the Xpert C.difficile/Epi,VIDAS CDAB,and our assay.C.difficile was isolated from samples,and the tcdB gene was identified when discrepant results were obtained from the three above assays.Our assay showed no cross-reaction with other diarrhea-associated pathogens.Its reproducibility was 100％in testing of two standard plasmids containing tcdB and tpi genes at two concentrations(105 and 102 copies/μL).Two standard plasmids were detected after the PCR and immunochromatography reagents had been stored for 3,6,9,and 12 months,and all the results were posi-tive.The limit of detection was 10 copies/μL for toxigenic C.difficile.Testing of 33 samples positive for C.difficile with our assay(33/215,15.3％)yielded findings statistically coherent with those of the Xpert C.difficile/Epi test(kappa value=0.965).The sensitivity,specificity,positive predictive value,and negative predictive value of our assay,with respect to Xpert C.difficile/Epi as the standard,were 94.3％,100.0％,100.0％,and 98.9％;these values were significantly higher than those of VIDAS CDAB(60.0％,98.9％,91.3％,and 92.7％)(Kappa=0.714,OR=157.50,95％CI:62.03-847.28,P=0.013).In conclusion,our newly developed assay is specific,stable,and reproducible,and may be used for rapid and accu-rate detection of toxigenic C.difficile.The assay could be used for C.difficile infection screening in outpatient and emergen-cy,community medical service center,and epidemiological settings.

Aim To explore the mechanism of baicalin combined with heat stimulation in treating acute lym-phoblastic leukemia(ALL)based on network pharma-cology and in vitro experiments.Methods The CCK-8 assay was used to screen the suitable conditions for heat stimulation to interfere ALL cell lines Jurkat,CCRF-CEM,Hut-78 and a normal lymphocyte HMy2.CIR,and the effects of baicalin combined with heat stimulation on the proliferation of three ALL cell lines and a normal lymphocyte were tested.The key targets of baicalin combined with fever stimulation for the treatment of ALL were obtained based on network phar-macological analysis,and the potential mechanisms were predicted by gene ontology(GO)annotation and kyoto encyclopedia of genes and genomes(KEGG)en-richment.The expression levels of TNF-α,AKT1,TYMS and CASP3 mRNA in ALL cell lines Jurkat and CCRF-CEM were examined by RT-qPCR with baicalin alone and baicalin combined with heat stimulation.Results The optimal conditions for heat stimulation to intervene ALL cells were 41 ℃ for 24 h,and heat stimulation combined with baicalin synergistically inhibited the growth of ALL cell lines and effectively reduced the cy-totoxicity of baicalin.Based on the network pharmaco-logical analysis,55 intersecting targets of baicalin with ALL diseases and 77 intersecting targets of baicalin with fever were obtained.The results of GO annotation and KEGG enrichment suggested that baicalin com-bined with fever stimulation to intervene ALL might be associated with influencing intracellular reactive oxygen species metabolism,DNA transcription and apoptotic processes involved in cysteine enzymes.Apoptosis,TNF and IL-17 signaling pathways were the key pathways for baicalin combined with heat stimulation in treating ALL.Under heat stimulation at 41 ℃ using SDHA gene as housekeeping gene,in vitro experiments showed that baicalin significantly up-regulated the expression of TNF-α and CASP3,and down-regulated the expression of TYMS in ALL cells.Conclusions Based on net-work pharmacologic analyses and in vitro experiments,baicalin combined with heat stimulation can regulate TNF-α and CASP3 gene levels in ALL cells and de-stroy cellular structure to promote cell apoptosis,thus synergistically treating ALL.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

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.

An assay was established for detection of toxigenic Clostridioides difficile by combining microfluidic chip analysis with immunochromatography,and its performance was evaluated and compared with those of the Xpert C.difficile/Epi and VIDAS CD AB tests.Primer pairs were designed according to the tcdB and tpi genes in C.difficile.The specificity,limit of detection,reproducibility,and stability were evaluated.A total of 215 stool samples from patients with diarrhea were collected and tested in parallel with the Xpert C.difficile/Epi,VIDAS CDAB,and our assay.C.difficile was isolated from samples,and the tcdB gene was identified when discrepant results were obtained from the three above assays.Our assay showed no cross-reaction with other diarrhea-associated pathogens.Its reproducibility was 100％in testing of two standard plasmids containing tcdB and tpi genes at two concentrations(105 and 102 copies/μL).Two standard plasmids were detected after the PCR and immunochromatography reagents had been stored for 3,6,9,and 12 months,and all the results were posi-tive.The limit of detection was 10 copies/μL for toxigenic C.difficile.Testing of 33 samples positive for C.difficile with our assay(33/215,15.3％)yielded findings statistically coherent with those of the Xpert C.difficile/Epi test(kappa value=0.965).The sensitivity,specificity,positive predictive value,and negative predictive value of our assay,with respect to Xpert C.difficile/Epi as the standard,were 94.3％,100.0％,100.0％,and 98.9％;these values were significantly higher than those of VIDAS CDAB(60.0％,98.9％,91.3％,and 92.7％)(Kappa=0.714,OR=157.50,95％CI:62.03-847.28,P=0.013).In conclusion,our newly developed assay is specific,stable,and reproducible,and may be used for rapid and accu-rate detection of toxigenic C.difficile.The assay could be used for C.difficile infection screening in outpatient and emergen-cy,community medical service center,and epidemiological settings.