Objective: To construct gene recombinant expression plasmids of human anti-P antibody with IgG1 and kappa chain based on the human hybridoma cell line. Methods: Starting from the specific RT-PCR products encoding the variable regions of the IgH chain and IgL chain of the anti-P monoclonal cell line, appropriate restriction enzyme digestion sites were introduced at both ends of the VH and VL fragments through nested PCR. The plasmids carrying the antibody constant region and the nested PCR products of VH and VL were ligated by the action of T4 ligase and subsequently transferred into competent E. coli DH5ɑ, and positive clones were selected in the antibiotic resistant LB medium. After sequence confirmation, recombinant plasmids DNA were transfected into HEK293T cells, and the recombinant antibody obtained in the culture supernatant. The characteristics of recombinant expression antibodies were determined by using rapid antibody isotying kit, serological agglutination tests and flow cytometry. Results: Recombinant gene expression vectors, pFUSEss-CHIg-hG1+VH, pFUSE2ss-CLIg-hκ+VL, were successfully constructed. Human IgG1 kappa light chain antibodies were detected in the supernatant of HEK293T cells transient transfected with recombinant plasmids. After the supernatant was ultra-filtered and concentrated, it could cause agglutination reactions with P antigen-positive red blood cells. The mean fluorescence intensity (MFI) of the reaction between recombinant antibodies and antigen-positive red blood cells in flow cytometry experiments was higher than that of antigen-negative red blood cells. Conclusion: The experimental study on the conversion of red blood group antibody types by genetic engineering technology represents a beneficial exploration towards establishing a feasible technical route for the development of genetic recombination and modification of antibodies reagent.

Objective To explore the mechanism of Quhan Zhufeng Mixture on proliferation and apoptosis of rheumatoid arthritis fibroblast-like synoviocyte(RA-FLS)based on NDRG2/JAK2/STAT3 signaling pathway.Methods RA-FLS cells were cultured in vitro,and were divided into ① blank serum group,methotrexate group,Quhan Zhufeng Mixture low-,medium-and high-dosage groups;② blank serum group,AG490 group,Quhan Zhufeng Mixture low-,medium-and high-dosage groups.Different concentrations of drug-containing serum were used to intervene cells.Cell proliferation was detected by CCK-8 method,apoptosis was detected by flow cytometry,and mRNA expressions of Bax,Bcl-2,Caspace-3,Caspace-9,N-myc downstream regulatory gene 2(NDRG2),Janus kinase 2(JAK2)and signal transduction and transcription activator 3(STAT3)were detected by RT-qPCR,Western blot was used to detect the protein expressions of Bax,Bcl-2,Caspace-3,Caspace-9,NDRG2,JAK2,STAT3,p-JAK2 and p-STAT3 in cells.Results Compared with the blank serum group,cell survival rate in methotrexate group,Quhan Zhufeng Mixture all dosage groups significantly decreased(P<0.01),the apoptosis rate significantly increased(P<0.01),the mRNA and protein expressions of Bax and Caspase-9 significantly increased(P<0.05,P<0.01),while the mRNA and protein expression of Bcl-2 significantly decreased(P<0.01),and Caspase-3 mRNA and protein expression in methotrexate group and Quhan Zhufeng Mixture medium-and high-dosage groups significantly increased(P<0.01).Compared with the blank serum group,the mRNA and protein expression of NDRG2 significantly increased in Quhan Zhufeng Mixture all dosage groups(P<0.05,P<0.01),the mRNA and protein expressions of JAK2 and STAT3 were significantly reduced in AG490 group and Quhan Zhufeng Mixture medium-and high-dosage groups(P<0.05,P<0.01),and the expressions of p-JAK2 and p-STAT3 proteins were significantly reduced(P<0.01).Conclusion Quhan Zhufeng Mixture can regulate the proliferation and apoptosis of RA-FLS by regulating the activity of NDRG2/JAK2/STAT3 signaling pathway,playing a role in treating rheumatoid arthritis.

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 investigate the expression of microRNA-574(miR-574)in placental tissue of pregnant women with preeclampsia(PE)and its significance in the pathogenesis of preeclampsia.Methods The placental tissue samples of 35 PE pregnant women(the PE group)and 20 normal pregnant women(the normal group)admitted to the Department of Obstetrics in Chengde Maternal and Child Health Care Hospital from March 2021 to June 2023 were collected,and the expression of miR-574 in the different placental tissues was detected by qRT-PCR.The trophoblast cells HTR8/Svneo were cultured in vitro and divided into the overexpression group,inhibition group and control group,which were transfected with miR-574 mimics,miR-574 inhibitor and miR-NC,respectively.The cell proliferation ability of each group was detected by CCK-8 assay;The cell apoptosis rate of each group was detected by flow cytometry;The cell invasion ability of each group was detected by transwell chamber experiment;The expression of EMT related proteins of cells in each group was detected by western blot.Results Compared with the normal group,the miR-574 expression of placental tissue in the PE group was significantly increased(P<0.05),and the expression of miR-574 in pregnant women with severe PE was significantly higher than that in pregnant women with mild PE(P<0.05).Compared with the control group,the expression of miR-574 of cells increased(P<0.05),the cell proliferation ability decreased(P<0.05),the cell apoptosis rate increased(P<0.05),the number of invasive cells reduced(P<0.05),the expression of E-cadherin protein increased(P<0.05),and the expression of MMP9 and N-cadherin proteins decreased in the overexpression group(P<0.05).Compared with the control group,the expression of miR-574 of cells decreased(P<0.05),the cell proliferation ability increased(P<0.05),the cell apoptosis rate reduced(P<0.05),the number of invasive cells increased(P<0.05),the expression of E-cadherin protein decreased(P<0.05),and the expression of MMP9 and N-cadherin proteins increased in the inhibition group(P<0.05).Conclusion The expression of miR-574 in the placental tissue of PE patients is increased,and it can participate in the pathogenesis of PE by influencing proliferation,apoptosis,invasion and EMT of trophoblast cell.

Synovium is the target organ of rheumatoid arthritis.The excessive proliferation of synovial cells and insufficient apoptosis lead to synovial hyperplasia,which in turn causes damage to the surrounding tissues of the joint and bone destruction."Yang transforming qi and yin forming elements"is derived from Su Wen and is a highly summarized description of the functions of yin and yang,which runs through the entire course of the disease.This article elucidated the theoretical connotation of"yang transforming qi and yin forming elements"and its connection with synovial hyperplasia,proposing that the insufficiency of"yang transforming qi"is the root of synovial hyperplasia,while the excess of"yin forming elements"is the manifestation of synovial hyperplasia.Based on this,it put forward that"assisting yang qi as the priority,and according to the bias of pathogenic factors of yin,supplementing the method of reducing yin forming elements"is an important principle for treating this disease,which could provide new ideas for the treatment of the disease.

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 To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective To explore the mechanism of Quhan Zhufeng Mixture on proliferation and apoptosis of rheumatoid arthritis fibroblast-like synoviocyte(RA-FLS)based on NDRG2/JAK2/STAT3 signaling pathway.Methods RA-FLS cells were cultured in vitro,and were divided into ① blank serum group,methotrexate group,Quhan Zhufeng Mixture low-,medium-and high-dosage groups;② blank serum group,AG490 group,Quhan Zhufeng Mixture low-,medium-and high-dosage groups.Different concentrations of drug-containing serum were used to intervene cells.Cell proliferation was detected by CCK-8 method,apoptosis was detected by flow cytometry,and mRNA expressions of Bax,Bcl-2,Caspace-3,Caspace-9,N-myc downstream regulatory gene 2(NDRG2),Janus kinase 2(JAK2)and signal transduction and transcription activator 3(STAT3)were detected by RT-qPCR,Western blot was used to detect the protein expressions of Bax,Bcl-2,Caspace-3,Caspace-9,NDRG2,JAK2,STAT3,p-JAK2 and p-STAT3 in cells.Results Compared with the blank serum group,cell survival rate in methotrexate group,Quhan Zhufeng Mixture all dosage groups significantly decreased(P<0.01),the apoptosis rate significantly increased(P<0.01),the mRNA and protein expressions of Bax and Caspase-9 significantly increased(P<0.05,P<0.01),while the mRNA and protein expression of Bcl-2 significantly decreased(P<0.01),and Caspase-3 mRNA and protein expression in methotrexate group and Quhan Zhufeng Mixture medium-and high-dosage groups significantly increased(P<0.01).Compared with the blank serum group,the mRNA and protein expression of NDRG2 significantly increased in Quhan Zhufeng Mixture all dosage groups(P<0.05,P<0.01),the mRNA and protein expressions of JAK2 and STAT3 were significantly reduced in AG490 group and Quhan Zhufeng Mixture medium-and high-dosage groups(P<0.05,P<0.01),and the expressions of p-JAK2 and p-STAT3 proteins were significantly reduced(P<0.01).Conclusion Quhan Zhufeng Mixture can regulate the proliferation and apoptosis of RA-FLS by regulating the activity of NDRG2/JAK2/STAT3 signaling pathway,playing a role in treating rheumatoid arthritis.

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.