Objective:To analyze the genetic characteristics of the VWF gene c.7332G＞A nonsense mutation and explore its molecular pathogenesis.Methods:Phenotypic diagnosis of the proband was performed using VWF:Ag,VWF:RCo,FⅧ:C and multimeric analysis.The probands were genotyped by NGS whole-exome sequencing,and the sequencing results were validated by sanger sequencing.The family members were genotyped by Sanger sequencing.The VWF gene c.7332G＞A nonsense mutant plasmid was constructed.After transfection,the function of VWF gene c.7332G＞A mutant plasmid was verified at cell level in vitro.The mRNA level was detected by qRT-PCR,and the expression level of protein was detected by Western blot,the function of multimerization was verified by the multimeric analysis.Results:VWF:Ag and VWF:RCo were all less than 3％in the proband,and the multimeric analysis showed multimer deficiency.The proband was diagnosed as type 3 VWD.The homozygous nonsense mutation of VWF gene c.7332G＞A was detected by gene sequencing.The VWF mRNA level of the mutant plasmid was decreased,and the VWF protein expression in the cell supernatant was decreased,the mutant protein was truncated and the function of VWF multimerization was impaired.Conclusion:A homozygous mutation in exon 43 of VWF gene,c.7332G＞A,was responsible for the probands type 3 VWD in the proband.The mutation caused a decrease in the relative level of VWF mRNA and protein,and impaired the function of VWF multimerization.

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 application value of flexible traction suspension (FTS) strategy in pure single-incision laparoscopic distal gastrectomy (PSILDG).Methods:The retrospective and descriptive study was conducted. The clinicopathological data of 12 patients who underwent PSILDG in The Second Affiliated Hospital of Army Medical University from November 2021 to March 2024 were collected. There were 8 males and 4 females, aged (53±14)years. Observation indicators: (1) intraoperative conditions; (2) postoperative conditions; (3) follow-up. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absolute numbers. Results:(1) Intraoperative conditions. All 12 patients underwent PSILDG with FTS strategy successfully, with the operation time of (260±31) minutes, the volume of intraoperative blood loss of 103.3(37.5,150.0)mL, the length of surgical incision of (3.9±0.6)cm. There was no intra-operative special circumstance or complication. (2) Postoperative conditions. Results of histopatho-logical examination showed that among the 12 patients, there were 10 cases of adenocarcinoma, 1 case of signet ring cell carcinoma, and 1 case of high-grade intraepithelial neoplasia. The distance of the proximal tumor margin was 2.8(2.0,3.4)cm, the distance of distal margin was 5.9(5.0,7.5)cm, the tumor diameter was (2.3±1.0)cm, and the number of lymph node dissected was 34±10. On the post-operative first day, all 12 patients had a visual analog score of 1.0. The time to postoperative removal of gastric tube was 1.25(1.00,1.75)days, the time to postoperative first intake of liquid food was 2.00(1.00,2.00)days, the time to postoperative first out-of-bed activity was 1.67(1.00,2.00)days, the time to postoperative first flatus was 2.40(2.00,3.00)days, the time to postoperative first bowel movement was 3.50(2.00,5.00)days, the duration of postoperative hospital stay was (7.10±1.40) days, and the satisfaction score for the abdominal wall incision was 20.6±2.7. No patient experien-ced postopera-tive complications. (3) Follow-up. All 12 patients completed a 30-day follow-up after surgery, with no complication or need for secondary surgery.Conclusion:Application of FTS strategy in PSILDG is safe and feasible.

Objective To evaluate the efficacy of an online-to-offline(O2O)health education guided by the'Timing Theory'in improving self-management behaviours among the patients with glaucoma after day surgery.Methods In this randomised controlled study conducted between July and December 2022,70 patients with glaucoma after day surgery in our hospital were assigned to a control group and an experimental group,with 35 patients per group.Patients in control group received routine nursing care,while those in experimental group received O2O health education based on timing theory in addition to the routine nursing care.Outcomes were evaluated using the glaucoma awareness and knowledge questionnaire(GAKQ),self-efficacy to manage chronic disease scale(SEMCD)and glaucoma self-management questionnaire(GSMQ)at baseline,at 1 month and 3 months after surgery.Results A total of 32 patients in the experimental group and 27 in the control group completed the study.The generalised estimating equation(GEE)analysis showed a significant difference,respectively,in total score of GSMQ in interaction effect(F=8.408,P=0.015)and SEMC in time main effect(F=54.660,P<0.001).There were significant differences in total scores of GAKQ in time main effect,inter-group main effect and interaction effect(F=128.483,P<0.001;F=7.991,P<0.05;F=32.652,P<0.001,respectively).At one-month after intervention,the experimental group showed significantly higher GAKQ and SEMCD scores than the control group(Z=-2.004,P<0.05;Z=-2.029,P<0.05,respectively).At 1-and 3-months after intervention,the experimental group demonstrated significantly higher GAKQ scores(Z=-3.987,P<0.001;Z=-4.505,P<0.001,respectively).Conclusion The timing theory based O2O health education significantly improves knowledge of glaucoma,self-efficacy and self-management behaviours among day surgery patients and helps patients better cope with perioperative self-management over day surgery.

AKT,also known as Protein Kinase B(PKB),plays a critical role in cell proliferation and metabolism.There are three isoforms of AKT:AKT1,AKT2,and AKT3.The effects of these isoforms on the pluripotency and differentiation of mouse embryonic stem cells(mESCs)remain unclear.This study aims to explore the impact of three AKT isoform-specific knockouts on the self-renewal and differen-tiation of mouse embryonic stem cells.Using CRISPR/Cas9 gene-editing technology,AKT isoform-spe-cific knockout cell lines were established.The phenotypic and molecular changes were analyzed through Western blotting,flow cytometry,qRT-PCR,CCK-8 assays,Alkaline Phosphatase(AP)staining,and RNA-seq.The construction of AKT isoform-specific knockout cell lines was successful.The loss of AKT1 and AKT2 inhibited the proliferation of mESCs.The knockout of any single AKT isoform did not affect the expression of pluripotency genes at both mRNA or protein levels.However,during embryoid body forma-tion,the deletion of any of the three AKT isoforms affected the mRNA expression levels of genes in all three germ layers.Transcriptome analysis showed that compared to wild-type mESCs,995,547,and 429 differentially expressed genes(|log2FC|≧1,P＜0.05)were identified inAKT1,AKT2,and AKT3 isoform-specific knockout cells,respectively.There was some overlap in the differentially expressed genes regulated by these three isoforms.In conclusion,the independent knockout of AKT isoforms does not af-fect the maintenance of pluripotency in mouse embryonic stem cells,but they are crucial for differentia-tion.The three AKT isoforms can collectively regulate gene expression while retaining their own regulato-ry specificity.This study provides a foundation for understanding the unique and overlapping roles of AKT isoforms in stem cell biology,highlighting their importance in maintaining stem cell function and differen-tiation.

To establish a method for detecting Toxoplasma gondii based on recombinant polymerase amplification(RPA)technology and apply it to clinical sample validation of pet cats.Using the 529 repeat sequence of the Toxoplasma gondii gene as the target gene sequence,primers and probes were designed,and the Rep-529 recombinant plasmid was constructed as the standard.A fluorescent RPA reaction system was established.Dilute the plasmid standard 10 times to different concentrations as the detection template for sensitivity testing;Specific testing was conducted using genomic DNA from several parasitic spe-cies,including Toxoplasma gondii,Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia flagellata,Babesia bo-vis and Theileria annulata as templates;Simultaneously,fluorescence RPA and RT-PCR were used to detect 52 positive and 40 negative cats clinical samples,and the coincidence rate of the detection results of the two methods were compared and ana-lyzed.The RPA reaction system was successfully established using PTRep recombinant plasmid as the standard,ToxD-F/ToxD-R as the primer,and RepD-P as the fluorescent probe.The reaction temperature was constant at 39 ℃,the reaction time was 30 minutes,and the detection sensitivity was 1 copy/μL.There is no significant cross reaction with parasites such as Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia,Babesia bovis and Theileria annulata,and the specificity is good.A total of 92 clinical fecal samples from cats were tested,and the positive coincidence rate of fluorescence RPA detection method was higher than that of conventional RT-PCR method(98.08％vs.82.69％),and the difference of the positive rate was not statistically significant(X2=1.392,P＞0.05).The fluorescence RPA detection method for Toxoplasma gondii suc-cessfully established in this study has the characteristics of being fast,sensitive,specific,accurate,and reliable.It can be used as a rapid clinical detection kit for Toxoplasma gondii in cats and other animals,providing new technical support for the subsequent epidemiological monitoring and precise clinical diagnosis of toxoplasmosis in cats,other animals,and humans in the future.

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.

To establish a method for detecting Toxoplasma gondii based on recombinant polymerase amplification(RPA)technology and apply it to clinical sample validation of pet cats.Using the 529 repeat sequence of the Toxoplasma gondii gene as the target gene sequence,primers and probes were designed,and the Rep-529 recombinant plasmid was constructed as the standard.A fluorescent RPA reaction system was established.Dilute the plasmid standard 10 times to different concentrations as the detection template for sensitivity testing;Specific testing was conducted using genomic DNA from several parasitic spe-cies,including Toxoplasma gondii,Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia flagellata,Babesia bo-vis and Theileria annulata as templates;Simultaneously,fluorescence RPA and RT-PCR were used to detect 52 positive and 40 negative cats clinical samples,and the coincidence rate of the detection results of the two methods were compared and ana-lyzed.The RPA reaction system was successfully established using PTRep recombinant plasmid as the standard,ToxD-F/ToxD-R as the primer,and RepD-P as the fluorescent probe.The reaction temperature was constant at 39 ℃,the reaction time was 30 minutes,and the detection sensitivity was 1 copy/μL.There is no significant cross reaction with parasites such as Cryptosporidium,Neosporidium,Trichinella spiralis,Giardia,Babesia bovis and Theileria annulata,and the specificity is good.A total of 92 clinical fecal samples from cats were tested,and the positive coincidence rate of fluorescence RPA detection method was higher than that of conventional RT-PCR method(98.08％vs.82.69％),and the difference of the positive rate was not statistically significant(X2=1.392,P＞0.05).The fluorescence RPA detection method for Toxoplasma gondii suc-cessfully established in this study has the characteristics of being fast,sensitive,specific,accurate,and reliable.It can be used as a rapid clinical detection kit for Toxoplasma gondii in cats and other animals,providing new technical support for the subsequent epidemiological monitoring and precise clinical diagnosis of toxoplasmosis in cats,other animals,and humans in the future.

Aim To investigate the intervention effect of Rehmannia radix water extract on bleomycin(BLM)-induced pulmonary fibrosis in mice combined with metabolomics and to reveal the potential mechanism,in order to provide new ideas for clinical treatment of pul-monary fibrosis.Methods Male C57BL/6N mice were randomly divided into the control group,model group,pirfenidone group(positive control,PFD,270 mg·kg-1),and low dose(DH-L,4.55 g·kg-1)group,medium dose(DH-M,9.1 g·kg-1)group and high dose(DH-H,18.2 g·kg-1)group of Rehman-nia.Except for the control group,BLM(5 mg·kg-1)was instilled into the trachea to establish the model of pulmonary fibrosis in the other groups.The survival rate,lung index and blood oxygen saturation of mice in each group were evaluated.HE and Masson staining were used to observe the pathological changes of lung tissue.WBP was used to detect lung function.Flow cytometry was used to detect the apoptosis of primary lung cells,ROS and immune cells.ELISA was used to detect the levels of fibrosis markers and inflammatory factors(α-SMA,collagen Ⅰ,collagen Ⅲ,TGF-β1,TNF-α,IL-1 β,and IL-6).Biochemical method was employed to detect the contents of GSH-Px,T-SOD and MDA.Liquid chromatograph mass spectrometer(LC-MS)metabolomics was used to analyze the changes of serum metabolic profile.Results Water extract of Re-hmannia significantly increased the survival rate,oxy-gen saturation and lung function of mice with pulmona-ry fibrosis,reduced the lung coefficient,ameliorated pathological damage and collagen deposition in lung tissue,reduced the levels of apoptosis and oxidative stress,and down-regulated the levels of inflammatory factors in lung tissue.It regulated the levels of metabo-lites such as bile acid metabolism,sphingolipid metabo-lism,and unsaturated fatty acid metabolism.Conclu-sions Water extract of Rehmannia inhibits lung injury and collagen deposition in mice with pulmonary fibrosis by inhibiting inflammatory response,which may be a-chieved by regulating the levels of inflammatory factors through the metabolic pathways of bile acid and sphin-golipid.

Objective To construct a fuzzy comprehensive evaluation model based on the analytic hierarchy process(AHP)to evaluate the quality of hemodialysis machines.Methods Firstly,the influencing factors for the quality of hemodialysis machines were determined with considerations on the requirements for medical technology assessment of medical devices and the hospital's many years of experience in use,maintenance and management of hemodialysis machines,and the indicators of the evaluation model were set with the general attributes of the product quality as the criterion level and the influencing factors as the sub-criterion level.Secondly,the AHP was used to qualitatively and quantitatively analyze relevant factors to construct a hierarchical judgment matrix,and the quality evaluation indicator weights for hemodylysis machines were determined with the consistency test.Finally,the operational principles of fuzzy mathematics were applied to establishing a fuzzy judgment matrix,and the evaluation results were calculated using Type Ⅳ fuzzy comprehensive evaluation model.Results The constructed fuzzy comprehensive evaluation model included one first-level indicator,seven second-level indicators and 21 third-level indicators.All the first-and second-level indicators passed the consistency tests.The evaluation results obtained with this model were practical and consistent with the hospital's long-term record data on hemodialysis machines.Conclusion The constructed fuzzy comprehensive evaluation model demonstrates a certain degree of scientific rigor for quality assessment of hemodialysis machines and can provide decision-making support for their procurement justification.[Chinese Medical Equipment Journal,2025,46(9):81-87]