ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

Objective:To analyze the effect of deep brain electrical stimulation therapy on Parkinson's disease patients with frozen gait and explore its prognostic factors.Methods:A retrospective study was conducted on 86 Parkinson's disease patients with frozen gait admitted to our hospital from January 2020 to December 2022.All patients received deep brain electrical stimulation therapy.Conduct a 2-year outpatient follow-up for all patients,and analyze the scores of the Parkinson's Disease Rating Scale Part 2(UPDRS Ⅱ),Parkinson's Disease Rating Scale Part 3(UPDRS Ⅲ),Fugl Meyer Lower Limb Motor Function Assessment Scale(FMA),and Schwab&England Daily Activity Scale(S&E)before and after medication opening and closing,6 months after surgery,1 year after surgery,and 2 years after surgery.And based on the 2-year follow-up results of the patients,the prognosis level of the patients was evaluated according to the S&E score during drug closure.60 patients with drug closure S&E score＞70 were divided into a good prognosis group,and 26 patients with drug closure S&E score≤70 were divided into a poor prognosis group.Logistic regression model was used to analyze the influencing factors of deep brain electrical stimulation therapy in Parkinson's disease gait freezing patients.Results:At 6 months,1 year,and 2 years after surgery,the UPDRS Ⅱ and UPDRS Ⅲ scores of all patients were lower than those before surgery(P＜0.05).The UPDRS Ⅱ and UPDRS Ⅲ scores of patients before surgery,6 months,1 year,and 2 years after surgery were lower than those of patients before surgery(P＜0.05);At 6 months,1 year,and 2 years after surgery,the FMA and S&E scores of all patients were higher than those before surgery(P＜0.05).There was no significant difference in the FMA and S&E scores between 6 months,1 year,and 2 years after surgery(P＞0.05).However,the FMA and S&E scores at 6 months,1 year,and 2 years after surgery were lower than those at the end of surgery(P＜0.05);There was no significant difference between the gender,BMI,combined underlying disease,levodopa equivalent dose,preoperative UPDRSⅢ score before the on and off periods,and FMA scores before the on and off periods(P＞0.05),Age,Parkinson's disease stage,preoperative UPDRS Ⅱ score between open and off period,and preoperative S&E score between the good prognosis and off prognosis groups(P＜0.05);The UPDRS Ⅱ score(95％CI:1.353～5.782,OR value:2.462),S&E score(95％CI:1.658～4.687,OR value:2.789),and S&E score(95％CI:1.265～6.879,OR value:3.645)before opening surgery are independent influencing factors on deep brain electrical stimulation therapy in Parkinson's disease gait freezing patients(P＜0.05).Conclusion:Deep brain electrical stimulation therapy can improve the condition and motor function of Parkinson's disease patients with frozen gait,but some patients may have poor prognosis due to the influence of UPDRS Ⅱ score before surgery and S&E scores during the opening and closing phases.

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 compare the contents of caffeic acid,ferulic acid,narirutin,calycosin,glycyrrhizic acid and atractylenolide Ⅲ of modified Liujunzi Decoction(MLJZD)during small test,pilot test(500,1 500 L)and large production.METHODS The samples were taken after soaking for 60 min,boiling for 0,5,10,15,20,30 min in the first decoction,and boiling for 5,10,15,20 min in the second decoction,respectively,after which the HPLC fingerprints were established,the contents of active constituents were determined.RESULTS There were 6 common peaks in the HPLC fingerprints for small test and pilot test,while 5 common peaks were observable in the HPLC fingerprints for large production,along with the similarities of more than 0.980.During pilot tests at different time points,various active constituents demonstrated consistent content changing trends,whose total content was higher than those during small test and large production.CONCLUSION Process amplification exhibits a little influence on active constituent contents in MLJZD,which don't show increasing trends with the expansion of container and enhancement of dosage.

Objective:To analyze the effect of deep brain electrical stimulation therapy on Parkinson's disease patients with frozen gait and explore its prognostic factors.Methods:A retrospective study was conducted on 86 Parkinson's disease patients with frozen gait admitted to our hospital from January 2020 to December 2022.All patients received deep brain electrical stimulation therapy.Conduct a 2-year outpatient follow-up for all patients,and analyze the scores of the Parkinson's Disease Rating Scale Part 2(UPDRS Ⅱ),Parkinson's Disease Rating Scale Part 3(UPDRS Ⅲ),Fugl Meyer Lower Limb Motor Function Assessment Scale(FMA),and Schwab&England Daily Activity Scale(S&E)before and after medication opening and closing,6 months after surgery,1 year after surgery,and 2 years after surgery.And based on the 2-year follow-up results of the patients,the prognosis level of the patients was evaluated according to the S&E score during drug closure.60 patients with drug closure S&E score＞70 were divided into a good prognosis group,and 26 patients with drug closure S&E score≤70 were divided into a poor prognosis group.Logistic regression model was used to analyze the influencing factors of deep brain electrical stimulation therapy in Parkinson's disease gait freezing patients.Results:At 6 months,1 year,and 2 years after surgery,the UPDRS Ⅱ and UPDRS Ⅲ scores of all patients were lower than those before surgery(P＜0.05).The UPDRS Ⅱ and UPDRS Ⅲ scores of patients before surgery,6 months,1 year,and 2 years after surgery were lower than those of patients before surgery(P＜0.05);At 6 months,1 year,and 2 years after surgery,the FMA and S&E scores of all patients were higher than those before surgery(P＜0.05).There was no significant difference in the FMA and S&E scores between 6 months,1 year,and 2 years after surgery(P＞0.05).However,the FMA and S&E scores at 6 months,1 year,and 2 years after surgery were lower than those at the end of surgery(P＜0.05);There was no significant difference between the gender,BMI,combined underlying disease,levodopa equivalent dose,preoperative UPDRSⅢ score before the on and off periods,and FMA scores before the on and off periods(P＞0.05),Age,Parkinson's disease stage,preoperative UPDRS Ⅱ score between open and off period,and preoperative S&E score between the good prognosis and off prognosis groups(P＜0.05);The UPDRS Ⅱ score(95％CI:1.353～5.782,OR value:2.462),S&E score(95％CI:1.658～4.687,OR value:2.789),and S&E score(95％CI:1.265～6.879,OR value:3.645)before opening surgery are independent influencing factors on deep brain electrical stimulation therapy in Parkinson's disease gait freezing patients(P＜0.05).Conclusion:Deep brain electrical stimulation therapy can improve the condition and motor function of Parkinson's disease patients with frozen gait,but some patients may have poor prognosis due to the influence of UPDRS Ⅱ score before surgery and S&E scores during the opening and closing phases.

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 establish a rat model of ovarian endometriosis(EMS)using the horn reversion method,to provide an ideal animal model for exploring the pathogenesis and treatment of EMS.Methods Fifty SPF-grade female SD rats were divided randomly into five groups:a sham group,and 1,2,3,and 4 weeks after surgery groups,respectively(n=10 rats per group).Apart from the sham group,an ovarian-type EMS model was established in the other groups by the uterine horn refracture method,and the modeling success rate,and ectopic foci volume and mass were observed in each group.The morphology of ectopic foci was observed by hematoxylin-eosin(HE),and expression of proliferating cell nuclear antigen(PCNA),Ki67,epithelial cadherin(E-cadherin),and neural cadherin(N-cadherin)in the uterus and ectopic foci tissues were detected by immunohistochemistry.The model was further evaluated and the degree of cell proliferation and epithelial mesenchymal transformation at different times after modeling were analyzed.Results The modeling success rates in the 1,2,3,and 4 weeks after surgery groups were 80%,90%,100%,and 100%,respectively(P＞0.05).The volume and mass of the ectopic foci were significantly greater in the 3 and 4 weeks after surgery groups compared with the 1 and 2 weeks after surgery groups(P＜0.01).HE staining showed endometrial epithelial cells,mesenchymal cells and a few glands in the ectopic foci tissues.Immunohistochemical staining showed that expression levels of Ki67,PCNA,and N-cadherin in uterus tissues were significantly higher(P＜0.05,P＜0.01)in all the model groups compared with the sham group,while expression levels of E-cadherin were significantly lower(P＜0.05,P＜0.01).Expression levels of Ki67,PCNA,and N-cadherin in the uterus and ectopic foci tissues were significantly higher(P＜0.05,P＜0.01)in the 2,3,and 4 weeks after surgery groups compared with the 1 week after surgery group,while expression levels of E-cadherin were significantly lower(P＜0.05,P＜0.01).Conclusion The uterine horn reversion method can be used to establish an ovarian EMS model in rats.Ectopic lesions can be observed 1 week after surgery.The success rate of modeling increases with modeling time,stabilizing at 3 weeks postoperatively.Ki67,PCNA,and N-cadherin were significantly expressed in the uterus and ectopic foci tissues,and their expression levels increased with modeling time,while E-cadherin expression in the uterus and ectopic foci tissues decreased with modeling time.These results showed good modeling success of the EMS rat model,suggesting that it could be used as a stable EMS modeling method.

Objective To establish a rat model of ovarian endometriosis(EMS)using the horn reversion method,to provide an ideal animal model for exploring the pathogenesis and treatment of EMS.Methods Fifty SPF-grade female SD rats were divided randomly into five groups:a sham group,and 1,2,3,and 4 weeks after surgery groups,respectively(n=10 rats per group).Apart from the sham group,an ovarian-type EMS model was established in the other groups by the uterine horn refracture method,and the modeling success rate,and ectopic foci volume and mass were observed in each group.The morphology of ectopic foci was observed by hematoxylin-eosin(HE),and expression of proliferating cell nuclear antigen(PCNA),Ki67,epithelial cadherin(E-cadherin),and neural cadherin(N-cadherin)in the uterus and ectopic foci tissues were detected by immunohistochemistry.The model was further evaluated and the degree of cell proliferation and epithelial mesenchymal transformation at different times after modeling were analyzed.Results The modeling success rates in the 1,2,3,and 4 weeks after surgery groups were 80%,90%,100%,and 100%,respectively(P＞0.05).The volume and mass of the ectopic foci were significantly greater in the 3 and 4 weeks after surgery groups compared with the 1 and 2 weeks after surgery groups(P＜0.01).HE staining showed endometrial epithelial cells,mesenchymal cells and a few glands in the ectopic foci tissues.Immunohistochemical staining showed that expression levels of Ki67,PCNA,and N-cadherin in uterus tissues were significantly higher(P＜0.05,P＜0.01)in all the model groups compared with the sham group,while expression levels of E-cadherin were significantly lower(P＜0.05,P＜0.01).Expression levels of Ki67,PCNA,and N-cadherin in the uterus and ectopic foci tissues were significantly higher(P＜0.05,P＜0.01)in the 2,3,and 4 weeks after surgery groups compared with the 1 week after surgery group,while expression levels of E-cadherin were significantly lower(P＜0.05,P＜0.01).Conclusion The uterine horn reversion method can be used to establish an ovarian EMS model in rats.Ectopic lesions can be observed 1 week after surgery.The success rate of modeling increases with modeling time,stabilizing at 3 weeks postoperatively.Ki67,PCNA,and N-cadherin were significantly expressed in the uterus and ectopic foci tissues,and their expression levels increased with modeling time,while E-cadherin expression in the uterus and ectopic foci tissues decreased with modeling time.These results showed good modeling success of the EMS rat model,suggesting that it could be used as a stable EMS modeling method.

Objective To explore the feasibility and corresponding implementation methods of constructing a sample resource bank based on individual-level data of completed clinical trials and using it to construct external controls for drug/device clinical trials.Methods Taking the pre-marketing clinical trial of transcatheter active valve replacement(TAVR)for the treatment of aortic valve stenosis as an example,the individual-level databases of multiple trials were standardized to form a sample bank.The original data of any trial in the sample bank were selected as the experimental group,and the remaining samples were selected as the control group.The potential confounding was handled by using the propensity score matching and stratification methods to clarify the process of constructing external controls based on the sample bank of individual-level data of clinical trials.Results This study included individual-level data of single-group trials of 4 TAVR devices,with a total of 569 subjects(59.2%male).The number of subjects in Trials 1 to 4 was 120,120,163,and 166,respectively.Propensity score matching enabled the matching of 113,117,125,and 147 subjects with comparable or similar characteristics from individual-level data from other trials,respectively,demonstrating a high matching success rate.The PS score distribution plot after stratification showed that the proportions of subjects in the experimental and control groups in strata 1 to 5 in scheme 1 were 4/103,11/103,22/92,32/87,and 51/64,respectively.For all constructed external controlled trials,a certain number of control samples with similar baseline characteristics to the experimental groups were distributed within each propensity score stratum.The results of the simulation test also reflected the potential differences between different devices in the 12-month all-cause mortality rate.Conclusions The sample bank constructed with individual-level data from clinical trials,as a high-quality data source,can serve as a source of external control for single-arm trials in the same field,and as a useful supplement to the external control scenario of real-world evidence to support drug and device development.At the same time,targeted research on research methods and bias control measures in related fields is also needed.

Objective To design an individually portable oral treatment device to solve the problems of oral diagnosis and treatment under field conditions in alpine regions.Methods The individually portable oral treatment device had a trolley box structure and consisted of an outer box,an inner framework and an operation panel.The outer box was made of low-density polyethylene material and formed by by one-time rotational moulding process;the inner framework integrated a plateau com-pressor,an independent negative-pressure compressor,an integrated control system for programmable logic controller(PLC),an individually portable respiratory synchronized pulsed oxygen supply module for plateau application;there were several curative devices equipped in the operation panel,including a 3-way syringe,a high-speed turbine handpiece,an electric variable-speed handpiece,a water control switch,a light curing machine and an ultrasonic dental cleaning handpiece.Trials were carried out with the test-phase prototype in alpine regions so as to verify the performance of the device.Results Trials proved that the prototype gained advantages in mobility,multifunctionality and pressure supply facilitating continuous operation of power gas source for oral diagnosis and treatment in alpine regions.Conclusion The device developed solves the problems in pressure insufficiency and instability,control system integration,portability and oxygen supply for medical staffs,improves the mobility of oral diagnosis and treatment in alpine regions and enhances the oral support service and equipment effectively.[Chinese Medical Equipment Journal,2025,46(1):108-113]