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.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

Objective: The purpose of this study was to explore the capacity for energy production under conditions of increased energy demand in schizophrenia (SCZ) subjects compared to healthy controls. Methods: Twelve healthy controls (33.00±6.07 years) and 12 subjects diagnosed with SCZ or schizoaffective disorder (36.00±8.33 years) matched for age and sex, were recruited for this study. Hypoxic stress was induced during MR scans to elevate the energy demand on the subjects’ bioenergetic systems. Participants breathed air with a lower oxygen concentration (FiO2=13%), maintaining their SpO2 levels (86%) during the initial phase of the scan. 31Phosphorus MR spectroscopy was employed to examine metabolite levels, including phosphocreatine (PCr), β-adenosine triphosphate (ATP), and inorganic phosphate (Pi), as well as the ratios of PCr/Pi and PCr/β-ATP, in regions such as the prefrontal cortex (PFC), anterior cingulate cortex (ACC), and posterior cortex (POC), as well as across the entire brain, during both hypoxia and hyperoxia scans. Results: Subjects with SCZ had significantly lower levels of Pi across the brain and particularly, in the PFC, POC, and ACC during the hypoxia scan. Moreover, levels of PCr/Pi, indicative of mitochondrial energy production, were found to be higher in the same brain regions in the SCZ group. No significant differences were found in hyperoxia scan phase. Conclusion These findings suggest a deficit in the bioenergetic systems of individuals with SCZ under conditions of heightened energy demand. Further studies are warranted.

Objective: The purpose of this study was to explore the capacity for energy production under conditions of increased energy demand in schizophrenia (SCZ) subjects compared to healthy controls. Methods: Twelve healthy controls (33.00±6.07 years) and 12 subjects diagnosed with SCZ or schizoaffective disorder (36.00±8.33 years) matched for age and sex, were recruited for this study. Hypoxic stress was induced during MR scans to elevate the energy demand on the subjects’ bioenergetic systems. Participants breathed air with a lower oxygen concentration (FiO2=13%), maintaining their SpO2 levels (86%) during the initial phase of the scan. 31Phosphorus MR spectroscopy was employed to examine metabolite levels, including phosphocreatine (PCr), β-adenosine triphosphate (ATP), and inorganic phosphate (Pi), as well as the ratios of PCr/Pi and PCr/β-ATP, in regions such as the prefrontal cortex (PFC), anterior cingulate cortex (ACC), and posterior cortex (POC), as well as across the entire brain, during both hypoxia and hyperoxia scans. Results: Subjects with SCZ had significantly lower levels of Pi across the brain and particularly, in the PFC, POC, and ACC during the hypoxia scan. Moreover, levels of PCr/Pi, indicative of mitochondrial energy production, were found to be higher in the same brain regions in the SCZ group. No significant differences were found in hyperoxia scan phase. Conclusion These findings suggest a deficit in the bioenergetic systems of individuals with SCZ under conditions of heightened energy demand. Further studies are warranted.

Objective: The purpose of this study was to explore the capacity for energy production under conditions of increased energy demand in schizophrenia (SCZ) subjects compared to healthy controls. Methods: Twelve healthy controls (33.00±6.07 years) and 12 subjects diagnosed with SCZ or schizoaffective disorder (36.00±8.33 years) matched for age and sex, were recruited for this study. Hypoxic stress was induced during MR scans to elevate the energy demand on the subjects’ bioenergetic systems. Participants breathed air with a lower oxygen concentration (FiO2=13%), maintaining their SpO2 levels (86%) during the initial phase of the scan. 31Phosphorus MR spectroscopy was employed to examine metabolite levels, including phosphocreatine (PCr), β-adenosine triphosphate (ATP), and inorganic phosphate (Pi), as well as the ratios of PCr/Pi and PCr/β-ATP, in regions such as the prefrontal cortex (PFC), anterior cingulate cortex (ACC), and posterior cortex (POC), as well as across the entire brain, during both hypoxia and hyperoxia scans. Results: Subjects with SCZ had significantly lower levels of Pi across the brain and particularly, in the PFC, POC, and ACC during the hypoxia scan. Moreover, levels of PCr/Pi, indicative of mitochondrial energy production, were found to be higher in the same brain regions in the SCZ group. No significant differences were found in hyperoxia scan phase. Conclusion These findings suggest a deficit in the bioenergetic systems of individuals with SCZ under conditions of heightened energy demand. Further studies are warranted.

Objective:This study aims to construct an evaluation index system suitable for the core competency of Clinical Research Coordinators (CRCs) in Investigator-Initiated Trials (IITs) in China.Methods:This study developed a system framework through the Onion Model, literature research, and expert interviews, utilized the Delphi method to build the index system. and analyzed the weight of each indicator through the Analytic Hierarchy Process (AHP).Results:Four first-level indicators were basic knowledge (0.143), job skills (0.300 8), professional quality (0.483 9), and personality traits (0.072 3). Besides, 18 second-level indicators and 49 third-level indicators were developed through the Delphi method. According to the third round expert′s consultation, the average scores of all indexes were >3.50, the authoritative coefficient was 0.86, the coefficient of variation of each index was <0.30, and Kendall coefficients of concordance were 0.183~0.366 ( P<0.001). The consistency ratios of single-sort were<0.1, and the overall sort of all indexes was 0.043 7, which showed good logical reliability. Conclusions:This evaluation index system for Clinical Research Coordinators is of great scientific sense. It provides IIT-conducting investigators in institutions with a proficient assessment tool to help them find qualified and reliable CRCs.

Objective To propose a Weka-based method for classifying acute lymphoblastic leukemia(ALL)images,aiming to improve ALL cell classification accuracy and stability.Methods Firstly,totally 180 images were randomly selected from ALL-IDB2 subset of Acute Lymphoblastic Leukemia Image Database(ALL-IDB),including 90 images of patients and 90 images of healthy people;secondly,the image preprocessing was carried out using ImageJ software and image features were extracted such as texture,edge and shape;thirdly,image classification was implemented with four classifiers of Weka,including random forest(RF),Bayesian network(BN),J48 decision tree and sequential minimal optimization(SMO),and the key parameters of each classifier were optimized;finally,the performance of the classifiers was verified using 80 independent test images.Results Before parameter optimization,the accuracy of RF,J48 decision tree,BN and SMO classifiers was 94.3％,86.2％,83.6％and 83.0％,respectively.After optimization,the accuracy increased to 95.2％,86.3％,86.3％and 89.7％,respectively.After optimization,RF behaved the best on the independent test set with a classification accuracy of 90.0％,followed by SMO(81.3％),BN(81.3％)and J48 decision tree(75.0％).Conclusion The Weka-based ALL image classification method with a high accuracy is efficient and reliable for automated classification of ALL cell.[Chinese Medical Equipment Journal,2025,46(2):10-15]

Objective: The purpose of this study was to explore the capacity for energy production under conditions of increased energy demand in schizophrenia (SCZ) subjects compared to healthy controls. Methods: Twelve healthy controls (33.00±6.07 years) and 12 subjects diagnosed with SCZ or schizoaffective disorder (36.00±8.33 years) matched for age and sex, were recruited for this study. Hypoxic stress was induced during MR scans to elevate the energy demand on the subjects’ bioenergetic systems. Participants breathed air with a lower oxygen concentration (FiO2=13%), maintaining their SpO2 levels (86%) during the initial phase of the scan. 31Phosphorus MR spectroscopy was employed to examine metabolite levels, including phosphocreatine (PCr), β-adenosine triphosphate (ATP), and inorganic phosphate (Pi), as well as the ratios of PCr/Pi and PCr/β-ATP, in regions such as the prefrontal cortex (PFC), anterior cingulate cortex (ACC), and posterior cortex (POC), as well as across the entire brain, during both hypoxia and hyperoxia scans. Results: Subjects with SCZ had significantly lower levels of Pi across the brain and particularly, in the PFC, POC, and ACC during the hypoxia scan. Moreover, levels of PCr/Pi, indicative of mitochondrial energy production, were found to be higher in the same brain regions in the SCZ group. No significant differences were found in hyperoxia scan phase. Conclusion These findings suggest a deficit in the bioenergetic systems of individuals with SCZ under conditions of heightened energy demand. Further studies are warranted.

Objective To analyze the basic conditions and pathological characteristics of the samples in the Human Brain Bank of Hebei Medical University,which were pathologically diagnosed as cerebral amyloid angiopathy,and to provide reference for the research of related diseases.Methods The basic data of gender,age,apolipoprotein E genotype,pathological classification of cerebral amyloid angiopathy,Alzheimer's disease-related pathological change score,comorbidities and other pathological information were analyzed.Results Up to October 2024,twenty samples were confirmed by pathological diagnosis,with a male to female ratio of 3:1 and an average age of(80.90±8.08)years.Involve three kinds of apolipoprotein E subtype,5 kinds of genotypes(ε2/ε3 xε2/ε4、ε3/ε3 xε3/ε4、ε4/ε4);There were 2 pathologic types,including 6 cases of type 1 and 14 cases of type 2.The pathological grade included 3 grades.The severity grade and subtype classification of cerebral amyloid vascular disease were correlated with the degree of pathological changes of Alzheimer's disease.Cerebral amyloid angiopathy samples could coexist with other degenerative diseases with high comorbidity.Conclusion The incidence of cerebral amyloid angiopathy is higher in the aged samples collected based on Brain Bank,which coexists with conditions such as Alzheimer's disease and microbleeds,etc.It provides more detailed pathological diagnosis basis for further scientific research sharing of samples.