Purpose To quantitatively compare the diffusion parameters of mono-and biexponential diffusion-weighted imaging models,and to obtain optimal sets of b-values in diffusion-weighted MRI for obtaining monoexponential apparent diffusion coefficient(ADC)close to perfusion-insensitive intravoxel incoherent motion(IVIM)model ADC(ADCIVIM)in identifying of pulmonary solid benign and malignant lesions.Materials and Methods IVIM was performed in 40 patients with solid nodule and masse in Xi'an Gaoxin Hospital from July 2021 to August 2022 using a 3.0T MR imager.Two experienced diagnostic radiologists subjectively evaluated the IVIM images.A single index model was used to calculate ADC values(ADC0-1 000,ADC20-1 000,ADC50-1 000,ADC80-1 000,ADC150-1 000,ADC300-1 000,ADC500-1 000,ADC300,500,1 000,ADC300,800,1 000,ADC300,500,ADC300,800 and ADC300,1 000).The reference standard ADCIVIM value were calculated using a double-exponential model.The physician's measurements between two physicians were measured.The malignant and benign groups were compared and receiver operator characteristic curve for all parameters were analyzed.Results The measurement consistency of ADC values under b value sets and ADCIVIM was very good,and the intraclass correlation coefficient was more significant than 0.75.The differences between ADCIVIM and ADC values in each b group were statistically significant(t=-6.016--2.500,all P<0.05).The area under the curve(AUC)of ADCIVIM was the largest(0.906),with an optimal threshold of 1.271×10-3 mm2/s,a sensitivity of 80.0%and a specificity of 93.0%.The diagnostic efficacy close to ADCIVIM were ADC300,800(AUC=0.891),ADC50-1 000(AUC=0.827)and ADC300,800,1 000(AUC=0.795),respectively.The optimal threshold of ADC300,800 was 1.140×10-3 mm2/s,the sensitivity and specificity were 80.0%and 93.7%,respectively.Conclusion Combining b-values 300 s/mm2 and 800 s/mm2 is recommended as routine scanning parameters for identifying the insensitive monoexponential ADC between benign and malignant solid pulmonary lesions.

Objective To explore the variable pressure matress and thermoplastic mold applied to cone beam CT-guided radiotherapy of abdominal and pelvic cancer in terms of translation error,rotation angle error and setup reproducibility of patients with different body mass indexes(BMIs),so as to provide references for the selection of body fixation mode.Methods Totally 70 patients with abdominal and pelvic tumors admitted to some hospital from April 2021 to March 2022 were retrospectively selected,and divided into a variable pressure mattress group and a thermoplastic mold group according to the fixation method,with 35 patients in each group.All the patients in the two groups underwent examinations with cone beam computed tomography(CBCT)at the first radiotherapy treatment and during the course of the treatment,and the image registration was carried out between validation images and planning images.The two groups were compared in terms of rotation angle error and thranlation error at the directoins of x axis(lateral directions),y axis(cranial-caudal)and z axis(ventral-dorsal).Taking the center point image of the initial positioning as the reference,the errors of the center points of the two groups at z and y axes(Δz and Δy)were compared.The setup reproducibility was set as Δz≤5 mm and Δy≤3 mm,and the setup reproducibility rates of the two groups were summarized.All the patients were categorized into non-overweight ones(BMI<25 kg/m2)and overweight ones(BMI≥25 kg/m2),and the setup reproducibility rates of the patients with different BMIs were counted.SPSS 26.0 software was used for statistical analysis.Results The two groups had no significant differences in translation error at the directions of x and y axes(P>0.05).The variable pressure mattress group had the translation error at the direction of z axis statistically lower than that of the thermoplastic mold group(P<0.05).There were no significant differences between the two groups in rotation angle error(P=0.219 3).The two groups had significant differences in setup reproducibility(P=0.033 4).The non-overweight patients had the setup reproducibility rate being 40.00%in the variable pressure mattress group,and 77.14%in the thermoplastic mold group;the overweight patients had the setup reproducibility rate being 25.71%in the variable pressure mattress group and only 2.86%in the thermoplastic mold group,with the differences between the two groups being statistically significant(P=0.002 9).Conclusion The variable pressure mattress and thermoplastic mold both result in low setup errors when applied to fixation during the radiotherapy of abdominal and pelvic cancer,the thermoplastic mold fixation can be used for the patients with BMIs lower than 25 kg/m2 with decreased translation errors at the direction of z axis,and the variable pressure mattress fixation was suitable for the patients with BMIs not lower than 25 kg/m2.[Chinese Medical Equipment Journal,2025,46(7):45-50]

Objective:To evaluate the performance of an artificial intelligence-based endoscopic virtual ruler (EVR) for non-invasive measurement of esophageal varices (EV) diameter.Methods:Patients with liver cirrhosis and EV hospitalized at the First Affiliated Hospital of Anhui Medical University between October 2022 and May 2023 were prospectively enrolled. EV diameter was measured using visual estimation, esophageal varix manometer (EVM), and EVR, with procedure times recorded. The intraclass correlation coefficient (ICC) was used to assess the consistency of EV diameter measurement obtained from the three methods, and repeated-measures ANOVA was used to compare differences in time measurements across three methods.Results:The study included 41 patients with liver cirrhosis and EV. Inter-observer ICC for visual estimation was 0.594, versus 0.840 for EVM and 0.884 for EVR. The ICC value between the EV diameters measured by EVR and EVM was higher than that of the visual assessment. The ICC value between EV diameter measurement by EVM and EVR was 0.991. Measurement times differed significantly across methods ( P<0.001): visual estimation 18.6±2.2 s (14.7-23.3 s), EVR 41.5±4.1 s (31.7-50.3 s), and EVM 170.8±26.4 s (129.3-229.3 s). Repeated measures analysis of variance (corrected using Greenhouse-Geisser) revealed significant differences in time across the three measurement methods [ F(1.033, 41.313)=1 233.800, P<0.001]. Subsequent Bonferroni post-hoc tests revealed significant differences in time between all method pairs ( P<0.001). Conclusion:EVR provides rapid, non-invasive EV diameter measurements with excellent agreement to EVM assessment, offering an efficient alternative to conventional techniques.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

PURPOSE: The study aimed to examine the pattern of motorization and the mortality rate related to road traffic crashes in Zunyi (a city in northern Guizhou province of China) from 2013 to 2022, and to identify the epidemiological characteristics of these crashes with to provide insights that could help improve road safety. METHODS: Data were obtained from the Zunyi traffic management data platform, and the mortality rates were calculated. We deployed various analytical methods, including descriptive analysis, Chi-square test or Fisher's exact test for categorical variables, circular distribution map analysis, and Rayleigh test to characterize the traits of road traffic crashes in the region. RESULTS: During the 10-year study period, 7488 people died due to road traffic accidents, with males accounting for 70.4% and females 29.6% (χ² = 101.97, p < 0.001). The mortality rate increased from 7.80 deaths per 100,000 people in 2013 to 10.70 deaths per 100,000 people in 2016, but then decreased to 9.54 deaths per 100,000 people in 2019. A notable finding was that the death rate per 10,000 vehicles declined from 16.09 deaths per 10,000 vehicles in 2013 to 5.48 deaths per 10,000 vehicles in 2022. The study also found that vulnerable road users represented nearly half (48.76%) of all accident fatalities, and unlicensed or inexperienced driving contributed significantly to the occurrence of road traffic accidents. CONCLUSION Although the number of road traffic accidents in Zunyi has decreased, there are still some critical issues that need to be addressed, particularly for vulnerable road users and unlicensed drivers. Our results highlight the need for targeted interventions to address the specific risk factors of road traffic crashes, particularly those affecting vulnerable road users and drivers without sufficient experience or license.
Humans ; Accidents, Traffic/statistics & numerical data* ; China/epidemiology* ; Male ; Female ; Adult ; Middle Aged ; Aged ; Adolescent ; Young Adult ; Child

Objective:To investigate the changes in brain functional network and structural-functional network coupling in children with drug-resistant epilepsy (DRE), and to analyze their correlation with cognitive function, disease duration, and age of onset.Methods:This study was a cross-sectional study. Clinical and imaging data of 19 children with DRE who received consultation and treatment at the Affiliated Hospital of Zunyi Medical University from August 2021 to August 2023 (DRE group) were prospectively included. Another 27 age-and sex-matched healthy children were collected as the healthy control group. All subjects had 3D-T 1WI, T 2 fluid-attenuated inversion recovery, diffusion tensor imaging (DTI), resting-state functional magnetic resonance imaging (rs-fMRI) scans and Wechsler Intelligence Scale assessments. Independent sample t-test and Mann-Whitney U test were used to analyze the global and local topological attributes, as well as the structural-functional coupling (SFC) values at the whole brain and modular levels in two groups. Correlations between abnormal resting state brain functional network indicators and the Wechsler Intelligence Scale score [verbal comprehension index (VCI), perceptual reasoning index (PRI), working memory index (WMI), processing speed index (PSI), full scale intelligence quotient (FSIQ)], disease duration and age of onset was evaluated using a Spearman or Pearson correlation analysis. Results:Compared to the healthy control group, DRE group exhibited decreased VCI, PRI, WMI, PSI, FSIQ and the differences were all statistically significant (all P<0.05). Both brain functional networks had small world attributes. There was a statistically significant difference in the area under the curve of sparsity of degree centrality (DC) in the left pallidum between the DRE group and healthy control group (2.998±0.942, 4.992±1.945, t=-4.07, FDR corrected P<0.05). Compared with the control group, the DRE group had decreased SFC within the limbic network (LN) ( P<0.05), increased SFC within the sensorimotor (SMN) ( P<0.05), decreased SFC between the default mode network-LN ( P<0.05), and increased SFC between the SMN-attentional network (AN) ( P<0.05). There was no statistically significant difference in SFC at the whole brain level between the two groups. Correlation analysis indicated that DC in left pallidum in DRE group negatively correlated with the PSI ( r=-0.537, P=0.018), and SFC between the SMN and AN demonstrated a negative correlation with age of onset ( r=-0.537, P=0.018). Conclusion:The altered DC in left pallidum may be related to cognitive impairment in children with DRE, providing biomarker information for the study of neural mechanisms in children with DRE.

Objective:This study aimed to validated the diagnostic accuracy of Global Leadership Initiative on Malnutrition(GLIM)criteria for malnutrition in pancreatic cancer patients undergoing pancreaticoduodenectomy and to evaluated its prognostic value for postoperative outcome.Methods:A retrospective analysis was conducted on 230 consecutive pancreatic cancer patients who underwent pancreaticoduodenectomy at the Department of Pancreatobiliary Surgery,Sun Yat-sen University Cancer Center,between January 2018 to January 2024.Patients were stratified into malnutrition group and non-malnutrition group using Nutritional Risk Screening 2002(NRS 2002)and GLIM criteria.Multivariable logistic regression identified independent risk factors for postoperative morbidity.Results:GLIM criteria identified malnutrition in 96 patients(41.7％).Compared with the non-malnourished group,the number of preoperative nutritional support(t=20.038,P<0.001),the number of preoperative enteral nutrition support(t=8.377,P=0.004),the number of preoperative parenteral nutrition support(t=22.302,P<0.001),the number of anemia(t=8.037,P=0.005)and preoperative parenteral nutrition use days(t=-2.898,P=0.009),the difference was statistically significant.There were statistically significant differences in C-reactive protein(t=10.944,P=0.008),NLR(t=-2.523,P=0.012)and PNI(t=-2.397,P=0.017)between the two groups before surgery.Preoperative BMI(t=-4.410,P<0.001)was significantly lower in the malnourished group.The number of postoperative parenteral nutrition days(Z=-2.283,P=0.022)and amino acid supplementation during postoperative hospitalization were significantly higher in the malnourished group(Z=-2.309,P=0.021).The incidence of malnutrition was higher in patients with Clavien-Dindo grade≥Ⅲ(P=0.030)and intra-abdominal infections(P=0.049).Multivariable analysis identified preoperative weight loss(OR=2.154,95％CI:1.158～4.005;P=0.015)and BMI reduction(OR=0.175,95％CI:0.040～0.775;P=0.022)as independent predictors of postoperative complications.Conclusions:The GLIM standard effectively characterize malnutrition status in pancreatic cancer patients after pancreaticoduodenectomy patients and demonstrate superior predictive performance for postoperative morbidity.It has good predictive performance and clinical application value.

OBJECTIVE: To prepare clinical-grade human umbilical cord-derived mesenchymal stem cells (hUC-MSC) with high expression of hematopoietic supporting factors and evaluate their stem cell characteristics. METHODS: Fetal umbilical cord tissues were collected from healthy postpartum women during full-term cesarean section. Wharton's jelly was mechanically separated and hUC-MSCs were obtained by explant culture method and enzyme digestion method in an animal serum-free culture system with addition of human platelet lysate. The phenotypic characteristics of hUC-MSCs obtained by two methods were detected by flow cytometry. The differences in proliferation ability between the two groups of hUC-MSCs were identified through CCK-8 assay and colony forming unit-fibroblast (CFU-F) assay. The differences in multilineage differentiation potential between the two groups of hUC-MSCs were identified through induction of adipogenic, osteogenic, and chondrogenic differentiation. The mRNA expression levels of hematopoietic supporting factors such as SCF, IL-3, CXCL12, VCAM1 and ANGPT1 in the two groups of hUC-MSCs were identified by real-time fluorescence quantiative PCR(RT-qPCR). RESULTS: The results of flow cytometry showed that hUC-MSCs obtained by the two methods both expressed high levels of CD73, CD90 and CD105, while lowly expressed CD31, CD45 and HLA-DR. The results of CCK-8 and CFU-F assay showed that the proliferation ability of hUC-MSCs obtained by explant culture method was better than those obtained by enzyme digestion method. The results of the triple lineage differentiation experiment showed that there was no significant difference in multilineage differentiation potential between the two grous of hUC-MSCs. The results of RT-qPCR showed that the mRNA expression levels of hematopoietic supporting factors SCF, IL-3, CXCL12, VCAM1 and ANGPT1 in hUC-MSCs obtained by explant cultrue method were higher than those obtained by enzyme digestion method. CONCLUSION Clinical-grade hUC-MSCs with high expression levels of hematopoietic supporting factors were successfully cultured in an animal serum-free culture system.
Humans ; Mesenchymal Stem Cells/metabolism* ; Umbilical Cord/cytology* ; Cell Differentiation ; Female ; Cell Proliferation ; Cells, Cultured ; Chemokine CXCL12/metabolism* ; Angiopoietin-1/metabolism* ; Vascular Cell Adhesion Molecule-1/metabolism* ; Stem Cell Factor/metabolism* ; Flow Cytometry ; Pregnancy

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation and joint damage, accompanied by the accumulation of plasma cells, which contributes to its pathogenesis. Understanding the genetic alterations occurring during plasma cell differentiation in RA can deepen our comprehension of its pathogenesis and guide the development of targeted therapeutic interventions. Here, our study elucidates the intricate molecular mechanisms underlying plasma cell differentiation by demonstrating that PRDX1 interacts with DOK3 and modulates its degradation by the autophagy-lysosome pathway. This interaction results in the inhibition of plasma cell differentiation, thereby alleviating the progression of collagen-induced arthritis. Additionally, our investigation identifies Salvianolic acid B (SAB) as a potent small molecular glue-like compound that enhances the interaction between PRDX1 and DOK3, consequently impeding the progression of collagen-induced arthritis by inhibiting plasma cell differentiation. Collectively, these findings underscore the therapeutic potential of developing chemical stabilizers for the PRDX1-DOK3 complex in suppressing plasma cell differentiation for RA treatment and establish a theoretical basis for targeting PRDX1-protein interactions as specific therapeutic targets in various diseases.