Objective: To explore whether the long-term and frequent use of citrate anticoagulants negatively affects the bone metabolism balance of female frequent plateletpheresis donors, so as to better protect their health. Methods: A total of 65 female plateletpheresis donors and 55 female whole-blood donors from Guangzhou Blood Center (May to December 2024) were enrolled as experimental and control groups respectively, stratified into age subgroups (18-39 years and 40-60 years). Serum levels of 25-hydroxyvitamin D [25(OH)D], procollagen type I N-terminal propeptide (PINP), osteocalcin (OC), and type I collagen carboxy-terminal telopeptide (CTX) were measured. Differences in bone metabolism markers between experimental and control groups across age subgroups were compared. ANOVA was used to analyze dose-response relationships between donation age, annual apheresis donation frequency, and biochemical indicators. Results: In the 40-60 age subgroup, 25(OH)D levels were significantly lower in the experimental group (P<0.05), exhibiting a linear increase with age and a linear decrease with annual donation frequency. No significant differences in CTX or PINP levels were observed between experimental and control groups in either age subgroup. Conclusion: High-frequency plateletpheresis donation does not disrupt bone metabolic balance in female donors. However, it is associated with reduced vitamin D levels in female donors aged >40 years, potentially increasing the risk of osteoporosis. Vitamin D supplementation is recommended for high-frequency female plateletpheresis donors in this age group.

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

Objective: To investigate the effect of loss of function of lanosterol synthase( LSS) gene on intestinal function in a mouse model of non-alcoholic fatty liver disease( NAFLD) induced by a high-fat diet． Methods: LSS gene heterozygous knockout C57 mice ( LSS + / －) were established using the CRISRP / Cas9 system．After being fed a high-fat diet with 60% fat content for 6 months，the fat deposition in liver tissues was detected by HE and Oil red O staining，the morphological changes of small intestine tissue were detected by HE staining．The changes in total cholesterol content in intestinal tissue were detected by kits．The gastrointestinal motility function of mice was detected by phenol red paste．The intestinal permeability was detected by Evans blue staining，and the expression of LSS，tight junction protein ( Claudin) -1，Claudin-5，cluster of differentiation 36 ( CD36) ，and Niemann-Pick type C1-like 1 protein ( NPC1L1) proteins in small intestinal tissues were detected by Western blot． Results : The results of HE and Oil red O staining of liver tissues showed that liver fat deposition in LSS gene heterozygous knockout mice was lower than that in wild-type mice in the high-fat diet group．The total cholesterol content in intestinal tis- sue of LSS gene heterozygous knockout mice decreased ( P ＜0. 01) ，but no morphological differences were ob- served between the two groups of mice by HE staining of intestinal tissues．The gastrointestinal motility function of LSS gene heterozygous knockout mice did not show significant changes．The intestinal permeability of LSS gene het- erozygous knockout mice in the high-fat diet group decreased as detected by Evans blue ( P＜0. 05) ．The expres- sion levels of Claudin-5 protein in the intestinal tissue of LSS gene heterozygous knockout mice in the high-fat diet group increased ( P ＜0. 05 ) ，while the expression of LSS protein in the intestinal tissues of LSS heterozygous knockout mice decreased ( P ＜0. 05) ． Conclusion In the NAFLD model induced by a high-fat diet，LSS gene heterozygous knockout reduces liver fat deposition induced by a high-fat diet and improves intestinal barrier function by regulating cholesterol metabolism in intestinal tissues and up-regulating the expression of Claudin-5．

PURPOSE: To judge the injury mode and injury severity of the real human body through the measured values of anthropomorphic test devices (ATD) injury indices, the mapping relationship of lumbar injury between ATD and human body model (HBM) was explored. METHODS: Through the ATD model and HBM simulation, the mapping relationship of lumbar injury between the 2 subjects was explored. The sled environment consisted of a semi-rigid seat with an adjustable seatback angle and a 3-point seat belt system with a seatback-mounted D-ring. Three seatback recline states of 25°, 45°, and 65° were designed, and the seat pan angle was maintained at 15°. A 23 g, 47 km/h pulse was used. The validity of the finite element model of the sled was verified by the comparison of ATD simulation and test results. ATD model was the test device for human occupant restraint for autonomous vehicles (THOR-AV) dummy model and HBM was the total human model for safety (THUMS) v6.1. The posture of the 2 models was adjusted to adapt to the 3 seat states. The lumbar response of THOR-AV and the mechanical and biomechanical data on L1 - L5 vertebrae of THUMS were output, and the response relationship between THOR-AV and THUMS was descriptive statistically analyzed. RESULTS: Both THOR-AV and THUMS were submarined in the 65° seatback angle case. With the change of seatback angle, the lumbar spine axial compression force (F_z) of THOR-AV and THUMS changed in the similar trend. The maximum F_z ratio of THOR-AV to THUMS at 25° and 45° seatback angle cases were 1.6 and 1.7. The flexion moment (M_y) and the time when the maximum M_y occurred in the 2 subjects were very different. In particular, the form of moment experienced by the L1 - L5 vertebrae of THUMS also changed. The changing trend of M_y measured by THOR-AV over time can reflect the changing trend of maximum stress of L1 and L2 of THUMS. CONCLUSION The F_z of ATD and HBM presents a certain proportional relationship, and there is a mapping relationship between the 2 subjects on F_z. The mapping function can be further clarified by applying more pulses and adopting more seatback angles. It is difficult to map M_y directly because they are very different in ATD and HBM. The M_y of ATD and stress of HBM lumbar showed a similar change trend over time, and there may be a hidden mapping relationship.
Humans ; Lumbar Vertebrae/injuries* ; Finite Element Analysis ; Biomechanical Phenomena ; Manikins ; Spinal Injuries/physiopathology*

Objective To explore the performance of a new multimodal feature fusion classification model based on distance matching and discriminative representation learning for differentiating high-grade glioma(HGG)from solitary brain metastasis(SBM).Methods We collected multi-parametric magnetic resonance imaging(MRI)data from 61 patients with HGG and 60 with SBM,and delineated regions of interest(ROI)on T1WI,T2WI,T2-weighted fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)images.The radiomics features were extracted from each sequence using Pyradiomics and fused using a multimodal feature fusion classification model based on distance matching and discriminative representation learning to obtain a classification model.The discriminative performance of the classification model for differentiating HGG from SBM was evaluated using five-fold cross-validation with metrics of specificity,sensitivity,accuracy,and the area under the ROC curve(AUC)and quantitatively compared with other feature fusion models.Visual experiments were conducted to examine the fused features obtained by the proposed model to validate its feasibility and effectiveness.Results The five-fold cross-validation results showed that the proposed multimodal feature fusion classification model had a specificity of 0.871,a sensitivity of 0.817,an accuracy of 0.843,and an AUC of 0.930 for distinguishing HGG from SBM.This feature fusion method exhibited excellent discriminative performance in the visual experiments.Conclusion The proposed multimodal feature fusion classification model has an excellent ability for differentiating HGG from SBM with significant advantages over other feature fusion classification models in discrimination and classification tasks between HGG and SBM.

Objective To predict microvascular invasion(MVI)in hepatocellular carcinoma(HCC)using a model based on multi-phase dynamic-enhanced CT(DCE-CT)radiomics feature and hierarchical fusion of multiple classifiers.Methods We retrospectively collected preoperative DCE-CT images from 111 patients with pathologically confirmed HCC in Guangzhou First People's Hospital between January,2016 and April,2020.The volume of interest was outlined in the early arterial phase,late arterial phase,portal venous phase and equilibrium phase,and radiomics features of these 4 phases were extracted.Seven classifiers based on different algorithms were trained using the filtered feature subsets to obtain multiple base classifiers under each phase.According to the hierarchical fusion strategy,a multi-criteria decision-making-based weight assignment algorithm was used for fusing each base classifier under the same phase with the model after extracting the phase information to obtain the prediction model.The proposed model was evaluated using a 5-fold cross-validation and assessed for area under the ROC curve(AUC),accuracy,sensitivity,and specificity.The prediction model was also compared with the fusion models using a single phase or multiple phases,models based on a single phase with a single classifier,models with different base classifier diversities,and 8 classifier models based on other ensemble methods.Results The experimental results showed that the performance of the proposed model for predicting HCCMVI was optimal after incorporating the 4 phases and 7 classifiers,with AUC,accuracy,sensitivity,and specificity of 0.828,0.766,0.877,and 0.648,respectively.Comparative experiments showed that this prediction model outperformed the models based on a single phase with a single classifier and other ensemble models.Conclusion The proposed prediction model is effective for predicting MVI in HCC with superior performance to other models.

Objective To evaluate the performance of magnetic resonance imaging(MRI)multi-sequence feature imputation and fusion mutual model based on sequence deletion in differentiating high-grade glioma(HGG)from low-grade glioma(LGG).Methods We retrospectively collected multi-sequence MR images from 305 glioma patients,including 189 HGG patients and 116 LGG patients.The region of interest(ROI)of T1-weighted images(T1WI),T2-weighted images(T2WI),T2 fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)were delineated to extract the radiomics features.A mutual-aid model of MRI multi-sequence feature imputation and fusion based on sequence deletion was used for imputation and fusion of the feature matrix with missing data.The discriminative ability of the model was evaluated using 5-fold cross-validation method and by assessing the accuracy,balanced accuracy,area under the ROC curve(AUC),specificity,and sensitivity.The proposed model was quantitatively compared with other non-holonomic multimodal classification models for discriminating HGG and LGG.Class separability experiments were performed on the latent features learned by the proposed feature imputation and fusion methods to observe the classification effect of the samples in two-dimensional plane.Convergence experiments were used to verify the feasibility of the model.Results For differentiation of HGG from LGG with a missing rate of 10%,the proposed model achieved accuracy,balanced accuracy,AUC,specificity,and sensitivity of 0.777,0.768,0.826,0.754 and 0.780,respectively.The fused latent features showed excellent performance in the class separability experiment,and the algorithm could be iterated to convergence with superior classification performance over other methods at the missing rates of 30%and 50%.Conclusion The proposed model has excellent performance in classification task of HGG and LGG and outperforms other non-holonomic multimodal classification models,demonstrating its potential for efficient processing of non-holonomic multimodal data.

Objective To analyze the factors affecting the prognosis of patients with knee osteoarthritis,and to construct a nomogram prediction model in conjunction with multi-dimensional clinical indicators.Methods The clinical data of 234 pa-tients with knee osteoarthritis who were treated in our hospital from January 2015 to June 2021 were retrospectively analyzed,including 126 males and 108 females;age more than 60 years old for 135 cases,age less than 60 years old for 99 cases.Lysholm knee function score was used to evaluate the prognosis of the patients,and the patients were divided into good progno-sis group for 155 patients and poor prognosis group for 79 patients according to the prognosis.The clinical data of the subjects in the experimental cohort were analyzed by single factor and multiple factors.The patients were divided into experimental co-hort and verification cohort,the results of the multiple factor analysis were visualized to obtain a nomogram prediction model,the receiver operating characteristic curve(ROC),calibration curve and decision curve were used to evaluate the model's dis-crimination,accuracy and clinical benefit rate.Results The results of multivariate analysis showed that smoking,pre-treatment K-L grades of Ⅲto Ⅳ,and high levels of interleukin 6(IL-6)and matrix metallo proteinase-3(MMP-3)were risk factors for the prognosis of patients with knee osteoarthritis.ROC test results showed that the area under the curve of the nomogram model in the experimental cohort and validation cohort was 0.806[95％CI(0.742,0.866)]and 0.786[(95％CI(0.678,0.893)],re-spectively.The results of the calibration curve showed that the Brier values of the experimental cohort and verification cohort were 0.151 points and 0.134 points,respectively.When the threshold probability value in the decision curve was set to 31％,the clinical benefit rates of the experimental cohort and validation cohort were 51％and 56％,respectively.Conclusion The prognostic model of patients with knee osteoarthritis constructed based on multi-dimensional clinical data has both theoretical and practical significance,and can provide a reference for taking targeted measures to improve the prognosis of patients.

AIM To study the chemical constituents of dichloromethane fraction from Hypericum perforatum L.METHODS The dichloromethane fraction from H.perforatum was isolated and purified by silica gel,ODS,Sephadex LH-20,semi-preparative HPLC and etc.The structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Eleven compounds were isolated and identified as hypernorpoleketone A(1),α-onocerin(2),(3R)-thunberginol C(3),2-geranyloxy-1-(2-methylpropanoyl)-phloroglucinol(4),4,6-dihydroxy-2-O-(3″,7″-dimethyl-2″,6″-octadienyl)-1-(2′-methylbutanoyl)benzene(5),norhyperpalum G(6),garsubellin A(7),garsubellin B(8),(2″R/S)-kellerine C(9),kobusone(10),eriodictyol(11).CONCLUSION Compound 1 is a new compound.Compounds 2-3 are isolated from the plants of family Guttiferae for the first time.Compounds 4-10 are isolated from this plant for the first time.

Objective To observe the clinical efficacy of"hegu needling"combined with"joint needling"in the treatment of chronic lumbar muscle strain.Methods A total of 64 patients with chronic lumbar muscle strain were randomly divided into observation group and control group,32 cases in each group.The control group was treated with routine acupuncture,and the observation group was treated with"hegu needling"combined with"joint needling"on the basis of the control group.One week for a course of treatment,a total of two courses of treatment.After two weeks of treatment,the clinical efficacy of the two groups was evaluated,and the changes of Visual Analogue Scale(VAS)of pain score and simplified Oswestry Dysfunction Index questionnaire(simplified ODI)score were observed before and after treatment.The changes of spinal mobility were compared before and after treatment between the two groups.Results(1)The total effective rate was 93.75%(30/32)in the observation group and 78.13%(25/32)in the control group.The curative effect of the observation group was superior to that of the control group,and the difference was statistically significant(P＜0.05).(2)After treatment,the simplified ODI score and spinal activity score of the two groups were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving the simplified ODI score and spinal activity score,the differences were statistically significant(P＜0.05).(3)After two weeks of treatment,the VAS scores of the two groups were significantly improved(P＜0.05),and the observation group was significantly superior to the control group in improving the VAS score,the difference was statistically significant(P＜0.05).After one month of treatment,there was no significant difference in VAS score of the observation group when compared with that after two weeks of treatment(P＞0.05).Conclusion"Hegu needling"combined with"joint needling"in the treatment of chronic lumbar muscle strain can significantly improve the patients'pain symptoms,enhance the patient's waist function,and improve the patients'spinal mobility.