Objective To analyze the structural and phylogenetic characteristics of the mitochondrial genome from Bulinus globosus, so as to provide a theoretical basis for classification and identification of species within the Bulinus genus, and to provide insights into understanding of Bulinus-schistosomes interactions and the mechanisms of parasite transmission. Methods B. globosus samples were collected from the Ruya River basin in Zimbabwe. Mitochondrial DNA was extracted from B. globosus samples and the corresponding libraries were constructed for high-throughput sequencing on the Illumina NovaSeq 6000 platform. After raw sequencing data were subjected to quality control using the fastp software, genome assembly was performed using the A5-miseq and SPAdes tools, and genome annotation was conducted using the MITOS online server. Circular maps and sequence plots of the mitochondrial genome were generated using the CGView and OGDRAW software, and the protein conservation motifs and structures were analyzed using the TBtools software. Base composition and codon usage bias were analyzed and visualized using the software MEGA X and the ggplot2 package in the R software. In addition, a phylogenetic tree was created in the software MEGA X after sequence alignment with the software MAFFT 7, and visualized using the software iTOL. Results The mitochondrial genome of B. globosus was a 13 730 bp double-stranded circular molecule, containing 2 ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and 13 protein-coding genes, with a marked AT preference. The mitochondrial genome composition of B. globosus was similar to that of other species within the Bulinus genus. Phylogenetic analysis revealed that the complete mitochondrial genome sequence of B. globosus was clustered with B. truncatus, B. nasutus, and B. ugandae into the same evolutionary clade, and gene superfamily analysis showed that the metabolism-related proteins of B. globosus were highly conserved, notably the cytochrome c oxidase family, which showed a significant consistency. Conclusions This is the first whole mitochondrial genome sequencing to decode the compositional features of the mitochondrial genome of B. globosus from Zimbabwe and its evolutionary relationship within the Bulinus genus, which provides important insights for further understanding of the phylogeny and mitochondrial genome characteristics of the Bulinus genus.

【Objective】 To analyze the genetic variation characteristics and clinical phenotypes of a family with primary microcephaly (MCPH) caused by RTTN gene variation, and to provide reference for genetic counseling and prenatal diagnosis. 【Methods】 Clinical data of the three patients (including 2 fetuses and 2-year-old proband,and one fetus with clinical diagnosis) and their parents were collected and analyzed. Two of the children and their parents were tested by trio whole exome sequencing (trio-WES), sanger sequencing validation sites, and the hazard of their compound heterozygous variants was predicted. Literature review was conducted through domestic and international databases to collect reported RTTN gene mutation cases. 【Results】 Three patients in this family had anomalies of the septum pellucidum, hypoplasia of the corpus callosum and other brain malformations during fetal period. The proband (G2) and fetus (G3) showed intrauterine growth retardation and MCPH in late pregnancy; besides, G2 was born with global developmental delay. Trio-WES detected a c.2101(exon16)C>T(p.Arg701Ter,1526) nonsense and a c.2863(exon22)G>A(p.Glu955Lys)missense in the RTTN gene of G2 and G3, which were inherited from their father and mother, forming a compound heterozygous variant. According to the American College of Medical Genetics and Genomics (ACMG) variant classification guidelines, two variants were likely to be pathogenic (LP) and uncertain significance (VUS). Among them, c.2863(exon22)G>A was a newly discovered missense, which was predicted by the software to be harmful to the gene product. 【Conclusions】 Complex heterozygous variations of RTTN gene (c.2101C>T and c.2863G>A) are the genetic cause of MCPH in this family. This report has enriched the variation spectrum of RTTN gene, provided guidance for prenatal diagnosis and reproduction of this family, as well as material and reference for further understanding of the diseases caused by this gene mutation.

Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.

Objective:To investigate the effect of pelvic rotation around coronal axis on the placement angle of acetabular prosthesis after total hip arthroplasty.Methods:According to Murary's definition, the angle between the acetabular axis and the sagittal plane was defined as the acetabular abduction angle, and the angle between the acetabular axis and the coronal plane as the anterior inclination angle. A simple mathematical solid geometry model was established by using the mathematical software GeoGebra to simulate the dynamic changes of the acetabular prosthesis when it rotated around the coronal axis, and the calculation formula of the dynamic changes of the anterior inclination and abduction angle of the acetabular prosthesis was derived. MatLab software was used to generate the function graph of pelvis forward inclination and abduction angle and deduce the motion of acetabular prosthesis.Results:The dynamic changes of acetabular tilt angle and abduction angle when the pelvis rotated around the coronal axis were functionally related to the anterior-posterior tilt of the pelvis in a nonlinear pattern. When the pelvis rotates around the coronary axis, the anterior inclination angle formula is α 1=arcsin (sinβ 1×cosα×cosθ+cosβ 1×sinα); When the acetabulum axis faces downwards the abduction angle formula is θ 1=arccot (cosβ 1×cotθ-sinβ 1×tanα/sinθ); When the acetabulum axis faces upwards the abduction angle formula is θ 1=π-abs[arccot (cosβ 1×cotθ-sinβ 1×tanα/sinθ)] withα being the initial acetabular forward angle, θ being the initial acetabular abduction angle, α 1 being the forward angle of the acetabular prosthesis after pelvic rotation, θ 1 being the external expansion angle of the acetabular prosthesis after pelvic rotation and β 1 being the rotation angle of the pelvis around the coronal axis. When the pelvis is tilted backward, the anterior inclination angle of the acetabular prosthesis increases first and then decreases, and the abduction angle continues to increase. When the pelvis is tilted forward, the abduction angle decreases first and then increases, and the anterior inclination angle continues to decrease to negative. Conclusion:When the initial anterior inclination angle and abduction angle of acetabular prosthesis change, the curve of anterior inclination and abduction angle change accordingly. The larger the initial anterior inclination angle is, the faster it reaches its peak value, and the larger the peak value is, the faster the abduction angle changes. The larger the initial abduction angle is, the slower the initial anterior inclination angle and the abduction angle change.

Objective To predict the potential geographic distribution of Oncomelania hupensis in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into O. hupensis surveillance and control in Yunnan Province. Methods The O. hupensis snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into O. hupensis snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population). Variables were screened with Pearson correlation test and variance inflation factor (VIF) test. The RF and MaxEnt models and the ensemble model were created using the biomod2 package of the software R 4.2.1, and the potential distribution of O. hupensis snails after 2016 was predicted in Yunnan Province. The predictive effects of models were evaluated through cross-validation and independent tests, and the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS) and Kappa statistics were used for model evaluation. In addition, the importance of environmental variables was analyzed, the contribution of environmental variables output by the models with AUC values of > 0.950 and TSS values of > 0.850 were selected for normalization processing, and the importance percentage of environmental variables was obtained to analyze the importance of environmental variables. Results Data of 148 O. hupensis snail distribution sites and 15 environmental variables were included in training sets of RF and MaxEnt models, and both RF and MaxEnt models had high predictive performance, with both mean AUC values of > 0.900 and all mean TSS values and Kappa values of > 0.800, and significant differences in the AUC (t = 19.862, P < 0.05), TSS (t = 10.140, P < 0.05) and Kappa values (t = 10.237, P < 0.05) between two models. The AUC, TSS and Kappa values of the ensemble model were 0.996, 0.954 and 0.920, respectively. Independent data verification showed that the AUC, TSS and Kappa values of the RF model and the ensemble model were all 1, which still showed high performance in unknown data modeling, and the MaxEnt model showed poor performance, with TSS and Kappa values of 0 for 24%(24/100) of the modeling results. The modeling results of 79 RF models, 38 MaxEnt models and their ensemble models with AUC values of > 0.950 and TSS values of > 0.850 were included in the evaluation of importance of environmental variables. The importance of annual sunshine duration (SSD) was 32.989%, 37.847% and 46.315% in the RF model, the MaxEnt model and their ensemble model, while the importance of annual mean relative humidity (RHU) was 30.947%, 15.921% and 28.121%, respectively. Important environment variables were concentrated in modeling results of the RF model, dispersed in modeling results of the MaxEnt model, and most concentrated in modeling results of the ensemble model. The potential distribution of O. hupensis snails after 2016 was predicted to be relatively concentrated in Yunnan Province by the RF model and relatively large by the MaxEnt model, and the distribution of O. hupensis snails predicted by the ensemble model was mostly the joint distribution of O. hupensis snails predicted by RF and MaxEnt models. Conclusions Both RF and MaxEnt models are effective to predict the potential distribution of O. hupensis snails in Yunnan Province, which facilitates targeted O. hupensis snail control.

Objective To assess transcriptomic differences between carbon tetrachloride(CCl4)-induced and diethyl 1,4-dihydro-2,4,6-trimethyl-3,5-pyridinedicarboxylate(DDC)diet-induced mouse models of liver fibrosis to provide a framework for future research using mouse liver fibrosis models.Methods Mouse models of liver fibrosis were induced by a 10％ CCl4(2 mL/kg)injection or a 0.1％DDC diet.After 4 weeks of induction,serum levels of ALT,AST,and TBil were measured.HE and Sirius red staining were used to observe hepatic inflammation and collagen deposition.Jamall's method was used to evaluate hydroxyproline(Hyp)content in liver tissues.Hepatic tumor necrosis factor-α(TNF-α),interleukin(IL)-6,and IL-1β were measured by ELISA.Total RNA was extracted from murine liver tissues for RNA-sequencing(RNA-seq).Differentially expressed genes of the two models were analyzed by R software and then GO and KEGG enrichment was performed.Then,genes with significant differences were verified.Results Compared with normal mice,serum levels of ALT,AST,and TBil and hepatic expression of TNF-α,IL-6,and IL-1β were significantly increased in mice that received CCl4 and DDC,while the Alb serum level was decreased.Pathological staining showed that the structures of liver tissues were destroyed and a large number of hepatocytes around the central vein were hyalinized and necrotic in CCl4-treated mice.In DDC diet-treated mice,a large amount of porphyrins had been deposited in the liver and a large number of inflammatory cells had infiltrated into the portal area and bile duct.Different degrees of collagen deposition were observed in the liver tissues of the two model mice.Different genes(DEGs)of CCl4-and DDC diet-treated mice were screened using a filter(|logFC|＞2-fold and P＜0.05).As a result,1820 and 2373 DEGs in CCl4-and DDC diet-treated mice were analyzed,including 1302 and 1978 upregulated genes,and 518 and 395 downregulated genes,respectively.GO annotation showed that the two models had important functions in molecular function,biological process,and cell component.KEGG analysis showed that 22 and 29 signaling pathways were activated in CCl4-and DDC diet-induced models,respectively.Among them,16 signaling pathways,such as extracellular matrix receptor interaction,cell cycle,protein digestion and absorption,focal adhesion,and PI3K-Akt,were significantly enriched in the two models(P＜0.05).Cluster analysis showed that Mup11,Mup15,Mup17,and Mup1 were significantly down-regulated in both models,which were identified by RT-qPCR(P＜0.05).Conclusions This study conducted a comparative analysis of the RNA-Seq transcriptomic features of liver fibrosis models induced by exposure to CCl4 and a DDC diet.It examined the gene expression patterns and the pathways influenced by gene expression.The findings serve as a valuable resource for selecting appropriate animal models for future research on the pathogenesis and treatment of liver fibrosis.

Objective To develop an intelligent recognition model based on deep learning algorithms of unmanned aerial vehicle (UAV) images, and to preliminarily explore the value of this model for remote identification, monitoring and management of cattle, a source of Schistosoma japonicum infection. Methods Oncomelania hupensis snail-infested marshlands around the Poyang Lake area were selected as the study area. Image datasets of the study area were captured by aerial photography with UAV and subjected to augmentation. Cattle in the sample database were annotated with the annotation software VGG Image Annotator to create the morphological recognition labels for cattle. A model was created for intelligent recognition of livestock based on deep learning-based Mask R-convolutional neural network (CNN) algorithms. The performance of the model for cattle recognition was evaluated with accuracy, precision, recall, F1 score and mean precision. Results A total of 200 original UAV images were obtained, and 410 images were yielded following data augmentation. A total of 2 860 training samples of cattle recognition were labeled. The created deep learning-based Mask R-CNN model converged following 200 iterations, with an accuracy of 88.01%, precision of 92.33%, recall of 94.06%, F1 score of 93.19%, and mean precision of 92.27%, and the model was effective to detect and segment the morphological features of cattle. Conclusion The deep learning-based Mask R-CNN model is highly accurate for recognition of cattle based on UAV images, which is feasible for remote intelligent recognition, monitoring, and management of the source of S. japonicum infection.

Objective: To determine the spatiotemporal distribution of Schistosoma (S.) japonicum infections in humans, livestock, and Oncomelania (O.) hupensis across the endemic foci of China. Methods: Based on multi-stage continuous downscaling of sentinel monitoring, county-based schistosomiasis surveillance data were captured from the national schistosomiasis surveillance sites of China from 2005 to 2019. The data included S. japonicum infections in humans, livestock, and O. hupensis. The spatiotemporal trends for schistosomiasis were detected using a Joinpoint regression model, with a standard deviational ellipse (SDE) tool, which determined the central tendency and dispersion in the spatial distribution of schistosomiasis. Further, more spatiotemporal clusters of S. japonicum infections in humans, livestock, and O. hupensis were evaluated by the Poisson model. Results: The prevalence of S. japonicum human infections decreased from 2.06% to zero based on data of the national schistosomiasis surveillance sites of China from 2005 to 2019, with a reduction from 9.42% to zero for the prevalence of S. japonicum infections in livestock, and from 0.26% to zero for the prevalence of S. japonicum infections in O. hupensis. Analysis using an SDE tool showed that schistosomiasis-affected regions were reduced yearly from 2005 to 2014 in the endemic provinces of Hunan, Hubei, Jiangxi, and Anhui, as well as in the Poyang and Dongting Lake regions. Poisson model revealed 11 clusters of S. japonicum human infections, six clusters of S. japonicum infections in livestock, and nine clusters of S. japonicum infections in O. hupensis. The clusters of human infection were highly consistent with clusters of S. japonicum infections in livestock and O. hupensis. They were in the 5 provinces of Hunan, Hubei, Jiangxi, Anhui, and Jiangsu, as well as along the middle and lower reaches of the Yangtze River. Humans, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the north of the Hunan Province, south of the Hubei Province, north of the Jiangxi Province, and southwestern portion of Anhui Province. In the 2 mountainous provinces of Sichuan and Yunnan, human, livestock, and O. hupensis infections with S. japonicum were mainly concentrated in the northwestern portion of the Yunnan Province, the Daliangshan area in the south of Sichuan Province, and the hilly regions in the middle of Sichuan Province. Conclusions: A remarkable decline in the disease prevalence of S. japonicum infection was observed in endemic schistosomiasis in China between 2005 and 2019. However, there remains a long-term risk of transmission in local areas, with the highest-risk areas primarily in Poyang Lake and Dongting Lake regions, requiring to focus on vigilance against the rebound of the epidemic. Development of high-sensitivity detection methods and integrating the transmission links such as human and livestock infection, wild animal infection, and O. hupensis into the surveillance-response system will ensure the elimination of schistosomiasis in China by 2030.

Objective To investigate the mechanism of Fuzheng Huayu(FZHY) decoction in the treatment of liver cancer based on network pharmacology. Methods TCMSP, BATMAN, and Drugbank databases were searched for the main chemical components and corresponding targets of FZHY, and STRING database was used to perform a PPI network analysis. Cytoscape software was used to establish a drug-disease network model and perform a network analysis, and R language was used to perform GO and KEGG enrichment analysis of targets. Results A total of 192 intersection genes between FZHY and liver cancer and 95 potential compounds were screened out, among which quercetin and luteolin were the active components with an important regulatory role. INS, IL-6, and EGFR were the key targets for the potential effect of FZHY. The GO enrichment analysis showed the involvement in various biological processes such as response to drug and response to oxygen level, and the KEGG enrichment analysis showed the involvement in the signaling pathways including apoptosis and tumor necrosis factor signaling pathways. Conclusion Based on the method of network pharmacology, this study reveals the mechanism of action of multiple targets and targets of FZHY in the treatment of liver cancer, which provides a theoretical basis for clinical and basic scientific research.

BACKGROUND: Zinc, an inorganic antibacterial material, has a suitable degradation rate and good antibacterial property. Adding alloying elements can improve the mechanical properties and biocompatibility of the material, which is the development direction of novel medical biodegradable metal materials. There is still lack a comparable research on the antibacterial properties among zinc-based materials. OBJECTIVE: To investigate the antibacterial properties of pure zine and zinc-based alloys in vivo. METHODS: Eighty Sprague-Dawley rats, SPF grade, were randomized into two groups (n=40/group) , and all rats were injected with Staphylococcus aureus or Escherichia coli solution to prepare infection models. Different materials (Zn, ZnAl, ZnSr, Zn3 Mg, Zn3 Ag, Zn3 Ca and Zn4 Cu; five rats for each material) were implanted into the medullary cavity of femur. The control group without any material was set. At 1, 4, 7 and 14 days after implantation, the changes of body temperature, white blood cell count, serum tumor necrosis factor α and serum zinc content in rats were detected. The secretions and tissues of the surgical site were collected to identify the bacterial species. RESULTS AND CONCLUSION: (1) The body temperature in all the rats was increased to different extents after bacterial infection, but the temperature of the rats implanted with zinc and zinc alloys was always lower than that in the control group at 7 and 14 days (P < 0.05) . The temperature in the Zn3 Ag group was significantly lower than that in the other groups at 7 and 14 days (P < 0.05) . (2) The white blood cell count and tumor necrosis factor α level in the zinc and zinc alloys groups were significantly lower than those in the control group at 7 and 14 days after implantation (P < 0.05) . The white blood cell count and tumor necrosis factor α level in the Zn3 Ag group were significantly lower than those in the other groups (P < 0.05) . (3) The serum zinc content in all groups has no significant difference (P> 0.05) . (4) The bacterial culture results showed S.aureus (+) in the Staphylococcus aureus infection group and E.coli (+) in the Escherichia coli infection group. (5) To conclude, degradable zinc-based alloys exert marked antibacterial effects, and Zn3 Ag alloys have the best antibacterial activity.