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 provide direction and reference for the adjustment of the discount rate （DR） in China’s pharmacoeconomic guidelines. METHODS Search was conducted on the official websites of the International Society for Pharmacoeconomics and Outcomes Research， health technology assessment agencies in various countries/regions， as well as relevant websites of other upper-middle-income or high-income countries/regions. The recommended DR， adjustment trends， and setting rationales in pharmacoeconomic evaluation guidelines across different countries/regions were then summarized and compared. Based on theoretical derivation and literature analysis， the effects of different DR on the incremental cost-effectiveness ratio （ICER） were examined. RESULTS & CONCLUSIONS Among the 40 included guidelines， the base-case DR ranged from 1.5% to 5%， with 5% being the most common value； the range for sensitivity analysis was 0 to 12%. Thirty-six countries/regions applied the same DR to both costs and health outcomes， while in the Netherlands， Belgium， Poland and Czech Republic， DR for costs was higher than for health outcomes. In recent years， Korea， France and Ireland had lowered their DR in response to economic changes， whereas the Netherlands and Czech Republic had raised their DR for cost. The setting of the DR was primarily based on the public project investment interest rate or referred to recommendations from internationally authoritative institutions and other relevant guidelines. The direction and magnitude of the impact of different DR on the ICER largely depended on the distribution of costs and health outcomes between the intervention and reference measure. The setting and adjustment of DR were closely associated with the economic environment. Based on international experience, the DR in China can be lowered by 0.5% to 1.5%， and localized empirical research can be conducted using internationally common estimation methods.

Photodynamic immunotherapy is a promising strategy for cancer treatment. However, the dysfunctional tumor vasculature results in tumor hypoxia and the low efficiency of drug delivery, which in turn restricts the anticancer effect of photodynamic immunotherapy. In this study, we designed photosensitive lipid nanoparticles. The synthesized PFBT@Rox Lip nanoparticles could produce type I/II reactive oxygen species (ROS) by electron or energy transfer through PFBT under light irradiation. Moreover, this nanosystem could alleviate tumor hypoxia and promote vascular normalization through Roxadustat. Upon irradiation with white light, the ROS produced by PFBT@Rox Lip nanoparticles in situ dysregulated calcium homeostasis and triggered endoplasmic reticulum stress, which further promoted the release of damage-associated molecular patterns, enhanced antigen presentation, and stimulated an effective adaptive immune response, ultimately priming the tumor microenvironment (TME) together with the hypoxia alleviation and vessel normalization by Roxadustat. Indeed, in vivo results indicated that PFBT@Rox Lip nanoparticles promoted M1 polarization of tumor-associated macrophages, recruited more natural killer cells, and augmented infiltration of T cells, thereby leading to efficient photodynamic immunotherapy and potentiating the anti-primary and metastatic tumor efficacy of PD-1 antibody. Collectively, photodynamic immunotherapy with PFBT@Rox Lip nanoparticles efficiently program TME through the induction of immunogenicity and oxygenation, and effectively suppress tumor growth through immunogenic cell death and enhanced anti-tumor immunity.

Alzheimer's disease (AD) is regarded as a neurodegenerative disease, and it has been proposed that AD may be a systemic disease. Studies have reported associations between non-neurological diseases and AD. The correlations between AD pathology and systemic (non-neurological) pathological changes are intricate, and the mechanisms underlying these correlations and their causality are unclear. In this article, we review the association between AD and disorders of other systems. In addition, we summarize the possible mechanisms associated with AD and disorders of other systems, mainly from the perspective of AD pathology. Regarding the relationship between AD and systemic pathological changes, we aim to provide a new outlook on the early warning signs and treatment of AD, such as establishing a diagnostic and screening system based on more accessible peripheral samples.
Alzheimer Disease/therapy* ; Humans ; Brain/pathology*

To investigate the clinical significance of platelet-neutrophil ratio in patients with anti-neutrophil cytoplasmic antibody-associated vasculitis(AAV),a total of 128 patients were recruited and retrospectively analyzed in our department from March 2015 to July 2023.Spearman correlation analysis indicated that there was negative correlation between the level of PNR and Birmingham vasculitis activity score(BVAS)in AAV patients(r=-0.268,P=0.002).According to the PNR optimal cutoff value(26.4)determinated by X-tile bioinformatics software version 3.6.1 for predicting the survival rate,AAV patients were divided into high level PNR(HPNR)group(≥26.4)(n=105)and low level PNR(LPNR)group(<26.4)(n=23).Kaplan-Meier survival analysis showed that the survival rate of HPNR group was significantly higher than that of LPNR group(P<0.001).The level of PNR was correlated with poor prognosis of kidney(OR=2.54,95%CI:1.1-5.88,P=0.029).In conclusion,the level of PNR is closely related to disease activity and prognosis of AAV,and it might be a potential biomarker for predicting the disease activity and predicting the prognosis.

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 compare the therapeutic effects of manual reduction and machine reduction in patients with benign paroxysmal positional vertigo(BPPV)at different ages.Methods Randomly select 300 patients clinically diagnosed with BPPV who visited the Hearing Center of the First Affiliated Hospital of Wenzhou Medical University from April 2022 to December 2023.They were divided into young and middle-aged group of 170 cases(18-59 years old)and elderly group of 130 cases(≥60 years old)according to age.Each group was further divided equally into experimental group and control group based on the diagnosis and treatment methods adopted by the patients.The experimental group patients were treated with a benign paroxysmal positional vertigo diagnosis and treatment system(model/specification:SRM-Ⅳ)for machine reduction.The control group patients were treated with manual reduction.Compare the effective rate of reduction,reduction frequency,incidence of residual dizziness symptoms,and duration of each group.Results In young and middle-aged patients,the incidence and duration of residual dizziness symptoms after reduction in experimental group were significantly lower than those in control group(P<0.05),and there was no statistically significant difference in the effective rate and number of reductions(P>0.05).In elderly group,the reduction efficiency of experimental group was significantly higher than that of control group,and the reduction frequency was lower than that of the control group(P<0.05).There was no statistically significant difference in the incidence and duration of residual dizziness symptoms after reduction(P>0.05).Conclusion Machine reduction can significantly improve the reduction efficiency of elderly BPPV patients,significantly shorten the duration of residual dizziness after reduction treatment in young and middle-aged patients,and reduce its incidence.

Rheumatoid arthritis （RA） is a chronic autoimmune disease with a complex pathogenesis. Immune dysfunction， synovial inflammation， and bone destruction are the key pathological links. The theory of "harmful hyperactivity and responding inhibition" is a high-level summary of the coordinated development of things in nature and the generation and restriction of the five elements and the six factors in nature. People and all things have the same origin， and the theory of "harmful hyperactivity and responding inhibition" represents the intrinsic regulation mechanism of the human body's homeostasis， reflecting the unity of opposites of "hyperactivity" and "inhibition" and emphasizing coordination and stabilization. In the pathogenesis of RA， the excessive immune response disrupts the normal body balance， which is closely related to the process of "hyperactivity becoming harmful". Synovial inflammation， tissue hyperplasia， and bone destruction are pathological results of the dysregulation of the body's immune self-stabilization function and can be regarded as the process of "failing to inhibition". Therefore， the theory of "hyperactivity harmful hyperactivity and responding inhibition" provides a unique perspective for understanding the modern pathological mechanisms of RA. Based on the theory of "harmful hyperactivity and responding inhibition" and the pathogenesis of RA， the author analyzed the modern medical basis of RA from the perspective of traditional Chinese medicine （TCM） and revealed the intrinsic connection between TCM pathogenesis such as insufficiency of vital energy and blood， strong defensive Qi and weak nutrient Qi， and intertwined phlegm and blood stasis and modern research on autoimmune disorders， synovial inflammation， and bone destruction. With the therapeutic criterion of "harm inhibition and responsible supporting"， the article summarized the mechanism of TCM in calming hyperactivity and supporting invincibility， which provided theoretical references for the clinical treatment of RA.

Purpose/Significance To grasp the technological advantages of digitization empowerment,and to explore the effective path of digitization enabling medical education.Method/Process From the three aspects of experience enhancement,content enrichment and process coordination,the function mode of digitization enabling medical education is clarified.Result/Conclusion To achieve digitization enabling medical education,it's necessary to deepen digital sharing,promote the reconstruction of digital scenes of medical education,op-timize the presentation of digital content of medical education,and coordinate the operation of digital process of medical education.

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.