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.

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

With widespread application of solid organ transplantation (SOT), the incidence of postoperative invasive fungal disease (IFD) in SOT recipients has been increased year by year. In recent years, the awareness of preventive antifungal therapy for SOT recipients has been gradually strengthened. However, the problem of fungal resistance has also emerged, leading to unsatisfactory efficacy of original standardized antifungal regimens. Drug-drug interaction and hepatorenal toxicity induced by drugs are also challenges facing clinicians. In this article, the characteristics of drug-drug interaction and hepatorenal toxicity among triazole, echinocandin and polyene antifungal drugs and immunosuppressants were reviewed, and postoperative preventive strategies for IFD in different types of SOT recipients and treatment strategies for IFD caused by infection of different pathogens were summarized, aiming to provide reference for physicians in organ transplantation and related disciplines.

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 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.

The application of combination antiretroviral therapy(cART)has significantly prolonged the life expectancy of patients infected with human immunodeficiency virus(HIV).However,viral infection and adverse reactions of cART drugs make patients more prone to organ failure.Solid organ transplantation has become a standard treatment for HIV-infected patients with end-stage organ failure.Nevertheless,among HIV-positive soild organ transplant recipients,multiple problems remain to be resolved,such as increased incidence of graft rejection,increased infection risk,drug toxicity and drug interaction between cART therapy and immunosuppressive drugs,etc.It is extremely challenging to deliver appropriate management for HIV-positive soild organ transplant recipients.Therefore,the application of immune induction therapy,calcineurin inhibitors,mammalian target of rapamycin(mTOR)inhibitors and other immunosuppressive drugs in HIV-positive soild organ transplant recipients was reviewed,aiming to provide reference for subsequent management of immunosuppression in HIV-positive soild organ transplant recipients.

Dynamic tracking analysis of monoclonal antibodies (mAbs) biotransformation in vivo is crucial, as certain modifications could inactivate the protein and reduce drug efficacy. However, a particular challenge (i.e. immune recognition deficiencies) in biotransformation studies may arise when modifications occur at the paratope recognized by the antigen. To address this limitation, a multi-epitope affinity technology utilizing the metal organic framework (MOF)@Au@peptide@aptamer composite material was proposed and developed by simultaneously immobilizing complementarity determining region (CDR) mimotope peptide (HH24) and non-CDR mimotope aptamer (CH1S-6T) onto the surface of MOF@Au nanocomposite. Comparative studies demonstrated that MOF@Au@peptide@aptamer exhibited significantly enhanced enrichment capabilities for trastuzumab variants in comparison to mono-epitope affinity technology. Moreover, the higher deamidation ratio for LC-Asn-30 and isomerization ratio for HC-Asn-55 can only be monitored by the novel bioanalytical platform based on MOF@Au@peptide@aptamer and liquid chromatography-quadrupole time of flight-mass spectrometry (LC-QTOF-MS). Therefore, multi-epitope affinity technology could effectively overcome the biases of traditional affinity materials for key sites modification analysis of mAb. Particularly, the novel bioanalytical platform can be successfully used for the tracking analysis of trastuzumab modifications in different biological fluids. Compared to the spiked phosphate buffer (PB) model, faster modification trends were monitored in the spiked serum and patients' sera due to the catalytic effect of plasma proteins and relevant proteases. Differences in peptide modification levels of trastuzumab in patients' sera were also monitored. In summary, the novel bioanalytical platform based on the multi-epitope affinity technology holds great potentials for in vivo biotransformation analysis of mAb, contributing to improved understanding and paving the way for future research and clinical applications.

Depressive disorder ranks as a major bur-den of disease worldwide,yet the current antidepressant medications are limited by frequent non-responsiveness and significant side effects.The lateral septum(LS)is thought to control of depression,however,the cellular and circuit substrates are largely unknown.Here,we identified a subpopulation of LS GABAergic adenosine A2A receptors(A2AR)-positive neurons mediating depres-sive symptoms via direct projects to the lateral habenula(LHb)and the dorsomedial hypothalamus(DMH).Activa-tion of A2AR in the LS augmented the spiking frequency of A2AR-positive neurons leading to a decreased activation of surrounding neurons and the bi-directional manipula-tion of LS-A2AR activity demonstrated that LS-A2ARs are necessary and sufficient to trigger depressive pheno-types.Thus,the optogenetic modulation(stimulation or inhibition)of LS-A2AR-positive neuronal activity or LS-A2AR-positive neurons projection terminals to the LHb or DMH,phenocopied depressive behaviors.Moreover,A2AR are upregulated in the LS in two male mouse mod-els of repeated stress-induced depression.This identifica-tion that aberrantly increased A2AR signaling in the LS is a critical upstream regulator of repeated stress-induced depressive-like behaviors provides a neurophysiological and circuit-based justification of the antidepressant poten-tial of A2AR antagonists,prompting their clinical transla-tion.

Background::The calcineurin inhibitor (CNI)-based immune maintenance regimen that is commonly used after renal transplantation has greatly improved early graft survival after transplantation; however, the long-term prognosis of grafts has not been significantly improved. The nephrotoxicity of CNI drugs is one of the main risk factors for the poor long-term prognosis of grafts. Sirolimus (SRL) has been employed as an immunosuppressant in clinical practice for over 20 years and has been found to have no nephrotoxic effects on grafts. Presently, the regimen and timing of SRL application after renal transplantation vary, and clinical data are scarce. Multicenter prospective randomized controlled studies are particularly rare. This study aims to investigate the effects of early conversion to a low-dose CNI combined with SRL on the long-term prognosis of renal transplantation.Methods::Patients who receive four weeks of a standard regimen with CNI + mycophenolic acid (MPA) + glucocorticoid after renal transplantation in multiple transplant centers across China will be included in this study. At week 5, after the operation, patients in the experimental group will receive an additional administration of SRL, a reduction in the CNI drug doses, withdrawal of MPA medication, and maintenance of glucocorticoids. In addition, patients in the control group will receive the maintained standard of care. The patients’ vital signs, routine blood tests, routine urine tests, blood biochemistry, serum creatinine, BK virus (BKV)/cytomegalovirus (CMV), and trough concentrations of CNI drugs and SRL at the baseline and weeks 12, 24, 36, 48, 72, and 104 after conversion will be recorded. Patient survival, graft survival, and estimated glomerular filtration rate will be calculated, and concomitant medications and adverse events will also be recorded.Conclusion::The study data will be utilized to evaluate the efficacy and safety of early conversion to low-dose CNIs combined with SRL in renal transplant patients.Trial registration::Chinese Clinical Trial Registry, ChiCTR1800017277.