ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

ObjectiveTo prepare triptolide-Chuanxiong Rhizoma extract ethanol transfersomes（TP-CX@TESs）， conduct its quality evaluation， and investigate its in vitro anti-inflammatory efficacy and the underlying mechanisms. MethodsTP-CX@TESs was prepared via the ultrasonic injection method. With encapsulation efficiency and particle size as evaluation indicators， Box-Behnken design-response surface methodology（BBD-RSM） was employed to optimize the formulation process. The TP-CX@TESs prepared under the optimal process was characterized and evaluated for in vitro transdermal performance. A lipopolysaccharide（LPS）-induced RAW264.7 cell inflammation model was established. After 24 h of drug intervention， the levels of inflammatory factors such as nitric oxide（NO）， interleukin-6（IL-6）， and tumor necrosis factor-α（TNF-α） in the cell supernatant were detected. Western blot was used to determine the protein expression levels of Janus kinase 2（JAK2）， signal transducer and activator of transcription 3（STAT3）， and α7 nicotinic acetylcholine receptor（α7nAChR）， and real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was applied to measure the mRNA expression levels of JAK2， STAT3， the encoding gene of α7nAChR（CHRNA7）， and nuclear transcription factor-κB（NF-κB）. ResultsResults of BBD-RSM showed that the optimal formulation for preparing TP-CX@TESs was as follows：egg yolk lecithin content of 2.3%， ethanol volume fraction of 30%， and ratio of polysorbate-80 to egg yolk lecithin of 2∶5. Microscopic characterization revealed that TP-CX@TESs exhibited a spherical-like structure with a particle size of （105.60±3.85） nm， a polydispersity index of 0.19±0.03， and a Zeta potential of （-15.89±0.98） mV. The encapsulation efficiencies of triptolide， ferulic acid， and ligustilide were （76.88±4.40）%， （78.84±4.40）%， and （65.88±0.06）%， respectively. Both in vitro release and transdermal penetration of triptolide， ferulic acid， and ligustilide in TP-CX@TESs all followed the first-order kinetic model， showing a certain sustained-release property. Experimental results in RAW264.7 cells indicated that TP-CX@TESs significantly inhibited the release of NO， TNF-α， and IL-6（P<0.01）， remarkably upregulated the protein expression levels of STAT3 and α7nAChR（P<0.01）， increased the mRNA expression level of CHRNA7， and significantly downregulated the mRNA expression level of NF-κB（P<0.05， P<0.01）. ConclusionThe optimized formulation process of TP-CX@TESs is simple and feasible， along with favorable in vitro release property， good transdermal permeability， and excellent in vitro anti-inflammatory activity， the mechanism is related to the inhibition of NF-κB.

Objective To analyze the factors influencing hypercoagulable state in patients with benign prostatic hyperplasia(BPH)after surgery,so as to provide reference for preventing postoperative thrombosis in BPH.Methods A retrospective analysis was conducted on the clinical data of 307 BPH patients who underwent surgery in the Department of Urology at the First Affiliated Hospital of Xi'an Jiaotong University during Apr.2022 and Sep.2023.Patients were divided into the hypercoagulable state group and non-hypercoagulable state group based on the presence of abnormal postoperative coagulation parameters.Single factor and binary logistic regression analysis were used to screen risk factors affecting postoperative blood hypercoagulability in BPH patients.Results Among the 307 BPH patients,45(14.66％)developed a hypercoagulable state postoperatively.Univariate analysis revealed statistically significant differences between the hypercoagulable and non-hypercoagulable groups regarding patients'age,length of hospital stay,body mass index(BMI),history of hypertension,history of diabetes,and blood type(P＜0.05).Binary logistic regression analysis identified BMI(OR=1.135,95％CI:1.006-1.281,P=0.039),history of hypertension(OR=2.342,95％CI:1.103-4.927,P=0.027),and blood type(OR=2.270,95％CI:1.066-4.836,P=0.034)as independent risk factors for postoperative hypercoagulable state.Conclusion Non-O blood type,high BMI,and history of hypertension are independent risk factors for the occurrence of hypercoagulable state following surgery for BPH.

Objective To analyze the factors influencing hypercoagulable state in patients with benign prostatic hyperplasia(BPH)after surgery,so as to provide reference for preventing postoperative thrombosis in BPH.Methods A retrospective analysis was conducted on the clinical data of 307 BPH patients who underwent surgery in the Department of Urology at the First Affiliated Hospital of Xi'an Jiaotong University during Apr.2022 and Sep.2023.Patients were divided into the hypercoagulable state group and non-hypercoagulable state group based on the presence of abnormal postoperative coagulation parameters.Single factor and binary logistic regression analysis were used to screen risk factors affecting postoperative blood hypercoagulability in BPH patients.Results Among the 307 BPH patients,45(14.66％)developed a hypercoagulable state postoperatively.Univariate analysis revealed statistically significant differences between the hypercoagulable and non-hypercoagulable groups regarding patients'age,length of hospital stay,body mass index(BMI),history of hypertension,history of diabetes,and blood type(P＜0.05).Binary logistic regression analysis identified BMI(OR=1.135,95％CI:1.006-1.281,P=0.039),history of hypertension(OR=2.342,95％CI:1.103-4.927,P=0.027),and blood type(OR=2.270,95％CI:1.066-4.836,P=0.034)as independent risk factors for postoperative hypercoagulable state.Conclusion Non-O blood type,high BMI,and history of hypertension are independent risk factors for the occurrence of hypercoagulable state following surgery for BPH.

Objective:To explore the feasibility of using low-dose computed tomography(LDCT)with deep learning reconstruction(DLR)on the chest for the screening of lung nodules,and to compare the image quality and detection rate of nodules between LDCT and routine dose CT(RDCT)-DLR.Methods:A total of 104 overweight or obese patients[body mass index(BMI)≥25 kg/m2]who received CT examination on chest due to pulmonary nodule screening from September to December 2023 were included to conduct prospective study.All patients underwent respectively RDCT(120 kV)and LDCT(100 kV)scans,all of the two scans used the modulation of automatic tube current,and adopted deep learning AI algorithm ClearInfinity to conduct reconstruction(RDCT:CI 40%,LDCT:CI 50%).Radiation dose and nodules number of them were recorded.At the T8 vertebral level,CT values(Hounsfield Units,HU)of mediastinal fat and lung parenchyma in the right lower lobe were measured,along with image noise(standard deviation,SD).The signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were subsequently calculated.Two radiologists independently performed subjective evaluations of image quality and pulmonary nodules using a Likert 4-point scale.Paired t-tests or Wilcoxon rank-sum test were employed to compare differences in radiation dose,objective image noise,and subjective scores between LDCT and RDCT.Results:A total of 104 patients were enrolled,including 54 males and 50 females,with a mean age of 52±13 years and a BMI of(27.77±2.64)kg/m2.The effective radiation dose of LDCT demonstrated a statistically significant reduction compared to RDCT(Z=-8.853,P<0.001),with a mean effective radiation dose reduction of 77.86%.The differences in lung CT value,lung noise,fat noise,lung parenchyma SNR,fat SNR and CNR of images between two groups were significant(Z=-3.022,-2.327,-4.785,-2.059,-3.765,-4.013,P<0.05),while there were not significant differences in the comparisons for fat CT value and lung parenchyma SNR(P>0.05).The image contrast,image noise,and subjective score for image quality of lung nodule of LDCT were lower than those of RDCT(t=2.877,2.387,5.096,P<0.05),but all subjective scores of that were>3,which can meet the requirements of clinical diagnosis.In terms of nodule detection,RDCT found out about 418 nodules,while LDCT found out about 421,the false positive rate of LDCT only was 0.72%.Conclusion:In overweight or obese patients,LDCT that combined with DLR algorithm on chest is equivalent to RDCT on image quality and the detection rate of lung nodule,and it significantly reduce radiation exposure on patients at the same time.

The purpose of this study was to establish a luciferase immunosorbent assay(LISA)using the Crimean-Congo hemorrhagic fever virus(CCHFV)glycoprotein C(Gc),a specific antigen,for the detection of CCHFV IgG antibodies.Three antigenic fragments based on CCHFV glycoprotein C were designed,and three recombinant plasmids were constructed by liga-tion with the NanoLuc luciferase(NLuc)expression vector pNLF1-N through molecular cloning.The accuracy of the sequences in the recombinant plasmids was confirmed through sequencing.The recombinant plasmids were transfected into eukaryotic cells to obtain fusion proteins containing specific antigens and luciferase,and the expression of the fusion proteins was verified by western blotting,thereby facilitating the establishment of the CCHFV-LISA detection technique.The assay's sensitivity,specificity,and stability were evaluated and compared with those of a commercial CCHFV IgG antibody test kit.Three recom-binant antigen fragments of CCHFV Gc—NLuc-Gc-Full,NLuc-Gc-C1,and NLuc-Gc-C2—were expressed,with molecular weights of 80.1 kDa,62.8 kDa,and 53.9 kDa,respectively.The optimal fragment for CCHFV detection was NLuc-Gc-C2.The sensitivity of the CCHFV-LISA was 90.9％,and the specificity was 100％;the findings were highly concordant with those for the commercial CCHFV enzyme-linked immunosorbent assay kit.Repeatability tests indicated no statistically significant differ-ences in inter-and intra-assay variability within the same batch.The LISA was highly specific,sensitive,and user-friendly in detecting IgG antibodies against the CCHFV.Therefore,this method may facilitate serological diagnosis and epidemiological studies in endemic regions,and provide essential technical support for disease surveillance and early warning.

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

The purpose of this study was to establish a luciferase immunosorbent assay(LISA)using the Crimean-Congo hemorrhagic fever virus(CCHFV)glycoprotein C(Gc),a specific antigen,for the detection of CCHFV IgG antibodies.Three antigenic fragments based on CCHFV glycoprotein C were designed,and three recombinant plasmids were constructed by liga-tion with the NanoLuc luciferase(NLuc)expression vector pNLF1-N through molecular cloning.The accuracy of the sequences in the recombinant plasmids was confirmed through sequencing.The recombinant plasmids were transfected into eukaryotic cells to obtain fusion proteins containing specific antigens and luciferase,and the expression of the fusion proteins was verified by western blotting,thereby facilitating the establishment of the CCHFV-LISA detection technique.The assay's sensitivity,specificity,and stability were evaluated and compared with those of a commercial CCHFV IgG antibody test kit.Three recom-binant antigen fragments of CCHFV Gc—NLuc-Gc-Full,NLuc-Gc-C1,and NLuc-Gc-C2—were expressed,with molecular weights of 80.1 kDa,62.8 kDa,and 53.9 kDa,respectively.The optimal fragment for CCHFV detection was NLuc-Gc-C2.The sensitivity of the CCHFV-LISA was 90.9％,and the specificity was 100％;the findings were highly concordant with those for the commercial CCHFV enzyme-linked immunosorbent assay kit.Repeatability tests indicated no statistically significant differ-ences in inter-and intra-assay variability within the same batch.The LISA was highly specific,sensitive,and user-friendly in detecting IgG antibodies against the CCHFV.Therefore,this method may facilitate serological diagnosis and epidemiological studies in endemic regions,and provide essential technical support for disease surveillance and early warning.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.