ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

Researchers commonly use cyclization recombination enzyme/locus of X-over P1 (Cre/loxP) technology-based conditional gene knockouts of model mice to investigate the functional roles of genes of interest in Sertoli and Leydig cells within the testis. However, the shortcomings of these genetic tools include high costs, lengthy experimental periods, and limited accessibility for researchers. Therefore, exploring alternative gene silencing techniques is of great practical value. In this study, we employed adeno-associated virus (AAV) as a vector for gene silencing in Sertoli and Leydig cells. Our findings demonstrated that AAV serotypes 1, 8, and 9 exhibited high infection efficiency in both types of testis cells. Importantly, we discovered that all three AAV serotypes exhibited exquisite specificity in targeting Sertoli cells via tubular injection while demonstrating remarkable selectivity in targeting Leydig cells via interstitial injection. We achieved cell-specific knockouts of the steroidogenic acute regulatory ( Star ) and luteinizing hormone/human chorionic gonadotropin receptor (Lhcgr) genes in Leydig cells, but not in Sertoli cells, using AAV9-single guide RNA (sgRNA)-mediated gene editing in Rosa26-LSL-Cas9 mice. Knockdown of androgen receptor ( Ar ) gene expression in Sertoli cells of wild-type mice was achieved via tubular injection of AAV9-short hairpin RNA (shRNA)-mediated targeting. Our findings offer technical approaches for investigating gene function in Sertoli and Leydig cells through AAV9-mediated gene silencing.
Animals ; Male ; Leydig Cells/metabolism* ; Mice ; Dependovirus/genetics* ; Sertoli Cells/metabolism* ; Gene Silencing ; Genetic Vectors ; Testis/cytology*

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

Objective To observe the effects of abdominal penetrating moxibustion combined with acupuncture at the"four chong points"on balance,walking function and trunk control in patients recovering from stroke.Methods Seventy-eight patients recovering from stroke were randomly divided into an observation group and a control group,with 39 patients in each group.The control group was given conventional rehabilitation exercises,while the observation group was given abdominal penetrating moxibustion combined with acupuncture at the"four chong points"on the basis of the control group.Both groups were treated for 2 consecutive months.After 2 months of treatment,the clinical efficacy of the two groups was evaluated,and the changes in the Berg Scale score and the Timed Up and Go Test(TUGT)were observed before and after treatment.The changes in the National Institutes of Health Stroke Scale(NIHSS)scores were compared before and after treatment between the two groups.The Sheikh Trunk Control Scale scores were also evaluated.Results(1)The total effective rate of the observation group was 94.87%(37/39),and the total effective rate of the control group was 80.00%(31/39),and the efficacy 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 Berg scores of the patients in the two groups were significantly increased(P＜0.05),and the Berg scores of the observation group were higher than those of the control group,and the difference was statistically significant(P＜0.05).(3)After treatment,the TUGT time and NIHSS score of patients in the two groups were significantly improved(P＜0.05),and the TUGT time of the observation group was shorter than that of the control group,and the NIHSS score was lower than that of the control group,and the difference was statistically significant(P＜0.05).(4)After treatment,the Sheikh trunk control scores of the two groups were significantly increased(P＜0.05),and the Sheikh trunk control score of the observation group was higher than that of the control group,and the difference was statistically significant(P＜0.05).Conclusion Abdominal penetrating moxibustion method combined with acupuncture at the four chong points for the treatment of stroke recovery can effectively restore the patients'balance and walking function,improve the patients'trunk control ability,and the therapeutic effect is precise.

Objective:To investigate whether long non-coding RNA(lncRNA) AW112010 can improve insulin resistance in aging adipocytes through the miR-204/POU2F2 signaling pathway.Methods:In vivo experiment: C57BL/6 mice were divided into young control group(4 months old) and aging model group(18 months old) based on body weight. The expression levels of AW112010, miR-204-5p, POU2F2, aging related indicators(p16, p21), and insulin signaling pathway genes [insulin receptor(INSR), insulin receptor substrate 1(IRS1), phosphatidylinositol kinase(PI3K), protein kinase B(AKT)] in epididymal adipose tissue were detected using real-time fluorescence quantitative PCR(RT-qPCR) and Western blotting. In vitro experiment: Using adriamycin(ADR) to induce 3T3-L1 aging adipocyte model, β-gal staining was used to observe cellular senescence, and miR-204 inhibitor and miR-204 mimic small interfering RNA were successfully constructed and transfected into 3T3-L1 adipocytes. Results:RT-qPCR and Western blot results showed that compared with the young group, the expression of AW112010 in the adipose tissue of aging mice was increased, while the expression of miR-204-5p was decreased. The expressions of POU2F2, p16, and p21 in the adipose tissue of aging mice were increased, while the expressions of INSR, IRS1, PI3K, GLUT4 mRNA and protein were decreased. The β-gal stainging results showed that the number of 3T3-L1 senescent adipocytes induced by ADR was significantly increased, and the expression levels of AW112010, POU2F2, p16, and p21 in ADR-induced senescent adipocytes were increased compared with the control group, while the expression levels of miR-204-5p, INSR, IRS1, PI3K, GLUT4 were decreased, and remaining glucose in the culture medium was increased. Compared with control, overexpression of miR-204 resulted in decreased expressions of aging indicators p16, p21, and target gene POU2F2 while the expressions of INSR and GLUT4 were increased.Conclusion:Upregulation of lncRNA AW112010 in adipocytes of aging mice may induce insulin resistance by targeting miR-204-5p/POU2F2/IRS1.

Objective To investigate the expression of PLCD3 mRNA in the synovium of osteoarthritis(OA)and its relationship with immune cell infiltration.Methods Based on the differentially expressed genes of OA found in the previous study,the expression of phospholipase Cδ3(PLCD3)mRNA was detected by col-lecting synovial samples from OA group and control group.CIBERSORT algorithm was used to analyze the infiltration pattern of immune cells in OA group and control group,and the correlation between PLCD3 and infiltrating immune cells was further analyzed.Results Compared with the control group,the relative expres-sion level of PLCD3 mRNA was significantly increased in synovial samples of OA group(P<0.05).The pro-portions of B cells naive,NK cells activated,M2 macrophages and mast cells activated in synovial tissues of OA group were relatively high(P<0.05).PLCD3 was positively correlated with the proportion of these four immune cells(P<0.05).Conclusion PLCD3 may be a key biomarker for the diagnosis of OA,which may be involved in the pathogenesis of OA by interacting with infiltrating immune cells.

OBJECTIVE To evaluate the economics of trastuzumab deruxtecan versus the physician-selected chemotherapy （TPC） regimen in the second-line treatment of advanced breast cancer with epidermal growth factor receptor 2 （HER-2） low expression from the perspective of the Chinese healthcare system. METHODS Based on the data of DESTINY-Breast04 clinical trial， the dynamic Markov model was constructed. The time frame of the model simulation was 10 years， and the cycle was 3 weeks. Taking cost， quality-adjusted life year （QALY） and incremental cost-effectiveness ratio （ICER） as the model output indicators， the discount rate of 5% was applied， and 3 times China’s per capita gross domestic product （GDP） in 2023 was taken as the willingness-to-pay （WTP） threshold value. Cost-utility analysis was used to evaluate the economics of the two treatment regiments in the hormone receptor-positive cohort and all patient cohorts， and uncertainty analysis was used to verify the robustness of the basic analysis result. RESULTS The results of the basic analysis showed that compared with the TPC regimen， the ICER value of trastuzumab deruxtecan regimen edu.cn were 1 045 655.76 and 906 404.99 yuan/QALY in the hormone receptor-positive cohort and all patients， respectively， both exceeding the WTP threshold （268 074 yuan/QALY）. The results of single factor sensitivity analysis showed that progression-free survival utility value， the price of trastuzumab deruxtecan and progression disease utility had a significant influence on the model results. The results of probability sensitivity analysis showed that when the WTP threshold was 3 times China’s per capita GDP in 2023， the probability of economic viability of trastuzumab deruxtecan was 0. The results of scenario analysis showed that when the patient assistance program for trastuzumab deruxtecan was considered， the probability of trastuzumab deruxtecan regimen being economical was 0. However， when the price of trastuzumab deruxtecan was reduced by 70%， the probability of its being cost-effective was significantly increased to 82.80%. CONCLUSIONS At a WTP threshold of 3 times China’s per capita GDP in 2023， the trastuzumab deruxtecan regimen is not cost-effective compared to TPC regimen for the second-line treatment of advanced breast cancer with HER-2 low expression. Reducing the price of trastuzumab deruxtecan by region can improve its cost-effectiveness.

Objective To explore the molecular mechanisms and cell-cell interactions in the injury process of pancreatic islet transplantation.Methods Single-cell transcriptome data from mouse islets treated with inflammatory factors were used,and data processing was performed using the Seurat package,with integrated data to remove batch effects.Cell subpopulations were annotated based on known markers.Cell-cell interactions in the inflammatory factor-treated group were analyzed using the CellChat package,and inferred based on the expression of cell surface receptors and ligands.Gene set enrichment analysis was used to clarify the biological processes enriched in β-cells after treatment with inflammatory factors.Finally,differentially expressed transcription factors were identified and verified using microarray datasets of donor islet ischemic injury and Western blotting.Results A total of 7 different cell subpopulations were found in mouse islets,with β-cells being the most abundant.Cell-cell interaction network analysis showed that the number and strength of interactions between ductal cells and other cells were the highest.Gene set enrichment analysis showed that after treatment with inflammatory factors,the immune response was positively enriched in β-cells,while peptide hormone metabolism,bile acid metabolism,and ion homeostasis were downregulated.The common differential transcription factors identified in the mouse single-cell transcriptome and the microarray dataset of donor islet ischemic injury were early growth response 1(EGR1),nuclear factor-κB inhibitor α(NFKBIA),and activating transcription factor 3(ATF3).Among them,NFKBIA and ATF3 were upregulated,while EGR1 was downregulated.The expression of EGR1 protein was downregulated after 24 h,48 h,and 72 h of cold ischemia.Conclusions EGR1 is a transcription factor closely related to islet cold ischemia,and future research should focus on the specific mechanisms of EGR1 and its downstream target genes,in order to provide more effective strategies for clinical treatment of islet transplantation.