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.

A centrifugation-free,single-reaction colorimetric method for detection of glucose,utilizing a dual nanozyme cascade system based on gold nanoparticles(AuNPs)and iron-doped carbon dots(FeCDs),was developed in this work.The AuNPs exhibited glucose oxidase-like activity to catalyze glucose oxidation for generation of H2O2,while the FeCDs demonstrated peroxidase-like activity to subsequently catalyze the H2O2-mediated oxidation of 3,3',5,5'-tetramethylbenzidine(TMB).To prevent interference from the blue signal generated by self-aggregation of AuNPs in subsequent quantitative detection,the reaction system was terminated with HCl,converting oxTMB into a stable yellow product.Based on changes in the absorbance at 450 nm of this yellow solution,a quantitative relationship was established between glucose concentration and absorbance at 450 nm(A450).Experimental results demonstrated that this sensor achieved a linear detection range of 44 μmol/L to 11.11 mmol/L(R2=0.993)with a detection limit of 30.68 μmol/L and spiked recoveries of 97.9%-104.7%.By integrating smartphone-based color recognition capabilities,a rapid visual detection platform was established for quantification of glucose through RGB analysis.The validation experimental results using commercial glucose injection samples further confirmed the practical application potential of this methodology.

Objective To investigate the population characteristics,distribution of traditional Chinese medicine(TCM)syndromes and influencing factors of long-term prognosis of diarrhea-predominant irritable bowel syndrome(IBS-D),and to provide evidence for the formulation of intervention program for IBS-D patients.Methods A total of 124 patients with IBS-D admitted to the medical institutions of the project team members from July 2020 to August 2022 were selected.According to the scoring results of IBS Quality of Life Measure(IBS-QOL),the patients were divided into the good prognosis group(81 cases)and the poor prognosis group(43 cases).The distribution of TCM syndromes in patients with IBS-D was explored,and the difference of IBS-QOL scores of the patients between good prognosis group and poor prognosis group was compared.Univariate logistic regression analysis and multivariate logistic regression analysis were used to determine the main risk factors for poor prognosis in patients with IBS-D.Results(1)The analysis of population characteristics showed that there was no significant difference in the proportion of male and female patients with IBS-D.The patients with IBS-D were usually middle-aged,and had a large interval span of the course of disease.The severity of their symptoms was mostly moderate.All of the patients with IBS-D had various degrees of anxiety and depression,and had nutritional imbalance.(2)The distribution of TCM syndromes in the patients with IBS-D were shown as the following:78 cases were identified as liver depression and spleen deficiency type,accounting for 62.90％;26 cases were identified as spleen-qi deficiency type,accounting for 20.97％;20 cases were identified as spleen and kidney yang deficiency type,accounting for 16.13％.(3)Analysis of IBS-QOL score showed that compared with the good prognosis group,the items scores of negative emotion,physical function,behavioral disorder,health status,being fastidious about food,social function,sexual behavior and interpersonal relationship of IBS-QOL in the poor prognosis group were significantly lowered(P＜0.01).(4)The univariate analysis showed that the risk of poor prognosis in patients with IBS-D would be increased by the factors of age,education level,course of disease,severity of symptoms,anxiety state,depression state,TCM syndrome types,Acute Physiology and Chronic Health Evaluation scoring system Ⅱ(APACHE 11)score,complication of neurological diseases,hemoglobin level,albumin level and total protein level(P＜0.01).(5)The multivariate Logistic regression analysis showed that the risk factors for poor prognosis of IBS-D patients involved age,education level below junior high school,the severity of symptoms being severe,Self-Rating Anxiety Scale(SAS)score,Self-Rating Depression Scale(SDS)score,TCM syndrome being liver depression and spleen deficiency type,hemoglobin level,albumin level and total protein level(P＜0.01).Conclusion Most of IBS-D patients exert long-term poor prognosis,and their long-term prognosis is affected by the factors of age,education level,severity of symptoms,anxiety and depression state,nutritional imbalance and TCM syndrome being liver depression and spleen deficiency type.The identification of the risk factors of poor prognosis will provide evidence for the formulation and adjustment of clinical intervention programs.

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.

46XY simple gonadal hypoplasia, also known as Sweyer syndrome, patients often due to primary amenorrhea or pubertal secondary sex characteristics do not develop the doctor, its combined gonadal tumor is more likely, in the treatment process is often recommended prophylactic removal of gonads, postoperative hormone replacement therapy. We describe two patients diagnosed with Sweyer syndrome, one with gonadowlastoma and mature teratoma, and one with nodular Leydig cell hyperplasia and ectopic adrenal tissue, and reviews the literature.

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.