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 explore the diagnosis and treatment of adolescence-onset methylenetetrahydrofolate reductase (MTHFR) deficiency.Methods:This was a retrospective case study. Nine patients with adolescence-onset MTHFR deficiency were diagnosed at Peking University First Hospital from January 2016 to December 2022, and followed up for more than 1 year. Their general information, clinical manifestations, laboratory tests, cranial images, MTHFR gene variants, diagnosis, treatment, and outcome were analyzed retrospectively.Results:The 9 patients came from 8 families. They had symptoms at age of 8.0 years to 17.0 years and diagnosed at 9.0 years to 17.5 years. Eight were male and 1 was female. Two patients were brothers, the elder brother developed abnormal gait at 17.0 years; and the younger brother was then diagnosed at 15.0 years of age and treated at the asymptomatic stage, who was 18.0 years old with normal condition during this study. The main manifestations of the 8 symptomatic patients included progressive dyskinesia and spastic paralysis of the lower limbs, with or without intellectual decline, cognitive impairment and behavioral abnormalities. Totally, 15 variants of MTHFR gene were identified in the 9 patients, including 8 novel variants. Five patients had brain image abnormalities. Increased plasma total homocysteine level (65-221 μmol/L) was found in all patients, and decreased to 20-70 μmol/L after treatment with betaine and calcium folinate. Besides, the 8 symptomatic patients had their behavior and cognitive problems significantly improved, with a legacy of lower limb motor disorders.Conclusions:Late-onset MTHFR deficiency can occur in adolescence. The diagnosis is usually delayed because of non-specific clinical symptoms. The test of blood total homocysteine could be used as a selective screening test. Eight novel varients of MTHFR gene were identified. Timely treatment can improve clinical condition significantly, and pre-symptomatic treatment may prevent brain damage.

Objective:To investigate the clinical features and outcomes of adolescence-onset methylmalonic acidemia (MMA) and explore preventive strategies.Methods:This was a retrospective case analysis of the phenotypes, genotypes and prognoses of adolescence-onset MMA patients. There were 55 patients diagnosed in Peking University First Hospital from January 2002 to June 2023, the data of symptoms, signs, laboratory results, gene variations, and outcomes was collected. The follow-ups were done through WeChat, telephone, or clinic visits every 3 to 6 months.Results:Among the 55 patients, 31 were males and 24 were females. The age of onset was 12 years old (range 10-18 years old). They visited clinics at Tanner stages 2 to 5 with typical secondary sexual characteristics. Nine cases (16%) were trigged by infection and 5 cases (9%) were triggered by insidious exercises. The period from onset to diagnosis was between 2 months and 6 years. Forty-five cases (82%) had neuropsychiatric symptoms as the main symptoms, followed by cardiovascular symptoms in 12 cases (22%), kidney damage in 7 cases (13%), and eye disease in 12 cases (22%). Fifty-four cases (98%) had the biochemical characteristics of methylmalonic acidemia combined with homocysteinemia, and 1 case (2%) had the isolated methylmalonic acidemia. Genetic diagnosis was obtained in 54 cases, with 20 variants identified in MMACHC gene and 2 in MMUT gene. In 53 children with MMACHC gene mutation,1 case had dual gene variants of PRDX1 and MMACHC, with 105 alleles. The top 5 frequent variants in MMACHC were c.482G>A in 39 alleles (37%), c.609G>A in 17 alleles (16%), c.658_660delAAG in 11 alleles (10%), c.80A>G in 10 alleles (10%), c.567dupT and c.394C>T both are 4 alleles (4%). All patients recovered using cobalamin, L-carnitine, betaine, and symptomatic therapy, and 54 patients (98%) returned to school or work.Conclusions:Patients with adolescence-onset MMA may triggered by fatigue or infection. The diagnosis is often delayed due to non-specific symptoms. Metabolic and genetic tests are crucial for a definite diagnosis. Treatment with cobalamin, L-carnitine, and betaine can effectively reverse the prognosis of MMA in adolescence-onset patients.

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 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.

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.