This case report describes a 68-year-old male patient diagnosed with primary hepatocellular carcinoma (HCC). After receiving Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT), the tumor significantly reduced in size, and tumor markers alpha fetoprotein (AFP) and abnormal prothrombin (PIVKA-Ⅱ) decreased. Postoperative pathological results showed minimal residual tumor cells, indicating that ⁹⁰Y-SIRT has good efficacy and safety in downstaging and conversion of HCC, thereby facilitating subsequent surgical resection.

The triterpenoid saponins of Centella asiatica, including asiaticoside, madecassoside, asiatic acid, and madecassic acid, are pivotal bioactive compounds of the plant. These constituents exhibit a spectrum of pharmacological activities, such as antioxidant, antitumor, and antidepressant effects, promotion of wound healing, and enhancement of microcirculation. Owing to these therapeutic properties, C. asiatica is widely employed in pharmaceutical and cosmetic industries. However, the escalating global demand for its extracts has led to potential supply shortages, prompting researchers to use multiple strategies such as multi-omics, molecular biology, and synthetic biology to conduct extensive studies. These studies encompass the elucidation of the biosynthetic pathways of triterpenoid saponins in C. asiatica, metabolic regulation, the hormonal induction of secondary metabolite synthesis, and the application of biotechnological strategies for natural product production to increase the yield of secondary metabolites in C. asiatica, or to produce active components via microbial chassis, thus satisfying market demands and promoting the sustainable exploitation of wild C. asiatica resources. This article first introduced the triterpenoid saponins of C. asiatica and their biological activities, then summarized the latest research advancements in their biosynthetic pathways, metabolic regulation, and heterologous biosynthesis, and provided an outlook on future development directions, with the aim of providing reference for comprehensive resource development and biotechnological synthesis of active components from C. asiatica.
Centella/genetics* ; Triterpenes/chemistry* ; Biosynthetic Pathways ; Humans ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts

Based on the traditional Chinese medicine(TCM) theory of "kidney-brain interaction", a two-sample Mendelian randomization(MR) analysis was conducted to investigate the causal effects of chronic kidney disease(CKD) on Alzheimer's disease(AD) and analyze the potential mechanisms of kidney-tonifying and essence-replenishing TCM to improve AD. From the perspective that CKD is closely related to the core pathogenesis of AD, namely "kidney deficiency, essence loss, and marrow reduction", genome-wide association study(GWAS) data was used, with the inverse variance weighting(IVW) method as the main approach to reveal the causal association between CKD and AD. Sensitivity analysis was conducted to evaluate the robustness of the results. To further investigate the causal effects of CKD on AD, two different AD datasets were used as outcomes, and the urinary albumin-to-creatinine ratio(UACR) data was used as the exposure for a supplementary analysis. On this basis, the modern scientific mechanism of the kidney-tonifying and essence-replenishing method for improving AD was further explored. The IVW analysis show that CKD(ieu-b-2: OR=1.084, 95%CI[1.011, 1.163], P=0.024; ieu-b-5067: OR=1.001, 95%CI[1.000, 1.001], P=0.002) and UACR(ieu-b-2: OR=1.247, 95%CI[1.021, 1.522], P=0.031; ieu-b-5067: OR=1.001, 95%CI[1.000, 1.003], P=0.015) both have significant causal effects on AD in different datasets, with CKD increasing the risk of AD. The sensitivity analysis further confirmed the reliability of the results. Genetic studies have shown that CKD has a significant causal effect on AD, suggesting that controlling CKD is an important intervention measure for preventing and treating AD. Therefore, further research on CKD's role in AD is crucial in clinical practice. The research enriches the theoretical implication of "kidney-brain interaction", deepens the understanding of AD' etiology, and provides further insights and directions for the prevention and treatment of AD with TCM, specifically from a kidney-based perspective.
Humans ; Alzheimer Disease/genetics* ; Renal Insufficiency, Chronic/genetics* ; Kidney/metabolism* ; Brain/physiopathology* ; Genome-Wide Association Study ; Medicine, Chinese Traditional ; Mendelian Randomization Analysis

Cardiotocography (CTG) is a non-invasive and important tool for diagnosing fetal distress during pregnancy. To meet the needs of intelligent fetal heart monitoring based on deep learning, this paper proposes a TWD-MOAL deep active learning algorithm based on the three-way decision (TWD) theory and multi-objective optimization Active Learning (MOAL). During the training process of a convolutional neural network (CNN) classification model, the algorithm incorporates the TWD theory to select high-confidence samples as pseudo-labeled samples in a fine-grained batch processing mode, meanwhile low-confidence samples annotated by obstetrics experts were also considered. The TWD-MOAL algorithm proposed in this paper was validated on a dataset of 16 355 prenatal CTG records collected by our group. Experimental results showed that the algorithm proposed in this paper achieved an accuracy of 80.63% using only 40% of the labeled samples, and in terms of various indicators, it performed better than the existing active learning algorithms under other frameworks. The study has shown that the intelligent fetal heart monitoring model based on TWD-MOAL proposed in this paper is reasonable and feasible. The algorithm significantly reduces the time and cost of labeling by obstetric experts and effectively solves the problem of data imbalance in CTG signal data in clinic, which is of great significance for assisting obstetrician in interpretations CTG signals and realizing intelligence fetal monitoring.
Humans ; Pregnancy ; Female ; Cardiotocography/methods* ; Deep Learning ; Neural Networks, Computer ; Algorithms ; Fetal Monitoring/methods* ; Heart Rate, Fetal ; Fetal Distress/diagnosis* ; Fetal Heart/physiology*

OBJECTIVE: To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) undergoing total knee arthroplasty (TKA). METHODS: A retrospective cohort study was conducted including RA patients who underwent unilateral TKA between January 2019 and December 2024. Inpatient and 30-day postoperative outpatient follow-up data were collected. Six machine learning algorithms, including decision tree, random forest, logistic regression, support vector machine, extreme gradient boosting, and light gradient boosting machine, were used to construct predictive models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall. SHapley Additive exPlanations (SHAP) values were employed to interpret and rank the importance of individual variables. RESULTS: According to the inclusion criteria, a total of 1 548 patients were enrolled. Ultimately, 18 preoperative indicators were identified as effective predictive features, and 8 postoperative complications were defined as prediction labels for inclusion in the study. Within 30 days after surgery, 453 patients (29.2%) developed one or more complications. Considering overall accuracy, precision, recall, and F1-score, the random forest model [AUC=0.930, 95% CI (0.910, 0.950)] and the extreme gradient boosting model [AUC=0.909, 95% CI (0.880, 0.938)] demonstrated the best predictive performance. SHAP analysis revealed that anti-cyclic citrullinated peptide antibody, C-reactive protein, rheumatoid factor, interleukin-6, body mass index, age, and smoking status made significant contributions to the overall prediction of postoperative complications. CONCLUSION Machine learning-based models enable accurate prediction of postoperative complication risks among RA patients undergoing TKA. Inflammatory and immune-related blood biomarkers, such as anti-cyclic citrullinated peptide antibody, C-reactive protein, and rheumatoid factor, interleukin-6, play key predictive roles, highlighting their potential value in perioperative risk stratification and individualized management.
Humans ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthritis, Rheumatoid/blood* ; Machine Learning ; Postoperative Complications/blood* ; Female ; Male ; Retrospective Studies ; Middle Aged ; Aged ; Risk Factors ; Preoperative Period ; C-Reactive Protein/analysis* ; Risk Assessment

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

OBJECTIVE: To assess the safety and topical efficacy of prim-O-glucosylcimifugin (POG) and investigate the molecular mechanisms of its therapeutic effects in atopic dermatitis (AD). METHODS: The effects of POG on human keratinocyte cell viability and its anti-inflammatory properties were evaluated using cell counting kit-8 assay and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Subsequently, the impact of POG on the differentiation of cluster of differentiation (CD) 4⁺ T cell subsets, including T-helper type (Th) 1, Th2, Th17, and regulatory T (Treg), was examined through in vitro experiments. Network pharmacology analysis was used to elucidate POG's therapeutic mechanisms. Furthermore, the therapeutic potential of topically applied POG was further evaluated in a calcipotriol-induced mouse model of AD. The protein and transcript levels of inflammatory markers, including cytokines, lymphocyte-specific protein tyrosine kinase (Lck) mRNA, and LCK phosphorylation (p-LCK), were quantified using immunohistochemistry, RT-qPCR, and Western blot analysis. RESULTS: POG was able to suppress cell proliferation and downregulate the transcription of interleukin 4 (Il4) and Il13 mRNA. In vitro experiments indicated that POG significantly inhibited the differentiation of Th2 cells, whereas it exerted negligible influence on the differentiation of Th1, Th17 and Treg cells. Network pharmacology identified LCK as a key therapeutic target of POG. Moreover, the topical application of POG effectively alleviated skin lesions in the calcipotriol-induced AD mouse models without causing pathological changes in the liver, kidney or spleen tissues. POG significantly reduced the levels of Il4, Il5, Il13, and thymic stromal lymphopoietin (Tslp) mRNA in the AD mice. Concurrently, POG enhanced the expression of p-LCK protein and Lck mRNA. CONCLUSION Our research revealed that POG inhibits Th2 cell differentiation by promoting p-LCK protein expression and hence effectively alleviates AD-related skin inflammation. Please cite this article as: Zhao H, Ma X, Wang H, Ding XJ, Kuai L, Song JK, Zhang Z, Yang D, Gao CJ, Li B, Zhou M. Prim-O-glucosylcimifugin mitigates atopic dermatitis by inhibiting Th2 differentiation through LCK phosphorylation modulation. J Integr Med. 2025; 23(3): 309-319.
Dermatitis, Atopic/drug therapy* ; Animals ; Humans ; Cell Differentiation/drug effects* ; Phosphorylation/drug effects* ; Mice ; Th2 Cells/drug effects* ; Keratinocytes/drug effects* ; Disease Models, Animal ; Mice, Inbred BALB C ; Calcitriol/analogs & derivatives*

Objective:To investigate the pollution levels and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust in five cities in northern China.Methods:Based on the "Chinese Indoor Environment and Health Surveillance" project carried out by the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention in 2018-2019, during the warm season (April 2018 to September 2018) and the cold season (November 2018 to March 2019), Lanzhou in Northwest China, Shijiazhuang in North China, Panjin in Northeast China, Luoyang in Central China, and Qingdao in East China were selected as the research sites. A total of 87 families were recruited to study residences in real-life scenarios. At the same time, dust samples were collected to detect the concentration of PBDEs. The level of household environmental indicators was measured, and the residential building characteristics and family behavior habits were collected through questionnaires. A total of 142 valid dust samples and 140 valid questionnaires were obtained. The differences in PBDE concentrations across seasons, wind zones, residential building characteristics, and family habits were analyzed. The exploratory factor analysis was performed to investigate the possible sources of PBDEs, and multivariate linear regression was used to explore the factors influencing PBDEs in household dust.Results:The M ( Q1,Q3) of total PBDE concentrations in 142 household dust samples in five cities was 144.51 (106.61, 222.65) ng/g in the warm season and 145.10 (98.57, 180.65) ng/g in the cold season, respectively. There were seasonal differences in the concentration of ∑ 12PBDEs in Luoyang and Shijiazhuang ( P<0.01). The concentration of BDE-71 was highest among PBDE homologues, followed by BDE-66 and BDE-47. Three factors were extracted by exploratory factor analysis in the warm season, and the cumulative variance contribution rate was 67.90%. The multivariate linear regression showed that the house completion less than ten years [ β (95% CI): 0.186 (0.013, 0.359)], infrequent home cooking [ β (95% CI):-0.342 (-0.570, -0.114)], and increased residential PM 10 concentration [ β (95% CI): 0.001 (0.000, 0.002)] during the warm season, as well as the house far from driveway [ β (95% CI): 0.093 (0.013, 0.172)], house area less than 90 m 2 [ β (95% CI):-0.138 (-0.264, -0.013)], and lower residential xylene concentration [ β (95% CI):-0.006 (-0.011, -0.001)] during the cold season might be related to the elevated concentrations of ∑ 12PBDEs in household dust. Conclusion:The pollution of PBDEs in household dust in five northern cities is at a medium to high level. Years of house completion, frequency of cooking at home, residential PM 10 concentration, distance from house to driveway, house area, and residential xylene concentration may influence household PBDE concentrations.

Objective To investigate the correlation between the level of N-terminal pro-Brain natriuretic peptide(NT-proBNP)and cardiorespiratory fitness following acute exposure to high altitude.Methods Forty-six subjects were recruited from the Second Affiliated Hospital of Army Medical University in June 2022,including 19 males and 27 females.After completing cardiopulmonary exercise test(CPET),serological detection of myocardial cell-related markers,and multiple metabolites at a plain altitude(300 meters above sea level),all subjects flew to a high-altitude location(3900 meters above sea level).Biomarker testing and CPET were repeated on the second and third days after arrival at high altitude.Changes in serum biomarker and key CPET indicators before and after rapid ascent to high altitude were compared,and the correlation between serum levels of various myocardial cell-related markers and metabolites and high altitude cardiorespiratory fitness was analyzed.Results Compared with the plain altitude,there was a significant decrease in maximal oxygen uptake after rapid ascent to high altitude[(25.41±6.20)ml/(kg.min)vs.(30.17±5.01)ml/(kg.min),P<0.001].Serum levels of NT-proBNP,Epinephrine(E),plasma renin activity(PRA),angiotensin Ⅱ(Ang Ⅱ),angiotensin-converting enzyme 2(ACE2)and leptin(LEP)significantly increased,with all differences being statistically significant(P<0.05)after acute high altitude exposure.In contrast,no statistically significant differences were observed for creatine kinase MB(CK-MB),cardiac troponin I(cTnI),myoglobin(Myo)and norepinephrine(NE)(P>0.05).Correlation analysis showed a significant negative correlation between NT-proBNP at plain altitude(r=-0.768,P<0.001)and at high altitude(r=-0.791,P<0.001)with maximal oxygen uptake at high altitude.Multivariate linear regression analysis indicated that maximal oxygen uptake at plain altitude(t=2.069,P=0.045),NT-proBNP at plain altitude(t=-2.436,P=0.020)and at high altitude(t=-3.578,P=0.001)were independent influencing factors of cardiorespiratory fitness at high altitude.Conclusion Cardiorespiratory fitness significantly decreases after rapid ascent to high altitude,and the baseline NT-proBNP level at plain altitude is closely related to cardiorespiratory fitness at high altitude,making it a potential predictor indicator for high altitude cardiorespiratory fitness.

Objective:To investigate the pollution levels and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust in five cities in northern China.Methods:Based on the "Chinese Indoor Environment and Health Surveillance" project carried out by the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention in 2018-2019, during the warm season (April 2018 to September 2018) and the cold season (November 2018 to March 2019), Lanzhou in Northwest China, Shijiazhuang in North China, Panjin in Northeast China, Luoyang in Central China, and Qingdao in East China were selected as the research sites. A total of 87 families were recruited to study residences in real-life scenarios. At the same time, dust samples were collected to detect the concentration of PBDEs. The level of household environmental indicators was measured, and the residential building characteristics and family behavior habits were collected through questionnaires. A total of 142 valid dust samples and 140 valid questionnaires were obtained. The differences in PBDE concentrations across seasons, wind zones, residential building characteristics, and family habits were analyzed. The exploratory factor analysis was performed to investigate the possible sources of PBDEs, and multivariate linear regression was used to explore the factors influencing PBDEs in household dust.Results:The M ( Q1,Q3) of total PBDE concentrations in 142 household dust samples in five cities was 144.51 (106.61, 222.65) ng/g in the warm season and 145.10 (98.57, 180.65) ng/g in the cold season, respectively. There were seasonal differences in the concentration of ∑ 12PBDEs in Luoyang and Shijiazhuang ( P<0.01). The concentration of BDE-71 was highest among PBDE homologues, followed by BDE-66 and BDE-47. Three factors were extracted by exploratory factor analysis in the warm season, and the cumulative variance contribution rate was 67.90%. The multivariate linear regression showed that the house completion less than ten years [ β (95% CI): 0.186 (0.013, 0.359)], infrequent home cooking [ β (95% CI):-0.342 (-0.570, -0.114)], and increased residential PM 10 concentration [ β (95% CI): 0.001 (0.000, 0.002)] during the warm season, as well as the house far from driveway [ β (95% CI): 0.093 (0.013, 0.172)], house area less than 90 m 2 [ β (95% CI):-0.138 (-0.264, -0.013)], and lower residential xylene concentration [ β (95% CI):-0.006 (-0.011, -0.001)] during the cold season might be related to the elevated concentrations of ∑ 12PBDEs in household dust. Conclusion:The pollution of PBDEs in household dust in five northern cities is at a medium to high level. Years of house completion, frequency of cooking at home, residential PM 10 concentration, distance from house to driveway, house area, and residential xylene concentration may influence household PBDE concentrations.