Background Liver cancer is one of the common malignant tumors. Phthalates (PAEs), as a widely used class of plasticizers, can participate in the occurrence and progression of liver diseases through multiple pathways. Objective To explore the association between PAEs exposure and liver cancer risk and to provide a scientific basis for the prevention of environment-related tumor risk events. Methods Chi-square test and logistic regression were employed to analyze data from the National Health and Nutrition Examination Survey (NHANES) database between 2001 and 2018, to investigate the association between PAEs exposure and liver cancer. Network toxicology combined with machine learning was used to screen independent prognostic genes associated with PAEs and liver cancer, and to evaluate their correlations with tumor immunity, tumor pathway activation, and tumor drug resistance. Finally, the prediction results were validated using GEO datasets, molecular docking, and molecular dynamics simulations. Results After screening, 11378 eligible samples were obtained from the NHANES database, including 108 patients with liver cancer and 11270 healthy controls. The logistic regression analysis revealed that exposure to nine types of PAEs was positively correlated with liver cancer (OR > 1, P < 0.05). The network toxicology analysis indicated that the association between PAEs exposure and liver cancer was related to three independent prognostic genes: uridine-cytidine kinase 2 (UCK2), glucose-6-phosphate dehydrogenase (G6PD), and albumin (ALB). These three independent prognostic genes were significantly associated with the tumor immune microenvironment, tumor pathway activation, and tumor drug resistance, and exhibited complex interactions with each other. All three independent prognostic genes showed significant differential expression in the validation datasets GSE58043 and GSE115469 (P < 0.05). The results of both molecular docking and molecular dynamics simulations confirmed that these three independent prognostic genes can freely bind to PAEs and form stable complexes. Conclusion Exposure to PAEs is positively correlated with liver cancer. The intrinsic association between the two may involve metabolic disorders, immunosuppression, and activation of inflammatory and tumor-related pathways.

OBJECTIVE: To develop an objective quantitative evaluative model of manual acupuncture manipulation (MAM) using three-dimensional motion tracking technology and machine learning, so as to provide a new approach to the study on acupuncture and moxibustion education and manipulation standardization. METHODS: A total of 120 undergraduate students in the major of acupuncture-moxibustion and tuina were recruited. The Simi Motion Ver.8.5 motion tracking system was used to collect the data of three types of MAM, balanced reinforcing and reducing by twisting, reinforcing technique by twisting and reducing technique by twisting. Eight quantitative parameters covering movement performance and stability were established. With 5 types of machine learning algorithms (logistic regression, random forest, support vector machine, K-nearest neighbor, and decision tree) adopted, the evaluative model was constructed, and the feature importance analyzed. RESULTS: In the evaluation of different types of MAM, the support vector machine presented the best for the effects of the balanced reinforcing and reducing by twisting, and the reducing by twisting (accuracy rates were both 0.88); and the logistic regression algorithm showed the optimal performance in evaluating the reinforcing by twisting (1.00 of accuracy rate). Feature importance analysis revealed that twisting velocity was the dominant parameter for evaluating the balanced reinforcing-reducing manipulation. The reinforcing and reducing of acupuncture techniques were more dependent on the left-hand twisting parameters and comprehensive performances, respectively. CONCLUSION The objective evaluative model of MAM based on three-dimensional motion tracking technology and machine learning demonstrates a reliable evaluative performance, providing a new technical approach to standardized assessment in acupuncture and moxibustion education.
Humans ; Male ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Female ; Young Adult ; Adult ; Motion

Arthritis, encompassing osteoarthritis (OA), rheumatoid arthritis (RA), and gouty arthritis (GA), is a prevalent inflammatory disease that significantly impacts quality of life. Natural products (NPs), derived from animals, plants, marine organisms, and microorganisms, have demonstrated beneficial effects in arthritis treatment both domestically and internationally. These natural compounds offer advantages in drug discovery due to their skeletal diversity, structural complexity, and multi-effect, multi-target, and low-toxicity properties compared to conventional small-molecule medicines. However, unclear mechanisms have hindered the development and clinical application of NPs. This review summarizes recent experimental studies from the past decade on natural medicine for arthritis treatment, emphasizing key NPs with therapeutic effects on OA, RA, and GA. It examines the effects and molecular mechanisms of NPs acting on different cells to treat arthritis. Furthermore, this review provides insights into the future prospects of NP research in this field, which is crucial for advancing NP-based arthritis treatments.
Humans ; Biological Products/therapeutic use* ; Animals ; Arthritis, Rheumatoid/drug therapy* ; Arthritis, Gouty/drug therapy* ; Arthritis/drug therapy* ; Osteoarthritis/drug therapy*

Objective To investigate the feasibility of the spatiotemporal filtering model in analysis of reported schistosomiasis cases, so as to provide insights into analysis of complicated data pertaining to schistosomiasis control. Methods Demographic and epidemiological data of reported schistosomiasis cases in Anhui Province from 1997 to 2010 were collected from Anhui Provincial Center for Disease Control and Prevention, and the annual prevalence of Schistosoma japonicum human infections was calculated. The meteorological data were captured from meteorological stations in counties (cities, districts) of Anhui Province where schistosomiasis cases were reported from 1997 to 2010 at the National Meteorological Information Center, including monthly average air temperature and precipitation. Meteorological data were interpolated using the inverse-distance weighting method, and the annual average air temperature and annual precipitation were calculated in each county (city, district). The centroid of the county (city, district) where schistosomiasis cases were reported was extracted using the software ArcGIS 10.0, and the Euclidean distance from each centroid to the Yangtze River was calculated as the distance between that county (city, district) and the Yangtze River. The global Moran’s I of the prevalence of S. japonicum human infections in Anhui Province for each year from 1997 to 2010 were calculated to analyze the spatial autocorrelation. A spatial weight matrix was constructed using Rook adjacency, and a first-order temporal weight matrix was built to quantify the relationship between disease changes over time. Subsequently, a spatiotemporal structure matrix was constructed. A negative binomial model was built based on the spatiotemporal structure matrix and data pertaining to reported schistosomiasis cases, and a linear model was created between the residual of the model and candidate set feature vectors to determine the optimal subset composition of the spatiotemporal filter through stepwise regression. Then, a spatio-temporal filtering model was constructed using the negative binomial model. Negative binomial models, Bayesian spatial models, and Bayesian spatiotemporal models were constructed and compared with the spatiotemporal filtering model to validate the performance of the spatiotemporal filtering model, and cross-validation was conducted for each model. The goodness of fit was evaluated using the deviance information criterion (DIC) and Watanabe-Akaike information criterion (WAIC), and the effectiveness of model validation was assessed using mean squared error (MSE), while the accuracy of assessment results was assessed using coefficients and their 95% confidence intervals (CI), and the computational efficiency was assessed based on the running time of the model. The four feature vectors with the largest Moran’s I values were selected to identify regions with autocorrelation through their schematic diagrams to investigate the differences in spatiotemporal patterns of specific regions. Results Of all models created, the spatiotemporal filtering model exhibited the highest goodness of fit (DIC = 3 240.70, WAIC = 3 257.80), the best model validation effectiveness (MSE = 42 617.52), and the runtime was 3.18 s, exhibiting the optimal performance. Across all modeling results, the distance from the Yangtze River showed a negative correlation with the number of reported schistosomiasis cases (coefficient values = −4.93 to −3.78, none of the 95% CIs included 0), and annual average air temperature or average precipitation posed no significant effects on numbers of reported schistosomiasis cases (both of the 95% CIs included 0). Schematic diagrams of feature vectors showed that the transmission of schistosomiasis might be associated with water systems in Anhui Province, and localized clustering patterns were primarily concentrated in the northern and western parts of schistosomiasis-endemic areas in the province. Conclusion The spatiotemporal filtering model is an effective spatiotemporal analysis characterized by simple modeling, user-friendly operation, accurate results and good flexibility, which may serve as an efficient alternative to conventional complex spatiotemporal models for data analysis in schistosomiasis researches.

Oocyte maturation disorders and fertilization failures are caused by a variety of factors, including complex factors such as chromosomal abnormalities and poor oocyte quality. With the widespread use of high-throughput sequencing technology, more and more genetic mutations have been found to be associated with oocyte maturation and fertilization process in infertile patients. This paper summarizes and discusses 11 key genes ( TRIP13, TBPL2, LHX8, PATL2, TUBB8, CDC20, WEE2, ZP, ASTL, JUNO and CD9) related to oocyte maturation and fertilization-related disorders in females, providing a basis for research on the prevention of diseases associated with oocyte maturation blockage and fertilization failure and the development of targeted therapies.

Non-classical congenital adrenal hyperplasia (NCCAH), an autosomal recessive disorder, stems from genetic mutations affecting the enzymes and cofactors integral to adrenal steroidogenesis. These mutations may result in diminished activity or a complete loss of function for critical enzymes, such as 21-hydroxylase, 11β-hydroxylase, 3β-hydroxysteroid dehydrogenase, 17α-hydroxylase, and the steroidogenic acute regulatory protein (StAR). The impairment of these enzymatic processes has profound implications for reproductive health in females, mediated through both genetic and endocrine pathways. This review aims to explore the pathogenesis of various enzyme defects in different types of NCCAH, their clinical features, and their impact on female fertility. It is hoped that this will help refine the diagnostic strategies for infertility associated with NCCAH, thereby enhancing fertility of patients and providing new directions and opportunities for further research in this field.

Oocyte maturation disorders and fertilization failures are caused by a variety of factors, including complex factors such as chromosomal abnormalities and poor oocyte quality. With the widespread use of high-throughput sequencing technology, more and more genetic mutations have been found to be associated with oocyte maturation and fertilization process in infertile patients. This paper summarizes and discusses 11 key genes ( TRIP13, TBPL2, LHX8, PATL2, TUBB8, CDC20, WEE2, ZP, ASTL, JUNO and CD9) related to oocyte maturation and fertilization-related disorders in females, providing a basis for research on the prevention of diseases associated with oocyte maturation blockage and fertilization failure and the development of targeted therapies.

Objective To investigate the mechanism of autophagy induced by House dust mites(HDM)on airway epithelial tight junction through β-catenin-Snail signaling pathway.Methods Human bronchial epithelial cells(16HBE)were stimulated with HDM at different time points(0,3,6,12,24,48 h)and different concen-trations(0,40,100,200 μg/mL)to screen the appropriate stimulation concentration and stimulation time.16HBE cells were treated with oxidative stress inhibitor N-acetylcysteine(NAC),autophagy inhibitor 3-methylad-enine(3-MA),HDM,and their combinations.Cells were transfected with mCherry-EGFP-LC3B,Beclin-1-siRNA,and ATG14-siRNA lentivirus and then stimulated with NAC and HDM.Immunofluorescence was used to detect the expression levels of autophagy-related protein LC3B,tight junction-related proteins Occludin,and ZO-1 in airway epithelial cells.The level of reactive oxygen species(ROS)was detected by using DCFH-DA in each group.The protein expression levels of Occludin,ZO-1,LC3B,Beclin-1,ATG5,ATG14,P62,Snail,β-catenin and p-β-catenin were detected by Western blot method.Results Immunofluorescence results showed that compared with the control group,200 μg/mL HDM stimulation induced cellular autophagy,increased the expression level of LC3B protein,and promoted the level of ROS,all with statistical significances(all P<0.05).Compared with the HDM group,the HDM+3-MA,HDM+ATG14-si,and HDM+Beclin-1-si groupsall showed significantincreases in the expression levels of tight junction-related proteins Occludin and ZO-1(P<0.05).The HDM+NAC group demonstrated significant decreases both in the level of ROS andin the expression level of LC3B protein.Western blot results revealed that compared with HDM,3-MA and autophagy protein low-expression beads(Beclin-1-si,ATG14-si)attenuated HDM-induced cellular autophagy(P<0.05),inhibited HDM-induced upregulation of Snail and p-β-catenin expression,and improved HDM-induced decreases in Occludin and ZO-1(P<0.05).Moreover,compared with the HDM group,the NAC+HDM group exhibited significant decreases both in the conversion of LC3BⅠ to LC3BⅡ(P<0.001)in the protein levels of Snail,p-β-catenin,Beclin-1 and ATG14(P<0.01),but significant increases in the protein levels of Occludin and ZO-1(P<0.05).Conclusion HDM affects the tight connections between airway epithelial cells by inducing autophagy,which may be attributed to the β-catenin-Snail signaling pathway.

Non-classical congenital adrenal hyperplasia (NCCAH), an autosomal recessive disorder, stems from genetic mutations affecting the enzymes and cofactors integral to adrenal steroidogenesis. These mutations may result in diminished activity or a complete loss of function for critical enzymes, such as 21-hydroxylase, 11β-hydroxylase, 3β-hydroxysteroid dehydrogenase, 17α-hydroxylase, and the steroidogenic acute regulatory protein (StAR). The impairment of these enzymatic processes has profound implications for reproductive health in females, mediated through both genetic and endocrine pathways. This review aims to explore the pathogenesis of various enzyme defects in different types of NCCAH, their clinical features, and their impact on female fertility. It is hoped that this will help refine the diagnostic strategies for infertility associated with NCCAH, thereby enhancing fertility of patients and providing new directions and opportunities for further research in this field.

Objective To investigate the mechanism of autophagy induced by House dust mites(HDM)on airway epithelial tight junction through β-catenin-Snail signaling pathway.Methods Human bronchial epithelial cells(16HBE)were stimulated with HDM at different time points(0,3,6,12,24,48 h)and different concen-trations(0,40,100,200 μg/mL)to screen the appropriate stimulation concentration and stimulation time.16HBE cells were treated with oxidative stress inhibitor N-acetylcysteine(NAC),autophagy inhibitor 3-methylad-enine(3-MA),HDM,and their combinations.Cells were transfected with mCherry-EGFP-LC3B,Beclin-1-siRNA,and ATG14-siRNA lentivirus and then stimulated with NAC and HDM.Immunofluorescence was used to detect the expression levels of autophagy-related protein LC3B,tight junction-related proteins Occludin,and ZO-1 in airway epithelial cells.The level of reactive oxygen species(ROS)was detected by using DCFH-DA in each group.The protein expression levels of Occludin,ZO-1,LC3B,Beclin-1,ATG5,ATG14,P62,Snail,β-catenin and p-β-catenin were detected by Western blot method.Results Immunofluorescence results showed that compared with the control group,200 μg/mL HDM stimulation induced cellular autophagy,increased the expression level of LC3B protein,and promoted the level of ROS,all with statistical significances(all P<0.05).Compared with the HDM group,the HDM+3-MA,HDM+ATG14-si,and HDM+Beclin-1-si groupsall showed significantincreases in the expression levels of tight junction-related proteins Occludin and ZO-1(P<0.05).The HDM+NAC group demonstrated significant decreases both in the level of ROS andin the expression level of LC3B protein.Western blot results revealed that compared with HDM,3-MA and autophagy protein low-expression beads(Beclin-1-si,ATG14-si)attenuated HDM-induced cellular autophagy(P<0.05),inhibited HDM-induced upregulation of Snail and p-β-catenin expression,and improved HDM-induced decreases in Occludin and ZO-1(P<0.05).Moreover,compared with the HDM group,the NAC+HDM group exhibited significant decreases both in the conversion of LC3BⅠ to LC3BⅡ(P<0.001)in the protein levels of Snail,p-β-catenin,Beclin-1 and ATG14(P<0.01),but significant increases in the protein levels of Occludin and ZO-1(P<0.05).Conclusion HDM affects the tight connections between airway epithelial cells by inducing autophagy,which may be attributed to the β-catenin-Snail signaling pathway.