Objective To optimize the extraction, separation and purification process of Actinoside E. Methods Single factor experiment combined with orthogonal test was used to determine the optimal extraction process of Actinoside E using its content as an index. The extracts were separated and purified by optimizing the chromatographic conditions of macroporous resin, silica gel and ODS column. Results 25 times amount of 55% ethanol with heating reflux at 95℃ for one hour were used as the optimal extraction process of Actinoside E. The optimum separation and purification process was as follows: D101 macroporous resin column was eluted with 7 BV of 50% ethanol, silica gel column was eluted with 5 BV of ethyl acetate-ethanol（10∶1）and 50% methanol eluted fraction was purified repeatedly by ODS column to obtain Actinoside E. The transfer rate of Actinoside E in the whole process was 53.70%, the yield was 0.35%, and the purity was 99.9%. Conclusion The process is stable and viable, which can provide material foundation for the development and utilization of Actinoside E.

ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

BACKGROUND:Extracellular vesicles mediate intercellular signal transduction through the proteins,nucleic acids,and lipids they carry,thereby influencing the function of target cells.This vesicle-mediated communication mechanism is involved in regulating female reproductive development.OBJECTIVE:To summarize and analyze the regulatory roles of extracellular vesicle-mediated intercellular communication in female reproductive development.METHODS:A search was conducted in the PubMed database using the search terms"extracellular vesicles,exosomes,reproduction,maternal-embryo communication,maternal-fetal crosstalk,embryo implantation,endometrium,oviduct,follicle."The initial screening was carried out by reading the titles and abstracts of the literature,and then the literature with poor relevance to the research purpose,outdated content,and duplication was excluded according to the inclusion and exclusion criteria.Ultimately,69 relevant articles were included for comprehensive analysis.RESULTS AND CONCLUSION:Extracellular vesicles play a crucial role in key processes of female reproductive development,from folliculogenesis to implantation.(1)Extracellular vesicles mediate intercellular communication within the follicle,particularly the interactions between oocytes and follicular cells,which are essential for follicle development and maturation.(2)Extracellular vesicles and their contents facilitate interactions between the embryo and the fallopian tube,influencing the trajectory of embryonic development.(3)Extracellular vesicles and their contents promote implantation by mediating bidirectional communication between the embryo and the endometrium.Uterine-derived extracellular vesicles regulate processes such as embryo adhesion,invasion,and decidualization,while embryo-derived extracellular vesicles modulate endometrial receptivity,convey embryonic signals,and adjust the endometrial microenvironment.Studying the roles of extracellular vesicles in female reproductive development can provide valuable insights into the mechanisms of infertility and support the development of new therapeutic strategies.

BACKGROUND:Extracellular vesicles mediate intercellular signal transduction through the proteins,nucleic acids,and lipids they carry,thereby influencing the function of target cells.This vesicle-mediated communication mechanism is involved in regulating female reproductive development.OBJECTIVE:To summarize and analyze the regulatory roles of extracellular vesicle-mediated intercellular communication in female reproductive development.METHODS:A search was conducted in the PubMed database using the search terms"extracellular vesicles,exosomes,reproduction,maternal-embryo communication,maternal-fetal crosstalk,embryo implantation,endometrium,oviduct,follicle."The initial screening was carried out by reading the titles and abstracts of the literature,and then the literature with poor relevance to the research purpose,outdated content,and duplication was excluded according to the inclusion and exclusion criteria.Ultimately,69 relevant articles were included for comprehensive analysis.RESULTS AND CONCLUSION:Extracellular vesicles play a crucial role in key processes of female reproductive development,from folliculogenesis to implantation.(1)Extracellular vesicles mediate intercellular communication within the follicle,particularly the interactions between oocytes and follicular cells,which are essential for follicle development and maturation.(2)Extracellular vesicles and their contents facilitate interactions between the embryo and the fallopian tube,influencing the trajectory of embryonic development.(3)Extracellular vesicles and their contents promote implantation by mediating bidirectional communication between the embryo and the endometrium.Uterine-derived extracellular vesicles regulate processes such as embryo adhesion,invasion,and decidualization,while embryo-derived extracellular vesicles modulate endometrial receptivity,convey embryonic signals,and adjust the endometrial microenvironment.Studying the roles of extracellular vesicles in female reproductive development can provide valuable insights into the mechanisms of infertility and support the development of new therapeutic strategies.

Objective: To investigate the current status of screening myopia and anxiety symptoms and associated factors among junior and senior high school students in Beijing, so as to provide evidence for myopia prevention and control and the improvement of mental health among adolescents. Methods: From September to November 2024, a total of 17 245 junior high schools, general senior high schools and vocational high schools from 16 districts in Beijing were enrolled by stratified cluster sampling method. Questionnaire surveys and vision screening were conducted to collect data on anxiety symptom and screening diagnosed myopia. The Chi square test was used to analyze the co-occurrence of myopia and anxiety symptoms, and binary Logistic regression analysis was adopted to explore the related factors of the co-occurrence. Results: The overall detection rate of cooccurrence screening myopia and anxiety symptoms among Beijing junior and senior high school students was 6.00%. The detection rate was higher in females ( 7.15 %) than in males (4.90%), higher in urban areas (6.65%) than in suburban areas (5.41%), and higher in general senior high school students (7.61%) than in vocational high school students (6.46%) and junior high school students (4.65%). All differences were statistically significant ( χ 2=38.49, 11.66, 54.88, all P <0.01). Binary Logistic regression analysis showed that female gender ( OR =1.43), general senior high school ( OR =1.60), vocational high school ( OR =1.59), daily sugar sweetened beverage intake ( OR =1.66), participation in academic extracurricular classes in preschool ( OR =1.30), electronic screen use for more than 2 hours per day ( OR =1.21), and insufficient sleep ( OR =2.41) were associated with an increased risk of co-occurring screening diagnosed myopia and anxiety symptoms (all P <0.05). Conclusions The co-occurrence of screening diagnosed of myopia and anxiety symptoms among junior and senior high school students in Beijing is common. Female gender, senior high school students, and unhealthy lifestyle behaviors are all risk factors for the co-occurrence of myopia and anxiety symptom. Comprehensive intervention measures can be adopted to simultaneously promote vision protection and mental health among junior and senior high school students.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

ObjectiveThis study aimed to investigate the anti-Mycoplasma pneumoniae (MP) activity of luteolin and elucidate its underlying mechanisms. MethodsLuteolin was identified as the primary active compound from the polyphenol extract ofF. diotrys using network pharmacology. Its efficacy was evaluated against two MP strains: the standard strain M129 and the multidrug-resistant strain M19. A modified culture medium with visual characteristics was employed to determine the minimum inhibitory concentration (MIC) of luteolin. The expression of key proteins involved in MP growth and pathogenicity was assessed by qRT-PCR following luteolin treatment. Additionally, the viability of A549 cells infected with MP was compared between luteolin-treated and untreated groups. In vivo anti-MP activity was evaluated using a mouse model, and the expression of inflammatory cytokines in lung tissues was analyzed. ResultsLuteolin effectively inhibited both MP strains, with MIC₉₀ values of 100 mg/L for M19 and M129. Treatment with luteolin significantly downregulated the expression of adhesion proteins P1 and P30 in both strains. However, the expression of P65, HMW3, TrmB, and CARDS TX was reduced only in the M19 strain following luteolin intervention. Luteolin also enhanced the growth and viability of A549 cells infected with MP. In the mouse model, luteolin treatment resulted in steady weight gain and was well tolerated. The bacteriostatic rate of luteolin in lung tissues was 50.7%, significantly higher than the 25.2% observed in the roxithromycin group. Furthermore, luteolin reduced the expression of inflammatory factors, including IL-6, TNF-α, and HMGB1, in MP-infected mice. ConclusionLuteolin effectively and safely inhibits the proliferation and pathogenicity of MP, particularly the drug-resistant M19 strain, by downregulating the expression of toxicity-associated proteins (P1, P30, P65, HMW3, TrmB, CARDS TX) and modulating host inflammatory responses. These findings suggest that luteolin may offer a novel therapeutic strategy for treating MP infections, especially those caused by drug-resistant strains.

AIM: To investigate the prevalence of pterygium in the southeast coastal area, analyze associated risk factors, and develop a multimodal machine learning predictive model.METHODS:A cross-sectional epidemiological study. A random sampling of the resident population of the Zhoushan Islands was performed. Data were collected through on-site ophthalmic examinations and epidemiological surveys. Univariate and multivariate analyses were performed to identify risk factors associated with pterygium. A multimodal artificial intelligence machine learning model was constructed to integrate and analyze both structured and unstructured data for predictive modeling. RESULTS:A total of 1 842 participants were enrolled in this study, including 926 males(50.27%)and 916 females(49.73%), with a mean age of 48.62±10.35 y. A total of 644 patients(34.96%), including 323 males(50.15%)and 321 females(49.84%)were diagnosed with pterygium, including 502 cases(77.95%)were unilateral, and 142 cases(22.05%)were bilateral. There were 1 198 cases without pterygium, including 603 males(50.33%)and 595 females(49.67%). Occupation, daily outdoor sunlight exposure duration, meibomian gland orifice obstruction, age, smoking, and alcohol consumption were identified as significant risk factors for pterygium. Occupation and daily outdoor sunlight exposure duration were the most potent risk factors(OR=6.125, P<0.001; OR=5.348, P<0.001, respectively), followed by age >40 y(OR=5.295, P<0.001)and meibomian gland orifice obstruction(OR=5.248, P<0.001). The multimodal machine learning model demonstrated good predictive performance, as evidenced by the receiver operating characteristic(ROC)curve, precision-recall(PR)curve, and confusion matrix, all indicating high predictive value, AUC=0.86, AP=0.77.CONCLUSION: Fishermen and farmers aged over 40 y with more than 4 h of daily sunlight exposure are at high risk for pterygium in the southeast coastal area. Meibomian gland dysfunction is correlated with corneal invasion of pterygium and may facilitate its progression; therefore, active health education and targeted intervention are recommended. The multimodal machine learning model provides accurate and reliable predictive capability for pterygium risk, which may facilitate risk stratification and early warning for pterygium in southeast coastal populations.

OBJECTIVE To investigate the current status of informatization tools applied to antimicrobial stewardship in county hospitals in China， and to provide a reference for promoting the informatization development of antimicrobial stewardship in county hospitals.METHODS From August to September 2025， an online questionnaire survey was conducted among 1 007 county hospitals across 31 provinces（autonomous regions， and municipalities） in China. The survey focused on the application of four types of informatization tools：the real-time monitoring system for antimicrobial use， the pre-prescription review system， the irrational use warning system， and the electronic prescription evaluation system（hereinafter referred to as the “monitoring system”“review system”“warning system”“evaluation system”，respectively）. Correlation analysis and binary Logistic regression analysis were employed to explore the influencing factors.RESULTS Of the county hospitals， 80.83% were equipped with at least one type of informatization tool for antimicrobial stewardship， while 19.17% had no relevant tool. Only 18.87% of the hospitals were equipped with all four types of tools. The monitoring system exhibited the highest equipped rate （70.80%）， whereas the warning system was equipped in only 33.96% of the hospitals. Four types of tools are evenly and adequately deployed in the eastern region， the central and western regions have far lower deployment rates of intervention tools including review system and warning system， accompanied by prominent intra-provincial gaps. The total number of the health technicians， hospital grade， and prescription review rate of outpatient antibacterial drug were significantly and positively correlated with the deployment rates of the four informatization tools （ P ＜0.05）. The results of the Logistic regression model fitting indicated that the model of the review system was rated “excellent” [area under the receiver operating characteristic curve （AUC）＝0.81]， and the model of the warning system was rated “further improvement” （AUC＝0.67）. The total number of health technicians was significantly positively correlated with the deployment rates of all four types of informatization tools （all P ＜0.05）.CONCLUSIONS The informatization of antimicrobial stewardship in county hospitals in China remains in the initial stage of transitioning from “passive statistics” to “active prevention and control”， with challenges such as structural imbalance and regional disparities. In the future， differentiated support strategies should be implemented， the allocation of resources should be optimized， to enhance the level of refined antimicrobial stewardship.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.