ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

OBJECTIVE To screen a single matrix， prepare dissolving microneedles of Pterocarya hupehensis total flavonoids（PHTF-MN）， and characterize it while evaluating its analgesic effects.METHODS Using microneedle morphology and puncture rate as evaluation indicators， the matrix was screened from polyvinyl alcohol （PVA）， polyvinylpyrrolidone K30 （PVP K30）， PVP K90， and sodium hyaluronate with relative molecular weights of 15 000 and 60 000 （HA 1.5w and HA 6w ）. PHTF-MN was prepared by the layer-by-layer casting method with the selected matrix， and the appearance and morphology， total flavonoid content， mechanical properties， puncture performance， dissolution properties， and drug release behavior of the obtained PHTF-MN were characterized. Using male BALB/c mice as test subjects and aspirin （ASA） as a positive control， the analgesic effects of the microneedles were evaluated using a formalin-induced pain model.RESULTS Blank microneedles prepared with 30% HA 1.5w exhibited optimal surface flatness and the membrane puncture rate （through 4 layers of parafilm membrane） reaching 78%. The PHTF-MNs （with PHTF contents of 10， 20， 30， 40， and 50 mg/g in the matrix） exhibited uniform arrays and intact tips， with RSDs for total flavonoid contents all below 7% （ n ＝8）. The single-needle puncture forces were 1.46 and 1.07 N （with PHTF contents of 30 and 50 mg/g in the matrix， respectively）. The skin penetration rate approached 100%， with visible puncture marks in the stratum corneum and drug residue （with a PHTF content of 50 mg/g in the matrix）. After 30 min of fixation， the needles had almost completely dissolved， and the skin retention rates all exceeded 90% （with PHTF contents of 10， 30， and 50 mg/g in the matrix， respectively）. The cumulative release within 8 h was （134.64±2.03） μg/cm 2 ， and the fit to the first-order kinetic equation （ R 2 ＝0.950 1） was highest （with a PHTF content of 50 mg/g in the matrix）. Low- and high-dose PHTF-MN （containing 85.26 and 145.03 μg of total flavonoids per patch， respectively； 1 patch/day） significantly shortened the cumulative time of phase Ⅱ pain response in mice （ P ＜0.05）， with pain inhibition rates （43.67% and 59.78%） comparable to those of ASA （53.70%）.CONCLUSIONS PHTF-MN using HA 1.5w as a single matrix was successfully prepared. This formulation features a simplified preparation process， uniform drug loading， favorable mechanical properties， resistance to fracture， and rapid dissolution. Its drug release behavior conforms to a first-order kinetic model， and its analgesic effect is comparable to that of ASA.

Objective To investigate the value of early maternal serological indicators in predic-ting the delivery of full-term small-for-gestational-age(SGA)infants.Methods The clinical data of pregnant women who delivered at Beijing Tongzhou District Maternal and Child Health Hospital from August 2023 to August 2024 were analyzed.A total of 180 pregnant women who delivered full-term SGA infants were included in case group,and 180 pregnant women who delivered full-term appropri-ate-for-gestational-age(AGA)infants during the same period were included in control group.The levels of serum pregnancy-associated plasma protein A(PAPP-A),placenta growth factor(PLGF),and soluble fms-like tyrosine kinase-1(sFlt-1)in the first trimester(11 to 13 weeks+6 days of ges-tation)of the two groups were compared.Receiver operating characteristic(ROC)curves were used to analyze the predictive value of early maternal serological indicators for the delivery of full-term SGA infants.Results The levels of serum PAPP-A and PLGF in the first trimester of the case group were lower than those in the control group,while the level of sFlt-1 was higher(P＜0.05).The area un-der the ROC curve(AUC)for the combined detection of serum PAPP-A,PLGF,and sFlt-1 levels in the first trimester in predicting the delivery of full-term SGA infants was 0.823,which was higher than the AUCs for detection of each indicator(0.738,0.720,0.724)(P＜0.05).Conclusion The detection of early maternal PAPP-A,PLGF,and sFlt-1 levels can reflect the fetal growth status in utero.The combined detection of these three indicators has a higher predictive value for the delivery of full-term SGA infants by pregnant women,which is helpful for clinicians to take intervention measures in advance.

Anticoagulants are widely used in the prevention and treatment of thromboembolism.Existing anticoagulants share the common feature of antagonizing or blocking critical steps in the coagulation cascade,which also increases the risk of bleeding.Studies have indicated that factor Ⅺ inhibitors represent a potential therapeutic option for balancing thrombosis and bleeding risks.In recent years,various factor Ⅺ inhibitors,including antisense oligonucleotides(ASOs),monoclonal antibodies,synthetic small molecules,natural peptides,and aptamers,have been extensively researched as potentially exploitable anticoagu-lants.Research findings also suggest that factor Ⅺ inhibitors can reduce bleeding risks while ensuring anticoagulant efficacy,ex-hibiting potential for thrombosis prevention and treatment in patient populations such as those with end-stage renal disease,non-cardioembolic ischemic stroke,and acute coronary syndrome.This article reviewed the mechanisms of action,drug classes,pharma-cological characteristics,and clinical research progress of factor Ⅺ inhibitors,aiming to provide insights into the development of new anticoagulants and clinical anticoagulant therapies.

Objective:To explore the adaptability of health resources allocation and the economic development level in Sichuan Province and its influencing factors,so as to provide reference and suggestions for optimizing health resources allocation.Methods:Based on the panel data of 21 cities(states)in Sichuan Province,it analyzes the adaptability of health resources allocation and economic development in Sichuan Province from 2017 to 2021 and its influencing factors through entropy method,coupling coordination model and grey relational model.Results:From 2017 to 2021,the allocation level of health resources in most areas of Sichuan Province showed a gradual upward trend,but the rising speed was obviously lower than the growth rate of economic development;In 2021,the adaptability between the allocation of health resources and the level of economic development in most parts of Sichuan Province is still in a low coordination stage.Conclusion:Different regions should adopt differentiated development strategies based on their actual geographical conditions,optimize the allocation of health resources according to local conditions,and promote the coordinated development of health resource allocation and economic level.

Objective:To explore the adaptability of health resources allocation and the economic development level in Sichuan Province and its influencing factors,so as to provide reference and suggestions for optimizing health resources allocation.Methods:Based on the panel data of 21 cities(states)in Sichuan Province,it analyzes the adaptability of health resources allocation and economic development in Sichuan Province from 2017 to 2021 and its influencing factors through entropy method,coupling coordination model and grey relational model.Results:From 2017 to 2021,the allocation level of health resources in most areas of Sichuan Province showed a gradual upward trend,but the rising speed was obviously lower than the growth rate of economic development;In 2021,the adaptability between the allocation of health resources and the level of economic development in most parts of Sichuan Province is still in a low coordination stage.Conclusion:Different regions should adopt differentiated development strategies based on their actual geographical conditions,optimize the allocation of health resources according to local conditions,and promote the coordinated development of health resource allocation and economic level.

Objective:To identify the risk factors for ascending aortic dilatation and develop a prediction model using LASSO-Logistic regression in patients with normally functioning bicuspid aortic valves（BAV）.Methods:Eight-four adult patients with BAV diagnosed as having normal valve function by transthoracic echocardiography who attended to the General Hospital of Ningxia Medical University between June 2024 and April 2025 were prospectively selected，there were 42 patients with ascending aortic dilatation and 42 patients without dilatation.The patients were divided into a training set（60 cases）and a test set（24 cases）using stratified random sampling at a ratio of 7 to 3 via the R caret package. All subjects underwent transthoracic echocardiography，lipid and plasma matrix metalloproteinases（MMP）and tissue inhibitors（TIMP）levels detection. The inverse probability of treatment weighting（IPTW）method was employed to control for potential confounding factors. LASSO and multifactorial binary Logistic regression was applied to screen the independent risk factors for ascending aortic dilatation of BAV and development a nomogram prediction model. The accuracy，consistency and clinical applicability of the prediction model were evaluated by applying the ROC curve，calibration curve，and decision curve analysis（DCA），respectively.Results:①After adjustment for IPTW，LASSO-Logistic regression analysis identified left ventricular global longitudinal strain（LVGLS）and plasma MMP-2 levels as independent risk factors for ascending aortic dilatation in BAV patients with normal valve function.②The nomogram prediction model constructed based on the above screening features，and the area under the curve（AUC）of ROC for the training set and test set were 0.917 and 0.903，with specificities of 0.867 and 0.917，and sensitivities of 0.933 and 0.916，respectively. ③Calibration curves demonstrated satisfactory alignment，with C-indices of 0.908（95% CI=0.879～0.937）for the training set and 0.903（95% CI=0.874 - 0.932）for the test set. Hosmer-Lemeshow goodness-of-fit tests indicated strong consistency between predicted and observed outcomes，with P-values of 0.138 and 0.750 for the training and test sets，respectively.The DCA curve demonstrated that within a threshold probability range of 0.04 - 0.90 in the test set，the clinical decision-making model provided a higher net benefit rate for patients with BAV. Conclusions:LVGLS absolute value reduction and elevated plasma MMP-2 levels are independent risk factors for predicting ascending aortic dilatation in BAV patients with normal valve function. The prediction model based on LASSO-Logistic regression has good predictive value，providing a scientific basis for clinical decision-making in patients with BAV and aortic diseases.

Anticoagulants are widely used in the prevention and treatment of thromboembolism.Existing anticoagulants share the common feature of antagonizing or blocking critical steps in the coagulation cascade,which also increases the risk of bleeding.Studies have indicated that factor Ⅺ inhibitors represent a potential therapeutic option for balancing thrombosis and bleeding risks.In recent years,various factor Ⅺ inhibitors,including antisense oligonucleotides(ASOs),monoclonal antibodies,synthetic small molecules,natural peptides,and aptamers,have been extensively researched as potentially exploitable anticoagu-lants.Research findings also suggest that factor Ⅺ inhibitors can reduce bleeding risks while ensuring anticoagulant efficacy,ex-hibiting potential for thrombosis prevention and treatment in patient populations such as those with end-stage renal disease,non-cardioembolic ischemic stroke,and acute coronary syndrome.This article reviewed the mechanisms of action,drug classes,pharma-cological characteristics,and clinical research progress of factor Ⅺ inhibitors,aiming to provide insights into the development of new anticoagulants and clinical anticoagulant therapies.

Objective:To identify the risk factors for ascending aortic dilatation and develop a prediction model using LASSO-Logistic regression in patients with normally functioning bicuspid aortic valves（BAV）.Methods:Eight-four adult patients with BAV diagnosed as having normal valve function by transthoracic echocardiography who attended to the General Hospital of Ningxia Medical University between June 2024 and April 2025 were prospectively selected，there were 42 patients with ascending aortic dilatation and 42 patients without dilatation.The patients were divided into a training set（60 cases）and a test set（24 cases）using stratified random sampling at a ratio of 7 to 3 via the R caret package. All subjects underwent transthoracic echocardiography，lipid and plasma matrix metalloproteinases（MMP）and tissue inhibitors（TIMP）levels detection. The inverse probability of treatment weighting（IPTW）method was employed to control for potential confounding factors. LASSO and multifactorial binary Logistic regression was applied to screen the independent risk factors for ascending aortic dilatation of BAV and development a nomogram prediction model. The accuracy，consistency and clinical applicability of the prediction model were evaluated by applying the ROC curve，calibration curve，and decision curve analysis（DCA），respectively.Results:①After adjustment for IPTW，LASSO-Logistic regression analysis identified left ventricular global longitudinal strain（LVGLS）and plasma MMP-2 levels as independent risk factors for ascending aortic dilatation in BAV patients with normal valve function.②The nomogram prediction model constructed based on the above screening features，and the area under the curve（AUC）of ROC for the training set and test set were 0.917 and 0.903，with specificities of 0.867 and 0.917，and sensitivities of 0.933 and 0.916，respectively. ③Calibration curves demonstrated satisfactory alignment，with C-indices of 0.908（95% CI=0.879～0.937）for the training set and 0.903（95% CI=0.874 - 0.932）for the test set. Hosmer-Lemeshow goodness-of-fit tests indicated strong consistency between predicted and observed outcomes，with P-values of 0.138 and 0.750 for the training and test sets，respectively.The DCA curve demonstrated that within a threshold probability range of 0.04 - 0.90 in the test set，the clinical decision-making model provided a higher net benefit rate for patients with BAV. Conclusions:LVGLS absolute value reduction and elevated plasma MMP-2 levels are independent risk factors for predicting ascending aortic dilatation in BAV patients with normal valve function. The prediction model based on LASSO-Logistic regression has good predictive value，providing a scientific basis for clinical decision-making in patients with BAV and aortic diseases.

Objective To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2(T2DM)in the middle-aged and elderly populations based on the results of a Meta-analysis,and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service.Methods Cohort studies evaluating T2DM risks were identified in Chinese and English databases.The logistic model utilized Meta-combined effect values such as the odds ratio(OR)to derive β,the partial regression coefficient,of the logistic model.The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model.Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service.The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7 602 individuals who did not have T2DM at their baseline medical checkups done at the community health center.This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people.Results A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM,including age,central obesity,smoking,physical inactivity,impaired fasting glucose,a reduced level of high-density lipoprotein cholesterol(HDL-C),hypertension,body mass index(BMI),triglyceride glucose(TYG)index,and a family history of diabetes,with the OR values and 95% confidence interval(CI)being 1.04(1.03,1.05),1.55(1.29,1.88),1.36(1.11,1.66),1.26(1.07,1.49),3.93(2.94,5.24),1.14(1.06,1.23),1.47(1.34,1.61),1.11(1.05,1.18),2.15(1.75,2.62),and 1.66(1.55,1.78),respectively,and the combined β values being 0.039,0.438,0.307,0.231,1.369,0.131,0.385,0.104,0.765,and 0.507,respectively.A total of 37 studies reported the incidence rate,with the combined incidence being 0.08(0.07,0.09)and the parameter α being-2.442 for the logistic model.The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7 602 individuals who had medical checkups and were followed up for at least once.External validation results showed that the predictive model had an area under curve(AUC)of 0.794(0.771,0.816),accuracy of 74.5%,sensitivity of 71.0%,and specificity of 74.7% in the 7 602 individuals.Conclusion The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.