Objective: To establish a risk prediction model for diabetic peripheral neuropathy (DPN) among patients with type 2 diabetes mellitus (T2DM), so as to provide a basis for DPN prevention and control. Methods: T2DM inpatients aged 18-65 years admitted to the department of endocrinology and metabolism at Affiliated Hospital Shandong Second Medical University from April to December 2024 were selected as study subjects. Age, T2DM duration, hypertension history, 25-hydroxyvitamin D, serum C-peptide, and high density lipoprotein cholesterol (HDL-C) were collected through electronic medical records. Risk predictors of DPN among T2DM patients were screened using multivariable logistic regression model, and a nomogram was established. The receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis were employed to evaluate the discrimination, calibration and clinical utility of the nomogram, respectively. Results: A total of 598 T2DM patients were enrolled, including 359 (60.03%) males and 239 (39.97%) females. The median age was 54.50 (interquartile range, 15.00) years, the median T2DM duration was 6.00 (interquartile range, 9.00) years. There were 262 cases of T2DM patients with DPN, accounting for 43.81%. Multivariable logistic regression identified hypertension history (OR=3.260, 95%CI: 2.220-4.790), alcohol use history (OR=2.150, 95%CI: 1.390-3.310), diabetes complications (OR=0.430, 95%CI: 0.270-0.680), T2DM duration (OR=1.040, 95%CI: 1.010-1.070), body mass index (OR=1.130, 95%CI: 1.070-1.200), 25-hydroxyvitamin D (OR=0.930, 95%CI: 0.910-0.960), and HDL-C (OR=0.400, 95%CI: 0.230-0.720) as risk predictors for DPN among T2DM patients. The area under the ROC curve of the established risk prediction model was 0.774 (95%CI: 0.737-0.812), with a sensitivity of 0.710 and a specificity of 0.723. The calibration curve after repeated sampling calibration approached the standard curve. Decision curve analysis showed that when the risk threshold probability was 0.2 to 0.4, the model demonstrates favorable clinical applicability. Conclusion The risk prediction model established in this study has favorable discrimination, calibration, and clinical utility, can effectively predict the risk of DPN among T2DM patients aged 18-65 years.

Objective To explore the mechanism of Glaucocalyxin A(GLA)in inhibiting ovalbumin(OVA)-induced airway remodeling in asthmatic mice through the topoisomerase Ⅱ α(TOP2A)/cyclin-dependent kinase 1(CDK1)signaling pathway.Methods Forty Balb/c mice were randomly divided into 5 groups:the control group,the model group,the low-dose GLA group,the high-dose GLA group and the Dexamethasone group,with 8 mice in each group.The effect of GLA on airway remodeling was examined by immunohistochemical staining,ELISA and other methods,and bioinformatics methods were used to predict new targets of GLA.The action targets of TOP2A were screened using the STRING database,and the interaction relationship between the two was verified by co-immunoprecipitation.In vitro,GLA and siRNA were used to interfere with interleukin-4(IL-4)-stimulated human airway epithelial cells BEAS-2B.The expressions of TOP2A,epidermal growth factor receptor(EGFR),Integrin β1,focal adhesion kinase(FAK),β-catenin,CDK1 and DRP1 were detected by Western Blot.Results GLA intervention could significantly reduce OVA-induced asthma airway remodeling,airway smooth muscle thickening,collagen deposition around the airway,the number of eosinophils in alveolar lavage fluid,the expression of pro-inflammatory cytokines such as IL-4,and the level of serum IgE.The new target of GLA screened out was TOP2A,which was highly expressed in the lung tissue of the asthma airway remodeling model.GLA intervention could down-regulate its expression.In vitro,intervention with GLA and si-TOP2A could significantly down-regulate the expressions of IL-4-induced TOP2A,EGFR,Integrin β1,FAK and β-catenin.Further studies have found that TOP2A had an interaction relationship with CDK1.si-TOP2A could downregulate the expression of CDK1,and knockdown of CDK1 could significantly down-regulate the expression of phosphorylated DRP1.Conclusion GLA may alleviate asthma airway remodeling by targeting the TOP2A/CDK1 signaling pathway,providing experimental evidence for the clinical diagnosis and treatment of asthma airway remodeling in asthma.

Objective:To explore the risk factors of respiratory failure within 48 hours of admission in patients with sepsis associated acute kidney injury(SA-AKI)and establish a predictive model and verify it.Methods:A retrospective selection was made of 702 patients with SA-AKI admitted to Dongyang People's Hospital from June 2012 to October 2024, and they were randomly divided into the training set (492 cases) and the validation set (210 cases) in a ratio of 7∶3. The risk factors of respiratory failure within 48 h of admission in patients with SA-AKI were analyzed in the training set to establish a nomogram. The discriminative ability of the model was evaluated by using the receiver operating characteristic (ROC) curve, and the clinical effectiveness of the predictive model was evaluated by using decision curve analysis (DCA). Meanwhile, validation was conducted in the validation set. The Sequential Organ Failure Assessment (SOFA) and National Early Warning Score (NEWS) models were established, and the Delong test was applied to compare them with this prediction model.Results:The results of Logistic regression analysis showed that lactic acid, D-dimer, pro-B-type natriuretic peptide precursor, albumin, globulin, percutaneous blood oxygen saturation and pulmonary infection were independent risk factors for respiratory failure within 48 h of admission in patients with SA-AKI ( P<0.05). The results of ROC curve analysis indicated that the area under the curve (AUC) of this model for predicting respiratory failure within 48 h of admission in SA-AKI patients in the training set was 0.818 (95% CI 0.777 - 0.860), and that in the validation set was 0.795 (95% CI 0.723 - 0.860). The calibration curves showed that the P values were 0.973 and 0.864 respectively. The DCA curve was applied to evaluate the clinical effectiveness. The model curves were above the two extreme curves in both the training set and the validation set suggested that the model had good significance in discrimination, calibration and clinical effectiveness. The AUC of the SOFA model was 0.583 in the training set and 0.628 in the validation set. The AUC of the NEWS model was 0.601 in the training set and 0.618 in the validation set. The Delong test suggests that in both the training set and the validation set, compared with the SOFA and NEWS models, this prediction model had advantages in discrimination ability ( P<0.01). Conclusions:The nomogram model based on lactic acid, D-dimer, B-type brain natriuretic peptide precursor, albumin, globulin, percutaneous blood oxygen saturation and pulmonary infection can effectively predict the risk of respiratory failure within 48 h after admission in patients with SA-AKI.

Cells and exosomes derived from them are extensively used as biological carrier systems. Cells demonstrate superior targeting specificity and prolonged circulation facilitated by their rich array of surface proteins, while exosomes, due to their small size, cross barriers and penetrate tumors efficiently. However, challenges remain, cells' large size restricts tissue penetration, and exosomes have limited targeting accuracy and short circulation times. To address these challenges, we developed a novel concept termed exosomal spheres. This approach involved incorporating platelet-derived exosomes shielded with phosphatidylserine (PS) and linked via pH-sensitive bonds for drug delivery applications. The study demonstrated that, compared with exosomes, the exosomal spheres improved blood circulation through the upregulation of CD47 expression and shielding of phosphatidylserine, thereby minimizing immune clearance. Moreover, the increased expression of P-selectin promoted adhesion to circulating tumor cells, thereby enhancing targeting efficiency. Upon reaching the tumor site, the hydrazone bonds of exosome spheres were protonated in the acidic tumor microenvironment, leading to disintegration into uniform-sized exosomes capable of deeper tumor penetration compared to platelets. These findings suggested that exosome spheres addressed the challenges and offered significant potential for efficient and precise drug delivery.

With the rapid advancement of vaccines, the research and application of vaccine adjuvants have garnered significant attention. Despite the development of numerous vaccine adjuvants, their applications in human vaccines remain limited due to either insufficient efficacy or severe side effects. Consequently, there is growing interest in developing bioactive compounds derived from traditional Chinese medicines (TCMs) as vaccine adjuvants, owing to their natural biocompatibility, diversity, and safety. Here, we systematically review the current application status and potential value of TCM-based bioactive compounds in vaccine adjuvants. Firstly, we elaborate on the types and characteristics of active ingredients, such as polysaccharides, saponins, flavonoids, acids, and alkaloids. The mechanisms by which these compounds function as vaccine adjuvants are then discussed, including their roles in enhancing humoral immunity, cellular immunity, and relieving the immune suppression in the microenvironment. Additionally, we summarize the current strategies for structural modification and platform optimization to adapt to different application scenarios. Finally, we offer insights into the future development directions for these potential adjuvants, highlighting research priorities, technical approaches, and application prospects. In conclusion, natural vaccine adjuvants derived from TCMs present broad application prospects and hold promise for future vaccine development.

Objective To investigate the relationship between extracranial carotid artery tortuosity-related indicators and extracranial internal carotid artery aneurysm(ICAA)in elderly patients with suspected cerebrovascular disease.Methods A retrospective analysis was performed on 124 elderly patients with suspected cerebrovascular diseases undergoing head CT angiography(CTA)in our hospital from January 2021 to December 2023.According to the diagnostic results,they were divided into ICAA group(68 cases)and control group(56 cases).The extracranial carotid artery tortuosity-related indicators were compared between the two groups.Multivariate logistic regression analysis was used to identify the influencing factors for ICAA.ROC curve analysis was employed to analyze the diagnostic value of head CTA parameters for extracranial ICAA,and the area under curve(AUC)was calculated.Results There were no statistical differences in the pro-portions of extracranial internal carotid artery(EICA)without kinking,tortuosity,and coiling be-tween the two groups(P＞0.05).The ICAA group had significantly higher proportion of EICA(32.4％vs 14.3％,P＜0.05),and obviously greater common carotid artery kinking index,EICA kinking index,and internal carotid artery angle than the control group(P＜0.01).Multivariate lo-gistic regression analysis showed that kinking,common carotid artery kinking index,EICA kin-king index,and internal carotid artery angle were influencing factors for ICAA(P＜0.05,P＜0.01).ROC curve analysis indicated that in diagnosing ICAA,the sensitivity and the specificity was 70.59％and 82.14％,respectively,for common carotid artery kinking index,was 83.82％and 87.50％,respectively,for EICA kinking index,and was 80.88％and 83.93％,respectively,for in-ternal carotid artery angle.Conclusion The degree of EICA kinking is correlated with extracranial ICAA,and EICA kinking is more likely to cause ICAA.Head CTA parameters can reflect the morphological features of internal carotid artery kinking and had high adjuvant diagnostic value for diagnosing ICAA.

Congenital heart disease(CHD)is the leading cause of mortality associated with birth defects.Whole-genome sequencing and whole-exome sequencing technologies have resulted in major advancements in our understanding of the genetics of CHD,and cell and animal models have emerged as reliable options for investigating the specific genetic mechanisms and factors underlying CHD.Human induced pluripotent stem cells(iPSCs)offer a novel approach for studying CHD by generating patient-specific iPSC-derived cardiomyocytes for related research.In addition,CRISPR-Cas9 gene editing tools enable the introduction or correction of variant genes in iPSCs,thus facilitating a more comprehensive exploration of variant pathogenicity and the molecular basis of CHD.This review considers the progress in understanding the genetic basis of CHD using genome sequencing,and explores how gene editing techniques and patient iPSCs contribute to this progress.We highlight the significance of combining these two approaches for disease research,providing valuable insights for clinical investigations on the mechanisms responsible for CHD.

Congenital heart disease(CHD)is the leading cause of mortality associated with birth defects.Whole-genome sequencing and whole-exome sequencing technologies have resulted in major advancements in our understanding of the genetics of CHD,and cell and animal models have emerged as reliable options for investigating the specific genetic mechanisms and factors underlying CHD.Human induced pluripotent stem cells(iPSCs)offer a novel approach for studying CHD by generating patient-specific iPSC-derived cardiomyocytes for related research.In addition,CRISPR-Cas9 gene editing tools enable the introduction or correction of variant genes in iPSCs,thus facilitating a more comprehensive exploration of variant pathogenicity and the molecular basis of CHD.This review considers the progress in understanding the genetic basis of CHD using genome sequencing,and explores how gene editing techniques and patient iPSCs contribute to this progress.We highlight the significance of combining these two approaches for disease research,providing valuable insights for clinical investigations on the mechanisms responsible for CHD.

Objective To explore the mechanism of Glaucocalyxin A(GLA)in inhibiting ovalbumin(OVA)-induced airway remodeling in asthmatic mice through the topoisomerase Ⅱ α(TOP2A)/cyclin-dependent kinase 1(CDK1)signaling pathway.Methods Forty Balb/c mice were randomly divided into 5 groups:the control group,the model group,the low-dose GLA group,the high-dose GLA group and the Dexamethasone group,with 8 mice in each group.The effect of GLA on airway remodeling was examined by immunohistochemical staining,ELISA and other methods,and bioinformatics methods were used to predict new targets of GLA.The action targets of TOP2A were screened using the STRING database,and the interaction relationship between the two was verified by co-immunoprecipitation.In vitro,GLA and siRNA were used to interfere with interleukin-4(IL-4)-stimulated human airway epithelial cells BEAS-2B.The expressions of TOP2A,epidermal growth factor receptor(EGFR),Integrin β1,focal adhesion kinase(FAK),β-catenin,CDK1 and DRP1 were detected by Western Blot.Results GLA intervention could significantly reduce OVA-induced asthma airway remodeling,airway smooth muscle thickening,collagen deposition around the airway,the number of eosinophils in alveolar lavage fluid,the expression of pro-inflammatory cytokines such as IL-4,and the level of serum IgE.The new target of GLA screened out was TOP2A,which was highly expressed in the lung tissue of the asthma airway remodeling model.GLA intervention could down-regulate its expression.In vitro,intervention with GLA and si-TOP2A could significantly down-regulate the expressions of IL-4-induced TOP2A,EGFR,Integrin β1,FAK and β-catenin.Further studies have found that TOP2A had an interaction relationship with CDK1.si-TOP2A could downregulate the expression of CDK1,and knockdown of CDK1 could significantly down-regulate the expression of phosphorylated DRP1.Conclusion GLA may alleviate asthma airway remodeling by targeting the TOP2A/CDK1 signaling pathway,providing experimental evidence for the clinical diagnosis and treatment of asthma airway remodeling in asthma.

Objective:To explore the risk factors of respiratory failure within 48 hours of admission in patients with sepsis associated acute kidney injury(SA-AKI)and establish a predictive model and verify it.Methods:A retrospective selection was made of 702 patients with SA-AKI admitted to Dongyang People's Hospital from June 2012 to October 2024, and they were randomly divided into the training set (492 cases) and the validation set (210 cases) in a ratio of 7∶3. The risk factors of respiratory failure within 48 h of admission in patients with SA-AKI were analyzed in the training set to establish a nomogram. The discriminative ability of the model was evaluated by using the receiver operating characteristic (ROC) curve, and the clinical effectiveness of the predictive model was evaluated by using decision curve analysis (DCA). Meanwhile, validation was conducted in the validation set. The Sequential Organ Failure Assessment (SOFA) and National Early Warning Score (NEWS) models were established, and the Delong test was applied to compare them with this prediction model.Results:The results of Logistic regression analysis showed that lactic acid, D-dimer, pro-B-type natriuretic peptide precursor, albumin, globulin, percutaneous blood oxygen saturation and pulmonary infection were independent risk factors for respiratory failure within 48 h of admission in patients with SA-AKI ( P<0.05). The results of ROC curve analysis indicated that the area under the curve (AUC) of this model for predicting respiratory failure within 48 h of admission in SA-AKI patients in the training set was 0.818 (95% CI 0.777 - 0.860), and that in the validation set was 0.795 (95% CI 0.723 - 0.860). The calibration curves showed that the P values were 0.973 and 0.864 respectively. The DCA curve was applied to evaluate the clinical effectiveness. The model curves were above the two extreme curves in both the training set and the validation set suggested that the model had good significance in discrimination, calibration and clinical effectiveness. The AUC of the SOFA model was 0.583 in the training set and 0.628 in the validation set. The AUC of the NEWS model was 0.601 in the training set and 0.618 in the validation set. The Delong test suggests that in both the training set and the validation set, compared with the SOFA and NEWS models, this prediction model had advantages in discrimination ability ( P<0.01). Conclusions:The nomogram model based on lactic acid, D-dimer, B-type brain natriuretic peptide precursor, albumin, globulin, percutaneous blood oxygen saturation and pulmonary infection can effectively predict the risk of respiratory failure within 48 h after admission in patients with SA-AKI.