Cancer ranks as the second leading cause of death globally and has surpassed cardiovascular diseases to become the primary cause of mortality in developed countries. Cancer stem cells (CSCs), which play crucial roles in cancer recurrence, metastasis, and drug resistance, have attracted significant attention in targeted therapeutic strategies. Aptamers, with unique three-dimensional structures capable of specifically recognizing the surface markers of CSCs, show promising potential in targeted drug delivery systems. Compared with conventional antibodies, aptamers are praised for small molecular weights, low production costs, and easy chemical modification. This review systematically summarizes recent advances in aptamer research targeting the surface markers of CSCs, with particular emphasis on aptamer-drug conjugate systems targeting the markers including EpCAM, CD133, CD44, and ABCG2. Both in vitro cellular studies and in vivo animal models have demonstrated the definite anti-cancer efficacy of aptamer-based drug delivery systems, which are of great significance to develop novel therapeutic strategies and improving the therapeutic effects of CSC-targeted treatment. Thus, aptamer-based drug delivery system has broad application prospects in the field of precise cancer treatment.
Humans ; Neoplastic Stem Cells/metabolism* ; Aptamers, Nucleotide/therapeutic use* ; Drug Delivery Systems/methods* ; Neoplasms/drug therapy* ; Biomarkers, Tumor/metabolism* ; Animals ; Epithelial Cell Adhesion Molecule ; AC133 Antigen ; Hyaluronan Receptors

Chronic non-healing wounds significantly impair patient rehabilitation and remain a critical clinical challenge. Stem cell-derived exosomes, owing to their biocompatibility and physiological activity, have emerged as a promising therapeutic approach in regenerative medicine. Beyond their intrinsic wound-healing properties, exosomes are increasingly explored as carriers for small-molecule drugs to enhance synergistic treatment effects. Although microRNAs (miRNAs) exhibit potential in promoting cell proliferation and re-epithelialization, their clinical application is hindered by poor stability. In this study, we investigated the therapeutic effects of miR-132-3p-loaded human umbilical mesenchymal stem cell-derived exosomes (miR-132-3p@UMSC-EXOs) on human foreskin fibroblast-1 (HFF-1). Our findings demonstrated that miR-132-3p@UMSC-EXOs significantly enhanced proliferation and migration of HFF-1, while reducing intracellular reactive oxygen species (ROS) levels compared with unloaded exosomes. Furthermore, qRT-PCR and Western blotting analyses revealed that miR-132-3p@UMSC-EXOs modulated the expression of genes associated with extracellular matrix (ECM) remodeling and inflammation, suggesting their potential to upregulate collagen synthesis and improve ECM metabolism. These results highlight the therapeutic promise of miR-132-3p@UMSC-EXOs in accelerating wound healing.
Humans ; MicroRNAs/pharmacology* ; Exosomes/metabolism* ; Mesenchymal Stem Cells/cytology* ; Wound Healing ; Umbilical Cord/cytology* ; Cell Proliferation ; Fibroblasts/cytology* ; Skin/injuries* ; Cell Movement ; Reactive Oxygen Species/metabolism* ; Cells, Cultured

Purpose To compare the clinical and cardiovascular magnetic resonance(CMR)characteristics of hypertrophic cardiomyopathy(HCM)with and without diabetes mellitus,and to investigate the effect of diabetes mellitus on left ventricular remodeling in HCM patients.Materials and Methods A total of 96 HCM patients diagnosed with CMR in Chengdu Fifth People's Hospital from January 2021 to March 2023,retrospectively.They were divided into HCM with diabetes mellitus group(n=22)and HCM without diabetes mellitus group(n=74)according to whether they had diabetes mellitus.The clinical baseline and CMR data of HCM patients were analyzed,and left ventricular function and strain were compared between the two groups.Results The HCM group with diabetes mellitus was observed to have a significantly higher left ventricular mass index compared to HCM without diabetes mellitus group[(1.33±0.50)g/ml vs.(1.10±0.23)g/ml;t=3.002,P=0.003],along with a significantly lower left ventricular global circumferential strain[-19.69(-21.82,-17.06)%vs.-16.33(-20.84,-13.86)%;Z=543.000,P<0.05]and global longitudinal strain[(-8.69±3.94)%vs.(-10.74±3.62)%;t=2.227,P<0.05)].Furthermore,diabetes mellitus was identified as an independent factor associated with an increased left ventricular mass index(β=0.330,P<0.05)by multivariate linear regression analysis.Conclusion In patients with HCM,diabetes mellitus is independently associated with left ventricular remodeling.The global circumferential strain and longitudinal strain of HCM patients with diabetes mellitus decreases significantly,suggesting that diabetes mellitus has a significant impact on left ventricular strain in HCM patients.

Objective To establish the construction and validation of a nomogram model for predicting the risk of early diabetic kidney disease(DKD)based on blood pressure and blood glucose variability.Methods Patients with early DKD were selected as the DKD group(n=247)and patients with T2DM alone as the T2DM group(n=150)from the Department of Endocrinology of our hospital during April 2020 to December 2023.All subjects were randomly divided into a training set(n=278)and a validation set(n=119)according to a ratio of 7∶3.The general data and biochemical indicators were compared between the two groups,and Cox proportional risk regression analysis was performed on the influencing factors for DKD in the training set.The risk nebulogram prediction model was constructed.The receiver operating characteristic(ROC)curve and consistency index(C-index)were used to analyze the effectiveness of the model in the training set and verification set,and Bootstrap internal verification was carried out.The calibration curve was drawn to evaluate the prediction calibration degree and discrimination validity of the model.Clinical decision curve(DCA)was applied to evaluate the clinical utility of the nomogram model.Results SBP,DBP,BUN,blood uric acid,24 h systolic blood pressure variation coefficient(24 hSBPCV),24 h diastolic blood pressure variation coefficient(24 h hDBPCV),coefficient of variation in daytime systolic blood pressure(dSBPCV),coefficient of variation in daytime diastolic blood pressure(dDBPCV),coefficient of variation in nighttime systolic blood pressure(nSBPCV),coefficient of Variation in nighttime diastolic blood pressure(nDBPCV),maximum daytime blood glucose fluctuation range(LAGE),average blood glucose throughout the day(MBG),and standard deviation of blood glucose throughout the day(SDBG),fasting blood glucose coefficient of variation(FBG-CV)and mean blood glucose fluctuation range(MAGE)were higher in DKD group than in T2DM group(P＜0.05).eGFR was lower in DKD group than in T2DM group(P＜0.05).Cox proportional risk regression analysis showed that 24 hSBPCV,24 hDBPCV,dSBPCV,dDBPCV,nSBPCV,nDBPCV,LAGE,MBG,SDBG,FBG-CV and MAGE were the influencing factors for the early occurrence of DKD.Accordingly,the prediction model of early DKD was established.ROC curve analysis showed that the area under the curve of the early DKD nomogram model were 0.834 and 0.805 in the training set and verification set,with the sensitivity 85.20%and 80.60%,and the specificity 71.40%and 72.40%,respectively.Calibration curve analysis showed that the C-index of the early DKD neomorph model were 0.839 and 0.801 in the training set and the verification set,respectively.The goodness of fit test results showed that the actual observed values are in good agreement with the predicted results.The results of DCA curve showed that when the threshold probability of early DKD occurrence was between 0 and 1,the net benefit value of this model was better.Conclusions In this study,the nomogram model constructed by BP and BG variability parameters can effectively predict the occurrence of early DKD,and provide a basis for clinical screening and evaluation.

Objective To establish the construction and validation of a nomogram model for predicting the risk of early diabetic kidney disease(DKD)based on blood pressure and blood glucose variability.Methods Patients with early DKD were selected as the DKD group(n=247)and patients with T2DM alone as the T2DM group(n=150)from the Department of Endocrinology of our hospital during April 2020 to December 2023.All subjects were randomly divided into a training set(n=278)and a validation set(n=119)according to a ratio of 7∶3.The general data and biochemical indicators were compared between the two groups,and Cox proportional risk regression analysis was performed on the influencing factors for DKD in the training set.The risk nebulogram prediction model was constructed.The receiver operating characteristic(ROC)curve and consistency index(C-index)were used to analyze the effectiveness of the model in the training set and verification set,and Bootstrap internal verification was carried out.The calibration curve was drawn to evaluate the prediction calibration degree and discrimination validity of the model.Clinical decision curve(DCA)was applied to evaluate the clinical utility of the nomogram model.Results SBP,DBP,BUN,blood uric acid,24 h systolic blood pressure variation coefficient(24 hSBPCV),24 h diastolic blood pressure variation coefficient(24 h hDBPCV),coefficient of variation in daytime systolic blood pressure(dSBPCV),coefficient of variation in daytime diastolic blood pressure(dDBPCV),coefficient of variation in nighttime systolic blood pressure(nSBPCV),coefficient of Variation in nighttime diastolic blood pressure(nDBPCV),maximum daytime blood glucose fluctuation range(LAGE),average blood glucose throughout the day(MBG),and standard deviation of blood glucose throughout the day(SDBG),fasting blood glucose coefficient of variation(FBG-CV)and mean blood glucose fluctuation range(MAGE)were higher in DKD group than in T2DM group(P＜0.05).eGFR was lower in DKD group than in T2DM group(P＜0.05).Cox proportional risk regression analysis showed that 24 hSBPCV,24 hDBPCV,dSBPCV,dDBPCV,nSBPCV,nDBPCV,LAGE,MBG,SDBG,FBG-CV and MAGE were the influencing factors for the early occurrence of DKD.Accordingly,the prediction model of early DKD was established.ROC curve analysis showed that the area under the curve of the early DKD nomogram model were 0.834 and 0.805 in the training set and verification set,with the sensitivity 85.20%and 80.60%,and the specificity 71.40%and 72.40%,respectively.Calibration curve analysis showed that the C-index of the early DKD neomorph model were 0.839 and 0.801 in the training set and the verification set,respectively.The goodness of fit test results showed that the actual observed values are in good agreement with the predicted results.The results of DCA curve showed that when the threshold probability of early DKD occurrence was between 0 and 1,the net benefit value of this model was better.Conclusions In this study,the nomogram model constructed by BP and BG variability parameters can effectively predict the occurrence of early DKD,and provide a basis for clinical screening and evaluation.

Purpose To compare the clinical and cardiovascular magnetic resonance(CMR)characteristics of hypertrophic cardiomyopathy(HCM)with and without diabetes mellitus,and to investigate the effect of diabetes mellitus on left ventricular remodeling in HCM patients.Materials and Methods A total of 96 HCM patients diagnosed with CMR in Chengdu Fifth People's Hospital from January 2021 to March 2023,retrospectively.They were divided into HCM with diabetes mellitus group(n=22)and HCM without diabetes mellitus group(n=74)according to whether they had diabetes mellitus.The clinical baseline and CMR data of HCM patients were analyzed,and left ventricular function and strain were compared between the two groups.Results The HCM group with diabetes mellitus was observed to have a significantly higher left ventricular mass index compared to HCM without diabetes mellitus group[(1.33±0.50)g/ml vs.(1.10±0.23)g/ml;t=3.002,P=0.003],along with a significantly lower left ventricular global circumferential strain[-19.69(-21.82,-17.06)%vs.-16.33(-20.84,-13.86)%;Z=543.000,P<0.05]and global longitudinal strain[(-8.69±3.94)%vs.(-10.74±3.62)%;t=2.227,P<0.05)].Furthermore,diabetes mellitus was identified as an independent factor associated with an increased left ventricular mass index(β=0.330,P<0.05)by multivariate linear regression analysis.Conclusion In patients with HCM,diabetes mellitus is independently associated with left ventricular remodeling.The global circumferential strain and longitudinal strain of HCM patients with diabetes mellitus decreases significantly,suggesting that diabetes mellitus has a significant impact on left ventricular strain in HCM patients.