The production of high-quality oocytes requires precisely orchestrated intercellular communication. Extracellular vesicles (EVs) are cell-derived nanoparticles that play a vital role in the transfer of bioactive molecules, which has gained much attention in the field of diagnosis and treatment. Over the past ten years, the participation of EVs in the reproductive processes of oocytes has been broadly studied and has shown great potential for elucidating the intricacies of female reproductive health. This review provides an extensive discussion of the influence of EVs on oocytes, emphasizing their involvement in normal physiology and altered cargo under pathological conditions. In addition, the positive impact of therapeutic EVs on oocyte quality and their role in alleviating ovarian pathological conditions are summarized.
Humans ; Extracellular Vesicles/physiology* ; Oocytes/cytology* ; Female ; Animals ; Cell Communication/physiology*

In this comprehensive review, we delve into the evolution of drug delivery systems in reproductive medicine with a focus on the emerging role of exosomes, a class of extracellular vesicles. Exosomes offer unique advantages in overcoming these challenges due to their inherent biocompatibility, stability, and ability to facilitate targeted delivery. This review provides a detailed examination of exosome biogenesis and their function in cellular communication, setting the stage for understanding their potential as drug delivery vehicles. We explore the mechanisms through which exosomes can be loaded with small molecule drugs and the benefits they offer over synthetic nanoparticles. The review highlights groundbreaking case studies that illustrate the successful application of exosome-mediated drug delivery in reproductive health, including enhancing fertility treatments, supporting gamete and embryo development, and facilitating maternal-fetal communication. This study aims to provide a precise understanding of how exosomal drug delivery can revolutionize treatments for reproductive health disorders, paving the way for future therapeutic applications. Lastly, we touch upon the promising therapeutic implications of exosomal delivery for proteins and genes, offering a window into future treatments for reproductive health disorders.

Objective To determine the effects of ciprofol and propofol on hemodynamics and cardiac work were determined by hemodynamic monitoring,so as to provide reference for anesthesia induction in car-diac surgery.Methods A total of 90 patients scheduled for mitral valve replacement under cardiopulmonary bypass from June 2022 to June 2023 were randomly divided into two groups:the ciprofol group (group P,n=45) and the propofol group (group B,n=45).The heart rate (HR),oxygen saturation (SpO2),index of con-sciousness (ICO1),mean arterial pressure (MAP),central venous pressure (CVP),stroke volume (SV),car-diac output (CO),systemic vascular resistance (SVR),cardiac cycle efficiency (CCE),stroke volume variation (SVV),maximum pressure gradient reflecting myocardial contractility (dp/dt) were recorded before adminis-tration (T0) and five min after administration (T1).Results In group P,ICO1,MAP,SV,CO,and SVR at T1 were lower than those at T0,and CCE was higher than that at T0 (P<0.01,P<0.05).In group B,ICO1, MAP,CVP,SV,CO,SVR,CCE,SVV,dp/dt at T1 were significantly lower than those at T0 (P<0.01,P<0.05).There was no statistically significant difference in HR,SpO2,ICO1,MAP,CVP and hemodynamic indi-cators between group B and group P at T0 (P>0.05).There was no statistically significant difference in HR, SpO2,ICO1,CVP and SVV between group B and group P at T1 (P>0.05).MAP,SV,CO,SVR,CCE and dp/dt at T1 in group P were higher than those in group B (P<0.05).Conclusion Ciprofol can better maintain hemodynamic stability and reduce cardiac impairment during the induction phase of mitral valve replacement surgery under cardiopulmonary bypass.

Objective:To explore the clinical effects of a 3D-printed intracranial pressure balancing device in preventing complications after suboccipital craniectomy (DC).Methods:This study is a retrospective cohort analysis. The clinical data of 35 patients who underwent DC at Department of Neurosurgery, Beijing Chaoyang Hospital, Capital Medical University, from September 2020 to September 2023 were reviewed. The cohort included 24 males and 11 females, with an age of (48.7±14.9) years (range:17 to 74 years). Nineteen patients (experimental group) received the intracranial pressure balancing device fixed to the bone defect site post-DC. This device was made using medical-grade dicyanamide resin and was three dimensional printed based on postoperative CT scans of the patients. The remaining 16 patients (control group) did not receive the intracranial pressure balancing device, while other treatments and procedures were consistent with the experimental group. Data were compared using the χ2 test or Fisher′s exact probability method. Results:Out of the 35 patients, 30 cases (85.7%) experienced complications following DC. Specific complications included cerebral infarction in 3 cases (8.6%), intracerebral hemorrhage in 1 case (2.9%), subdural effusion in 27 cases (77.1%) with a median onset of (8.8±6.5) days (range: 1 to 23 days), brain tissue protrusion in 15 cases (42.9%) with a median onset of ( M(IQR)) 7.0 (21.0) days (range:2 to 106 days), and hydrocephalus in 6 cases (17.14%) with a median onset of 34.5 (111.0) days (range: 22 to 136 days). There were no significant differences in the occurrence of complications(all P>0.05). However, there was a significant reduction in the incidence of subdural effusion in the experimental group prior to cranioplasty ( P=0.013). No significant differences were noted in mRS scores between the two groups after cranioplasty ( P>0.05). Conclusions:The intracranial pressure balancing device has the effect of prevention and treatment of subdural effusion. However, it did not significantly improve patient prognosis post-DC, warranting further investigation.

Objective To investigate the predictive efficacy of serum aminoterminal brain natriuretic pep-tide precursor(NT-proBNP),hypersensitive C-reactive protein(hs-CRP),D-dimer(D-D)and procalcitonin(PCT)in heart failure after acute myocardial infarction(AMI),Methods A total of 100 AMI patients admit-ted to the hospital from July 2021 to July 2023 were enrolled in the study as the observation group,In addi-tion,100 healthy people who underwent physical examination in the hospital during the same period were en-rolled as the control group,The serum levels of NT-proBNP,hs-CRP,D-D and PCT were detected and com-pared between the observation group and the control group,The AMI patients enrolled in the study were fur-ther divided into the heart failure group(31 cases)and the non-heart failure group(69 cases)according to the presence or absence of heart failure.The serum levels of NT-proBNP,hs-CRP,D-D,and PCT were compared between the two groups,Univariate analysis and multivariate Logistic regression analysis were used to analyze the risk factors of heart failure after AMI,Receiver operating characteristic(ROC)curve and decision curve a-nalysis(DCA)were used to analyze the predictive efficacy of serum NT-proBNP,hs-CRP,D-D and PCT for heart failure after AMI.Results The levels of serum NT-proBNP,hs-CRP,D-D and PCT in the observation group were higher than those in the control group(P＜0.05).The serum levels of NT-proBNP,hs-CRP,D-D and PCT in the complicated heart failure group were higher than those in the non-heart failure group(P＜0.05),Body mass index(BMI),smoking history,hypertension,number of diseased vessels,serum uric acid(SUA),low-density lipoprotein cholesterol(LDL-C),NT-proBNP,hs-CRP,D-D and PCT were risk factors for heart failure after AMI(P＜0.05).ROC curve analysis showed that the area under the curve(AUC)of combined detection of serum NT-proBNP,hs-CRP,D-D and PCT for predicting heart failure after AMI was 0.857(95％CI:0.811-0.948),the sensitivity was 96.12％,and the specificity was 91.28％,which were higher than the corresponding efficacy indexes of single detection(P＜0.05).DCA analysis showed that when the high-risk threshold was 0-0.99,the net benefit rate was greater than 0,which had clinical significance,When the threshold was 0-0.76,the net benefit rate of combined detection of serum NT-proBNP,hs-CRP,D-D and PCT was better than that of serum NT-proBNP,hs-CRP,D-D and PCT alone.Conclusion Combined detection of serum NT-proBNP,hs-CRP,D-D and PCT can improve the predictive efficiency of AMI compli-cated with heart failure,BMI,smoking history,hypertension,number of diseased vessels,SUA,LDL-C,NT-proBNP,hs-CRP,D-D and PCT are risk factors for AMI complicated with heart failure.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

ObjectiveTo explore the therapeutic effect and mechanism of Guipitang on rats with myocardial ischemia. MethodFifty SD rats were divided into five groups： a control group， a model group， low and high-dose Guipitang （7.52， 15.04 g·kg^-1） groups， and a trimetazidine group （0.002 g·kg^-1）. By intragastric administration of vitamin D₃ and feeding rats with high-fat forage and injecting isoproterenol， the rat model of myocardial ischemia was established. After drug treatment of 15 d， an electrocardiogram （ECG） was performed to analyze the degree of myocardial injury. A fully automatic biochemical analyzer was used to detect the changes in the serum levels of total cholesterol （TC）， high-density lipoprotein cholesterol （HDL-C）， triglyceride （TG）， and low-density lipoprotein cholesterol （LDL-C）. Hematoxylin-eosin （HE） staining and Masson staining were used to observe myocardial histopathological changes. TdT-mediated dUTP nick end labeling （TUNEL） staining was used to detect cardiomyocyte apoptosis. Western blot was adopted to detect the protein levels of extracellular signal-regulated kinase 1/2 （ERK1/2）， phospho-ERK1/2 （p-ERK1/2）， p38 mitogen-activated protein kinase （p38 MAPK）， phospho-p38 MAPK （p-p38 MAPK）， B-cell lymphoma-2 （Bcl-2）-associated X （Bax）， Bcl-2， and cleaved cysteine aspartate proteolytic enzyme （cleaved Caspase-3）. ResultCompared with the control group， the ECG S-T segment decreased in the model group. The serum levels of TC， TG， and LDL-C were increased significantly （P<0.05）. The arrangement of myocardial tissue was disordered， and the proportion of cardiomyocyte apoptosis increased. The protein levels of cleaved Caspase-3， Bax， and p-p38 MAPK in the heart were increased， and the Bcl-2 expression was decreased （P<0.05）. Compared with the model group， the S-T segment downward shift was restored in the low and high-dose Guipitang groups and trimetazidine group， and the levels of TC， TG， and LDL-C were decreased. The protein expression of cleaved Caspase-3 and Bax in the heart dropped， and p-p38 MAPK and p-ERK1/2 protein expressions increased significantly （P<0.05）. The degree of myocardial injury was alleviated， and the proportion of cardiomyocyte apoptosis decreased. Bcl-2 protein expression was increased significantly in the low-dose Guipitang group （P<0.05）. ERK1/2 and p38 MAPK proteins had no significant difference among different groups. ConclusionGuipitang could alleviate myocardial injury and inhibit cardiomyocyte apoptosis in rats by activating the expression of ERK1/2 and p38 MAPK.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.

Objective:To explore the effectiveness of a hysteroscopic endometrial lesion diagnosis model de-veloped based on deep learning(DL)algorithm combined with gradient-weighted class activation mapping(Grad-CAM)visualization technology.Methods:303 hysteroscopy videos(4781 images)of 291 patients who un-derwent hysteroscopy examination in the Department of Gynecology,Renmin Hospital of Wuhan University from June 1,2021 to December 31,2022 were selected.The dataset was divided into a training set(3703 images)and a test set(1078 images)by weight sampling method.After the training set was used for model learning and train-ing,two model architectures,residual neural network(ResNet18)and efficient neural network(EfficientNet-B0),were selected to verify the model in the test set by five-class and two-class classification tasks,respectively.Tak-ing histopathology as the gold standard,the diagnostic efficacy was evaluated to select the optimal model,and the Grad-CAM layer was embedded in the optimal model to output hysteroscopy images of Grad-CAM.Results:①In the five-class classification tasks,the accuracy of EfficientNet-B0 model(93.23％)was higher than that of Res-Net18 model(84.23％);the area under the curve(AUC)of EfficientNet-B0 model in the diagnosis of five disea-ses,including atypical endometrial hyperplasia,endometrial polyps,endometrial cancer,endometrial atypical hy-perplasia,and submucous myoma,was slightly higher than that of ResNet18 model,and the AUC of both models was almost above 0.980.②In the binary classification task of accuracy and the evaluation of specificity,the two models were similar,both above 93.00％,and the sensitivity of EfficientNet-B0 model(91.14％)was significantly better than that of ResNet18 model(77.22％).③EfficientNet-B0 model combined with Grad-CAM algorithm could identify the abnormal areas in the image.After biopsy and pathological examination,it was confirmed that about 95％of the marked areas in the model's output heatmap were lesion areas.Conclusions:The hysteroscopy di-agnostic model developed by EfficientNet-B0 model combined with Grad-CAM has high diagnostic accuracy,sen-sitivity,and specificity,and has application value in the diagnosis of endometrial lesions.