Membranous extracellular matrix (ECM)-based scaffolds are one of the most promising biomaterials for skin wound healing, some of which, such as acellular dermal matrix, small intestinal submucosa, and amniotic membrane, have been clinically applied to treat chronic wounds with acceptable outcomes. Nevertheless, the wide clinical applications are always hindered by the poor mechanical properties, the uncontrollable degradation, and other factors after implantation. To highlight the feasible strategies to overcome the limitations, in this review, we first outline the current clinical use of traditional membranous ECM scaffolds for skin wound healing and briefly introduce the possible repair mechanisms; then, we discuss their potential limitations and further summarize recent advances in the scaffold modification and fabrication technologies that have been applied to engineer new ECM-based membranes. With the development of scaffold modification approaches, nanotechnology and material manufacturing techniques, various types of advanced ECM-based membranes have been reported in the literature. Importantly, they possess much better properties for skin wound healing, and would become promising candidates for future clinical translation.

This study analyzed the effects of male age and abstinence time on semen quality and explored the best abstinence time for Chinese males among different age groups. Semen parameters, including sperm kinetics, morphology, and DNA fragmentation index (DFI), were reviewed from 2952 men. Samples were divided into six age groups (≤25 years, 26–30 years, 31–35 years, 36–40 years, 41–45 years, and >45 years) and were divided into six groups according to different abstinence time (2 days, 3 days, 4 days, 5 days, 6 days, and 7 days). The differences in semen quality between the groups were compared, and the effect of age and abstinence time on semen quality was analyzed. Significant differences were observed in semen volume, progressive motility (PR), and DFI among the age groups (all P < 0.05), and no significant differences were observed in sperm morphological parameters (all P > 0.05). There were significant differences in semen volume, PR, and DFI among different abstinence time groups (all P < 0.05) and no significant differences in sperm morphological parameters (all P > 0.05). Pearson analysis showed that male age and abstinence time were both significantly correlated with sperm kinetics and DFI (both P < 0.05), while no significant correlation was found with sperm morphological parameters (all P > 0.05). The box plots and histograms of men's age, abstinence time, and semen quality show that most semen quality parameters differ significantly between the 2 days and 7 days abstinence groups and other groups at different ages. Except for the sperm morphology parameters, sperm kinetic parameters and sperm DFI are linearly related to male age and abstinence time.

Objective: This study aims to investigate the effect of diminished ovarian reserve (DOR) on the clinical outcomes and maternal and infant safety of in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) procedures in young women aged ≤ 35 years. Methods: A retrospective cohort study was performed to analyze the clinical data of 4,203 infertile women aged ≤ 35 years who underwent fresh embryo transfer (ET) in IVF/ICSI cycles. The data were collected from their initial visits to Fujian Maternity and Child Health Hospital between January 2015 and January 2022. Based on their ovarian reserve, the participants were categorized into two groups: DOR group (n = 1,027) and non-DOR group (n = 3,176). A propensity score matching (PSM) method was employed to ensure a relatively balanced distribution of covariates. The primary outcome assessed in this study was the live birth rate, while the secondary observation indicators included rates of high-quality embryo development, blastocyst formation, clinical pregnancy, and miscarriage, along with perinatal complications, neonatal birth weight, and the incidence of low birth weight (LBW). Results: The DOR group showed notably lowered rates of blastocyst formation (59.8% vs. 64.1%), embryo implantation (29.8% vs.33.3%), clinical pregnancy (47.9% vs. 53.6%), and live birth (40.6% vs. 45.7%) compared to the non-DOR group (all P < 0.05). However, no statistically significant differences were observed in the high-quality embryo rate, miscarriage rate, perinatal complications, neonatal birth weight, or LBW incidence in infants between both groups (all P > 0.05). Conclusion: DOR has been found to reduce both clinical pregnancy and live birth rates in young females undergoing fresh ET in IVF/ICSI cycles. However, this reduction does not increase the risk of perinatal complications or LBW of infants through live birth cycles.

To investigate the determinants affecting live birth outcomes in fresh embryo transfer among polycystic ovary syndrome (PCOS) patients using various machine learning (ML) algorithms and to construct predictive models, offering novel insights for enhancing live birth rates in this specific group. A sum of 1,062 fresh embryo transfer cycles involving PCOS patients were analyzed, with 466 resulting in live births. The dataset was split randomly into training and testing subsets at a 7:3 ratio. Least absolute shrinkage and selection operator and recursive feature elimination methods were utilized for feature selection within the training data. A grid search strategy identified the optimal parameters for seven ML models: decision tree (DT), K-nearest neighbors (KNN), light gradient boosting machine (LightGBM), naive Bayes model(NBM), random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGBoost). The evaluation of model effectiveness incorporated diverse metrics, encompassing area under the curve (AUC), accuracy, positive predictive value, negative predictive value, F1 score, and Brier score. Calibration curves and decision curve analysis were employed to ascertain the optimal model. Furthermore, Shapley additive explanations were applied to elucidate the importance of predictor variables in the top-performing model. The AUC values of DT, KNN, LightGBM, NBM, RF, SVM and XGBoost models in the training set were 0.813, 1.000, 0.724, 0.791, 1.000, 0.819 and 0.853, respectively. Corresponding values in the testing set were 0.773, 0.719, 0.705, 0.764, 0.794, 0.806 and 0.822. XGBoost emerged as the most effective ML model. SHAP analysis revealed that variables encompassing embryo transfer count, embryo type, maternal age, infertility duration, body mass index, serum testosterone (T) levels, and progesterone (P) levels on the day of human chorionic gonadotropin administration were pivotal predictors of live birth outcomes in individuals with PCOS receiving fresh embryo transfer. This study developed a live birth prediction model tailored for PCOS fresh embryo transfer cycles, leveraging ML algorithms to compare the efficacy of multiple models. The XGBoost model demonstrated superior predictive capacity, enabling prompt and precise identification of critical risk factors influencing live birth outcomes in PCOS patients. These findings offer actionable insights for clinical intervention, guiding strategies to improve pregnancy outcomes in this population. Not applicable.

Objective: It is well known that circRNAs are closely involved in the progression of various diseases. However, their functions and potential regulatory mechanisms in polycystic ovary syndrome (PCOS) remain largely unknown. In the present study, our aim was to investigate the potential diagnostic value of circRNAs in PCOS. Methods: The circRNA dataset GSE145296, mRNA dataset GSE155489 and miRNA GSE138572 were downloaded from Gene Expression Omnibus (GEO) database. Then, differentially expressed genes (DEGs) were identified. Based on the potential interactions, a network of cirRNA-related competing endogenous RNAs (ceRNAs) was constructed. Biological functions were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. For further validation, qRT-PCR method was used to detect the expression level of the candidate circRNAs. Then, receiver operating characteristics (ROC) were constructed to evaluate the diagnostic value of the three differentially expressed circRNA (DE-circRNA). Results: We constructed a network of cirRNA-related ceRNA network. Hsa_circ_0075691, hsa_circ_0075692 and hsa_circ_0085997 were validate to be dysregulated in PCOS. Conclusion: Hsa_circ_0075691, hsa_circ_0075692 and hsa_circ_0085997 may be potential diagnostic biomarkers of PCOS, but their specific regulatory mechanisms still need to be further studied.