Interpretable machine learning models for predicting clinical pregnancies associated with surgical sperm retrieval from testes of different etiologies: a retrospective study.

BACKGROUND: The relationship between surgical sperm retrieval of different etiologies and clinical pregnancy is unclear. We aimed to develop a robust and interpretable machine learning (ML) model for predicting clinical pregnancy using the SHapley Additive exPlanation (SHAP) association of surgical sperm retrieval from testes of different etiologies. METHODS: A total of 345 infertile couples who underwent intracytoplasmic sperm injection (ICSI) treatment with surgical sperm retrieval due to different etiologies from February 2020 to March 2023 at the reproductive center were retrospectively analyzed. The six machine learning (ML) models were used to predict the clinical pregnancy of ICSI. After evaluating the performance characteristics of the six ML models, the Extreme Gradient Boosting model (XGBoost) was selected as the best model, and SHAP was utilized to interpret the XGBoost model for predicting clinical pregnancies and to reveal the decision-making process of the model. RESULTS: Combining the area under the receiver operating characteristic curve (AUROC), accuracy, precision, recall, F1 score, brier score, and the area under the precision-recall (P-R) curve (AP), the XGBoost model has the best performance (AUROC: 0.858, 95% confidence interval (CI): 0.778-0.936, accuracy: 79.71%, brier score: 0.151). The global summary plot of SHAP values shows that the female age is the most important feature influencing the model output. The SHAP plot showed that younger age in females, bigger testicular volume (TV), non-tobacco use, higher anti-müllerian hormone (AMH), lower follicle-stimulating hormone (FSH) in females, lower FSH in males, the temporary ejaculatory disorders (TED) group, and not the non-obstructive azoospermia (NOA) group all resulted in an increased probability of clinical pregnancy. CONCLUSIONS: The XGBoost model predicts clinical pregnancies associated with testicular sperm retrieval of different etiologies with high accuracy, reliability, and robustness. It can provide clinical counseling decisions for patients with surgical sperm retrieval of various etiologies.

Combining Porous Se@SiO2 Nanocomposites and dECM Enhances the Myogenic Differentiation of Adipose-Derived Stem Cells.

Background: Volumetric Muscle Loss (VML) denotes the traumatic loss of skeletal muscle, a condition that can result in chronic functional impairment and even disability. While the body can naturally repair injured skeletal muscle within a limited scope, patients experiencing local and severe muscle loss due to VML surpass the compensatory capacity of the muscle itself. Currently, clinical treatments for VML are constrained and demonstrate minimal efficacy. Selenium, a recognized antioxidant, plays a crucial role in regulating cell differentiation, anti-inflammatory responses, and various other physiological functions. Methods: We engineered a porous Se@SiO2 nanocomposite (SeNPs) with the purpose of releasing selenium continuously and gradually. This nanocomposite was subsequently combined with a decellularized extracellular matrix (dECM) to explore their collaborative protective and stimulatory effects on the myogenic differentiation of adipose-derived mesenchymal stem cells (ADSCs). The influence of dECM and NPs on the myogenic level, reactive oxygen species (ROS) production, and mitochondrial respiratory chain (MRC) activity of ADSCs was evaluated using Western Blot, ELISA, and Immunofluorescence assay. Results: Our findings demonstrate that the concurrent application of SeNPs and dECM effectively mitigates the apoptosis and intracellular ROS levels in ADSCs. Furthermore, the combination of dECM with SeNPs significantly upregulated the expression of key myogenic markers, including MYOD, MYOG, Desmin, and myosin heavy chain in ADSCs. Notably, this combination also led to an increase in both the number of mitochondria and the respiratory chain activity in ADSCs. Conclusion: The concurrent application of SeNPs and dECM effectively diminishes ROS production, boosts mitochondrial function, and stimulates the myogenic differentiation of ADSCs. This study lays the groundwork for future treatments of VML utilizing the combination of SeNPs and dECM.