Background: According to a recent report by the WHO, approximately 17.5\% (about one-sixth) of the global adult population is affected by infertility. Consequently, researchers worldwide have proposed various machine learning models to improve the prediction of clinical pregnancy outcomes during IVF cycles. The objective of this study is to develop a machine learning(ML) model that predicts the outcomes of pregnancies following in vitro fertilization (IVF) and assists in clinical treatment.Methods: This study conducted a retrospective analysis on provincial reproductive centers in China from March 2020 to March 2021, utilizing 13 selected features. The algorithms used included XGBoost, LightGBM, KNN, Naïve Bayes, Random Forest, and Decision Tree. The results were evaluated using performance metrics such as precision, recall, F1-score, accuracy and AUC, employing five-fold cross-validation repeated five times.Results: Among the models, LightGBM achieved the best performance, with an accuracy of 92.31%, recall of 87.80%, F1-score of 90.00\%, and an AUC of 90.41%. The model identified the estrogen concentration at the HCG injection(etwo), endometrium thickness (mm) on HCG day(EM TNK), years of infertility(Years), and body mass index(BMI) as the most important features.Conclusion: This study successfully demonstrates the LightGBM model has the best predictive effect on pregnancy outcomes during IVF cycles. Additionally, etwo was found to be the most significant predictor for successful IVF compared to other variables. This machine learning approach has the potential to assist fertility specialists in providing counseling and adjusting treatment strategies for patients.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects reproductive dysfunction and metabolism in women of childbearing age. An increasing number of studies have suggested that the bone morphogenetic protein 15 (BMP15) signalling pathway serves an important role in the pathogenesis of PCOS; however, the full mechanism remains unknown. The present study revealed that intrinsic follicular dysplasia may be associated with regulation disorders of ovarian granulosa cell apoptosis. Compared with the control group, body mass index, luteinising hormone and testosterone levels were significantly increased (P<0.05). The percentage of S phase cells was significantly higher, cells in G2/M phase cells was significantly lower, and cells undergoing apoptosis was significantly higher in the PCOS group compared with the control group (P<0.05). The expression levels of B‑cell lymphoma 2 was significantly decreased in granulosa cells of PCOS group, whereas the expression of caspase‑3 was higher than the control group (P<0.05). The rate of apoptosis of granulosa cells was measured by a terminal deoxynucleotide transferase dUTP nick‑end labelling assay. The relative mRNA expression levels of BMP receptor 2 and SMAD1 were significantly decreased in granulosa cells in the PCOS group compared with the control (P<0.05). In addition, the expression of BMP15 in follicular fluid and Smad1 in granulosa cells was significantly decreased in the PCOS group compared with the control (P<0.05). The data suggested that the BMP15/Smad1 signalling pathway may be involved in granulosa cell apoptosis, and may be a target for clinical treatment for PCOS.

The prognostic value of long non coding RNAs in cervical cancer: A meta-analysis The prognostic value of long non coding RNAs in cervical cancer: A meta-analysis

Background: Inflammatory response of central nervous system is an important component mechanism in the bladder pain of interstitial cystitis/bladder pain syndrome (IC/BPS). Exosomes transfer with microRNAs (miRNA) from mesenchymal stem cell (MSCs) might inhibit inflammatory injury of the central nervous system. Herein, the purpose of our study was to explore the therapeutic effects by which extracellular vesicles （EVs） derived from miR‐9‐edreched MSCs in IC/BPS and further investigate the potential mechanism to attenuate neuroinflammation.Methods: On the basis of IC/BPS model, we used various techniques including bioinformatics, cell and molecular biology, and experimental zoology, to elucidate the role and molecular mechanism of TLR4 in regulating the activation of NLRP3 inflammasome in bladder pain of IC/BPS, and investigate the mechanism and feasibility of MSC‐EVs enriched with miR‐9 in the treatment of bladder pain of IC/BPS.Results: The inflammatory responses in systemic and central derived by TLR4 activation were closely related to the cystitis‐induced pelvic/bladder nociception in IC/BPS model. Intrathecal injection of miR‐9‐enreched MSCs derived exosomes were effective in the treatment of cystitis‐induced pelvic/bladder nociception by inhibiting TLR4/NF‑κb/NLRP3 signal pathway in central nervous system of IC/BPS mice.Conclusions: This study demonstrated that miR‐9‐enreched MSCs derived exosomes alleviate neuroinflammaiton and cystitis‐induced bladder pain by inhibiting TLR4/NF‑κb/NLRP3 signal pathway in interstitial cystitis mice, which is a promising strategy against cystitis‐induced bladder pain.