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PURPOSE: This review aimed to investigate the association of insulin resistance (IR) in women with recurrent pregnancy loss compared to women with normal pregnancy history. METHODS: PubMed, EMBASE, the Web of Science and Google Scholar databases were accessed to collect published observational studies that compared IR of recurrent pregnancy loss women with healthy women until the 6th of October 2022. Outcomes assessed in this review and meta-analysis included fasting blood glucose, fasting plasma insulin, homeostasis model assessment for IR, glucose to insulin ratio. Mean differences, odds ratios with 95% confidence interval were pooled using the fixed or random effect models. Sensitivity analyses were performed to validate the robustness of the results. Review Manager version 5.4.1 and Stata version 8.0 were used. RESULTS: A total of nineteen studies involving 4453 individuals were included. Recurrent pregnancy loss patients presented significantly higher fasting blood glucose, fasting plasma insulin, homeostasis model assessment for IR, and lower glucose to insulin ratios. Additionally, recurrent pregnancy loss patients had higher rates of IR as defined by abnormal fasting plasma insulin, homeostasis model assessment for IR, and glucose to insulin ratio. Sensitivity analyses validated the robustness of the results. CONCLUSION: In the current review, we show that recurrent pregnancy loss is associated with a higher degree of IR and highlight the importance of screening and treatment of IR.

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Introduction: Infertility is a worldwide problem. To evaluate the outcome of in vitro fertilization (IVF) treatment for infertility, many indicators need to be considered and the relation among indicators need to be studied. Objectives: To construct an IVF predicting model by a robust decision tree method and find important factors and their interrelation. Methods: IVF and intracytoplasmic sperm injection (ICSI) cycles between January 2010 and December 2020 in a women's hospital were collected. Comprehensive evaluation and examination of patients, specific therapy strategy and the outcome of treatment were recorded. Variables were selected through the significance of 1-way analysis between the clinical pregnant group and the nonpregnant group and then were discretized. Then, gradient boosting decision tree (GBDT) was used to construct the model to compute the score for predicting the rate of clinical pregnancy. Result: Thirty-eight variables with significant difference were selected for binning and thirty of them in which the pregnancy rate varied in different categories were chosen to construct the model. The final score computed by model predicted the clinical pregnancy rate well with the Area Under Curve (AUC) value achieving 0.704 and the consistency reaching 98.1%. Number of two-pronuclear embryo (2PN), age of women, AMH level, number of oocytes retrieved and endometrial thickness were important factors related to IVF outcome. Moreover, some interrelations among factors were found from model, which may assist clinicians in making decisions. Conclusion: This study constructed a model predicting the outcome of IVF cycles through a robust decision tree method and achieved satisfactory prediction performance. Important factors related to IVF outcome and some interrelations among factors were found.

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Polycystic ovary syndrome (PCOS) is a typical reproductive and endocrinological disorder of women at child-bearing age. In this study, we used miRNA sequencing technology and verified miR-let-7d-3p as a vital miRNA in PCOS. RT-qPCR confirmed miR-let-7d-3p was significantly increased in granulosa cells (GCs) of PCOS. Cell counting kit-8 (CCK-8) identified the suppression of miR-let-7d-3p mimic in KGN cell proliferation and PI3K/Akt signaling pathway. Dual luciferase reporter assay proved that Toll-like receptor 4 (TLR4) was a target of miR-let-7d-3p, and TLR4 was significantly down-regulated by miR-let-7d-3p. Furthermore, over-expression of TLR4 promoted KGN cell proliferation and rescued the inhibition of miR-let-7d-3p on KGN cells. In conclusion, miR-let-7d-3p was a crucial miRNA up-regulated in GCs of PCOS, and inhibited cell proliferation by targeting TLR4 gene.

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BACKGROUND: Lymph node metastasis (LNM) is an important prognostic factor in endometrial cancer. Anomalous microRNAs (miRNAs) are associated with cell functions and are becoming a powerful tool to characterize malignant transformation and metastasis. The aim of this study was to construct a miRNA signature to predict LNM in endometrial endometrioid carcinoma (EEC). METHOD: Candidate target miRNAs related to LNM in EEC were screened by three methods including differentially expressed miRNAs (DEmiRs), weighted gene co-expression network analysis (WGCNA), and decision tree algorithms. Samples were randomly divided into the training and validation cohorts. A miRNA signature was built using a logistic regression model and was evaluated by the area under the curve (AUC) of receiver operating characteristic curve (ROC) and decision curve analysis (DCA). We also conducted pathway enrichment analysis and miRNA-gene regulatory network to look for potential genes and pathways engaged in LNM progression. Survival analysis was performed, and the miRNAs were tested whether they expressed differently in another independent GEO database. RESULT: Thirty-one candidate miRNAs were screened and a final 15-miRNA signature was constructed by logistic regression. The model showed good calibration in the training and validation cohorts, with AUC of 0.824 (95% CI, 0.739-0.912) and 0.821 (95% CI, 0.691-0.925), respectively. The DCA demonstrated the miRNA signature was clinically useful. Hub miRNAs in signature seemed to contribute to EEC progression via mitotic cell cycle, cellular protein modification process, and molecular function. MiR-34c was statistically significant in survival that a higher expression of miR-34c indicated a higher survival time. MiR-34c-3p, miR-34c-5p, and miR-34b-5p were expressed differentially in GSE75968. CONCLUSION: The miRNA signature could work as a noninvasive method to detect LNM in EEC with a high prediction accuracy. In addition, miR-34c cluster may be a key biomarker referring LNM in endometrial cancer.

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Objective: To evaluate associations between serum lipid levels and treatment outcomes in women undergoing assisted reproduction. Materials and Methods: The study included 2011 women who underwent in vitro fertilization/intracytoplasmic sperm injection with fresh embryo transfer. Serum lipid evaluation included total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Ovarian stimulation outcomes included endometrial thickness and the number of oocytes retrieved, and reproductive outcomes included live birth, clinical pregnancy, and miscarriage. Results: Higher HDL-C quartiles were associated with more oocytes retrieved. Lower TC (quartile 1 odds ratio [OR] 1.59 [1.21-2.08], quartile 3 OR 1.36 [1.04-1.77]), LDL-C (quartile 1 OR 1.41 [1.07-1.86]), and TG (quartile 2 OR 1.39 [1.06-1.84]) were independently associated with clinical pregnancy after adjusting for potential confounders. Lower LDL-C (quartile 1 OR 2.22 [1.58-3.13], quartile 2 OR 1.78 [1.27-2.50], quartile 3 OR 1.51 [1.07-2.13]), TC (quartile 1 OR 1.39 [1.00-1.93]), TG (quartile 1 OR 1.44 [1.03-2.03], quartile 2 OR 1.46 [1.04-2.04], quartile 3 OR 1.44 [1.04-1.99]), and higher HDL-C (quartile 2 OR 0.71 [0.51-0.99]) were independently associated with live birth. Higher LDL-C (quartile 1 OR 0.44 [0.30-0.66], quartile 2 OR 0.49 [0.33-0.73], quartile 3 OR 0.63 [0.43-0.94]) and lower HDL-C (quartile 1 OR 1.60 [1.07-2.39]) were independently associated with miscarriage. Conclusions: Serum lipid levels were associated with treatment outcomes in women undergoing assisted reproduction.

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Objectives: Unexplained infertility has been one of the indications for utilization of intracytoplasmic sperm injection (ICSI). However, whether ICSI should be preferred to IVF for patients with unexplained infertility remains an open question. This study aims to determine if ICSI improves the clinical outcomes over conventional in vitro fertilization (IVF) in couples with unexplained infertility. Methods: This was a retrospective cohort study of 549 IVF and 241 ICSI cycles for patients with unexplained infertility at a fertility center of a university hospital from January 2016 and December 2018. The live birth rate and clinical pregnancy rate were compared between the two groups. Other outcome measures included the implantation rate, miscarriage rate, and fertilization rate. Results: The live birth rate was 35.2% (172/488) in the IVF group and 33.3% (65/195) in ICSI group, P = 0.635. The two groups also had similar clinical pregnancy rates, implantation rates, and miscarriage rates. The fertilization rate of IVF group was significantly higher than that of ICSI group (53.8 vs. 45.7%, P = 0.000, respectively). Sixty-one and 46 patients did not transfer fresh embryos in IVF and ICSI cycles, respectively. Patients with IVF cycles had lower cancellation rates than those with ICSI (11.1 vs. 19.1%, P = 0.003, respectively). Conclusion: ICSI does not improve live birth rates but yields higher cancellation rates than conventional IVF in the treatment of unexplained infertility.