Impact of elevated serum estradiol levels before progesterone administration on pregnancy outcomes in frozen-thawed embryo transfer for hormone replacement therapy.

OBJECTIVE: The objective of this retrospective cohort study is to investigate the impact of monitoring serum estradiol (E2) levels before progesterone administration within hormone replacement therapy (HRT) on pregnancy outcomes in women undergoing frozen-thawed embryo transfer (FET). METHODS: Analyzed HRT-FET cycles conducted at a reproductive center from 2017 to 2022. Serum E2 levels were measured prior to progesterone administration. Multivariate stratified and logistic regression analyses were performed on 26,194 patients grouped according to terciles of serum E2 levels before progesterone administration. RESULTS: The clinical pregnancy rate (CPR) and live birth rate (LBR) exhibited a gradual decline with increasing serum E2 levels across the three E2 groups. Even after controlling for potential confounders, including female age, body mass index, infertility diagnosis, cycle category, number of embryos transferred, fertilization method, indication for infertility, and endometrial thickness, both CPR and LBR persistently showed a gradual decrease as serum E2 levels increased within the three E2 groups. The same results were obtained by multivariate logistic regression analysis. CONCLUSIONS: This large retrospective study indicates that elevated serum E2 levels before progesterone administration during HRT-FET cycles are associated with reduced CPR and LBR post-embryo transfer. Therefore, it is advisable to monitor serum E2 levels and adjust treatment strategies accordingly to maximize patient outcomes.

Total gonadotropin dose did not affect euploid blastocyst rates: an analysis of more than 19,000 oocytes.

BACKGROUND: To evaluate whether increasing total gonadotropin (Gn) dose is associated with changes in euploid blastocyst rate in preimplantation genetic testing (PGT) oocytes. METHODS: This retrospective cohort study was conducted between 2017 and 2022, and 19,246 oocytes were grouped and analyzed based on tri-sectional quantiles of total Gn doses. SETTING: Single reproductive medical center. SUBJECTS: All the patients who underwent PGT cycles, including PGT for aneuploidy, monogenic disorders, and structural rearrangements, were included. EXPOSURE: Next-generation sequencing platforms for chromosomal analysis. MAIN OUTCOME MEASURES: Blastocyst formation and euploid blastocyst rates. RESULTS: In total, 19,246 oocytes and 5375 PGT blastocysts were analyzed. There were significant differences in blastocyst formation and euploid blastocyst rates among the groups classified according to tri-sectional quantiles of total Gn doses. Significant differences in age, body mass index (BMI), proportion of primary infertility, anti-Müllerian hormone (AMH) levels, number of oocytes retrieved, controlled ovarian stimulation (COS) regimen, type of Gn, and PGT category were observed among the three groups. After stratifying the analysis by age, BMI, infertility diagnosis, AMH levels, number of oocytes retrieved, PGT category, type of Gn, and COS regimen, significant differences were only seen in a small number of specific subgroups. Furthermore, the results of the multiple logistic regression analysis showed that the blastocyst formation and euploid blastocyst rates did not significantly increase or decrease with the total Gn dose, whether treated as a continuous variable or divided into three Gn groups as categorical variables. Notably, advancing age was a risk factor for blastocyst formation and euploid blastocyst rates. PGT for structural rearrangements was a risk factor for blastocyst formation and euploid blastocyst rates as compared with PGT for aneuploidy. CONCLUSION: In the total PGT cycles, advancing age, and preimplantation genetic testing for structural rearrangements negatively affected blastocyst formation and euploid blastocyst rates; however, the total Gn dose did not affect blastocyst formation and euploid blastocyst rates.

Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study.

Background: The incidence of depression has been increasing globally, which has brought a serious burden to society. Sinisan Formula (SNSF), a well-known formula of traditional Chinese medicine (TCM), has been found to demonstrate an antidepressant effect. However, the therapeutic mechanism of this formula remains unclear. Thus, the present study aimed to explore the mechanism of SNSF in depression through network pharmacology combined with molecular docking methods. Materials and methods: Bioactive compounds, potential targets of SNSF, and related genes of depression were obtained from public databases. Essential ingredients, potential targets, and signaling pathways were identified using bioinformatics analysis, including protein-protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, Autodock software was further performed for conducting molecular docking to verify the binding ability of active ingredients to targets. Results: A total of 91 active compounds were successfully identified in SNSF with the use of the comprehensive network pharmacology approach, and they were found to be closely connected to 112 depression-related targets, among which CREB1, NOS3, CASP3, TP53, ESR1, and SLC6A4 might be the main potential targets for the treatment of depression. GO analysis revealed 801 biological processes, 123 molecular functions, and 67 cellular components. KEGG pathway enrichment analysis indicated that neuroactive ligand-receptor interaction, serotonergic synapse pathways, dopaminergic synapse pathways, and GABAergic synapse pathways might have played a role in treating depression. Molecular docking suggested that beta-sitosterol, nobiletin, and 7-methoxy-2-methyl isoflavone bound well to the main potential targets. Conclusion: This study comprehensively illuminated the active ingredients, potential targets, primary pharmacological effects, and relevant mechanism of the SNSF in the treatment of depression. SNSF might exert its antidepressant effects by regulating the signaling pathway of 5-hydroxytryptamine, dopamine, GABA, and neuroactive ligand receptor interactions. Still, more pharmacological experiments are needed for verification.