Reproductive Biology and Endocrinology最新文献

Background: Insulin resistance (IR) is known to be prevalent amongst women with polycystic ovarian syndrome (PCOS). Its presence has been linked to chronic anovulation and marked long term complications in women. Hence, identification and treatment of IR in women with PCOS is required to prevent the metabolic and reproductive complications of the disease. The aim of this study is to determine if serum adiponectin could be used as a surrogate marker for insulin resistance among women with PCOS.

Materials and methods: A total number of 148 consenting women with PCOS diagnosed using the Rotterdam criteria were recruited for this study. Fifty-two of these women had insulin resistance were compared with 96 of the women who did not have insulin resistance. The serum Adiponectin levels, fasting blood glucose and fasting insulin levels were assayed in all study participants. Insulin resistance was assessed in all the study participants using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR). Data were analyzed using relevant inferential statistics at 95% confidence interval and p value of < 0.05.

Results: The prevalence of insulin resistance among the study participants was 35.1%. Majority of the women (83.1%) had a high body mass index (BMI). More than half (68.2%) of the participants were in the age range of 21-30years and 76.4% (113) were nulliparous. There was no statistically significant difference in the median adiponectin level among insulin resistant (3.735 ug/ml) and non-insulin resistant participants vs. (3.705 ug/ml) (p = 0.6762). Both univariate and multivariate regression analysis did not show a statistically significant relationship between adiponectin and insulin resistance in PCOS.

Conclusion: The prevalence of insulin resistance in women with PCOS is high and serum adiponectin is not a suitable surrogate marker of insulin resistance in women with PCOS.

Background: Polycystic ovary syndrome (PCOS) is one of the most common reproductive endocrine disorders in females of childbearing age. Various types of ovarian cells work together to maintain normal reproductive function, whose discordance often takes part in the development and progression of PCOS. Understanding the cellular heterogeneity and compositions of ovarian cells would provide insight into PCOS pathogenesis, but are, however, not well understood. Transcriptomic characterization of cells isolated from PCOS cases have been assessed using bulk RNA-seq but cells isolated contain a mixture of many ovarian cell types.

Methods: Here we utilized the reference scRNA-seq data from human adult ovaries to deconvolute and estimate cell proportions and dysfunction of ovarian cells in PCOS, by integrating various granulosa cells(GCs) transcriptomic data.

Results: We successfully defined 22 distinct cell clusters of human ovarian cells. Then after transcriptome integration, we obtained a gene expression matrix with 13,904 genes within 30 samples (15 control vs. 15 PCOS). Subsequent deconvolution analysis revealed decreased proportion of small antral GCs and increased proportion of KRT8^high mural GCs, HTRA1^high cumulus cells in PCOS, especially increased differentiation from small antral GCs to KRT8^high mural GCs. For theca cells, the abundance of internal theca cells (TCs) and external TCs was both increased. Less TCF21^high stroma cells (SCs) and more STAR^high SCs were observed. The proportions of NK cells and monocytes were decreased, and T cells occupied more in PCOS and communicated stronger with inTCs and exTCs. In the end, we predicted the candidate drugs which could be used to correct the proportion of ovarian cells in patients with PCOS.

Conclusions: Taken together, this study provides insights into the molecular alterations and cellular compositions in PCOS ovarian tissue. The findings might contribute to our understanding of PCOS pathophysiology and offer resource for PCOS basic research.

The quandary known as the Intracytoplasmic Sperm Injection (ICSI) paradox is found at the juncture of Assisted Reproductive Technology (ART) and 'andrological ignorance' - a term coined to denote the undervalued treatment and comprehension of male infertility. The prevalent use of ICSI as a solution for severe male infertility, despite its potential to propagate genetically defective sperm, consequently posing a threat to progeny health, illuminates this paradox. We posit that the meteoric rise in Industrial Revolution 4.0 (IR 4.0) and Artificial Intelligence (AI) technologies holds the potential for a transformative shift in addressing male infertility, specifically by mitigating the limitations engendered by 'andrological ignorance.' We advocate for the urgent need to transcend andrological ignorance, envisaging AI as a cornerstone in the precise diagnosis and treatment of the root causes of male infertility. This approach also incorporates the identification of potential genetic defects in descendants, the establishment of knowledge platforms dedicated to male reproductive health, and the optimization of therapeutic outcomes. Our hypothesis suggests that the assimilation of AI could streamline ICSI implementation, leading to an overall enhancement in the realm of male fertility treatments. However, it is essential to conduct further investigations to substantiate the efficacy of AI applications in a clinical setting. This article emphasizes the significance of harnessing AI technologies to optimize patient outcomes in the fast-paced domain of reproductive medicine, thereby fostering the well-being of upcoming generations.

Background: Recurrent implantation failure (RIF) represents a vague clinical condition with an unclear diagnostic challenge that lacks solid scientific underpinning. Although euploid embryos have demonstrated consistent implantation capabilities across various age groups, a unanimous agreement regarding the advantages of preimplantation genetic testing for aneuploidy (PGT-A) in managing RIF is absent. The ongoing discussion about whether chromosomal aneuploidy in embryos significantly contributes to recurrent implantation failure remains unsettled. Despite active discussions in recent times, a universally accepted characterization of recurrent implantation failure remains elusive. We aimed in this study to measure the reproductive performance of vitrified-warmed euploid embryos transferred to the uterus in successive cycles.

Methods: This observational cohort study included women (n = 387) with an anatomically normal uterus who underwent oocyte retrieval for PGT-A treatment with at least one biopsied blastocyst, between January 2017 and December 2021 at a university-affiliated public fertility center. The procedures involved in this study included ICSI, blastocyst culture, trophectoderm biopsy and comprehensive 24-chromosome analysis of preimplantation embryos using Next Generation Sequencing (NGS). Women, who failed a vitrified-warmed euploid embryo transfer, had successive blastocyst transfer cycles (FET) for a total of three using remaining cryopreserved euploid blastocysts from the same oocyte retrieval cycle. The primary endpoints were sustained implantation rate (SIR) and live birth rate (LBR) per vitrified-warmed single euploid embryo. The secondary endpoints were mean euploidy rate (m-ER) per cohort of biopsied blastocysts from each patient, as well as pregnancy and miscarriage rates.

Results: The mean age of the patient population was 33.4 years (95% CI 32.8-33.9). A total of 1,641 embryos derived from the first oocyte retrieval cycle were biopsied and screened. We found no associations between the m-ER and the number of previous failed IVF cycles among different ranges of maternal age at oocyte retrieval (P = 0.45). Pairwise comparisons showed a significant decrease in the sustained implantation rate (44.7% vs. 30%; P = 0.01) and the livebirth rate per single euploid blastocyst (37.1% vs. 25%; P = 0.02) between the 1st and 3rd FET. The cumulative SIR and LBR after up to three successive single embryo transfers were 77.1% and 68.8%, respectively. We found that the live birth rate of the first vitrified-warmed euploid blastocyst transferred decreased significantly with the increasing number of previously failed IVF attempts by categories (45.3% vs. 35.8% vs. 27.6%; P = 0.04). A comparable decrease in sustained implantation rate was also observed but did not reach statistical significance (50% vs. 44.2 vs. 37.9%; P = NS). Using a logistic regression model, we confirmed the p

Biomarker identification could help in deciphering endometriosis pathophysiology in addition to their use in the development of non invasive diagnostic and prognostic approaches, that are essential to greatly improve patient care. Despite extensive efforts, no single potential biomarker or combination has been clinically validated for endometriosis.Many studies have investigated endometriosis-associated biological markers in specific tissues, but an integrative approach across tissues is lacking. The aim of this review is to propose a comprehensive overview of identified biomarkers based on tissue or biological compartment, while taking into account endometriosis phenotypes (superficial, ovarian or deep, or rASRM stages), menstrual cycle phases, treatments and symptoms.We searched PubMed and Embase databases for articles matching the following criteria: 'endometriosis' present in the title and the associated term 'biomarkers' found as Medical Subject Headings (MeSH) terms or in all fields. We restricted to publications in English and on human populations. Relevant articles published between 01 January 2005 (when endometriosis phenotypes start to be described in papers) and 01 September 2022 were critically analysed and discussed.Four hundred forty seven articles on endometriosis biomarkers that included a control group without endometriosis and provided specific information on endometriosis phenotypes are included in this review. Presence of information or adjustment controlling for menstrual cycle phase, symptoms and treatments is highlighted, and the results are further summarized by biological compartment. The 9 biological compartments studied for endometriosis biomarker research are in order of frequency: peripheral blood, eutopic endometrium, peritoneal fluid, ovaries, urine, menstrual blood, saliva, feces and cervical mucus. Adjustments of results on disease phenotypes, cycle phases, treatments and symptoms are present in 70%, 29%, 3% and 6% of selected articles, respectively. A total of 1107 biomarkers were identified in these biological compartments. Of these, 74 were found in several biological compartments by at least two independent research teams and only 4 (TNF-a, MMP-9, TIMP-1 and miR-451) are detected in at least 3 tissues with cohorts of 30 women or more.Integrative analysis is a crucial step to highlight potential pitfalls behind the lack of success in the search for clinically relevant endometriosis biomarkers, and to illuminate the physiopathology of this disease.