Reproductive Biology and Endocrinology最新文献

{"title":"Effect of estradiol supplementation on luteal support following a significant reduction in serum estradiol levels after hCG triggering: a prospective randomized controlled trial","authors":"Na Li, Yu Huang, LiJuan Fan, Zan Shi, He Cai, JuanZi Shi, Hui Wang","doi":"10.1186/s12958-024-01275-x","DOIUrl":"https://doi.org/10.1186/s12958-024-01275-x","url":null,"abstract":"This study aimed to evaluate the impact of adding 4 mg estradiol valerate to progesterone for luteal support on pregnancy rates in IVF cycles following a long protocol with reduced luteal serum estradiol levels post-hCG triggering. The prospective randomized controlled trial was conducted at a public tertiary hospital reproductive center with 241 patients who experienced a significant decrease in serum estrogen levels post-oocyte retrieval. Participants received either a daily 4 mg dose of estradiol valerate in addition to standard progesterone or standard progesterone alone for luteal support. The ongoing pregnancy rate did not show a significant difference between the E2 group and the control group (56.6% vs. 52.2%, with an absolute rate difference (RD) of 4.4%, 95% CI -0.087 to 0.179, P = 0.262). Similarly, the live birth rate, implantation rate, clinical pregnancy rate, early abortion rate, and severe OHSS rate were comparable between the two groups. Notably, the E2 group had no biochemical miscarriages, contrasting significantly with the control group (0.0% vs. 10.7%, RD -10.7%, 95% CI -0.178 to -0.041, P = 0.000). In the blastocyst stage category, the clinical pregnancy rate was notably higher in the E2 group compared to the control group (75.6% vs. 60.8%, RD 14.9%, 95% CI 0.012 to 0.294, P = 0.016). Adding 4 mg estradiol valerate to progesterone for luteal support does not affect the ongoing pregnancy rate in embryo transfer cycles using a long protocol with a significant decrease in serum estradiol levels after hCG triggering. However, it may reduce biochemical miscarriages and positively impact clinical pregnancy rates in blastocyst embryo transfer cycles. ChiCTR1800020342.","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"14 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142198177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing predictive models for egg donation: time to blastocyst hatching and machine learning insights","authors":"Jorge Ten, Leyre Herrero, Ángel Linares, Elisa Álvarez, José Antonio Ortiz, Andrea Bernabeu, Rafael Bernabéu","doi":"10.1186/s12958-024-01285-9","DOIUrl":"https://doi.org/10.1186/s12958-024-01285-9","url":null,"abstract":"Data sciences and artificial intelligence are becoming encouraging tools in assisted reproduction, favored by time-lapse technology incubators. Our objective is to analyze, compare and identify the most predictive machine learning algorithm developed using a known implantation database of embryos transferred in our egg donation program, including morphokinetic and morphological variables, and recognize the most predictive embryo parameters in order to enhance IVF treatments clinical outcomes. Multicenter retrospective cohort study carried out in 378 egg donor recipients who performed a fresh single embryo transfer during 2021. All treatments were performed by Intracytoplasmic Sperm Injection, using fresh or frozen oocytes. The embryos were cultured in Geri® time-lapse incubators until transfer on day 5. The embryonic morphokinetic events of 378 blastocysts with known implantation and live birth were analyzed. Classical statistical analysis (binary logistic regression) and 10 machine learning algorithms were applied including Multi-Layer Perceptron, Support Vector Machines, k-Nearest Neighbor, Cart and C0.5 Classification Trees, Random Forest (RF), AdaBoost Classification Trees, Stochastic Gradient boost, Bagged CART and eXtrem Gradient Boosting. These algorithms were developed and optimized by maximizing the area under the curve. The Random Forest emerged as the most predictive algorithm for implantation (area under the curve, AUC = 0.725, IC 95% [0.6232–0826]). Overall, implantation and miscarriage rates stood at 56.08% and 18.39%, respectively. Overall live birth rate was 41.26%. Significant disparities were observed regarding time to hatching out of the zona pellucida (p = 0.039). The Random Forest algorithm demonstrated good predictive capabilities for live birth (AUC = 0.689, IC 95% [0.5821–0.7921]), but the AdaBoost classification trees proved to be the most predictive model for live birth (AUC = 0.749, IC 95% [0.6522–0.8452]). Other important variables with substantial predictive weight for implantation and live birth were duration of visible pronuclei (DESAPPN-APPN), synchronization of cleavage patterns (T8-T5), duration of compaction (TM-TiCOM), duration of compaction until first sign of cavitation (TiCAV-TM) and time to early compaction (TiCOM). This study highlights Random Forest and AdaBoost as the most effective machine learning models in our Known Implantation and Live Birth Database from our egg donation program. Notably, time to blastocyst hatching out of the zona pellucida emerged as a highly reliable parameter significantly influencing our implantation machine learning predictive models. Processes involving syngamy, genomic imprinting during embryo cleavage, and embryo compaction are also influential and could be crucial for implantation and live birth outcomes.","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"30 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: IVF laboratory management through workflow-based RFID tag witnessing and real-time information entry.","authors":"Man-Xi Jiang, Lei Guo, Sen Li, Xiao-Feng Xiao, Wei Chen, Shao-Qing Chen, Nan-Qiao Chen, Yuan-Yuan Sun, Guang-Li Zhang, Xiao-Hai Zeng, Yan-Mei Xiao, Li-Hua Fan","doi":"10.1186/s12958-024-01286-8","DOIUrl":"10.1186/s12958-024-01286-8","url":null,"abstract":"","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"115"},"PeriodicalIF":4.2,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373212/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142133547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: The thrombospondin-1 receptor CD36 is an important mediator of ovarian angiogenesis and folliculogenesis.","authors":"Kata Osz, Michelle Ross, Jim Petrik","doi":"10.1186/s12958-024-01287-7","DOIUrl":"10.1186/s12958-024-01287-7","url":null,"abstract":"","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"114"},"PeriodicalIF":4.2,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11367902/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142120479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The prediction of semen quality based on lifestyle behaviours by the machine learning based models.","authors":"Aykut Aykaç, Coşkun Kaya, Özer Çelik, Mehmet Erhan Aydın, Mustafa Sungur","doi":"10.1186/s12958-024-01268-w","DOIUrl":"https://doi.org/10.1186/s12958-024-01268-w","url":null,"abstract":"<p><strong>Purpose: </strong>To find the machine learning (ML) method that has the highest accuracy in predicting the semen quality of men based on basic questionnaire data about lifestyle behavior.</p><p><strong>Methods: </strong>The medical records of men whose semen was analyzed for any reason were collected. Those who had data about their lifestyle behaviors were included in the study. All semen analyses of the men included were evaluated according to the WHO 2021 guideline. All semen analyses were categorized as normozoospermia, oligozoospermia, teratozoospermia, and asthenozoospermia. The Extra Trees Classifier, Average (AVG) Blender, Light Gradient Boosting Machine (LGBM) Classifier, eXtreme Gradient Boosting (XGB) Classifier, Logistic Regression, and Random Forest Classifier techniques were used as ML algorithms.</p><p><strong>Results: </strong>Seven hundred thirty-four men who met the inclusion criteria and had data about lifestyle behavior were included in the study. 356 men (48.5%) had abnormal semen results, 204 (27.7%) showed the presence of oligozoospermia, 193 (26.2%) asthenozoospermia, and 265 (36.1%) teratozoospermia according to the WHO 2021. The AVG Blender model had the highest accuracy and AUC for predicting normozoospermia and teratozoospermia. The Extra Trees Classifier and Random Forest Classifier models achieved the best performance for predicting oligozoospermia and asthenozoospermia, respectively.</p><p><strong>Conclusion: </strong>The ML models have the potential to predict semen quality based on lifestyles.</p>","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"112"},"PeriodicalIF":4.2,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11360792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142111378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fance deficiency impaired DNA damage repair of prospermatogonia and altered the repair dynamics of spermatocytes.","authors":"Huan Yin, Zhixian Zhou, Chun Fu","doi":"10.1186/s12958-024-01284-w","DOIUrl":"https://doi.org/10.1186/s12958-024-01284-w","url":null,"abstract":"<p><strong>Background: </strong>Non-obstructive azoospermia (NOA) is the most severe form of male infertility and affects approximately 1% of men worldwide. Fanconi anemia (FA) genes were known for their essential role in DNA repair and growing evidence showed the crucial role of FA pathway in NOA. However, the underlying mechanisms for Fance deficiency lead to a serious deficit and delayed maturation of male germ cells remain unclear.</p><p><strong>Methods: </strong>We used Fance deficiency mouse model for experiments, and collected testes or epididymides from mice at 8 weeks (8W), 17.5 days post coitum (dpc), and postnatal 11 (P11) to P23. The mice referred to three genotypes: wildtype (Fance ^+/+), heterozygous (Fance ^+/-), and homozygous (Fance ^-/-). Hematoxylin and eosin staining, immunofluorescence staining, and surface spread of spermatocytes were performed to explore the mechanisms for NOA of Fance ^-/-mice. Each experiment was conducted with a minimum of three biological replicates and Kruskal-Wallis with Dunn's correction was used for statistical analysis.</p><p><strong>Results: </strong>In the present study, we found that the adult male Fance ^-/- mice exhibited massive germ cell loss in seminiferous tubules and dramatically decreased sperms in epididymides. During the embryonic period, the number of Fance ^-/- prospermatogonia decreased significantly, without impacts on the proliferation (Ki-67, PCNA) and apoptosis (cleaved PARP, cleaved Caspase 3) status. The DNA double-strand breaks (γH2AX) increased at the cellular level of Fance ^-/- prospermatogonia, potentially associated with the increased nonhomologous end joining (53BP1) and decreased homologous recombination (RAD51) activity. Besides, Fance deficiency impeded the progression of meiotic prophase I of spermatocytes. The mechanisms entailed the reduced recruitment of the DNA end resection protein RPA2 at leptotene and recombinases RAD51 and DMC1 at zygotene. It also involved impaired removal of RPA2 at zygotene and FANCD2 foci at pachytene. And the accelerated initial formation of crossover at early pachytene, which is indicated by MLH1.</p><p><strong>Conclusions: </strong>Fance deficiency caused massive male germ cell loss involved in the imbalance of DNA damage repair in prospermatogonia and altered dynamics of proteins in homologous recombination, DNA end resection, and crossover, providing new insights into the etiology and molecular basis of NOA.</p>","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"113"},"PeriodicalIF":4.2,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11360510/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142111362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vaginal and endometrial microbiome dysbiosis associated with adverse embryo transfer outcomes.","authors":"Weijue Su, Chaochao Gong, Haoyue Zhong, Huaqing Yang, Yuyan Chen, Xiaoyuan Wu, Jing Jin, Haitao Xi, Junzhao Zhao","doi":"10.1186/s12958-024-01274-y","DOIUrl":"10.1186/s12958-024-01274-y","url":null,"abstract":"<p><strong>Background: </strong>Assisted reproductive technology (ART) is the most effective method to treat infertility and the pathogenesis of implantation failure after in vitro fertilization-embryo transfer (IVF-ET) is a challenging filed in infertility. Microbes in the female reproductive tract are considered to be associated with gynecological and obstetric diseases. However, its effects on embryo implantation failure are unsured.</p><p><strong>Purpose: </strong>This study aimed to investigate reproductive tract dysbiosis, identify different bacteria in reproductive tract as potential biomarkers of embryo implantation failure and demonstrate the pathogenesis through metabolites analysis.</p><p><strong>Methods: </strong>We compared the data from 16S rRNA gene and metagenome in reproductive tracts through QIIME2 and HUMAnN2 by the times of embryo implantation failure on 239 infertile patients and 17 healthy women.</p><p><strong>Results: </strong>Our study revealed a strong positive correlation between Lactobacillus abundance and embryo implantation success (IS) after IVF-ET. The microbial community composition and structure in reproductive tract showed substantially difference between the embryo implantation failure (IF) and healthy control. Moreover, we established a diagnostic model through receiver operating characteristic (ROC) with 0.913 area under curve (AUC) in IS and multiple implantation failures (MIF), verified its effectiveness with an AUC = 0.784 demonstrating microbial community alterations could efficiently discriminate MIF patients. Metagenome functional analyses of vaginal samples from another independent infertile patients after IVF-ET revealed the L-lysine synthesis pathway enriched in IF patients, along with ascended vaginal pH and decreased Lactobacillus abundance.</p><p><strong>Conclusions: </strong>This study clarifies several independent relationships of bacteria in vagina and endometrial fluid on embryo implantation failure and undoubtedly broadens the understanding about female reproductive health.</p>","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"111"},"PeriodicalIF":4.2,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11351450/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142093699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of ubiquitin-conjugating enzyme in the process of spermatogenesis.","authors":"Peng Lv, Jihong Liu, Xiaming Liu","doi":"10.1186/s12958-024-01282-y","DOIUrl":"10.1186/s12958-024-01282-y","url":null,"abstract":"<p><p>The ubiquitination is crucial for controlling cellular homeostasis and protein modification, in which ubiquitin-conjugating enzyme (E2) acts as the central player in the ubiquitination system. Ubiquitin-conjugating enzymes, which have special domains that catalyse substrates, have sequence discrepancies and modulate various pathophysiological processes in different cells of multiple organisms. E2s take part in the mitosis of primordial germ cells, meiosis of spermatocytes and the formation of mature haploid spermatids to maintain normal male fertility. In this review, we summarize the various types of E2s and their functions during distinct stages of spermatogenesis.</p>","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"110"},"PeriodicalIF":4.2,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11351103/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142093698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Varied cellular abnormalities in thin vs. normal endometrium in recurrent implantation failure by single-cell transcriptomics.","authors":"Xiaoying Fu, Xiaoyan Guo, Han Xu, Yini Li, Bihui Jin, Xirong Zhang, Chongyi Shu, Yuhang Fan, Yiqi Yu, Yuqing Tian, Jiao Tian, Jing Shu","doi":"10.1186/s12958-024-01283-x","DOIUrl":"10.1186/s12958-024-01283-x","url":null,"abstract":"","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"109"},"PeriodicalIF":4.2,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11348642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142081418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uric acid and risk of gestational diabetes mellitus: an observational study and mendelian randomization analysis.","authors":"Nuerbiya Xilifu, Rui Zhang, Yongling Dai, Miyeshaer Maimaiti, Zhangyan Li, Ju Yang, Shufei Zang, Jun Liu","doi":"10.1186/s12958-024-01278-8","DOIUrl":"10.1186/s12958-024-01278-8","url":null,"abstract":"<p><strong>Objective: </strong>Our aim was to explore the relationship between serum uric acid (UA) levels in early pregnancy and the development of gestational diabetes mellitus (GDM), and to further explore whether there is a causal relationship.</p><p><strong>Methods: </strong>684 pregnant women with GDM and 1162 pregnant women without GDM participated in this study. 311 pregnant women with GDM and 311 matched controls were enrolled in a 1:1 case-control study. We used conditional logistic regression to explore the relationship between UA levels and the risk of developing GDM. The causal relationship between the two was examined by two-sample Mendelian randomization (MR) analysis.</p><p><strong>Results: </strong>In the 1:1 matched population, the odds ratio (OR) of developing GDM compared with the extreme tertiles of UA levels was 1.967 (95% confidence interval [CI]: 1.475-2.625; P < 0.001). Restricted cubic spline analyses showed a linear relationship between UA and GDM when UA exceeded 222 µmol/L. GDM and UA levels maintained a statistically significant positive correlation in different stratified regression analyses (P < 0.001). However, no evidence of a causal relationship between uric acid and GDM was found by MR analyses with an OR of 1.06 (95% CI: 0.91-1.25) per unit increase in UA.</p><p><strong>Conclusion: </strong>There is a positive correlation between UA levels in early pregnancy and the subsequent risk of developing GDM. However, no genetic evidence was found to support a cause-effect relationship between UA and GDM.</p>","PeriodicalId":21011,"journal":{"name":"Reproductive Biology and Endocrinology","volume":"22 1","pages":"108"},"PeriodicalIF":4.2,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11348557/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142081419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}