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Background: Endometrial CD138+ plasma cells serve as a diagnostic biomarker for endometrial inflammation, and their elevated occurrence correlates positively with adverse pregnancy outcomes. Infertility-related conditions like polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) are closely associated with systemic and local chronic inflammatory status, wherein endometrial CD138+ plasma cell accumulation could also contribute to endometrial pathology. Current methods for quantifying CD138+ cells typically involve laborious and time-consuming microscopic assessments of only a few random areas from a slide. These methods have limitations in accurately representing the entire slide and are susceptible to significant biases arising from intra- and interobserver variations. Implementing artificial intelligence (AI) for CD138+ cell identification could enhance the accuracy, reproducibility, and reliability of analysis. Methods: Here, an AI algorithm was developed to identify CD138+ plasma cells within endometrial tissue. The AI model comprised two layers of convolutional neural networks (CNNs). CNN1 was trained to segment epithelium and stroma across 28,363 mm2 (2.56 mm2 of epithelium and 24.87 mm2 of stroma), while CNN2 was trained to distinguish stromal cells based on CD138 staining, encompassing 7345 cells in the object layers (6942 CD138− cells and 403 CD138+ cells). The training and performance of the AI model were validated by three experienced pathologists. We collected 193 endometrial tissues from healthy controls (n = 73), women with PCOS (n = 91), and RIF patients (n = 29) and compared the CD138+ cell percentages based on cycle phases, ovulation status, and endometrial receptivity utilizing the AI model. Results: The AI algorithm consistently and reliably distinguished CD138− and CD138+ cells, with total error rates of 6.32% and 3.23%, respectively. During the training validation, there was a complete agreement between the decisions made by the pathologists and the AI algorithm, while the performance validation demonstrated excellent accuracy between the AI and human evaluation methods (intraclass correlation; 0.76, 95% confidence intervals; 0.36–0.93, p = 0.002) and a positive correlation (Spearman's rank correlation coefficient: 0.79, p

Background: The human endometrium undergoes a monthly cycle of tissue growth and degeneration. During the mid-secretory phase, the endometrium establishes an optimal niche for embryo implantation by regulating cellular composition (e.g., epithelial and stromal cells) and differentiation. Impaired endometrial development observed in conditions such as polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) contributes to infertility. Surprisingly, despite the importance of the endometrial lining properly developing prior to pregnancy, precise measures of endometrial cellular composition in these two infertility-associated conditions are entirely lacking. Additionally, current methods for measuring the epithelial and stromal area have limitations, including intra- and inter-observer variability and efficiency. Methods: We utilized a deep-learning artificial intelligence (AI) model, created on a cloud-based platform and developed in our previous study. The AI model underwent training to segment both areas populated by epithelial and stromal endometrial cells. During the training step, a total of 28.36 mm2 areas were annotated, comprising 2.56 mm2 of epithelium and 24.87 mm2 of stroma. Two experienced pathologists validated the performance of the AI model. 73 endometrial samples from healthy control women were included in the sample set to establish cycle phase-dependent dynamics of the endometrial epithelial-to-stroma ratio from the proliferative (PE) to secretory (SE) phases. In addition, 91 samples from PCOS cases, accounting for the presence or absence of ovulation and representing all menstrual cycle phases, and 29 samples from RIF patients on day 5 after progesterone administration in the hormone replacement treatment cycle were also included and analyzed in terms of cellular composition. Results: Our AI model exhibited reliable and reproducible performance in delineating epithelial and stromal compartments, achieving an accuracy of 92.40% and 99.23%, respectively. Moreover, the performance of the AI model was comparable to the pathologists’ assessment, with F1 scores exceeding 82% for the epithelium and >96% for the stroma. Next, we compared the endometrial epithelial-to-stromal ratio during the menstrual cycle in women with PCOS and in relation to endometrial receptivity status in RIF patients. The ovulatory PCOS endometrium exhibited epithelial cell proportions similar to those of control and healthy women’s samples in every cycle phase, from the PE to the late SE, correlating with progesterone levels (control SE, r2 = 0.64, FDR < 0.001; PCOS SE, r2 = 0.52, FDR < 0.001). The mid-SE endometrium showed the highest epithelial percentage compared to both the early and late SE endometrium in both healthy women and PCOS patients. Anovulatory PCOS cases showed epithelial cellular fractions comparable to those of PCOS cases in the PE (Anovulatory, 14.54%; PCOS PE, 15.56%, p = 1.00). We did not observe significant differences in the epithelial-to-stroma ratio in the hormone-induced endometrium in RIF patients with different receptivity statuses. Conclusion: The AI model rapidly and accurately identifies endometrial histology features by calculating areas occupied by epithelial and stromal cells. The AI model demonstrates changes in epithelial cellular proportions according to the menstrual cycle phase and reveals no changes in epithelial cellular proportions based on PCOS and RIF conditions. In conclusion, the AI model can potentially improve endometrial histology assessment by accelerating the analysis of the cellular composition of the tissue and by ensuring maximal objectivity for research and clinical purposes.

Abstract Hyperandrogenic women with PCOS show disrupted decidualization (DE) and placentation. Dihydrotestosterone (DHT) is reported to enhance DE in non-PCOS endometrial stromal cells (eSCCtrl); however, this has not been assessed in PCOS cells (eSCPCOS). Therefore, we studied the transcriptome profile of non-decidualized (non-DE) and DE eSCs from women with PCOS and Ctrl in response to short-term estradiol (E2) and/or progesterone (P4) exposure with/without (±) DHT. The non-DE eSCs were subjected to E2 ± DHT treatment, whereas the DE (0.5 mM 8-Br-cAMP, 96 h) eSCs were post-treated with E2 and P4 ± DHT, and RNA-sequenced. Validation was performed by immunofluorescence and immunohistochemistry. The results showed that, regardless of treatment, the PCOS and Ctrl samples clustered separately. The comparison of DE vs. non-DE eSCPCOS without DHT revealed PCOS-specific differentially expressed genes (DEGs) involved in mitochondrial function and progesterone signaling. When further adding DHT, we detected altered responses for lysophosphatidic acid (LPA), inflammation, and androgen signaling. Overall, the results highlight an underlying defect in decidualized eSCPCOS, present with or without DHT exposure, and possibly linked to the altered pregnancy outcomes. We also report novel factors which elucidate the mechanisms of endometrial dysfunction in PCOS.

Abstract Background Ovarian insufficiency is a major concern for long-term cancer survivors. Although semen freezing is well established to preserve male fertility, the possibilities to secure post-cancer female fertility are mostly limited to oocyte or embryo freezing. These methods require time-consuming ovarian stimulation with or without in vitro fertilization (IVF) that evidently delays cancer therapy. Ovarian tissue cryopreservation and subsequent thawed tissue autotransplantation are considered the most promising alternative strategy for restoring the fertility of oncology patients, which has not yet received the full clinical acceptance. Therefore, all successful cases are needed to prove its reliability and safety. Case presentation Here we report a single case in Estonia, where a 28-year-old woman with malignant breast neoplasm had ovarian cortex cryopreserved before commencing gonadotoxic chemo- and radiotherapy. Two years after cancer therapy, the patient underwent heterotopic ovarian tissue transplantation into the lateral pelvic wall. The folliculogenesis was stimulated in the transplanted tissue by exogenous follicle-stimulating hormone and oocytes were collected under ultrasound guidance for IVF and embryo transfer. The healthy boy was born after full-term gestation in 2014, first in Eastern Europe. Conclusion Despite many countries have reported the first implementation of the ovarian tissue freezing and transplantation protocols, the data is still limited on the effectiveness of heterotopic ovarian transplant techniques. Thus, all case reports of heterotopic ovarian tissue transplantation and long-term follow-ups to describe the children’s health are valuable source of clinical experience.

The maintenance of the pluripotency of human embryonic stem (hES) cells requires special conditions for culturing. These conditions include specific growth factors containing media and extracellular matrix (ECM) or an appropriate substrate for adhesion. Interactions between the cells and ECM are mediated by integrins, which interact with the components of ECM in active conformation. This study focused on the characterisation of the role of integrin β1 in the adhesion, migration and differentiation of hES cells. Blocking integrin β1 abolished the adhesion of hES cells, decreasing their survival and pluripotency. This effect was in part rescued by the inhibition of RhoA signalling with Y-27632. The presence of Y-27632 increased the migration of hES cells and supported their differentiation into embryoid bodies. The differences in integrin β1 recycling in the phosphorylation of the myosin light chain and in the localisation of TSC2 were observed between the hES cells growing as a single-cell culture and in a colony. The hES cells at the centre and borders of the colony were found to have differences in their morphology, migration and signalling network activity. We concluded that the availability of integrin β1 was essential for the contraction, migration and differentiation ability of hES cells.

Targeting of G proteins to the cell cortex and their activation is one of the triggers of both asymmetric and symmetric cell division. Resistance to inhibitors of cholinesterase 8 (RIC8), a guanine nucleotide exchange factor, activates a certain subgroup of G protein α-subunits in a receptor independent manner. RIC8 controls the asymmetric cell division in Caenorhabditis elegans and Drosophila melanogaster, and symmetric cell division in cultured mammalian cells, where it regulates the mitotic spindle orientation. Although intensely studied in mitosis, the function of RIC8 in mammalian meiosis has remained unknown. Here we demonstrate that the expression and subcellular localization of RIC8 changes profoundly during mouse oogenesis. Immunofluorescence studies revealed that RIC8 expression is dependent on oocyte growth and cell cycle phase. During oocyte growth, RIC8 is abundantly present in cytoplasm of oocytes at primordial, primary and secondary preantral follicle stages. Later, upon oocyte maturation RIC8 also populates the germinal vesicle, its localization becomes cell cycle dependent, and it associates with chromatin and the meiotic spindle. After fertilization, RIC8 protein converges to the pronuclei and is also detectable at high levels in the nucleolus precursor bodies of both maternal and paternal pronucleus. During first cleavage of zygote RIC8 localizes in the mitotic spindle and cell cortex of forming blastomeres. In addition, we demonstrate that RIC8 co-localizes with its interaction partners Gαi1/2:GDP and LGN in meiotic/mitotic spindle, cell cortex and polar bodies of maturing oocytes and zygotes. Downregulation of Ric8 by siRNA leads to interferred translocation of Gαi1/2 to cortical region of maturing oocytes and reduction of its levels. RIC8 is also expressed at high level in female reproductive organs e.g. oviduct. Therefore we suggest a regulatory function for RIC8 in mammalian gametogenesis and fertility.

Resistance to inhibitors of cholinesterase 8 (RIC8) is a guanine nucleotide exchange factor required for the intracellular regulation of G protein signalling. RIC8 activates different Gα subunits via non-canonical pathway, thereby amplifying and prolonging the G protein mediated signal. In order to circumvent the embryonic lethality associated with the absence of RIC8A and to study its role in the nervous system, we constructed Ric8a conditional knockout mice using Cre/loxP technology. Introduction of a synapsin I promoter driven Cre transgenic mouse strain (SynCre) into the floxed Ric8a (Ric8a (F/F) ) background ablated RIC8A function in most differentiated neuron populations. Mutant SynCre (+/-) Ric8 (lacZ/F) mice were born at expected Mendelian ratio, but they died in early postnatal age (P4-P6). The mutants exhibited major developmental defects, like growth retardation and muscular weakness, impaired coordination and balance, muscular spasms and abnormal heart beat. Histological analysis revealed that the deficiency of RIC8A in neurons caused skeletal muscle atrophy and heart muscle hypoplasia, in addition, the sinoatrial node was misplaced and its size reduced. However, we did not observe gross morphological changes in brains of SynCre (+/-) Ric8a (lacZ/F) mutants. Our results demonstrate that in mice the activity of RIC8A in neurons is essential for survival and its deficiency causes a severe neuromuscular phenotype.