Daniel Dufort

Leukocytes at the maternal-fetal interface have critical functions during pregnancy in the prevention of maternal reactivity towards fetal alloantigens, suppression of excess inflammation and promotion of placental angiogenesis. Failed maternal immune adaptations to pregnancy can lead to placental insufficiency and the development of severe reproductive complications. Recent evidence from mouse models has suggested that Nodal, a secreted morphogen of the TGFβ superfamily, is an immunoregulator of pregnancy. The absence of Nodal expression in the female reproductive tract (Nodal ^Δ/Δ ) resulted in the loss of preimplantation regulatory T cells and a 50% implantation failure rate. By mid-gestation, Nodal-deficient pregnancies showed placental dysfunction, fetal loss and intrauterine growth restriction. Therefore, the Nodal ^Δ/Δ model represents a unique system to study immune-mediated reproductive failure. In this study, single-cell RNA-sequencing was used to characterize leukocytes within the mid-gestational decidua and placenta during physiological and pathological Nodal ^Δ/Δ pregnancies. Eleven distinct immune cell clusters were identified, with an emphasis on myeloid populations (macrophages and neutrophils). In particular, the transcriptional characterization of placenta-associated maternal macrophages revealed functions consistent with the regulation of angiogenesis, immune suppression and endocytosis. In Nodal ^Δ/Δ females, the differential abundance and expression profile of these leukocytes reflected the immune dysfunction observed in human reproductive pathologies. Taken together, elucidating roles of leukocytes in placental development provides a basis in the understanding of mechanisms associated with physiological pregnancy and reproductive failures.

Background and Objectives: This study aimed at developing an AI-based predictive model for live birth based on a combination of a support vector machine (SVM) using clinical and embryological features, together with a convolutional neural network (CNN) using embryo time-lapse videos. Materials and Methods: This was a retrospective cohort analysis. Two hundred fifty-nine infertile couples treated between January 2012 and December 2019, with a total of 2330 embryos, were included in this study, and clinical data and images from 355 transferred embryos were used to build a predictive model. The main outcome was accuracy of live birth prediction. The secondary outcomes included accuracy in the prediction of biochemical pregnancy, clinical pregnancy and transferrable embryos. Results: The model was able to predict the transferrable embryo (i.e., embryos suitable for transfer or cryopreservation) with an accuracy of 0.98 in an internal set. The accuracy for predicting live birth, clinical pregnancy, and biochemical pregnancy exclusively using clinical data as input for an SVM model was 0.67, 0.68, and 0.67, respectively. With six frames from time-lapse embryo development, the CNN produced an accuracy of 0.57, 0.67, and 0.72. The predictive model performed best when combining input from clinical data and images from multiple embryo developmental frames, obtaining 0.71, 0.73, and 0.77 for predicting live birth, clinical pregnancy, and biochemical pregnancy. Conclusions: This study highlights the potential of combining clinical data and embryo development images to enhance predictive models in reproductive medicine.

The placenta is a vital mediator of maternal–foetal communication, and extracellular vesicles (EVs) derived from placental tissue have gained attention as promising biomarkers of pregnancy health. Accurate molecular profiling of placental EVs is critical for advancing their diagnostic and mechanistic applications. However, how different EV isolation methods influence their composition remains poorly understood. This study directly compared EVs isolated from mouse placental tissue using two common approaches, enzymatic digestion and explant culture, evaluating their structural features, size distribution and proteomic content. Both methods successfully isolated small EVs (sEVs) with canonical markers (CD63, TSG101 and HSC70) and characteristic EV morphology. The digestion method produced a higher yield of larger EVs with a broader size range. Proteomic profiling showed substantial overlap but also revealed method‐specific enrichment. Explant‐derived EVs were enriched in RNA‐binding proteins, translation factors and proteins related to post‐transcriptional regulation and stress responses. In contrast, digestion‐derived EVs were enriched for extracellular matrix (ECM) proteins and ER‐ and mitochondrial‐associated proteins. These EVs also demonstrated stronger enrichment for placental‐specific proteins. Density gradient purification confirmed that canonical EV markers localized to expected fractions. However, the ER protein GRP94 was also present, indicating possible vesicle association, although its intracellular versus extracellular origin remains unclear. Together, our findings show that the tissue dissociation strategy significantly shapes placental EV composition. Enzymatic digestion may improve the recovery of matrix‐embedded EVs, but it increases the likelihood of capturing intracellular components. An explant culture approach yields a more selective EV population, potentially influenced by prolonged ex vivo conditions. These results underscore the importance of aligning EV isolation methods with specific experimental objectives and highlight key considerations for placental EV biomarker discovery and translational applications.

Background: Placental dysfunction is often associated with reproductive complications such as preeclampsia, intrauterine growth restriction (IUGR), and preterm birth. Currently, the early diagnosis and intervention of these pathologies remain challenging due to the invasive nature of placental tissue sampling. Liquid biopsies of extracellular vesicles (EVs) released from the placenta have emerged as a prospective minimally invasive diagnostic strategy that could provide insight into the maternal-fetal interface because of the active role EVs play in mediating placental development and function. However, the lack of information on EVs directly from placenta at disease onset has questioned the representativeness of placental EVs as pathological indicators. To address these concerns, this study assessed the accuracy with which tissue-derived D10.5 placental EVs could identify phenotypes exhibited by a reproductively challenged Nodal conditional knockout mouse model at mid-gestation.Method: Implantation sites from female mice with a uterine-specific knockdown of the Nodal gene were examined from D8.5 to D14.5 utilizing histological analysis, Western blotting, and RT-qPCR to characterize their mid-gestational phenotypes. Placental EVs were then isolated from D10.5 placenta using enzymatic digestion, differential centrifugation, filtration, and size-exclusion chromatography. The final EV fractions were concentrated and validated with size analysis, canonical protein markers, and morphology assessment. Differential expression analysis across the EV samples was performed using proteomics and miRNA-Seq. Functional enrichment analysis of dysregulated EV factors was then completed using several gene ontology databases along with a literature review to determine whether placental EVs could indicate the reproductive abnormalities presented by the mutant mice.Results: Uterine-specific deletion of Nodal resulted in IUGR and fetal loss in mutant dams. Decidualization and placentation defects were observed, including thinner decidual and placental tissues, impaired angiogenesis, and an altered junctional zone within the maternal-fetal interface. Bioinformatics analysis of EV cargo identified 31 differentially expressed proteins and 10 miRNAs specifically linked to placental development, oxidative stress, angiogenesis, and immunomodulation. Notably, 15 of these proteins and six of these miRNAs have been previously associated with pregnancy complications, further supporting the prospects of placental EVs as biomarkers for various placental diseases.Conclusion: These findings suggest that placental EVs can reflect compromised placental function and could serve as pathological indicators for the early detection of pregnancy complications. Their potential diagnostic utility could improve maternal and neonatal health outcomes by enabling earlier intervention and monitoring of high-risk pregnancies.

Background/Objectives: Intrauterine insemination (IUI) is a common first-line approach in the treatment of numerous infertile couples, especially in cases of unexplained infertility. Its relatively low success rate, however, could benefit from the development of AI-based support tools to predict its outcome, thus helping the clinical management of patients undergoing IUI cycles. Our objective was to develop a robust and accurate machine learning model that predicts pregnancy outcomes following IUI. Methods: A retrospective, observational, and single-center study was conducted. In total, 3535 couples (aged 18–43 years) that underwent IUI between January 2011 and December 2015 were recruited. Twenty-one clinical and laboratory parameters of 9501 IUI cycles were used to train different machine learning algorithms. Accuracy of pregnancy outcome was evaluated by an area under the curve (AUC) analysis. Results: The linear SVM outperformed AdaBoost, Kernel SVM, Random Forest, Extreme Forest, Bagging, and Voting classifiers. Pre-wash sperm concentration, the ovarian stimulation protocol, cycle length, and maternal age were strong predictors of a positive pregnancy test following IUI (AUC = 0.78). Paternal age was found to be the worst predictor. Conclusions: Our Linear SVM model predicts a positive pregnancy outcome following IUI. Although this model shows value for the clinical management of infertile patients and informed decision-making by the patients, further validation using independent datasets is required prior to clinical implementation.

Introduction: Proper placentation is essential for fetal growth and development in mammals. Nodal signaling is essential to ensure proper embryo development and requires Cripto-1 as a co-receptor. Both factors have been shown to be expressed in the maternal decidua and developing placenta. Notably, a maternal loss of either Nodal or Cripto-1 leads to defective placentation resulting in intrauterine growth restriction and fetal loss. However, the role of Nodal or Cripto-1 in placental development has not been determined.Methods: To better understand the roles of Nodal and Cripto-1 in trophoblast populations, we employed a trophoblast-specific deletion model using Tat-Cre recombinant protein to induce deletion of the floxed Nodal or Cripto-1 genes exclusively in the trophectoderm at the blastocyst stage (TE-KO). Treated embryos were then transferred into the uteri of pseudopregnant mice, and implantation sites were examined at gestational days (d) 8.5 and 10.5. Placental morphology and trophoblast populations were analyzed through histological and molecular marker analysis.Results: TE-KO of Nodal led to a decrease in the implantation site size and placental thickness, primarily due to a smaller labyrinth area while the junctional zone was increased. Immunostaining revealed an important expansion of PL⁺ trophoblast giant cells and decrease of TPBPA⁺ spongiotrophoblast/glycogen cells. TE-KO of Cripto-1 also led to smaller implantation sites and reduced placental thickness, but this was attributed to a smaller junctional zone. A decrease in TPBPA⁺ spongiotrophoblast cells without affecting Pcdh12⁺ glycogen cells was observed. A reduction in MCT1⁺ and Gcm1⁺ syncytiotrophoblasts and an increase in total area of maternal blood sinuses within the labyrinth emphasized its disorganization. Earlier effects of Cripto-1 TE-KO on the trophoblast maintenance were witnessed at d8.5, with a marked reduction in TPBPA⁺ cells, reduced trophoblast cell proliferation (PCNA⁺) and increased apoptosis (TUNEL⁺).Discussion: The distinct phenotypes observed indicate the different roles Nodal and Cripto-1 play in placental development. This highlights the importance of other TGF-β-dependent and independent pathways involving Cripto-1. Overall, our findings highlight the critical role of Nodal and Cripto-1 in regulating key aspects of placental development, including trophoblast differentiation, cellular specification, and structural organization, promising avenues for future research in placental biology.

Pregnancy success is dependent on the establishment of maternal tolerance during the preimplantation period. The immunosuppressive function of regulatory T cells is critical to limit inflammation arising from implantation of the semi-allogeneic blastocyst. Insufficient maternal immune adaptations to pregnancy have been frequently associated with cases of female infertility and recurrent implantation failure. The role of Nodal, a secreted morphogen of the TGFβ superfamily, was recently implicated during murine pregnancy as its conditional deletion (Nodal^Δ/Δ) in the female reproductive tract resulted in severe subfertility. Here, it was determined that despite normal preimplantation processes and healthy, viable embryos, Nodal^Δ/Δ females had a 50% implantation failure rate compared to Nodal^loxP/loxP controls. Prior to implantation, the expression of inflammatory cytokines MCP-1, G-CSF, IFN-γ and IL-10 was dysregulated in the Nodal^Δ/Δ uterus. Further analysis of the preimplantation leukocyte populations in Nodal^Δ/Δ uteri showed an overabundance of infiltrating, pro-inflammatory CD11b^high Ly6C⁺ macrophages coupled with the absence of CD4⁺ FOXP3⁺ regulatory T cells. Therefore, it is proposed that uterine Nodal expression during the preimplantation period has a novel role in the establishment of maternal immunotolerance, and its dysregulation should be considered as a potential contributor to cases of female infertility and recurrent implantation failure.

Adhesion of the implanting blastocyst involves the interaction between integrin proteins expressed by trophoblast cells and components present in the basement membrane of the endometrial luminal epithelium. Although several factors regulating integrins and their adhesion to fibronectin are already known, we showed that Wnt signaling is involved in the regulation of blastocyst adhesion through the trafficking of integrins expressed by trophoblast cells. Localization of Itgα5β1 by immunofluorescence and FN-binding assays were conducted on peri-implantation blastocysts treated with either Wnt5a or Wnt7a proteins. Both Wnt5a and Wnt7a induced a translocation of Itgα5β1 at the surface of the blastocyst and an increase in FN-binding activity. We further demonstrated that uterine fluid is capable of inducing integrin translocation and this activity can be specifically inhibited by the Wnt inhibitor sFRP2. To identify the Wnt signaling pathway involved in this activity, blastocysts were incubated with inhibitors of either p38MAPK, PI3K pathway or CamKII prior to the addition of Wnts. Whereas inhibition of p38MAPK and PI3K had not effect, inhibition of CamKII reduced FN-binding activity induced by Wnts. Finally, we demonstrated that inhibition of Wnts by sFRP2 reduced the binding efficiency of the blastocyst to uterine epithelial cells. Our findings provide new insight into the mechanism that regulates integrin trafficking and FN-binding activity and identifies Wnts as a key player in blastocyst attachment to the uterine epithelium.