Introduction: Thailand’s assisted reproductive technology (ART) practice has shifted towards a “freeze-all” embryo transfer strategy following regulatory reforms in 2015, but national outcomes in this post-regulation era have not yet been analysed. Aims: To analyse ART treatment trends, efficacy and safety in Thailand from 2017 to 2023 and compare these outcomes with prior Thai registry data and international benchmarks. Methods: We performed a retrospective analysis of 105,354 ART cycles reported in the Thai national ART registry from 2017 to 2023. Cycle volume, the utilisation of fresh versus frozen embryo transfer (FET), clinical pregnancy rate (CPR) per transfer, live birth rate (LBR) per transfer and complications (e.g. ovarian hyperstimulation syndrome, OHSS) were assessed over time. Outcomes were compared with earlier Thai registry phases (2001–2007, 2008–2014) and with the International Committee for Monitoring ART (ICMART) global most recent reports (2017–2021). Results: The number of initiated ART cycles grew from 11,924 in 2017 to 18,189 in 2023. By 2023, 94.7% of embryo transfers were performed as FET. This shift was accompanied by higher efficacy, with a CPR per transfer of 52.0% for FET versus 33.7% for fresh transfers. Thai FET outcomes surpassed international averages (2021 LBR: 36.3% vs. 29.5% globally). The safety profile also improved, as the mean number of embryos transferred declined to 1.34 and the incidence of severe OHSS was 0.4%. Conclusions: From 2017 to 2023, Thailand achieved marked improvements in ART success rates and safety by embracing a freeze-all strategy. These national results surpassed previous domestic benchmarks and compare favourably with global standards, underscoring the maturity of Thailand’s ART practice.
Recurrent spontaneous abortion (RSA) is a multifactorial reproductive disorder characterised by repeated pregnancy loss before foetal viability, and a substantial proportion of cases remain unexplained despite detailed clinical evaluation. Emerging evidence suggests that epigenetic dysregulation contributes to early pregnancy failure by influencing gene expression, immune balance and placental development. SET domain bifurcated histone lysine methyltransferase 1 (SETDB1), a key mediator of histone H3 lysine 9 trimethylation (H3K9me3), has been implicated in transcriptional repression, genome stability and developmental regulation during early embryogenesis and placentation. This narrative review summarises current knowledge on the molecular structure and biological functions of SETDB1, with emphasis on its potential roles in reproductive biology and maternal–foetal immune tolerance. Experimental evidence indicates that SETDB1-dependent silencing of transposable elements, maintenance of imprinting integrity and regulation of lineage-specific gene expression are involved in oocyte maturation, preimplantation development, trophoblast differentiation and placental function. Potential mechanisms linking SETDB1 dysregulation to RSA include endogenous retrovirus activation, inflammatory signalling, impaired trophoblast–decidual interactions and disruption of immune homeostasis at the maternal–foetal interface. However, direct clinical evidence supporting a role for SETDB1 in human RSA remains limited, and most insights are derived from experimental and multi-omic studies. Accordingly, SETDB1 should be considered a biologically plausible epigenetic regulator rather than a confirmed driver of pregnancy loss. While its potential diagnostic or prognostic relevance has been proposed, such applications remain speculative. Further studies integrating clinical and functional data will be necessary to clarify the role of SETDB1 in RSA and its relevance within broader epigenetic frameworks in reproductive medicine.
Testicular Dysgenesis Syndrome (TDS) encompasses a spectrum of male reproductive disorders that originate during fetal development. Among the critical players in testicular morphogenesis, fetal Leydig cells perform essential functions through the secretion of insulin-like 3 (INSL3) and androgens, which act via their respective receptors, RXFP2 and the androgen receptor (AR). While the individual signalling pathways of INSL3–RXFP2 and AR have been extensively studied, emerging evidence points toward a potential transcriptional crosstalk between these axes that influences gubernacular development and testicular descent. This review consolidates current molecular insights into the expression profiles, signalling cascades, and co-regulatory networks governing INSL3 and AR activity in fetal Leydig cells. We further examine how environmental disruptors and genetic or epigenetic alterations may impair this interplay, thereby contributing to the pathogenesis of TDS. Additionally, we evaluate in vivo and in vitro models that elucidate these mechanisms and consider the clinical potential of INSL3–AR interactions as biomarkers or therapeutic targets. A deeper understanding of this transcriptional crosstalk may offer new avenues for early diagnosis and intervention in male reproductive disorders.
Artificial intelligence (AI) in reproductive medicine is shifting from brittle, task-specific models toward versatile foundation models, yet translation into clinical practice remains uneven due to data heterogeneity and domain shift. This review bridges the gap between model metrics and clinical utility by defining an ‘IVF Foundation Model Stack’ and establishing engineering principles for safe deployment. We discuss emerging in vitro fertilization (IVF) AI scenarios from an engineering perspective, proposing a layered architecture spanning data, pretraining, adaptation, deployment and monitoring. Seven core engineering principles are identified, including defining action boundaries prior to prediction, ensuring provenance-first data contracts and implementing privacy-preserving federated learning; these are incorporated into a scenario-specific checklist to guide clinical implementation. IVF is a decision-dense, safety-critical environment, and clinically successful foundation models will be defined not just by scale but also by system design that prioritises provenance, human–AI teaming and continuous lifecycle governance.
Introduction: Endometriosis is a benign, chronic inflammatory condition affecting about 10% of women, particularly of reproductive age. It is characterised by ectopic endometrial glands and stroma, often causing pelvic pain, dysmenorrhoea and infertility. Although its association with infertility is established, the underlying mechanisms remain incompletely understood. Aims: To investigate the contributing factors related to endometriosis, focusing on demographic, metabolic, hormonal, lifestyle and inflammatory parameters, and to assess its association with adverse health outcomes. Methods: A total of 300 women were recruited, comprising 150 diagnosed cases of endometriosis and 150 healthy controls. Data on demographic, anthropometric, physiological, clinical and lifestyle factors were collected using a structured questionnaire. Laboratory investigations assessed biochemical and hormonal profiles. Results: Socio-demographic characteristics were similar between groups, except for significant differences in geographic residence and religious affiliation. Women with endometriosis showed a higher occurrence of impaired glucose metabolism, dyslipidaemia, thyroid dysfunction, psychological stress, menorrhagia, dysmenorrhoea, painful bowel movements during menstruation, polycystic ovary syndrome, parental consanguinity, dyspareunia and distinctive dietary patterns. Physiological variations included shorter menstrual cycles, longer menstruation duration, increased abdominal circumference and elevated body mass index. These findings suggest a multifactorial aetiology involving genetic predisposition, hormonal imbalance, lifestyle influences and inflammatory processes. Conclusion: The findings suggest an association between endometriosis and metabolic, hormonal and immune dysregulation. Biomarkers such as fasting glucose, triglycerides, prolactin and uric acid may support early detection and diagnosis. Combining biochemical and metabolic assessments with advanced molecular diagnostics may enhance individualised risk evaluation and targeted therapeutic strategies.
