Chronic inflammation is increasingly recognized as a critical factor in female reproductive health; influencing natural conception and the outcomes of assisted reproductive technologies such as in vitro fertilization (IVF). An essential component of innate immunity, the NLR family pyrin domain-containing 3 (NLRP3) inflammasome is one of the major mediators of inflammatory responses, and its activation is closely linked to oxidative stress. This interaction contributes to a decline in oocyte quality, reduced fertilization potential, and impaired embryo development. In the ovarian milieu, oxidative stress and NLRP3 inflammasome activation interact intricately, and their combined effects on oocyte competence and reproductive outcomes are significant. The aims of this review are to examine these molecular mechanisms and to explore therapeutic strategies targeting oxidative stress and NLRP3 inflammasome activity, with the goal of enhancing female fertility and improving clinical outcomes in reproductive health.

Immunological factors have gained growing recognition as key contributors to recurrent pregnancy loss (RPL) after in vitro fertilization (IVF), representing a major challenge in reproductive medicine. RPL affects approximately 1–2% of women trying to conceive naturally and up to 10–15% of those undergoing IVF, where overall success rates remain around 30–40% per cycle. An imbalance in maternal immunological tolerance toward the semi-allogeneic fetus during pregnancy may lead to miscarriage and implantation failure. IVF-related ovarian stimulation and embryo modification offer additional immunological complications that can exacerbate existing immune dysregulation. Recent advances in reproductive immunology have significantly deepened our understanding of the immune mechanisms underlying RPL following IVF, particularly highlighting the roles of regulatory T cells (T regs), natural killer cells, cytokine dysregulation, and disruptions in maternal–fetal immune tolerance. In order to better customize therapies, this evaluation incorporates recently discovered immunological biomarkers and groups patients according to unique immune profiles. Beyond conventional treatments like intralipid therapy and intravenous immunoglobulin, it also examines new immunomodulatory medications that target certain immune pathways, such as precision immunotherapies and novel cytokine modulators. We also discuss the debates over immunological diagnostics and therapies, such as intralipid therapy, intravenous immunoglobulin, corticosteroids, and anticoagulants. The heterogeneity of patient immune profiles combined with a lack of strong evidence highlights the imperative for precision medicine to improve therapeutic consistency. Novel indicators for tailored immunotherapy and emerging treatments that target particular immune pathways have encouraging opportunities to increase pregnancy success rates. Improving management approaches requires that future research prioritize large-scale clinical trials and the development of standardized immunological assessments. This review addresses the immunological factors in RPL during IVF, emphasizing underlying mechanisms, ongoing controversies, and novel therapeutic approaches to inform researchers and clinicians.

Background: The widespread use of the human papillomavirus (HPV) vaccine and the rise in digital technologies like artificial intelligence (AI) are causing significant changes in the paradigms surrounding cervical cancer screening. Objective: This review addresses potential future paths toward risk-based, customized screening and prevention while summarizing the available data on how vaccination and digital innovation are changing cervical cancer screening methods. Results: A shift from cytology-based screening to HPV-based primary testing with longer intervals has been supported by the notable decrease in high-grade cervical lesions brought about by HPV vaccination. However, AI and digital health tools, such as digital colposcopy, automated cytology, telemedicine, and self-sampling, have the potential to increase diagnostic access, accuracy, and efficiency, especially in low-resource environments. Implementation hurdles, data security, and algorithmic bias are major obstacles. Conclusions: Digital platforms, molecular diagnostics, and vaccination histories must all be incorporated into screening methods in order to keep up with the decline in HPV-related illness. The elimination of cervical cancer could be accelerated and equality and efficiency increased with customized, risk-based algorithms.

Conventional semen analysis frequently fails to identify the underlying pathophysiology of male infertility, which is a complicated clinical disease, especially in cases of idiopathic infertility. A growing body of research indicates that inflammation and oxidative stress (OS) are important and related factors in male reproductive failure. Excessive reactive oxygen species (ROS) promote lipid peroxidation, protein oxidation, mitochondrial dysfunction, and sperm DNA fragmentation, thereby compromising motility, morphology, and fertilizing capacity. Concurrently, pro-inflammatory mediators like interleukin-6 (IL-6), interleukin-8 (IL-8), and tumor necrosis factor-alpha (TNF-α) are frequently found in the seminal plasma of infertile men and are linked to poor semen parameters and testicular dysfunction. It is crucial that oxidative and inflammatory pathways work together to create a self-sustaining pathophysiological cycle that exacerbates sperm damage and destabilizes the reproductive milieu. The diagnostic significance, clinical suitability, and limitations of oxidative stress and inflammation biomarkers, such as malondialdehyde (MDA), 8-hydroxy-2′-deoxyguanosine (8-OHdG), total antioxidant capacity (TAC), and specific inflammatory markers, are critically assessed in this comprehensive review. The lack of established diagnostic thresholds, methodological variation, and translational issues that still restrict their widespread clinical implementation are highlighted in particular. Additionally, the potential contribution of biomarker-guided approaches to focused therapy decisions and individualized patient management is explored. This study examines how oxidative and inflammatory markers may complement conventional male infertility assessments by supporting more precise, mechanism-based approaches in reproductive medicine, while addressing diagnostic readiness and translational limitations.

Background: Despite significant advances in genetics, immunology, and endometrial research, the underlying cause of nearly half of recurrent pregnancy loss (RPL) cases remains unknown. This highlights the limitations of conventional diagnostic approaches and underscores the need for methods that can detect complex, subtle biological patterns. Objectives: To summarize and critically assess how artificial intelligence (AI) is changing our knowledge of, ability to predict, and future therapeutic management of RPL, with a focus on machine learning (ML) approaches that identify latent biological pathways and multifactorial contributors to pregnancy loss. Methods: This narrative review summarizes contemporary research on AI applications in reproductive medicine. Research using imaging, proteomic, genomic, clinical, and multi-omics information to create predictive or mechanistic models associated with RPL provided evidence. Results: AI-based approaches are increasingly demonstrating the ability to detect complex interactions among environmental, immunological, biochemical, and genetic factors associated with RPL. ML and deep learning (DL) models enhance prognostic accuracy, identify novel candidate biomarkers, and provide insights into the systemic and molecular mechanisms underlying pregnancy loss. Integrating heterogeneous data through AI supports the development of personalized reproductive profiles and can improve prediction and counseling. Conclusions: AI has the potential to improve both personalized prediction and mechanistic understanding of RPL. However, clinical translation is currently hampered by a number of important issues, including small and diverse datasets, conflicting diagnostic definitions, limited external validation, and a lack of prospective clinical trials. To responsibly integrate AI tools into reproductive care, these limitations must be addressed.

Vascular endothelial growth factor (VEGF) plays a crucial role in angiogenesis and placental development, which are vital for a healthy pregnancy. Preeclampsia (PE), a hypertension condition that can cause major difficulties for both the mother and the fetus, has been linked to VEGF gene polymorphisms in several studies. PE susceptibility has been associated with several VEGF polymorphisms, including VEGF −2578C/A, −634G/C, +936C/T, and +405G/C, with differing outcomes in various ethnicities. Some polymorphisms, like VEGF −2578C/A, are linked to the disease’s progression, whereas others, like VEGF +405G/C, may protect severe PE. The findings are still uncertain, though, with some studies reporting noteworthy outcomes and others finding no correlation. Further complicating our knowledge of VEGF’s role in PE is the possibility that the interaction between maternal and fetal VEGF polymorphisms may affect PE risk. Studies on environmental variables and placental and fetal VEGF gene polymorphisms point to a complicated interaction in influencing the severity and susceptibility of PE. The precise genetic processes behind PE are still unknown, despite the mounting evidence, necessitating additional research to confirm possible biomarkers and treatment targets. In at-risk pregnancies, a better understanding of the connection between VEGF polymorphisms and PE may help with risk assessment and management techniques.