Systems Biology in Reproductive Medicine最新文献

Advancements in next generation sequencing technologies, including 16S rRNA amplicon sequencing, have vastly expanded our understanding of reproductive microbiota and its role in fertility. For example, in humans, the bacterial genus of Lactobacillus is the overwhelmingly dominant commensal bacterium within reproductive tissues and fluids, such as the vagina, and is an indicator of fertility in women. Shifts away from Lactobacillus allow for opportunistic pathogenic bacteria to inhabit the reproductive tract and result in dysbiosis and infertility. The goal of this review is to explore human reproductive microbiota including bacteria that commensally inhabit reproductive tissues and fluids as well as opportunistic pathogenic bacteria that can result in dysbiosis, infertility, and disease. Continued exploration of the microbiome and its association with reproductive health will aid in the development of targeted therapeutic strategies to positively modulate bacteria and improve fertility.

Advancements in the management of male infertility, particularly azoospermia, have significantly improved with the evolution of testicular biopsy techniques. This review explores the clinical applications and outcomes of three primary methods: testicular sperm aspiration (TESA), testicular sperm extraction (TESE), and microdissection TESE (mTESE). TESA remains a practical, minimally invasive solution for obstructive azoospermia, offering high success rates. However, its limited effectiveness in non-obstructive azoospermia (NOA) highlights the need for more refined approaches. mTESE has emerged as the preferred method in NOA cases due to its microsurgical precision, higher sperm retrieval rates, and reduced damage to testicular tissue. Multiple factors influence the success of these procedures, including patient age, testicular volume, hormone levels, and underlying histopathology. The identification of reliable predictive biomarkers such as follicle-stimulating hormone (FSH), inhibin B, anti-Müllerian hormone (AMH), and TEX101 has enhanced patient selection and procedural planning. Additionally, imaging techniques and metabolite profiling are emerging as valuable non-invasive tools for predicting outcomes. The integration of AI and machine learning into clinical practice further supports individualized treatment strategies by improving predictive accuracy and intraoperative decision-making. Despite clinical success, ethical and psychosocial considerations remain central to the comprehensive care of affected individuals. Financial constraints and unequal access to specialized reproductive services also pose challenges. Future efforts should prioritize the development of validated predictive models, the expansion of biomarker research, and the implementation of standardized clinical protocols. A multidisciplinary, patient-centered approach will be essential in optimizing outcomes for men facing infertility due to azoospermia.

Chronic prostatitis (CP) imposes a considerable global disease burden, with notable regional disparities in China and significant associated healthcare costs. Traditional classification systems, particularly type III subtypes, are hindered by high symptom heterogeneity and low treatment response rates. Recent advances in multi-omics approaches have elucidated the molecular mechanisms underlying CP, including genomic and epigenetic regulation, transcriptomic and immune microenvironment interactions, metabolomic and microbiome interplay, as well as proteomic and neural remodeling. Precision diagnostic techniques are evolving, integrating multi-omics biomarkers, imaging, and functional assessments for molecular subtyping and clinical translation. Targeted therapeutic strategies are emerging, focusing on immune microenvironment modulation, neuro-immune cross-intervention, and microbiome modulation. However, challenges in clinical translation remain, including technical bottlenecks in integrating dynamic multi-omics data and limitations of animal models. To address these issues, complementary strategies between real-world evidence and traditional randomized controlled trials are proposed. Looking forward, future directions include the development of AI-driven multimodal high-precision diagnostic systems and innovative combination therapies involving targeted, immunotherapeutic, and neuro-stimulatory approaches.

Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder affecting numerous women of reproductive age, characterized by a variety of clinical and biochemical features. Accurate classification and diagnosis of PCOS remains challenging due to the heterogeneous nature of its manifestations. This study introduces a robust machine learning framework that combines a voting ensemble model with two distinct feature selection techniques, Sequential Forward Selection (SFS) and Boruta, to enhance the accuracy in classifying PCOS. We also utilized Explainable Artificial Intelligence (XAI) techniques, such as Shapley Additive Explanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), Partial Dependence Plot (PDP), AnchorTabular, and Permutation Importance, to interpret the ensemble model. These methods provide essential insights into the significance of key features for predicting PCOS patients. Results show that the proposed ensemble learning model achieved optimal performance with the feature selection technique used. Specifically, the proposed voting ensemble classifier and features picked by SFS had the highest accuracy among all models. This method can help in PCOS diagnosis and support early intervention.

Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this study is to build Machine learning (ML) decision-support models to predict the optimal range of embryo numbers to transfer, using data from infertile couples identified through literature reviews. Binary classification models were developed to classify cases into two groups: those transferring two or fewer embryos and those transferring three or four. Four popular ML algorithms were used, including random forest (RF), logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN), considering seven criteria: the woman's age, sperm origin, the developmental qualities of four potential embryos, infertility duration, assessment of the woman, morphological qualities of the four best embryos on the day of transfer, and number of oocytes extracted. The stratified 3-fold cross-validation results show that the SVM model obtained the highest average accuracy (95.83%) and demonstrated the best overall performance, closely followed by the ANN and LR models with an average accuracy equal to 91.67%. The RF model achieved a slightly lower average accuracy (88.89%), which demonstrated the lowest variability. Testing on a new dataset revealed all models performed well, with ANN and SVM models classified all test set instances correctly, while the RF and LR models achieved 91.68% accuracy. These results highlight the superior generalization and effectiveness of the ANN and SVM models in guiding ART decisions.

In recent years, the incidence of male infertility has increased to approximately 10%, with a continued upward trend. Therefore, understanding the mechanisms underlying male infertility and developing effective treatment strategies have become essential areas of focus. Mitochondria are regulated by a complex quality control system including mitochondrial dynamics, mitophagy and biogenesis, which not only maintains mitochondrial structural and functional integrity, but also supports the stability of testicular tissue and the intracellular environment necessary for male fertility. Several studies have demonstrated that dysfunction in mitochondrial dynamics and mitophagy is closely associated with a decline in male fertility. Disruptions caused by excessive external stimuli or gene mutations can impair these processes, resulting in oxidative damage, apoptosis, inflammation, and ferroptosis. These pathological changes ultimately damage testicular cells and tissues. Consequently, this review will focus on the two key mechanisms: mitochondrial dynamics and mitophagy. Furthermore, mitochondrial biogenesis-responsible for producing new mitochondria and regulating the number of mitochondria-also plays an important role in maintaining male fertility. Related studies have shown that mitochondrial biogenesis dysfunction can trigger a cascade of pathological events that lead to testicular tissue damage. In summary, this review systematically examines the roles of mitochondrial dynamics and mitophagy in regulating male fertility. It provides an in-depth analysis of the pathological mechanisms by which dysfunction in these processes leads to male infertility. Additionally, this review summarizes current therapeutic agents targeting mitochondrial dynamics and mitophagy, aiming to identify potential strategies for the clinical treatment of male infertility.

One of the major advancements in in vitro fertilization (IVF) has been the development of culture media that enhance gamete maturation in vitro and sustain embryo development up to the blastocyst stage. The deep understanding of the mechanisms involved in gametogenesis and the complex sequence of events surrounding nuclear and cytoplasmic maturation has also enabled the development of efficient in vitro maturation (IVM) protocols. This review outlines the major landmarks in the history of in vitro maturation of oocytes, the advantages and importance of its clinical application in human, especially in patients with Polycystic Ovary Syndrome (PCOS), Resistant Ovary Syndrome, high antral follicle count or oncology patients, as well as the safety and efficacy of the technique. IVM has not been shown yet to be as effective as controlled ovarian stimulation in terms of maturation rates, fertilization rates, and clinical outcome, possibly owing to a dysfunctional or asynchronous nuclear/cytoplasmic maturation process. A confusing set of IVM clinical protocols may also have contributed to the slow incorporation of the technology into routine IVF practice. However, recent improvements have led to comparable live birth rates between IVM and IVF, in women with high antral follicle count. The current status of IVM in the Assisted Reproductive Technology (ART) laboratory and its future perspectives, aiming to provide maximum fertility care to patients will be discussed.

Sperm cryopreservation is a critical component of assisted reproductive technologies employed for both livestock breeding and human fertility management. Sperm are the highly specialized motile cells prone to cryodamage during freezing. Moreover, buffalo, pig and sheep sperm are more susceptible to cryoinjury leading to increased semen rejection rates and substantial economic losses due to reduced fertility. Advances in freezing protocols and modulation in composition of semen diluents protect sperm from cryodamage; however, inconsistency and inter-individual variability in semen freezability exist due to multifactorial etiology. The use of molecular technologies, particularly genomics, transcriptomics, proteomics, and metabolomics led to identification of potential biomarkers associated with cryotolerance. These omics-driven insights have not only enlightened our understanding of the molecular basis of cryoinjury but also has the potential in selecting bulls with good semen freezability. A multidisciplinary approach toward the development of targeted strategies such as supplementing extenders with novel cryotolerant biomolecules to mitigate the sperm damage. This review consolidates current knowledge on the molecular and physiological underpinnings of sperm cryodamage offering a holistic perspective that may guide refinement of existing cryopreservation protocols and extenders for improving sperm cryo-survivability in breeding males.

Polycystic ovary syndrome (PCOS) has an endocrine pathophysiology that needs immediate clinical attention for effective mitigation, as a significant portion of the reproductive population is affected globally. Current treatment options for PCOS are symptom-specific, and more extensive research is imperative to meet the therapeutic needs of the disease. Besides in vitro studies, the assessment of novel anti-PCOS drugs can be more effectively carried out through in vivo experimentation, for which the choice of appropriate animal models based on parameters and pathways to be evaluated is crucial. For a good preclinical evaluation, the animal model must ensure disease reproducibility and predictive validity. The present review provides insights into the animal models reported in the literature for PCOS studies and the aspects in which various therapeutics under study can be evaluated using these models. These animal models are also classified based on the mode of induction, duration essential for induction, and species. Besides, mammalian, non-mammalian and transgenic models are also included. This review will provide a detailed analysis to the researchers working in the domain of PCOS to facilitate an easy choice of appropriate animal model for their study and to identify the scope of developing newer animal models for PCOS study.

This review provides a comprehensive overview of the genetic factors underlying male and female infertility. Infertility affects an estimated one in six couples worldwide, with both male and female factors contributing equally to its prevalence. Approximately, 50% of infertility cases are attributed to genetic causes. We explore three main categories of genetic causes: chromosomal abnormalities, monogenic disorders, and syndromic conditions. Chromosomal causes, including numerical and structural aberrations, are discussed with a focus on their impact on gametogenesis and reproductive outcomes. We review key monogenic causes of infertility, highlighting recent discoveries in genes critical for gonadal development, gametogenesis, and hormonal regulation. Syndromic conditions affecting fertility are examined, highlighting their impact on reproductive function. Throughout the review, we address the challenges in identifying genetic mechanisms of infertility, particularly focusing on the intricate processes involved in oogenesis and spermatogenesis. We also discuss how advancements in genetic testing, such as next-generation sequencing (NGS) and genome-wide association studies (GWAS), have significantly enhanced our understanding of idiopathic infertility and promise further insights in the future. We also discuss the clinical implications of genetic diagnoses, including the role of preimplantation genetic testing (PGT) and genetic counseling in reproductive medicine. This review synthesizes current knowledge on the genetic basis of infertility, providing a comprehensive overview of chromosomal, monogenic, and syndromic causes. It aims to offer readers a solid foundation for understanding the complex genetic factors underlying reproductive disorders.