Search Results (46)

Introduction: Fertility is fundamental to human well-being, significantly impacting both individual lives and societal development. In particular, sperm morphology—referring to the shape, size, and structural integrity of sperm cells—is a key indicator in diagnosing male infertility and selecting viable sperm in assisted reproductive technologies such as in vitro fertilisation (IVF) and intracytoplasmic sperm injection (ICSI). However, traditional manual evaluation methods are highly subjective and inconsistent, creating a need for standardized, automated systems. Objectives: This study aims to develop a robust and fully automated sperm morphology classification framework capable of accurately identifying a wide range of morphological abnormalities, thereby minimizing observer variability and improving diagnostic support in reproductive healthcare. Methods: We propose a novel ensemble-based classification approach that combines convolutional neural network (CNN)-derived features using both feature-level and decision-level fusion techniques. Features extracted from multiple EfficientNetV2 variants are fused and classified using Support Vector Machines (SVM), Random Forest (RF), and Multi-Layer Perceptron with Attention (MLP-Attention). Decision-level fusion is achieved via soft voting to enhance robustness and accuracy. Results: The proposed ensemble framework was evaluated using the Hi-LabSpermMorpho dataset, which contains 18 distinct sperm morphology classes. The fusion-based model achieved an accuracy of 67.70%, significantly outperforming individual classifiers. The integration of multiple CNN architectures and ensemble techniques effectively mitigated class imbalance and enhanced the generalizability of the model. Conclusions: The presented methodology demonstrates a substantial improvement over traditional and single-model approaches in automated sperm morphology classification. By leveraging ensemble learning and multi-level fusion, the model provides a reliable and scalable solution for clinical decision-making in male fertility assessment. Full article

The study of the microbiome has rapidly progressed over the past few decades, capturing the interest of both scientists and the general public. Nevertheless, there is still no widely agreed-upon definition for the term “microbiome” despite tremendous advances in our knowledge. The international scientific literature consistently underscores the difference between the human microbiome and human microbiota. Recent research has emphasized the importance of the female reproductive tract microbiome in fertility, impacting natural conception and assisted reproductive technologies (ARTs). This review explores the relationship between infertility and the microbiota of the female reproductive tract through a thorough evaluation of research papers and large-scale studies published up to 2024. The objective of this review is to critically assess current evidence on the role of the reproductive tract microbiome in female infertility and ART outcomes. Relevant papers were identified and analyzed through the electronic medical databases PubMed/MEDLINE and Scopus. A comprehensive synthesis of data from 36 original studies was performed, including observational, case–control, cohort, and randomized trials. By focusing on the vagina, cervix, and endometrium, this study offers a comprehensive overview of the microbiome throughout the female reproductive tract. RIF and poor reproductive outcomes are strongly linked to dysbiosis, which is characterized by a reduction in Lactobacillus species. Lactobacillus crispatus, in particular, plays a significant role in protecting against bacterial vaginosis and infertility. A thorough understanding of how the microbiome impacts fertility and the development of clinical strategies to improve reproductive outcomes requires standardized microbiome investigation techniques and larger, randomized trials that account for diverse patient characteristics. Full article

Advances in artificial intelligence (AI) are transforming assisted reproductive technologies by significantly enhancing fertility diagnostics. This review focuses on integrating AI with Computer-Aided Sperm Analysis (CASA) systems to improve assessments of sperm motility, morphology, and DNA integrity. By employing a spectrum of techniques, from classic machine learning (ML), often valued for its interpretability and efficiency with structured data, to deep learning (DL), which excels at extracting intricate features directly from image and video data, the field now achieves more accurate, automated, and high-throughput evaluations. These advanced systems offer significant advantages, including enhanced objectivity, improved consistency over manual methods, and the ability to detect subtle predictive patterns not discernible by human observation. The emergence of extensive open datasets and big data analytics has enabled the development of more robust models. However, limitations persist, such as the dependency on large, high-quality annotated datasets for training DL models, potential challenges in model generalizability across diverse clinical settings, and the “black-box” nature of some complex algorithms, alongside crucial needs for rigorous clinical validation, data standardization, and ethical management of sensitive information. Despite promising progress, these challenges must be addressed. Overall, this review outlines current innovations and future research directions essential for advancing personalized, efficient, and accessible fertility care. Full article

Male fertility is strongly influenced by environmental exposures, lifestyle, and advancing age. While advanced paternal age (APA) has been linked with a progressive decline in male fertility, poor reproductive outcomes, and decreased offspring health, the molecular mechanisms underlying these alterations remain unclear. In this work, we investigated the impact of men’s age on human sperm protein expression and phosphorylation to identify molecular alterations possibly responsible for the age-associated decline in male fertility. Semen samples from volunteers attending fertility consultations at the Hospital of Aveiro were collected, analyzed according to WHO’s guidelines, and processed by the density gradient technique. The proteome and phosphoproteome of 19 normozoospermic human sperm samples divided into four age groups were evaluated by mass spectrometry: ≤30 years old; 31–35 years old; 36–40 years old; and >40 years old. Proteomic analysis revealed 46 differentially expressed proteins (DEPs) between groups, some of them associated with infertility-related phenotypes. Gene ontology (GO) analysis, performed using the DAVID database, revealed that DEPs in older men were enriched in pathways related to stress response, metabolism, and embryo implantation. Additionally, 94 differentially phosphorylated sites corresponding to 76 differentially expressed phosphorylated proteins between the groups were identified, related to key reproductive processes such as sperm motility, spermatogenesis, and sperm binding to zona pellucida, and involved in metabolic and stress response pathways, like HSF1 activation. The set of proteins and phosphorylated residues altered in the sperm fraction usually used in assisted reproductive technology (ART) highlights the need to consider the age of the male partner during fertility assessment and treatment planning. These markers can also be used to explain cases of idiopathic infertility, failure in ART, or repeated abortion associated with APA, overcoming the subjectivity of the conventional semen analysis. Full article

This study evaluated the effects of chlorogenic acid (CGA) on human semen and on oxidative stress (OS) induced in vitro in human spermatozoa. After the treatment of the basal semen with 100 µM CGA, rapid and slow sperm progressive motility were evaluated and seminal F₂-Isoprostanes (F₂-IsoPs), a marker of OS, were quantified by ELISA. In a second set of experiments, semen was treated with 100 µM CGA, 1 mM H₂O₂ to induce OS, or H₂O₂+CGA; untreated samples were used as controls. Then, sperm motility, DNA integrity by the acridine orange test, F₂-IsoPs and Nrf2 mRNA expression by RT-PCR were quantified. In CGA-treated specimens, rapid progressive sperm motility was increased (p < 0.01) and F₂-IsoP levels decreased (p < 0.001) versus controls. The increase of F₂-IsoP levels and DNA damage and the decrease of sperm motility after H₂O₂ treatment was reversed in the presence of CGA, which upregulated Nrf2 mRNA expression. These findings contributed to clarifying CGA’s antioxidant activity and highlighted the positive impact of CGA on sperm progressive motility, suggesting also a possible mechanism of action based on the Nrf2 pathway. CGA can be useful during human semen handling procedures in the laboratory and in optimizing the recovery of motile spermatozoa through selection techniques during assisted reproductive technology protocols. Full article

Background: Myo-inositol plays a vital role in human health, functioning as a second messenger of FSH and facilitating the transport of glucose into the cell. Consequently, myo-inositol is regularly utilized in the treatment of polycystic ovary syndrome (PCOS), wherein it acts upon metabolic factors, improving insulin sensitivity and reducing total androgen levels. Patients with PCOS frequently suffer from infertility; thus, the use of myo-inositol has been explored in improving assistive reproductive technique (ART) procedures. This is by no means limited to patients with PCOS, as inositol has found applications in non-PCOS patient groups in addition to in male factor infertility. This joint statement from the Experts Group on Inositol in Basic and Clinical Research and on PCOS (EGOI-PCOS), the Polish Society of Andrology, and the International Scientific Association for the Support and Development of Medical Technologies discusses the latest evidence on this topic, with the aim of interrogating whether myo-inositol could be implemented in everyday ART patient care. Methods: The authors conducted a narrative review performed via an independent literature search between July and August 2024, using the search platforms PubMed, Web of Science, and Google Scholar. Results: In both non-PCOS and PCOS populations seeking IVF care, MI supplementation prior to ovarian stimulation may positively affect gonadotropin use and duration, oocyte and embryo quality, fertilization, and clinical pregnancy rates. Conclusions: This position statement recommends that myo-inositol be considered as a potential pretreatment strategy prior to ovarian hyperstimulation with gonadotropins. Full article

Neurofibromatosis is a genetic disorder arising de novo or with an autosomal dominant transmission that typically presents either at birth or in early childhood, manifesting through distinctive clinical features such as multiple café-au-lait spots, benign tumors in the skin, bone enlargement, and deformities. This literature review aims to resume the spectrum of maternal and fetal complications encountered in pregnant women with neurofibromatosis type 1 (NF1). Thorough research was conducted on databases such as Web of Science, PubMed, Science Direct, Google Scholar, and Wiley Online Library. This review includes 48 case reports, original studies, and reviews on NF1 in pregnancy. The research on the interlink between NF1 and fertility and its influence on human-assisted reproduction techniques is limited. Preimplantation testing (by in vitro fertilization) and prenatal diagnosis (by chorionic villus sampling or amniocentesis) are available to detect affected fetuses. However, genotype–phenotype correlation is difficult to predict. Preconceptional planning and targeted investigations are crucial in understanding the extent of maternal disease. Although in some cases lesions can evolve rapidly during pregnancy, most pregnancies and births in NF1 go well with careful planning. There is a higher incidence of pheochromocytomas and pre-eclampsia, vascular rupture, and cardio-respiratory issues. Anesthesia at birth is a challenge in most cases, and before offering spinal anesthesia, imaging tests should be performed to characterize spinal lesions. General anesthesia may also be challenging when the disease affects the face, neck, upper spine, or airways. Birth-related difficulties may arise because of large neurofibromas located at the level of skin incision or birth canal; uterine atony may be expected if there are uterine lesions. Some complications can develop in postpartum, and affected women should be carefully followed even after pregnancy. Fetal risks include preterm birth (spontaneous or iatrogenic), growth restriction and developmental issues, birth complications, cardiovascular risk, and fetal/neonatal demise. Pregnancies in women with NF1 should be regarded as high-risk and followed in a multidisciplinary fashion. Careful assessment of lesions is of utmost importance before and during pregnancy for anticipating potential maternal risks and before birth to plan anesthesia and delivery. Full article

Infertility affects a significant number of humans. A supported reproduction technology was verified to ease infertility problems. In vitro fertilization (IVF) is one of the best choices, and its success relies on the preference for a higher-quality embryo for transmission. These have been normally completed physically by testing embryos in a microscope. The traditional morphological calculation of embryos shows predictable disadvantages, including effort- and time-consuming and expected risks of bias related to individual estimations completed by specific embryologists. Different computer vision (CV) and artificial intelligence (AI) techniques and devices have been recently applied in fertility hospitals to improve efficacy. AI addresses the imitation of intellectual performance and the capability of technologies to simulate cognitive learning, thinking, and problem-solving typically related to humans. Deep learning (DL) and machine learning (ML) are advanced AI algorithms in various fields and are considered the main algorithms for future human assistant technology. This study presents an Embryo Development and Morphology Using a Computer Vision-Aided Swin Transformer with a Boosted Dipper-Throated Optimization (EDMCV-STBDTO) technique. The EDMCV-STBDTO technique aims to accurately and efficiently detect embryo development, which is critical for improving fertility treatments and advancing developmental biology using medical CV techniques. Primarily, the EDMCV-STBDTO method performs image preprocessing using a bilateral filter (BF) model to remove the noise. Next, the swin transformer method is implemented for the feature extraction technique. The EDMCV-STBDTO model employs the variational autoencoder (VAE) method to classify human embryo development. Finally, the hyperparameter selection of the VAE method is implemented using the boosted dipper-throated optimization (BDTO) technique. The efficiency of the EDMCV-STBDTO method is validated by comprehensive studies using a benchmark dataset. The experimental result shows that the EDMCV-STBDTO method performs better than the recent techniques. Full article

The microbiota plays an important role in numerous physiological processes, pathogenesis, development, and metabolism in different animal species. In humans, several studies have demonstrated an association between the vaginal microbiota and fertility rates, and even success in assisted reproduction techniques. In the context of cattle reproduction, although few studies have addressed the microbiota in a healthy state (which is not associated with diseases that affect the reproductive tract of cows), changes in its composition also seem to influence fertility. This review aims to explain the importance of the reproductive microbiota in female bovines and what is available in the literature regarding its possible role in increasing fertility. What are the challenges involved in this process? Future perspectives on its use and manipulation as a selection or intervention tool. Will it be possible to one day extrapolate the findings to reality and apply them in the field? In short, understanding the role of the reproductive microbiota of female bovines can signal the prospect of increasing production, whether of milk or meat, from the same number of animals, as it can optimize reproductive efficiency and perhaps become an allied tool for the economic profitability and sustainability of livestock farming. Full article

Human sperm parameters serve as a first step in diagnosing male infertility, but not in determining the potential for successful pregnancy during assisted reproductive technologies (ARTs) procedures. Here, we investigated the relationship between sperm head morphology at high magnification, based on strict morphologic criteria, and the nuclear architecture analyzed by fluorescence in situ hybridization (FISH). We included five men. Two of them had an elevated high-magnification morphology score of 6 points (Score 6) indicating high fertility potential, whereas three had a low score of 0 points (Score 0), indicating low fertility potential. We used FISH to study the inter-telomeric distance and the chromosomal territory area of chromosome 1 (Chr. 1). We then compared these two parameters between subjects with high and low scores. FISH data analysis showed that the inter-telomeric distance (ITD) and chromosomal territory area (CTA) of Chr. 1 were significantly higher in subjects with low scores (score 0) than high scores (score 6). Our results suggest that (i) there is a link between nuclear architecture and sperm head abnormalities, particularly vacuoles; and (ii) it is possible to select spermatozoa with normal nuclear architecture, which might indirectly explain the positive ART outcomes observed with this technique. Full article

Infertility has become a common problem in global health, and unsurprisingly, many couples need medical assistance to achieve reproduction. Many human behaviors can lead to infertility, which is none other than unhealthy sperm. The important thing is that assisted reproductive techniques require selecting healthy sperm. Hence, machine learning algorithms are presented as the subject of this research to effectively modernize and make accurate standards and decisions in classifying sperm. In this study, we developed a deep learning fusion architecture called SwinMobile that combines the Shifted Windows Vision Transformer (Swin) and MobileNetV3 into a unified feature space and classifies sperm from impurities in the SVIA Subset-C. Swin Transformer provides long-range feature extraction, while MobileNetV3 is responsible for extracting local features. We also explored incorporating an autoencoder into the architecture for an automatic noise-removing model. Our model was tested on SVIA, HuSHem, and SMIDS. Comparison to the state-of-the-art models was based on F1-score and accuracy. Our deep learning results accurately classified sperm and performed well in direct comparisons with previous approaches despite the datasets’ different characteristics. We compared the model from Xception on the SVIA dataset, the MC-HSH model on the HuSHem dataset, and Ilhan et al.’s model on the SMIDS dataset and the astonishing results given by our model. The proposed model, especially SwinMobile-AE, has strong classification capabilities that enable it to function with high classification results on three different datasets. We propose that our deep learning approach to sperm classification is suitable for modernizing the clinical world. Our work leverages the potential of artificial intelligence technologies to rival humans in terms of accuracy, reliability, and speed of analysis. The SwinMobile-AE method we provide can achieve better results than state-of-the-art, even for three different datasets. Our results were benchmarked by comparisons with three datasets, which included SVIA, HuSHem, and SMIDS, respectively (95.4% vs. 94.9%), (97.6% vs. 95.7%), and (91.7% vs. 90.9%). Thus, the proposed model can realize technological advances in classifying sperm morphology based on the evidential results with three different datasets, each having its characteristics related to data size, number of classes, and color space. Full article

Assisted reproduction techniques have improved considerably in recent decades, but despite these advances, success rates remain relatively low. Endometrial immune profiling involves the analysis of cytokine biomarkers in the endometrium during the mid-luteal phase. This profiling aims to provide insights into the immune environment of the uterus. The aim is to identify immune disturbances and thus guide the development of personalized therapeutic approaches. The first part of the review looks back at the emergence of innovative concepts, highlighting the specificity of the human uterine environment at the time of implantation. Based on this new knowledge, biomarkers have been selected for endometrial immune profiling. The second part details the results of clinical studies conducted over the last ten years. These clinical results suggest that this approach can increase the rate of live births in patients suffering from repeated implantation failures or repeated pregnancy loss. Uterine immune profiling represents a clinical innovation that can significantly improve the performance of medically assisted reproduction treatments through personalized strategies tailored to the local immune profile. Innovation in personalized medicine for assisted reproduction is crucial to improving the success rates of fertility treatments, while reducing the risks and costs associated with ineffective or unnecessary interventions. Full article

Brain abscesses are a possible complication of bacterial sepsis or central nervous system infection but are uncommon in the neonatal period. Gram-negative organisms often cause them, but Serratia marcescens is an unusual cause of sepsis and meningitis in this age group. This pathogen is opportunistic and frequently responsible for nosocomial infections. Despite the existing antibiotics and modern radiological tools, mortality and morbidity remain significant in this group of patients. We report an unusual unilocular brain abscess in a preterm neonate caused by Serratia marcescens. The infection had an intrauterine onset. The pregnancy was achieved through assisted human reproduction techniques. It was a high-risk pregnancy, with pregnancy-induced hypertension, imminent abortion, and required prolonged hospitalization of the pregnant woman with multiple vaginal examinations. The infant was treated with multiple antibiotic cures and percutaneous drainage of the brain abscess associated with local antibiotic treatment. Despite treatment, evolution was unfavorable, complicated by fungal sepsis (Candida parapsilosis) and multiple organ dysfunction syndrome. Full article

Cryopreservation is an expanding strategy to allow not only fertility preservation for individuals who need such procedures because of gonadotoxic treatments, active duty in dangerous occupations or social reasons and gamete donation for couples where conception is denied, but also for animal breeding and preservation of endangered animal species. Despite the improvement in semen cryopreservation techniques and the worldwide expansion of semen banks, damage to spermatozoa and the consequent impairment of its functions still remain unsolved problems, conditioning the choice of the technique in assisted reproduction procedures. Although many studies have attempted to find solutions to limit sperm damage following cryopreservation and identify possible markers of damage susceptibility, active research in this field is still required in order to optimize the process. Here, we review the available evidence regarding structural, molecular and functional damage occurring in cryopreserved human spermatozoa and the possible strategies to prevent it and optimize the procedures. Finally, we review the results on assisted reproduction technique (ARTs) outcomes following the use of cryopreserved spermatozoa. Full article

For decades now, sperm cryopreservation has been a pillar of assisted reproduction in animals as well as humans. Nevertheless, the success of cryopreservation varies across species, seasons, and latitudes and even within the same individual. With the dawn of progressive analytical techniques in the field of genomics, proteomics, and metabolomics, new options for a more accurate semen quality assessment have become available. This review summarizes currently available information on specific molecular characteristics of spermatozoa that could predict their cryotolerance before the freezing process. Understanding the changes in sperm biology as a result of their exposure to low temperatures may contribute to the development and implementation of appropriate measures to assure high post-thaw sperm quality. Furthermore, an early prediction of cryotolerance or cryosensitivity may lead to the establishment of customized protocols interconnecting adequate sperm processing procedures, freezing techniques, and cryosupplements that are most feasible for the individual needs of the ejaculate. Full article