Assessment and quantification of ovarian reserve on the basis of machine learning models

Exploration of the mechanism and therapy of ovarian aging by targeting cellular senescence

The ovary is a crucial gonadal organ that supports female reproductive and endocrine functions. Ovarian aging can result in decreased fertility and dysfunction across multiple organs. Research has demonstrated that cellular senescence in various cell types within the ovary can trigger a decline in ovarian function through distinct stress responses, resulting in ovarian aging. This review explores how cellular senescence may contribute to ovarian aging and reproductive failure. Additionally, we discuss the factors that cause ovarian cellular senescence, including the accumulation of advanced glycation end products, oxidative stress, mitochondrial dysfunction, DNA damage, telomere shortening, and exposure to chemotherapy. Furthermore, we discuss senescence in six distinct cell types, including oocytes, granulosa cells, ovarian theca cells, immune cells, ovarian surface epithelium, and ovarian endothelial cells, inside the ovary and explore their contribution to the accelerated ovarian aging. Lastly, we describe potential senotherapeutics for the treatment of ovarian aging and offer novel strategies for ovarian longevity.

Kidney disease and reproductive health

Understanding the relationship between reproductive health and kidney function is important to provide holistic care for people living with kidney disease. Chronic kidney disease (CKD) has negative impacts on both male and female fertility owing to factors including inflammation, hormonal dysregulation, reduced ovarian reserve, reduced sperm quality and sexual dysfunction. However, pregnancy is achievable for most cisgender women with kidney disease, including kidney transplant recipients and patients on dialysis. CKD in pregnancy is associated with health risks to the mother and child, including increased risk of progression of kidney disease, hypertensive complications of pregnancy, and neonatal complications including fetal growth restriction, preterm birth and stillbirth. However, with appropriate pre-pregnancy counselling, fertility assessment and support, health optimization, and evidence-based antenatal care, the majority of patients will achieve a good outcome. Medication safety should be reviewed before and during pregnancy and lactation, weighing the risk of disease flare against potential adverse effects on the offspring. Important areas for further research include the optimal timing of delivery and the short- and long-term cardiovascular and renal impacts of pregnancy in patients with CKD, as well as long-term kidney and cardiovascular outcomes in their offspring.

Relationship of length of the estrous cycle to antral follicle number in crossbred beef heifers

Length of the menstrual cycle was positively associated with antral follicle number in women. If this pattern is consistent in cattle, a value-added benefit to using automated activity monitors to determine estrous status could be the ability to predict antral follicle count (AFC). We, therefore, hypothesized that as inter-estrous interval increased ultrasonographic AFC would be greater in crossbred beef heifers. Over 3 yr, crossbred beef heifers (n = 1,394) were fitted with automated activity monitors for 81 d. From days 42 to 46, heifers were submitted for ultrasonographic examination to determine AFC. From days 60 to 81, heifers were visually observed twice daily for 45 min for signs of behavioral estrus. Heifers that had a behavioral estrus that coincided with a sensor-based estrus and had a previous sensor-based estrus between 15 and 26 d earlier were used for the analysis (n = 850). A combination of regression analyses and correlation analyses were applied to understand the association between data collected by sensors and follicle number determined by ultrasonographic examination. Antral follicle count was analyzed using the GLM procedure of SAS with estrous cycle length (15 to 26 d) as a fixed effect. Estrus was more likely to initiate in the early morning hours and peak activity was greater (P < 0.0001) when estrus initiated between 0200 and 0800 hours then when estrus initiated at other times of the day. Antral follicle count did not differ due to length of the estrous cycle (P = 0.87). Thus, length of the estrous cycle obtained from three-axis accelerometers cannot be used to predict follicle number in crossbred beef heifers; however, machine learning approaches that combine multiple features could be used to integrate parameters of activity with other relevant environmental and management data to quantify AFC and improve reproductive management in beef cows.

Creation of a machine learning-based prognostic prediction model for various subtypes of laryngeal cancer

Depending on the source of the blastophore, there are various subtypes of laryngeal cancer, each with a unique metastatic risk and prognosis. The forecasting of their prognosis is a pressing issue that needs to be resolved. This study comprised 5953 patients with glottic carcinoma and 4465 individuals with non-glottic type (supraglottic and subglottic). Five clinicopathological characteristics of glottic and non-glottic carcinoma were screened using univariate and multivariate regression for CoxPH (Cox proportional hazards); for other models, 10 (glottic) and 11 (non-glottic) clinicopathological characteristics were selected using least absolute shrinkage and selection operator (LASSO) regression analysis, respectively; the corresponding survival models were established; and the best model was evaluated. We discovered that RSF (Random survival forest) was a superior model for both glottic and non-glottic carcinoma, with a projected concordance index (C-index) of 0.687 for glottic and 0.657 for non-glottic, respectively. The integrated Brier score (IBS) of their 1-year, 3-year, and 5-year time points is, respectively, 0.116, 0.182, 0.195 (glottic), and 0.130, 0.215, 0.220 (non-glottic), demonstrating the model's effective correction. We represented significant variables in a Shapley Additive Explanations (SHAP) plot. The two models are then combined to predict the prognosis for two distinct individuals, which has some effectiveness in predicting prognosis. For our investigation, we established separate models for glottic carcinoma and non-glottic carcinoma that were most effective at predicting survival. RSF is used to evaluate both glottic and non-glottic cancer, and it has a considerable impact on patient prognosis and risk factor prediction.

The Relationship Between Serum Anti-Müllerian Hormone and Basal Antral Follicle Count in Infertile Women Under 35 Years: An Assessment of Ovarian Reserve

Introduction Estimating ovarian reserve has been the cornerstone of designing treatment plans for female infertility over the last few years. The most reliable biomarker for assessing female fertility is the antral follicle count (AFC). Also, the anti-müllerian hormone (AMH) is a sensitive test for predicting ovarian reserve and is precisely associated with AFC value. Objective The study aimed to investigate the relationship between serum AFC and AMH levels. Methods This cross-sectional type of observational study included 101 healthy infertile women aged 20-35 years and with low serum AMH. The mean difference in basal AFC among different age groups was evaluated using an independent sample t-test, revealing no significant difference. A multiple regression model was used to assess the association between serum AMH, and other factors related to demographics and other aspects of infertile women with basal AFC. Results The mean age of infertile women in our study was 30.7±3.69, and 29.7% of females had secondary infertility. The highest ovarian reserve was notable among the group 20-25 years, and the lowest follicular volume was observed in the 31 to below 35 years. Multiple regression analyses revealed that serum AFC and AMH had a strong positive association with basal ovarian volume. Additionally, every one-unit surge in AFC and AMH was statistically significant (p<0.05) and concomitant increases with 0.45 cc and 3.98 cc in basal ovarian volume, respectively. Conclusion The AMH and AFC strongly associate with basal ovarian volume, which declines as age progresses.

Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review

Artificial intelligence (AI) plays a more and more important role in our everyday life due to the advantages that it brings when used, such as 24/7 availability, a very low percentage of errors, ability to provide real time insights, or performing a fast analysis. AI is increasingly being used in clinical medical and dental healthcare analyses, with valuable applications, which include disease diagnosis, risk assessment, treatment planning, and drug discovery. This paper presents a narrative literature review of AI use in healthcare from a multi-disciplinary perspective, specifically in the cardiology, allergology, endocrinology, and dental fields. The paper highlights data from recent research and development efforts in AI for healthcare, as well as challenges and limitations associated with AI implementation, such as data privacy and security considerations, along with ethical and legal concerns. The regulation of responsible design, development, and use of AI in healthcare is still in early stages due to the rapid evolution of the field. However, it is our duty to carefully consider the ethical implications of implementing AI and to respond appropriately. With the potential to reshape healthcare delivery and enhance patient outcomes, AI systems continue to reveal their capabilities.