Polycystic ovary syndrome (PCOS) is a metabolic disorder associated with obesity and energy metabolic system disturbances in adipose tissue. Neuregulin 4 (NRG4), which is secreted by adipose tissue, regulates energy metabolism. In the present study, we aimed to evaluate the association between serum NRG4 levels in obese and normal weight PCOS patients. This cross-sectional study was conducted at a tertiary hospital in Turkey from April to August 2017. We included 148 women who were divided into four groups as follows: 40 normal weight and 39 obese PCOS women diagnosed according to the Rotterdam criteria as well as 38 normal weight and 31 obese, age-matched, non-hyperandrogenemic women with a regular menstrual cycle (controls). Levels of serum NRG4, anti-Müllerian hormone (AMH), fasting blood glucose (FBG), insulin, and high-sensitivity C-reactive protein (hs-CRP); lipid and hormone profiles; insulin resistance indices [homeostasis model assessment of insulin resistance (HOMA-IR)];and anthropometric parameters were evaluated. Serum NRG4 levels were elevated in the normal weight PCOS group than in the control group. Moreover, serum NRG4 levels were higher in the obese PCOS group than in the normal weight PCOS and obese control groups (p < .01). Serum NRG4 levels were positively correlated with body mass index (BMI); waist/hip ratio; HOMA-IR; and levels of triglycerides, hs-CRP, FBG, insulin, AMH, and dehydroepiandrosterone sulphate. Multiple regression analyses revealed that serum NRG4 levels were independently associated with BMI. Obesity appears to be the most influential factor for NRG4 secretion in PCOS patients. Management of obesity may be a key factor for resolving PCOS-related metabolic abnormalities and fertility problems.

This study assesses the efficacy of ChatGPT-4, an advanced artificial intelligence (AI) language model, in delivering precise and comprehensive answers to inquiries regarding managing polycystic ovary syndrome (PCOS)-related infertility. The research team, comprising experienced gynecologists, formulated 460 structured queries encompassing a wide range of common and intricate PCOS scenarios. The queries were: true/false (170), open-ended (165), and multiple-choice (125) and further classified as ‘easy’, ‘moderate’, and ‘hard’. For true/false questions, ChatGPT-4 achieved a flawless accuracy rate of 100% initially and upon reassessment after 30 days. In the open-ended category, there was a noteworthy enhancement in accuracy, with scores increasing from 5.53 ± 0.89 initially to 5.88 ± 0.43 at the 30-day mark (p < 0.001). Completeness scores for open-ended queries also experienced a significant improvement, rising from 2.35 ± 0.58 to 2.92 ± 0.29 (p < 0.001). In the multiple-choice category, although the accuracy score exhibited a minor decline from 5.96 ± 0.44 to 5.92 ± 0.63 after 30 days (p > 0.05). Completeness scores for multiple-choice questions remained consistent, with initial and 30-day means of 2.98 ± 0.18 and 2.97 ± 0.25, respectively (p > 0.05). ChatGPT-4 demonstrated exceptional performance in true/false queries and significantly improved handling of open-ended questions during the 30 days. These findings emphasize the potential of AI, particularly ChatGPT-4, in enhancing decision-making support for healthcare professionals managing PCOS-related infertility.

Male infertility, a multifaceted condition characterized by the inability to achieve pregnancy within a partner after a year of unprotected intercourse, affects approximately 7% of men globally. The etiology of male infertility is diverse, including genetic abnormalities, hormonal imbalances, physical obstructions, and lifestyle factors. This review synthesizes current knowledge on the causes, diagnostic methods, and therapeutic interventions for male infertility, with an emphasis on recent advances in genetic and assisted reproductive technologies (ART). The diagnostic approach to male infertility involves a comprehensive evaluation, including semen analysis, hormonal profiling, genetic testing, and imaging techniques, to identify underlying causes. Management strategies range from lifestyle modifications and pharmacological treatments to surgical interventions and ART, such as in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI). Emerging technologies, including the use of artificial intelligence in semen analysis and the development of novel sperm retrieval techniques, promise to enhance diagnostic accuracy and treatment outcomes. Despite significant progress, challenges remain in improving access to care and addressing ethical considerations in the use of ART. This review highlights the importance of a multidisciplinary approach to the management of male infertility, integrating advances in medical science with considerations of patient well-being and ethical standards. Future research directions include elucidating the genetic basis of idiopathic male infertility, optimizing ART outcomes, and developing personalized treatment strategies. The ultimate goal is to improve the reproductive health and quality of life for affected individuals and couples.

Objective: To compare embryo transfer (ET) technique based on catheter rotation during its withdrawal in cases with unexplained infertility in a prospective, randomized trial (NCT03097042). Methods: Two hundred intracytoplasmic sperm injection (ICSI) patients undergoing ET with cleaving or blastocyst-stage fresh embryos were randomized into 2 groups: cases with (n = 100), and without (n = 100) catheter rotation during its withdrawal. Groups were matched for age and some clinical parameters. A soft catheter was used to transfer a single embryo with catheter rotation during its withdrawal in the study group and without rotation in the control. The use of a stiff catheter or tenaculum was not needed in any case. Groups were compared in terms of cycle characteristics and clinical pregnancy rates. Results: Pregnancy rate was significantly higher in the study group (41 vs. 26%, p = 0.04). Clinical pregnancy rate was also significantly higher in the study group (39 vs. 25%, OR 1.9 [1.1–3.5], p = 0.05). On the other hand, the ongoing pregnancy rate was similar between the 2 groups (33 vs. 23%, p = 0.2). Conclusion: Catheter rotation during its withdrawal may be associated with increased pregnancy and clinical pregnancy rates; however, the difference in ongoing pregnancy rates did not reach statistical significance.

The aim of this study is to evaluate the effects of obesity on clinical outcomes in diminished ovarian reserve (DOR) patients undergoing intracytoplasmic sperm injection cycles. In this retrospective observational cross-sectional study, women admitted to current clinic with DOR undergoing intracytoplasmic sperm injection were divided into 2 groups according to the obesity. Patient age, body mass index, anti-mullerian hormone, baseline follicle stimulating hormone and baseline estradiol levels, antral follicle count, total gonadotropin dose, day of stimulation, number of mature (MII) oocytes, and clinical pregnancy were evaluated. There were no statistically significant differences between groups in terms of age, anti-mullerian hormone, baseline follicle stimulating hormone, baseline estradiol levels, antral follicle count, and clinical pregnancy ( P > .05). Total gonadotropin dose, the days of ovarian stimulation were higher and number of MII oocyte were less in the obese group ( P < .05). Logistic regression analyses also revealed that the days of ovarian stimulation and number of MII oocyte were significant factors in the study group. ROC curve analysis showed obesity is a negatively affecting factor in DOR patients. Obesity causes more gonadotropin dose longer days of stimulation, and less number of MII oocyte. However clinical pregnancy rate is not negatively affected by obesity according to the current study.