The aim of this study was to evaluate the effect of an electromagnetic field (EMF), generated close to the ovaries, on primordial follicles. A total of 16 rats were used in this study. The study group consisted of rats exposed to an EMF in the abdominal region for 15 min/d for 15 days. Both the study and control group were composed of eight rats. After the treatment period of 15 days, the ovaries of the rats were extracted, and sections of ovarian tissue were taken for histological evaluation. The independent samples t test was used to compare the two groups. In the study group, the means of the right and left ovarian follicle numbers were 34.00 ± 10.20 and 36.00 ± 10.53, respectively. The average total ovarian follicle number was 70.00 ± 19.03. In the control group, the means of the right and left ovarian follicle numbers were 78.50 ± 25.98 and 71.75 ± 29.66, respectively, and the average total ovarian follicle number was 150.25 ± 49.53. The comparisons of the means of the right and left ovarian follicle numbers and the means of the total ovarian follicle numbers between the study and control groups indicated that the study group had significantly fewer follicles (p < 0.001, p = 0.011, and p = 0.002, respectively). This study found a significant decrease in the number of ovarian follicles in rats exposed to an EMF. Further clinical studies are needed to reveal the effects of EMFs on ovarian reserve and infertility.
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http://dx.doi.org/10.1016/j.kjms.2015.03.004 | DOI Listing |
Cureus
December 2024
Department of Obstetrics and Gynecology, Royal Medical Services, Amman, JOR.
Ovarian agenesis (OA) is a rare congenital condition characterized by the absence of one or both ovaries, often associated with chromosomal abnormalities, hormonal imbalances, and structural deformities. The condition is frequently diagnosed in females presenting with primary amenorrhea and delayed sexual development. This case report highlights a unique presentation of bilateral ovarian agenesis in a patient with chromosome X translocation, bone modeling disease, and primary amenorrhea.
View Article and Find Full Text PDFF S Rep
December 2024
Department of Obstetrics and Gynecology, University of South Florida, Morsani College of Medicine, Tampa, Florida.
Objective: To compare pregnancy outcomes after single blastocyst embryo transfer among patients whose first autologous embryo transfer was either a fresh embryo transfer or a frozen embryo transfer (FET) after a freeze-all, in the absence of preimplantation genetic testing for aneuploidy (PGT-A).
Design: A multicenter retrospective cohort analysis.
Setting: National multicenter fertility practice.
Sheng Li Xue Bao
December 2024
School of Exercise and Health, Shenyang Sport University, Shenyang 110102, China.
Fetuin-B (FETUB) is a glycoprotein mainly synthesized and secreted by the liver. It is involved in many physiological and pathological processes including glucose metabolism, inflammatory response, nonalcoholic fatty liver disease, myocardial infarction, tumor and so on. In recent years, FETUB has also been confirmed to play roles in the female reproductive system.
View Article and Find Full Text PDFJ Ovarian Res
January 2025
Reproductive Health Research Center, Clinical Research Institute, Urmia University of Medical Sciences, Urmia, Iran.
Background: To investigate the impact of Melatonin on follicular oxidative stress and assisted reproductive technology (ART) outcomes in women with diminished ovarian reserve (DOR).
Method: We put 68 women with DOR who were going through ART into a randomized controlled trial. Starting on the fifth day of their menstrual cycle, we gave them either 3 mg of Melatonin or a placebo every day before stimulating their ovaries.
Nat Commun
January 2025
Department of Metabolism, Digestion, and Reproduction, Imperial College London, London, UK.
Infertility affects one-in-six couples, often necessitating in vitro fertilization treatment (IVF). IVF generates complex data, which can challenge the utilization of the full richness of data during decision-making, leading to reliance on simple 'rules-of-thumb'. Machine learning techniques are well-suited to analyzing complex data to provide data-driven recommendations to improve decision-making.
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