Aim: The connective tissue located between the uterine cervix and sacrospinous ligament (the uterospinous connective tissue; USCT) has recently been noted as the level 1 supportive tissue instead of the classical uterosacral ligament. We examined whether or not the USCT changes its histological architecture by vaginal delivery in correlation with the levels 2 and 3 supportive tissues.
Methods: In the pelvic floors of 17 female cadavers (9 nuliparous and 8 multiparous), we compared histological architectures among the USCT, arcus tendineus fasciae pelvis (ATFP) and perineal membrane (PM).
Results: The USCT was evident as a string-like tissue structure in multiparous women or a thick mesh in nuliparous women. It consistently contained fewer elastic and smooth muscle fibers than other levels. In contrast, the ATFP usually contained abundant elastic fibers and smooth muscle. Likewise, the PM also displayed a constant morphology.
Conclusion: Although all three sites were likely to be injured by delivery, the USCT seemed to be more severely damaged and/or more difficult to be recovered than the ATFP and PM.
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http://dx.doi.org/10.1111/j.1447-0756.2010.01298.x | DOI Listing |
BMC Womens Health
December 2024
Department of Physical Medicine and Rehabilitation,, Montefiore Medical Center, Bronx, NY, USA.
Background: Endometriosis, a condition that significantly impacts the quality of life for affected women, manifests with a spectrum of symptoms ranging from mild discomfort to severe pelvic pain, dysmenorrhea, dyspareunia, and infertility. A previous single-center study suggested an elevated prevalence of endometriosis in Jordan, prompting the need for larger studies to confirm these findings.
Methods: We conducted a cross-sectional study involving a sample of 866 women who underwent various laparoscopic procedures for different indications at the Department of Obstetrics and Gynecology at Jordan University Hospital and Al-Karak Governmental Hospital, two tertiary referral hospitals in Jordan between January 2015 and March 2023.
PLoS One
December 2024
Department of Ophthalmology, School of Medicine and Health Science, Debre Tabor University, Debre Tabor, Ethiopia.
Background: Breast cancer is a significant global health issue, responsible for a large number of female cancer deaths. Early detection through breast cancer screening is crucial in reducing mortality rates. However, regions such as Sub-Saharan Africa (SSA) face challenges in identifying breast cancer early, resulting in higher mortality rates and a lower quality of life.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Nursing, College of Medicine and Health Science, Woldia University, Woldia, Ethiopia.
Introduction: An unintended pregnancy refers to a situation where a pregnancy occurs either when there is no desire for a child (unwanted) or when it takes place at a time that was not anticipated (mistimed). Pregnant women infected with HIV face a two to tenfold increased risk of mortality during both pregnancy and the postpartum period compared to those who are not infected. A national level cohort study has identified that about 70 babies born HIV positive, 60% of them were from unplanned pregnancy.
View Article and Find Full Text PDFJ Cardiovasc Dev Dis
November 2024
Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA.
Ischemic stroke is a major cause of mortality and disability and has become a significant public health concern among women. Overall, women have more ischemic stroke events than men, in part due to their longer life span, and also suffer from more severe stroke-related disabilities compared to men. Women are also more likely than men to present with atypical non-focal neurological symptoms, potentially leading to delayed diagnosis and treatment.
View Article and Find Full Text PDFJ Imaging
December 2024
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
Deep learning has shown significant value in automating radiological diagnostics but can be limited by a lack of generalizability to external datasets. Leveraging the geometric principles of non-Euclidean space, certain geometric deep learning approaches may offer an alternative means of improving model generalizability. This study investigates the potential advantages of hyperbolic convolutional neural networks (HCNNs) over traditional convolutional neural networks (CNNs) in neuroimaging tasks.
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