Predictive Value and Potential of Targeting Complement Factor C3 in Patients with Renal Injury in Preeclampsia.

Aim: The activation of the complement system is accompanied by the occurrence and development of preeclampsia, as well as kidney diseases. Here, the role of complement C3 [C3] in renal injury in preeclampsia was explored, and its potential application as an early diagnostic biomarker or drug target to ameliorate kidney injury induced by preeclampsia was preliminarily evaluated.

Method: A total of 48 subjects were included in the present study, and the complement C3 levels and renal function were analyzed.

Relationship between chronic endometritis and fallopian tube obstruction and its influence on pregnancy outcome after fallopian tubal recanalization.

Background: Chronic endometritis (CE), frequently asymptomatic, is associated with female infertility. Fallopian tube obstruction (FTO) is also one of the factors contributing to female infertility. More than 90% of cases of proximal FTO can be successfully treated after fallopian tubal recanalization (FTR) and the spontaneous pregnancy rate of treated women after FTR is only about 30%.

Development and Validation of a Model Predicting Malignant Potential of Adnexal Masses in Areas with Scarcity of Ultrasound Resources.

Introduction: Appropriately stratifying the risk of adnexal masses is of great importance. Many diagnostic algorithms have been devised, most of which rely on ultrasound features. However, some remote areas lack trained sonographers.

Genetic risk stratification and risk factors of early menopause in women: a multi-center study utilizing polygenic risk scores.

Objective: This study aims to evaluate the utility of polygenic risk scores (PRS) in women with early menopause (EM) and to investigate the clinical characteristics and risk factors associated with EM based on genetic risk.

Study Design: Genotyping data and clinical data from women with EM and women with normal age of menopause retrieved from UK Biobank were used for early menopause risk prediction model establishment. Subsequently, 99 women diagnosed with EM and 1027 control women underwent PGT-M were recruited for model validation from across eight hospitals in China.

A ketogenic diet alleviates the apoptosis of granulosa cells by inhibiting the activation of cGAS-STING signaling pathway in PCOS mice.

Background: Polycystic ovary syndrome (PCOS) is the most common cause of anovulatory infertility. The ketogenic diet (KD), a diet high in fat and low in carbohydrates, has been applied clinically for the treatment of obese women with PCOS. We have previously demonstrated that KD improved the reproductive phenotype in an androgen-induced PCOS mouse model, yet the underlying molecular mechanisms remain largely unclear.

Secondary cytoreductive surgery followed by olaparib tablets as maintenance therapy in patients with BRCA mutated recurrent ovarian cancer: A multi-center retrospective study.

Objective: To evaluate the effect of secondary cytoreductive surgery (SeCRS) followed by platinum-based chemotherapy (PBC) and olaparib tablets as maintenance therapy in patients with BRCA mutated recurrent epithelial ovarian cancer.

Methods: This was a retrospective study of a prospective database. We collected information on 623 patients diagnosed with BRCA mutated recurrent epithelial ovarian cancer, all of whom underwent SeCRS followed by PBC in combination with or without olaparib.

Interactive segmentation of medical images using deep learning.

Medical image segmentation algorithms based on deep learning have achieved good segmentation results in recent years, but they require a large amount of labeled data. When performing pixel-level labeling on medical images, labeling a target requires marking ten or even hundreds of points along its edge, which requires a lot of time and labor costs. To reduce the labeling cost, we utilize a click-based interactive segmentation method to generate high-quality segmentation labels.

Revolutionizing hysteroscopy outcomes: AI-powered uterine myoma diagnosis algorithm shortens operation time and reduces blood loss.

Background: The application of artificial intelligence (AI) powered algorithm in clinical decision-making is globally popular among clinicians and medical scientists. In this research endeavor, we harnessed the capabilities of AI to enhance the precision of hysteroscopic myomectomy procedures.

Methods: Our multidisciplinary team developed a comprehensive suite of algorithms, rooted in deep learning technology, addressing myomas segmentation tasks.

Associations between HT, BMI, and allergic rhinitis in perimenopausal women.

Background: Increasing evidence suggests that hormone therapy (HT) and obesity exert an influence on allergic rhinitis (AR). It is important to investigate the association and interactions between HT, BMI, and AR in perimenopausal women.

Methods: From May 2020 to March 2021, a cross-sectional survey was completed by patients who visited the Allergy Department and Gynecology Department of Shijitan Hospital.

N-acetylcysteine and Hydroxychloroquine Ameliorate ADMA-Induced Fetal Growth Restriction in Mice via Regulating Oxidative Stress and Autophagy.

Fetal growth restriction (FGR) seriously threatens perinatal health. The main cause of FGR is placental malperfusion, but the specific mechanism is still unclear, and there is no effective treatment for FGR. We constructed a FGR mouse model by adding exogenous asymmetric dimethylarginine (ADMA) through in vivo experiments and found that ADMA could cause placental dysplasia and induce the occurrence of FGR.

Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications.

Motivation: Ovarian cancer (OC) is a highly lethal gynecological malignancy. Extensive research has shown that OC cells undergo significant metabolic alterations during tumorigenesis. In this study, we aim to leverage these metabolic changes as potential biomarkers for assessing ovarian cancer.

WA-ResUNet: A Focused Tail Class MRI Medical Image Segmentation Algorithm.

Medical image segmentation can effectively identify lesions in medicine, but some small and rare lesions cannot be well identified. Existing studies do not take into account the uncertainty of the occurrence of diseased tissue, and the problem of long-tailed distribution of medical data. Meanwhile, the grayscale image obtained from Magnetic Resonance Imaging (MRI) detection has problems, such as the features being difficult to extract and invalid features being difficult to distinguish.

A retrospective analysis of secondary cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy in patients with recurrent ovarian cancer.

Aim: To evaluate the effect of secondary cytoreductive surgery (SeCRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC) in recurrent epithelial ovarian cancer patients.

Methods: This retrospective study analyzed a prospective database. We collected information of 389 patients who were diagnosed with recurrent epithelial ovarian cancer.

An Instance Segmentation Model Based on Deep Learning for Intelligent Diagnosis of Uterine Myomas in MRI.

Uterine myomas affect 70% of women of reproductive age, potentially impacting their fertility and health. Manual film reading is commonly used to identify uterine myomas, but it is time-consuming, laborious, and subjective. Clinical treatment requires the consideration of the positional relationship among the uterine wall, uterine cavity, and uterine myomas.

Improving the Segmentation Accuracy of Ovarian-Tumor Ultrasound Images Using Image Inpainting.

Diagnostic results can be radically influenced by the quality of 2D ovarian-tumor ultrasound images. However, clinically processed 2D ovarian-tumor ultrasound images contain many artificially recognized symbols, such as fingers, crosses, dashed lines, and letters which assist artificial intelligence (AI) in image recognition. These symbols are widely distributed within the lesion's boundary, which can also affect the useful feature-extraction-utilizing networks and thus decrease the accuracy of lesion classification and segmentation.

Effects of a ketogenic diet on reproductive and metabolic phenotypes in mice with polycystic ovary syndrome†.

Polycystic ovary syndrome (PCOS) is one of the most common female reproductive and metabolic disorders. The ketogenic diet (KD) is a diet high in fat and low in carbohydrate. The beneficial effects of KD intervention have been demonstrated in obese women with PCOS.

Pre-pregnancy body mass index has greater influence on newborn weight and perinatal outcome than weight control during pregnancy in obese women.

Background: The pre-pregnancy weight and gestational weight gain (GWG) are closely related to perinatal maternal and infant complications, but the relationship between pre-pregnancy weight and GWG and the pattern of interaction have not been reported. This study investigated the influence of weight control during pregnancy on the perinatal maternal and infant outcomes.

Methods: A total of 835 singleton pregnant women who were hospitalized between January 2018 and December 2018 were retrospectively included in this study and divided into two groups: the diet guidance (DG) group (n = 167) and the control group (n = 668).