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Background: Embryo implantation involves two key elements: a good quality embryo and receptive endometrium. Endometrial receptivity abnormalities are known as one of the possible causes of recurrent implantation failure (RIF), especially when the embryo is euploid. This study was aimed to evaluate the impact of age and other clinical factors on endometrial receptivity in women with RIF.

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Objectives: To construct a prediction model based on deep learning (DL) and radiomics features of diffusion weighted imaging (DWI), and clinical variables for evaluating TP53 mutations in endometrial cancer (EC).

Methods: DWI and clinical data from 155 EC patients were included in this study, consisting of 80 in the training set, 35 in the test set, and 40 in the external validation set. Radiomics features, convolutional neural network-based DL features, and clinical variables were analyzed.

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Uterine Corpus Endometrial Carcinoma (UCEC) represents a common malignant neoplasm in women, with its prognosis being intricately associated with available therapeutic interventions. In the past few decades, there has been a burgeoning interest in the role of mitochondria within the context of UCEC. Nevertheless, the development and application of prognostic models predicated on mitochondrial-related genes (MRGs) in UCEC remains in the exploratory stages.

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Single-cell and spatial transcriptomic profiling revealed niche interactions sustaining growth of endometriotic lesions.

Cell Genom

January 2025

National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China. Electronic address:

Endometriosis is a chronic condition with limited therapeutic options. The molecular aberrations promoting ectopic attachment and interactions with the local microenvironment sustaining lesion growth have been unclear, prohibiting development of targeted therapies. Here, we performed single-cell and spatial transcriptomic profiling of ectopic lesions and eutopic endometrium in endometriosis.

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POLE status determination is necessary for the molecular classification of endometrial carcinomas (EC). However, this determination is only achievable by molecular techniques, which are not available in many practice settings. A previously published study reported elevated AMF/GPI and AMFR/gp78 levels in POLE-mutant EC.

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