AIMC Topic: Endometrium

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WISP2/CCN5 revealed as a potential diagnostic biomarker for endometriosis based on machine learning and single-cell transcriptomic analysis.

Functional & integrative genomics
OBJECTIVE: Endometriosis is a prevalent gynecological disease characterized by the ectopic growth of functional endometrial tissue outside the uterine cavity, affecting millions of women worldwide. Currently, the definitive diagnosis relies on invasi...

Evaluation of endometrial vascular flow index and echogenicity following experimental induction of subclinical endometritis in dairy cows.

Scientific reports
This study was conducted aiming to investigate impacts of experimentally induced endometritis on the vascular perfusion and echogenicity of the endometrium in dairy cows. Following estrus synchronization and applying cytological and bacteriological e...

The inconsistent pathogenesis of endometriosis and adenomyosis: insights from endometrial metabolome and microbiome.

mSystems
UNLABELLED: Endometriosis (EM) and adenomyosis (AM) are interrelated gynecological disorders characterized by the aberrant presence of endometrial tissue and are frequently linked with chronic pelvic pain and infertility, yet their pathogenetic mecha...

Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study.

Annals of medicine
OBJECTIVE: Asherman's syndrome (AS) is a significant cause of subfertility in women from developing countries. Over 80% of AS cases in these regions are linked to dilation and curettage (D&C) procedures following pregnancy. The incidence of AS in pat...

Effectors and predictors of conceptus survival in cattle: What is next?

Domestic animal endocrinology
In cattle, the physiological process of switching from cycling to pregnant is complex. Ultimately, that process relies on endometrial luminal epithelial cells and is based on the paracrine context of the uterine lumen. Cells either release luteolytic...

Machine learning Nomogram for Predicting endometrial lesions after tamoxifen therapy in breast Cancer patients.

Scientific reports
Objective Endometrial lesions are a frequent complication following breast cancer, and current diagnostic tools have limitations. This study aims to develop a machine learning-based nomogram model for predicting the early detection of endometrial les...

The association between Vitamin D deficiency and clinical pregnancy rate in IVF patients with different age.

Frontiers in endocrinology
BACKGROUND: The aim of the present study was to investigate the impact of serum VD status on IVF outcomes and to observe the effect of VD deficiency on the expression of the endometrial receptivity marker HOXA10.

Optimizing evaluation of endometrial receptivity in recurrent pregnancy loss: a preliminary investigation integrating radiomics from multimodal ultrasound via machine learning.

Frontiers in endocrinology
BACKGROUND: Recurrent pregnancy loss (RPL) frequently links to a prolonged endometrial receptivity (ER) window, leading to the implantation of non-viable embryos. Existing ER assessment methods face challenges in reliability and invasiveness. Radiomi...

Bridging the Diagnostic Gap between Histopathologic and Hysteroscopic Chronic Endometritis with Deep Learning Models.

Medicina (Kaunas, Lithuania)
Chronic endometritis (CE) is an inflammatory pathologic condition of the uterine mucosa characterized by unusual infiltration of CD138(+) endometrial stromal plasmacytes (ESPCs). CE is often identified in infertile women with unexplained etiology, tu...