AIMC Topic: Pre-Eclampsia

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Iron metabolism and preeclampsia: new insights from bioinformatics analysis.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
OBJECTIVE: Preeclampsia (PE) is a multifactorial systemic pregnancy disease, in which iron metabolism and ferroptosis play significant roles during its pathogenesis. The diagnosis and prevention of PE remain urgent clinical issues that need to be add...

Investigation of serum neuroserpin levels in pregnant women diagnosed with pre-eclampsia: a prospective case-control study.

BMC pregnancy and childbirth
OBJECTIVE: Neuroserpin, a serine protease inhibitor, is recognized for its anti-inflammatory and neuroprotective properties. Given the central role of inflammation and neurological involvement in the pathophysiology of preeclampsia, this study aimed ...

Predicting preeclampsia in early pregnancy using clinical and laboratory data via machine learning model.

BMC medical informatics and decision making
BACKGROUND: This study was performed to characterize the relationship of various laboratory test indicators with clinical information and Preeclampsia (PE) development. Then, prediction models for early-onset preeclampsia (EOPE), late-onset preeclamp...

ULK2 deficiency stratifies autophagy-driven molecular subtypes and exacerbates trophoblasts apoptosis in preeclampsia.

Placenta
INTRODUCTION: Preeclampsia (PE), a placenta-originated hypertensive disorder of pregnancy, lacks targeted therapies despite its significant contribution to maternal and fetal morbidity. Emerging evidence implicates autophagy dysregulation in PE patho...

Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.

BMC pregnancy and childbirth
BACKGROUND: Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for the early detection of preeclampsia (PE). However, the current methods for selecting disease-specific biomarkers are often inefficient and typically on...

Identification of critical biomarkers and immune infiltration in preeclampsia through bioinformatics and machine learning methods.

BMC pregnancy and childbirth
BACKGROUND: Preeclampsia (PE) is a multisystem progressive disease that occurs during pregnancy. Previous studies have shown that the immune system is involved in the placental trophoblast function and the pathological process of uterine vascular rem...

Association between deep learning radiomics based on placental MRI and preeclampsia with fetal growth restriction: A multicenter study.

European journal of radiology
PURPOSE: Preeclampsia (PE) is associated with placental insufficiency and could lead to adverse pregnancy outcomes. The study aimed to develop a placental T2-weighted image-based automatic quantitative model for the identification of PE pregnancies a...

Consecutive prediction of adverse maternal outcomes of preeclampsia, using the PIERS-ML and fullPIERS models: A multicountry prospective observational study.

PLoS medicine
BACKGROUND: Preeclampsia is a potentially life-threatening pregnancy complication. Among women whose pregnancies are complicated by preeclampsia, the Preeclampsia Integrated Estimate of RiSk (PIERS) models (i.e., the PIERS Machine Learning [PIERS-ML]...

Construction and evaluation of machine learning-based predictive models for early-onset preeclampsia.

Pregnancy hypertension
OBJECTIVE: To analyze the influencing factors of early-onset preeclampsia (EOPE). And to construct and validate the prediction model of EOPE using machine learning algorithm.

Development of immune-derived molecular markers for preeclampsia based on multiple machine learning algorithms.

Scientific reports
Preeclampsia (PE) is a major pregnancy-specific cardiovascular complication posing latent life-threatening risks to mothers and neonates. The contribution of immune dysregulation to PE is not fully understood, highlighting the need to explore molecul...