AIMC Topic: Placenta

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Identification and validation of PANX1 as an inflammasome-related biomarker in gestational diabetes mellitus: insights from machine learning and experimental approaches.

Mammalian genome : official journal of the International Mammalian Genome Society
Gestational diabetes mellitus (GDM) is characterized by glucose intolerance during pregnancy, resulting from insulin resistance, and is associated with increased maternal and neonatal risks. Inflammasomes play a critical role in GDM pathophysiology b...

Mitochondria-associated endoplasmic reticulum membrane (MAM)-associated calpains system in preeclampsia.

BMC pregnancy and childbirth
BACKGROUND: Preeclampsia (PE) is a multisystem disorder characterized primarily by hypertension and proteinuria after 20 weeks of gestation, significantly impacting maternal and fetal health. The etiology remains unclear, but it is primarily attribut...

Evaluation of biomarkers and immune microenvironment of gestational diabetes mellitus evidence from omics data and machine learning.

Scientific reports
This study aimed to identify core genes of Gestational diabetes mellitus (GDM) and explore its immune microenvironment. Using the limma package, we were able to identify differentially expressed genes (DEGs) between GDM and normal placental tissue. W...

Self-supervised deep metric learning for prototypical zero-shot lesion retrieval in placenta whole-slide images.

Computers in biology and medicine
Postnatal adverse outcomes can often be explained and predicted by the pathological evaluation of the placenta after a pregnancy. However, placenta whole-slide image (WSI) analysis is not performed systematically due to the specialized skills require...

Birth weight prediction using artificial intelligence-based placental assessment from macroscopic photo: a retrospective study.

Placenta
BACKGROUND: This study aimed to predict newborn birth weight through multifactorial analysis of macroscopic placental images using artificial intelligence (AI).

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...

PBScreen: A server for the high-throughput screening of placental barrier-permeable contaminants based on multifusion deep learning.

Environmental pollution (Barking, Essex : 1987)
Contaminants capable of crossing the placental barrier (PB) adversely affect female reproduction and fetal development. The rapid identification of PB-permeable contaminants is urgently needed due to the inefficiencies of conventional cell-based tran...

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...

Machine learning-enhanced surface-enhanced spectroscopic detection of polycyclic aromatic hydrocarbons in the human placenta.

Proceedings of the National Academy of Sciences of the United States of America
The detection and identification of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, polycyclic aromatic compounds (PACs), are essential for environmental and health monitoring, for assessing toxicological exposure and their associated ...