Stillbirth Associated With Anomalous Origin and Course of the Left Coronary Artery: A Report of 2 Cases.

Coronary artery anomalies and their potential sequelae are not well studied in association with stillbirth. Herein, we report the autopsy findings in two term stillborn fetuses with coronary artery anomalies. Both fetuses showed identical findings consisting of an abnormal origin of the left coronary artery from the right sinus of Valsalva and an interarterial course of the left coronary artery. Histologic vascular and myocardial changes were also present. These coronary artery findings are associated with sudden death in adults and neonates, and therefore, their potential to be a cause and/or contributor to fetal death is suspected.

Decreased Alpha Klotho Expression in Placentas Exposed to Severe Maternal Vascular Malperfusion.

BACKGROUND: Placental maternal vascular malperfusion (MVM) is characterized by accelerated villous maturation and has been associated with a decrease in the antiaging protein, alpha-klotho (AK). Our aim was to characterize AK protein and gene expression in the placenta and fetal organs. METHODS: We utilized 2 cohorts. First, we characterized AK protein expression in an autopsy cohort where cases were defined as MVM as the cause of fetal death compared to a stillborn control population. Second, we characterized placental and umbilical cord blood AK gene expression in a liveborn population with and without MVM. RESULTS: We found decreased protein expression in the villous trophoblastic cells of placentas exposed to severe MVM and decreased AK gene expression in placental tissue exposed to MVM. We did not see any statistically significant differences in fetal organ or umbilical cord blood AK expression based on the presence or absence of MVM. Furthermore, in liveborn infants, we also found increased odds of preterm birth with lower placental AK expression. CONCLUSIONS: Decreased AK gene and protein expression in the placenta in the setting of MVM is consistent with the theory of placental aging in MVM and is associated with increased odds of preterm birth.

Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY.

Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta's heterogeneity and temporal variability pose challenges for histology analysis. To address this issue, we developed the 'Histology Analysis Pipeline.PY' (HAPPY), a deep learning hierarchical method for quantifying the variability of cells and micro-anatomical tissue structures across placenta histology whole slide images. HAPPY differs from patch-based features or segmentation approaches by following an interpretable biological hierarchy, representing cells and cellular communities within tissues at a single-cell resolution across whole slide images. We present a set of quantitative metrics from healthy term placentas as a baseline for future assessments of placenta health and we show how these metrics deviate in placentas with clinically significant placental infarction. HAPPY's cell and tissue predictions closely replicate those from independent clinical experts and placental biology literature.