Definition and Quantification of Three-Dimensional Imaging Targets to Phenotype Pre-Eclampsia Subtypes: An Exploratory Study.

Pre-eclampsia is a severe placenta-related complication of pregnancy with limited early diagnostic and therapeutic options. Aetiological knowledge is controversial, and there is no universal consensus on what constitutes the early and late phenotypes of pre-eclampsia. Phenotyping of native placental three-dimensional (3D) morphology offers a novel approach to improve our understanding of the structural placental abnormalities in pre-eclampsia. Healthy and pre-eclamptic placental tissues were imaged with multiphoton microscopy (MPM). Imaging based on inherent signal (collagen, and cytoplasm) and fluorescent staining (nuclei, and blood vessels) enabled the visualization of placental villous tissue with subcellular resolution. Images were analysed with a combination of open source (FIJI, VMTK, Stardist, MATLAB, DBSCAN), and commercially (MATLAB) available software. Trophoblast organization, 3D-villous tree structure, syncytial knots, fibrosis, and 3D-vascular networks were identified as quantifiable imaging targets. Preliminary data indicate increased syncytial knot density with characteristic elongated shape, higher occurrence of paddle-like villous sprouts, abnormal villous volume-to-surface ratio, and decreased vascular density in pre-eclampsia compared to control placentas. The preliminary data presented indicate the potential of quantifying 3D microscopic images for identifying different morphological features and phenotyping pre-eclampsia in placental villous tissue.

Computational investigation of the dynamic control of cAMP signaling by PDE4 isoform types.

Cyclic adenosine monophosphate (cAMP) is a generic signaling molecule that, through precise control of its signaling dynamics, exerts distinct cellular effects. Consequently, aberrant cAMP signaling can have detrimental effects. Phosphodiesterase 4 (PDE4) enzymes profoundly control cAMP signaling and comprise different isoform types wherein enzymatic activity is modulated by differential feedback mechanisms. Because these feedback dynamics are non-linear and occur coincidentally, their effects are difficult to examine experimentally but can be well simulated computationally. Through understanding the role of PDE4 isoform types in regulating cAMP signaling, PDE4-targeted therapeutic strategies can be better specified. Here, we established a computational model to study how feedback mechanisms on different PDE4 isoform types lead to dynamic, isoform-specific control of cAMP signaling. Ordinary differential equations describing cAMP dynamics were implemented in the VirtualCell environment. Simulations indicated that long PDE4 isoforms exert the most profound control on oscillatory cAMP signaling, as opposed to the PDE4-mediated control of single cAMP input pulses. Moreover, elevating cAMP levels or decreasing PDE4 levels revealed different effects on downstream signaling. Together these results underline that cAMP signaling is distinctly regulated by different PDE4 isoform types and that this isoform specificity should be considered in both computational and experimental follow-up studies to better define PDE4 enzymes as therapeutic targets in diseases in which cAMP signaling is aberrant.