Novel 3D Microscopic Analysis of Human Placental Villous Trees Reveals Unexpected Significance of Branching Angles

The villous trees of human placentas delineate the fetomaternal border and are complex three-dimensional (3D) structures. Thus far, they have primarily been analyzed as thin, two-dimensional (2D) histological sections. However, 2D sections cannot provide access to key aspects such as branching nodes and branch order. Using samples taken from 50 normal human placentas at birth, in the present study we show that analysis procedures for 3D reconstruction of neuronal dendritic trees can also be used for analyzing trees of human placentas. Nodes and their branches (e.g., branching hierarchy, branching angles, diameters, and lengths of branches) can be efficiently measured in whole-mount preparations of isolated villous trees using high-end light microscopy. Such data differ qualitatively from the data obtainable from histological sections and go substantially beyond the morphological horizon of such histological data. Unexpectedly, branching angles of terminal branches of villous trees varied inversely with the fetoplacental weight ratio, a widely used clinical parameter. Since branching angles have never before been determined in the human placenta, this result requires further detailed studies in order to fully understand its impact

Estimating the evolution of elasticities of natural gas demand: the case of Istanbul, Turkey

Much of the existing literature on demand for natural gas assumes constant and single-value elasticities, overlooking the possibility of dynamic responses to the changing conditions. We aim to fill this gap by providing individual time series of short-run elasticity estimates based on maximum entropy resampling in a fixed-width rolling window framework. This approach does not only enable taking the variability of the elasticities into account, but also helps obtain more efficient and robust results in small samples in comparison with conventional inferences based on asymptotic distribution theory. To illustrate the methodology, we employ monthly time-series data between 2004 and 2012 and analyze the dynamics of residential natural gas demand in Istanbul, the largest metropolitan area in Turkey. Our findings reveal that the elasticities of the demand model do not remain constant and they are sensitive to the economic situation as well as weather fluctuations