Villus packing density and lacunarity: Markers of placental efficiency?

Shah, Ruchit; Salafia, Carolyn M.; Girardi, Theresa; Merz, George

doi:10.1016/j.placenta.2016.09.018

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…The marked variation in the appearance of the villi has been well appreciated irrespective of the placental size. The variation in villous distribution (measured as both packing density and lacunarity) has been demonstrated to impact the placental efficiency [60]. This histologic variation is likely associated with the high capacity of the placenta for genetic variation, in terms of chromosomal mosaicism and epigenetic variation (in terms of DNA methylation).…”

Section: Villous Spatial Distributionmentioning

confidence: 99%

Placental Growth and Development Analyzed through 2D and 3D Fractals

Shah¹,

Salafia²,

Girardi³

et al. 2023

Fractal Analysis - Applications and Updates

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Fractal geometry has many applications in physiology and anatomy, providing novel insights into the structure and function of biological systems and organs, including the placenta. The placenta is a vital fetal organ that is the means by which essential nutrients and oxygen are extracted from maternal blood and transferred to the developing fetus. Anatomically, the placenta is a highly intricate structure exhibiting self-similarity at different scales. The complex relationship between placental function in nutrient transfer and fetal growth follows the allometric metabolic scaling law. Variability of shape of the placental chorionic plate, a 2D plane which contains the major chorionic arteries and veins, has been linked to measures of child health and neurodevelopmental outcomes. The microscopic arrangement of chorionic villi have also been demonstrated to have fractal properties that vary by gestational age and in different pathological conditions. Geographical Information Systems theory could be used to analyze the placental topography in the context of its surface vasculature and measures of spatial autocorrelation can model placental growth and development over gestation. An ideal model would mark timing, nature, and severity of gestational pathology modifying placental growth and, by extension, fetal development that leads to poor pregnancy outcomes.

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Section: Villous Spatial Distributionmentioning

confidence: 99%

Placental Growth and Development Analyzed through 2D and 3D Fractals

Shah¹,

Salafia²,

Girardi³

et al. 2023

Fractal Analysis - Applications and Updates

View full text Add to dashboard Cite

show abstract

“…2.2. GBL has been applied to measurements of soil moisture (Cumbrera et al 2012), radar echos (Azzaz and Haddad 2017), urban land cover (Myint and Lam 2005), ham quality (Valous et al 2009), ecosystem services (Roces-Díaz et al 2014), landscape evapotranspiration (Liu and Zhang 2010), deforestation (Pintilii et al 2017), urbanisation (Sung et al 2013), racial segregation (Sui and Wu 2006), biological tissues (Gould et al 2011;Shah et al 2016), and crystallisation (Velazquez-Camilo et al 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Data may be missing because of pixel noise, specular reflections, preparation artefacts in microscopy, or cloud occlusions in satellite images. This problem is widely recognised; proposed solutions include reconstruction of missing data (Shah et al 2016) and, for small amounts of missing data, modification of (1) (Sui and Wu 2006).…”

Section: Introductionmentioning

confidence: 99%

Computation of Lacunarity from Covariance of Spatial Binary Maps

Hingee

Baddeley

Caccetta

et al. 2019

JABES

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We consider a spatial binary coverage map (binary pixel image) which might represent the spatial pattern of the presence and absence of vegetation in a landscape. 'Lacunarity' is a generic term for the nature of gaps in the pattern: a popular choice of summary statistic is the 'gliding-box lacunarity' (GBL) curve. GBL is potentially useful for quantifying changes in vegetation patterns, but its application is hampered by a lack of interpretability and practical difficulties with missing data. In this paper we find a mathematical relationship between GBL and spatial covariance. This leads to new estimators of GBL that tolerate irregular spatial domains and missing data, thus overcoming major weaknesses of the traditional estimator. The relationship gives an explicit formula for GBL of models with known spatial covariance and enables us to predict the effect of changes in the pattern on GBL. Using variance reduction methods for spatial data, we obtain statistically efficient estimators of GBL. The techniques are demonstrated on simulated binary coverage maps and remotely sensed maps of local-scale disturbance and meso-scale fragmentation in Australian forests. Results show in some cases a fourfold reduction in mean integrated squared error and a twentyfold reduction in sensitivity to missing data.Supplementary materials accompanying the paper appear online and include a software implementation in the R language.

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Placental Weight, Shape and Gross Vascular Morphology

Salafia

Roberts

2018

Pathology of the Placenta

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Villus packing density and lacunarity: Markers of placental efficiency?

Cited by 6 publications

References 17 publications

Placental Growth and Development Analyzed through 2D and 3D Fractals

Placental Growth and Development Analyzed through 2D and 3D Fractals

Computation of Lacunarity from Covariance of Spatial Binary Maps

Placental Weight, Shape and Gross Vascular Morphology

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