Biology subjects

McElrath, T. F.

Publications and source records attributed to McElrath, T. F..

3 recordsLinked to original sources

bioRxiv2025

The Binary Cellular Biology of Human Growth I Quantifying the Creation and Growth of the Body and its Parts

Assessing and understanding the Growth and Development of animals generally, and of human fetuses specifically, provides essential information for the management of the health of the newborn and its mother. Here we show that a consideration of the formation of the body, in units of numbers of cells, N, and the change in these numbers by the binary either/or decisions of cells to divide or not, an approach we call Binary Cellular Analysis, provides new insights and new equations for quantifying the growth and development of the body and its parts. These equations include: 1) The Binary Cellular Universal Growth Equation, which captures growth from conception to adulthood, and provides a method for biologically-based, data-driven, Growth Curves; 2) The Binary Cellular Universal Mitotic Fraction Equation, which lies within the Binary Cellular Universal Growth Equation, and captures the mechanism of growth to adult size, control of cell division; 3) The Binary Cellular Allometric Growth Equation, which captures the creation and growth of the Tissues, Organs, and Anatomical Structures of the body, and how the embryo creates each Body Part from a Single Founder Cell; and, 4) Binary Cellular Estimated Fetal Weight Equations, derived from the Binary Cellular Allometric Growth Equation, which captures the relationship between Ultrasound Measurement and the Size of the body as a whole. These equations capture the developmental process of Cellular Selection, resulting from Differential Cellular Proliferation, which molds the formation of the body from a single fertilized ovum into a multicellular animal. The parameters of these equations both capture the differences in Size and Growth between animals across the taxonomic spectrum, and between human fetuses, as well as identify the individual mechanisms of mitosis that drive Growth and Development. From the Binary Cellular Universal Growth Equation, the Growth of human fetuses can be measured, thus providing a much-needed tool for understanding the biological forces that cause a fetus to grow to Small, Average, or Large Size at birth, for providing the basis of biologically-based, data-driven, Growth Curves, and for assisting the management of the obstetric care of the fetus and its mother.

developmental biology↗

bioRxiv2025

The Binary Cellular Biology of Human Growth II Calculating the Size of the Human Fetus from the Size of its Parts

Assessing and understanding the Size of the human fetus provides essential information for the management of the health of the newborn and its mother, a quality that is commonly measured by Fetal Ultrasound. Many equations for making such calculations have been considered, none of which have been entirely satisfactory. As we have shown in the previous paper in this series, a consideration of the formation of the body, in units of numbers of cells, N, an approach we call Binary Cellular Analysis, provides new quantitative tools for estimating the Size and Age of the fetus. These tools include a new mathematical basis for creating useful expressions, Binary Cellular Estimated Fetal Weight Equations, for calculating human Fetal Weight from Ultrasound Measurements. As we show here, the most promising of these expressions, the Abdominal Circumference Binary Cellular Estimated Fetal Weight Equation, performs better than other currently used Fetal Weight Equations, while also yielding up new methods for improving ultrasound size assessment. Web-based calculators (https://kidzgrowth.com) make these mathematical manipulations available for obstetric care.

developmental biology↗

bioRxiv2020

Risk of preeclampsia in patients with genetic predisposition to common medical conditions: a case-control study

ObjectiveTo assess whether women with a genetic predisposition to medical conditions known to increase preeclampsia risk have an increased risk of preeclampsia in pregnancy. DesignCase-control study. Setting and populationPreeclampsia cases (n=498) and controls (n=1864) of European ancestry from 5 US sites genotyped on a cardiovascular gene-centric array. MethodsSignificant single nucleotide polymorphisms (SNPs) from 21 traits in 7 disease categories (cardiovascular, inflammatory/autoimmune, insulin resistance, liver, obesity, renal, thrombophilia) with published genome-wide association studies (GWAS) were used to create a genetic instrument for each trait. Multivariable logistic regression was used to test the association of each continuous, scaled genetic instrument with preeclampsia. Odds of preeclampsia were compared across quartiles of the genetic instrument and evaluated for significance using a test for trend. Main Outcome Measurespreeclampsia. ResultsAn increasing burden of risk alleles for elevated diastolic blood pressure (DBP) and increased body mass index (BMI) were associated with an increased risk of preeclampsia (DBP: overall OR 1.11 (1.01-1.21), p=0.025; BMI: OR 1.10 (1.00-1.20), p=0.042), while risk alleles associated with elevated alkaline phosphatase (ALP) were protective (OR 0.89 (0.82-0.97), p=0.008), driven primarily by pleiotropic effects of variants in the FADS gene region. The effect of DBP genetic loci was even greater in early-onset (<34 weeks) preeclampsia cases (OR 1.30 (1.08-1.56), p=0.005). For all other traits, the genetic instrument was not robustly associated with preeclampsia risk. ConclusionsThese results suggest that the underlying genetic architecture of preeclampsia is shared with other disorders, specifically hypertension and obesity. TWEETABLE ABSTRACTGenetic predisposition to increased diastolic blood pressure and obesity increases the risk of preeclampsia.

genetics↗