MFA15 (MFA 2015)

Catalogue of a culminating student exhibition held at the Mildred Lane Kemper Art Museum, May 1 - August 2, 2015 . Introduction / Heather Corcoran and Patricia Olynyk -- Diana Casanova / Emily J. Hanson -- Andrea M. Coates : in the operating theater / Stephanie Dering -- Margaux Crump -- Brandon Daniels -- Addoley Dzegede : do you prefer answers or truth? / Aaron Coleman -- Vita Eruhimovitz -- Carling Hale -- Amanda Helman -- Mike Helms / Ming Ying Hong -- Ming Ying Hong / Emily J. Hanson -- Sea A Joung / Ervin Malakaj -- Stephanie Kang / Jeremy Shipley -- Dayna Jean Kriz / Andrew Johnson -- Thomas Moore : you should move to the city / Nathaniel Rosenthalis -- Jacob Muldowney -- Laurel Panella / Garrett Clough -- Caitlin Penny -- On the bridge, between Juarez and El Paso / Eric Lyle Schultz -- Jeremy Shipley -- Emmeline Solomon -- Kellie Spano / Margaux Crump -- Michael Aaron Williams -- Austin R. Wolf : monumental labor / Adam Turl.https://openscholarship.wustl.edu/books/1015/thumbnail.jp

A NOVEL APPLICATION OF THE NEWCOMB-BENFORD LAW TO EXPOSURE DATA

The Newcomb-Benford Law (NBL) is a powerful mathematical concept that describes the distribution frequency of the significant digits for in large data sets (Judge and Schechter 2009). NBL suggests that the probability for the significant digits (1 through 9) of a randomly occurring number is not equally distributed but follows a distribution where 1 occurs more frequently than 2, 2 more than 3, and so on. Use of the NBL has frequently been used to identify fraudulent or manipulated data in the political, economic, and natural sciences. However, few studies have used the NBL to identify underlying mechanisms in toxicokinetic and toxicodynamic analyses. We applied NBL to five different exposure data sets with the aim of understanding how toxicokinetics and toxicodynamics (TK-TD) of essential, beneficial, and nonessential elements may influence conformity to the Newcomb-Benford distribution (NBD) in mammalian biosamples. Data sets were collected for observational and experimental studies and measured a range of concentrations of essential, beneficial, and nonessential elements in human adults and children as well as mice. Findings suggest that underlying physiological mechanisms, such as preferential uptake of essential elements, may lead to violations of the NBD and that in these cases, the violation appeared to follow a characteristic rotated sigmoidal curve. Findings also indicate that competitive co-exposure to a beneficial and nonessential element results in a violation without a characteristic trend. Therefore, the use of the NBL in exposure data to detect data manipulation may be flawed

Human Biomonitoring Data in Health Risk Assessments Published in Peer-Reviewed Journals between 2016 and 2021: Confronting Reality after a Preliminary Review

Human biomonitoring (HBM) is a rapidly developing field that is emphasized as an important approach for the assessment of health risks. However, its value for health risk assessment (HRA) remains to be clarified. We performed a review of publications concerned with applications of HBM in the assessment of health risks. The selection of publications for this review was limited by the search engines used (only PubMed and Scopus) and a timeframe of the last five years. The review focused on the clarity of 10 HRA elements, which influence the quality of HRA. We show that the usage of HBM data in HRA is limited and unclear. Primarily, the key HRA elements are not consistently applied or followed when using HBM in such assessments, and secondly, there are inconsistencies regarding the understanding of fundamental risk analysis principles and good practices in risk analysis. Our recommendations are as follows: (i) potential usage of HBM data in HRA should not be non-critically overestimated but rather limited and aligned to a specific value for exposure assessment or for the interpretation of health damage; (ii) improvements to HRA approaches, using HBM information or not, are needed and should strictly follow theoretical foundations of risk analysis