Medicine and Health Sciences Commons^™

Association Between In Utero Arsenic Exposure, Placental Gene Expression, And Infant Birth Weight: A Us Birth Cohort Study, Dennis Liang Fei, Devin C. Koestler, Zhigang Li, Camilla Giambelli, Avencia Sanchez-Mejias, Julie Gosse, Carmen J. Marsit, Margaret R. Karagas, David J. Robbins

Dartmouth Scholarship

Epidemiologic studies and animal models suggest that in utero arsenic exposure affects fetal health, with a negative association between maternal arsenic ingestion and infant birth weight often observed. However, the molecular mechanisms for this association remain elusive. In the present study, we aimed to increase our understanding of the impact of low-dose arsenic exposure on fetal health by identifying possible arsenic-associated fetal tissue biomarkers in a cohort of pregnant women exposed to arsenic at low levels.

Methods: Arsenic concentrations were determined from the urine samples of a cohort of 133 pregnant women from New Hampshire. Placental tissue samples collected from …

Patterning In Placental 11-B Hydroxysteroid Dehydrogenase Methylation According To Prenatal Socioeconomic Adversity, Allison A. Appleton, David A. Armstrong, Corina Lesseur, Joyce Lee, James F. Padbury, Barry M. Lester

Dartmouth Scholarship

Background:

Prenatal socioeconomic adversity as an intrauterine exposure is associated with a range of perinatal outcomes although the explanatory mechanisms are not well understood. The development of the fetus can be shaped by the intrauterine environment through alterations in the function of the placenta. In the placenta, the HSD11B2 gene encodes the 11-beta hydroxysteroid dehydrogenase enzyme, which is responsible for the inactivation of maternal cortisol thereby protecting the developing fetus from this exposure. This gene is regulated by DNA methylation, and this methylation and the expression it controls has been shown to be susceptible to a variety of stressors from …

Dna Methylation Analysis Reveals Distinct Methylation Signatures In Pediatric Germ Cell Tumors, James F. Amatruda, Julie A. Ross, Brock Christensen, Nicholas J. Fustino, Kenneth S. Chen, Anthony J. Hooten, Heather Nelson, Jacquelyn K. Kuriger, Dinesh Rakheja, A. Lindsay Frazier, Jenny N. Poynter

Dartmouth Scholarship

Background: Aberrant DNA methylation is a prominent feature of many cancers, and may be especially relevant in germ cell tumors (GCTs) due to the extensive epigenetic reprogramming that occurs in the germ line during normal development. Methods: We used the Illumina GoldenGate Cancer Methylation Panel to compare DNA methylation in the three main histologic subtypes of pediatric GCTs (germinoma, teratoma and yolk sac tumor (YST); N = 51) and used recursively partitioned mixture models (RPMM) to test associations between methylation pattern and tumor and demographic characteristics. We identified genes and pathways that were differentially methylated using generalized linear models and …

Ensemble-Based Methods For Forecasting Census In Hospital Units, Devin C. Koestler, Hernando Ombao, Jesse Bender

Dartmouth Scholarship

The ability to accurately forecast census counts in hospital departments has considerable implications for hospital resource allocation. In recent years several different methods have been proposed forecasting census counts, however many of these approaches do not use available patient-specific information. In this paper we present an ensemble-based methodology for forecasting the census under a framework that simultaneously incorporates both (i) arrival trends over time and (ii) patient-specific baseline and time-varying information. The proposed model for predicting census has three components, namely: current census count, number of daily arrivals and number of daily departures. To model the number of daily arrivals, …