Data related uncertainty in near-surface vulnerability assessments for agrochemicals in the San Joaquin Valley.

Precious groundwater resources across the United States have been contaminated due to decades-long nonpoint-source applications of agricultural chemicals. Assessing the impact of past, ongoing, and future chemical applications for large-scale agriculture operations is timely for designing best-management practices to prevent subsurface pollution. Presented here are the results from a series of regional-scale vulnerability assessments for the San Joaquin Valley (SJV). Two relatively simple indices, the retardation and attenuation factors, are used to estimate near-surface vulnerabilities based on the chemical properties of 32 pesticides and the variability of both soil characteristics and recharge rates across the SJV. The uncertainties inherit to these assessments, derived from the uncertainties within the chemical and soil data bases, are estimated using first-order analyses. The results are used to screen and rank the chemicals based on mobility and leaching potential, without and with consideration of data-related uncertainties. Chemicals of historic high visibility in the SJV (e.g., atrazine, DBCP [dibromochloropropane], ethylene dibromide, and simazine) are ranked in the top half of those considered. Vulnerability maps generated for atrazine and DBCP, featured for their legacy status in the study area, clearly illustrate variations within and across the assessments. For example, the leaching potential is greater for DBCP than for atrazine, the leaching potential for DBCP is greater for the spatially variable recharge values than for the average recharge rate, and the leaching potentials for both DBCP and atrazine are greater for the annual recharge estimates than for the monthly recharge estimates. The data-related uncertainties identified in this study can be significant, targeting opportunities for improving future vulnerability assessments.

Mutation risk associated with paternal and maternal age in a cohort of retinoblastoma survivors.

Autosomal dominant conditions are known to be associated with advanced paternal age, and it has been suggested that retinoblastoma (Rb) also exhibits a paternal age effect due to the paternal origin of most new germline RB1 mutations. To further our understanding of the association of parental age and risk of de novo germline RB1 mutations, we evaluated the effect of parental age in a cohort of Rb survivors in the United States. A cohort of 262 Rb patients was retrospectively identified at one institution, and telephone interviews were conducted with parents of 160 survivors (65.3%). We classified Rb survivors into three groups: those with unilateral Rb were classified as sporadic if they had no or unknown family history of Rb, those with bilateral Rb were classified as having a de novo germline mutation if they had no or unknown family history of Rb, and those with unilateral or bilateral Rb, who had a family history of Rb, were classified as familial. We built two sets of nested logistic regression models to detect an increased odds of the de novo germline mutation classification related to older parental age compared to sporadic and familial Rb classifications. The modeling strategy evaluated effects of continuous increasing maternal and paternal age and 5-year age increases adjusted for the age of the other parent. Mean maternal ages for survivors classified as having de novo germline mutations and sporadic Rb were similar (28.3 and 28.5, respectively) as were mean paternal ages (31.9 and 31.2, respectively), and all were significantly higher than the weighted general US population means. In contrast, maternal and paternal ages for familial Rb did not differ significantly from the weighted US general population means. Although we noted no significant differences between mean maternal and paternal ages between each of the three Rb classification groups, we found increased odds of a survivor being in the de novo germline mutation group for each 5-year increase in paternal age, but these findings were not statistically significant (de novo vs. sporadic ORs 30-34 = 1.7 [0.7-4], ≥ 35 = 1.3 [0.5-3.3]; de novo vs. familial ORs 30-34 = 2.8 [1.0-8.4], ≥ 35 = 1.6 [0.6-4.6]). Our study suggests a weak paternal age effect for Rb resulting from de novo germline mutations consistent with the paternal origin of most of these mutations.