Neurotoxicology and Teratology

The data files here included are simulated data, the ranges for which were based on data from studies of C57BL6J mice, previously analyzed and published. The files include one data set of N = 180 from 30 litters, 3 treatment groups, 10 litters per treatment, 6 mice per litter, with equal numbers of males (n = 3) and females (n = 3) per litter. Also provided are 4 data sets of N = 60 each, that were drawn from the larger data set of N = 180, and which include 1 "representative" male and 1 "representative" female per litter. Each data set includes five variables: mouse ID, litter, sex, group, and body weight at post-natal day 21. *These datasets were created solely for the purpose of demonstrating differences in statistical modeling when litter clusters complicate data analysis. Please see complete manuscript for a full discussion of the topic.

These excel files contain the raw data for each animal and each endpoint. Each excel file contains 1 worksheet for chemical information and another 6 worksheets, named as “Run A”, “Run B”, “Run C”, “Run D”, “Run E”, “Run F”, which correspond to different plate orientations (See the PDF). Eighteen chemicals were screened twice in two independent screens, one as a subset of the NTP 87-compound library, which we previously reported on (screen 1; (Zhang et al., 2018)), and the other as a flame retardant library (screen 2). Each screen contained 3 replicate runs with 3 different orientations of concentrations. The 8 animals in one row were exposed to the same concentration. In screen 1, chemical #1 – 8 were screened in 3 replicates of run A, B and C; chemical #9-18 were screened in 3 replicates of run B, D and E (for details, see (Zhang et al., 2018)). In screen 2, chemical #1 – 8 were screened in 3 replicates of run D, E and F; chemical #9-18 were screened in 3 replicates of run A, C and F. All worksheets contain the raw data in adult and regenerating (tail) planarians, except that the worksheets in “Eye regeneration - day 7 - FR. xlsx” only contain regenerating planarian data as eyes were not evaluated in full worms. In both sections (regenerating tails and adult worms), each column refers to one chemical, and each row represents one well in the 48-well plate with tested chemical concentrations labeled.

Data used for SAS analysis for USV, ASR/PPI, MA, SA, and CMP

Thyroid hormones (THs) control normal brain development and function in humans, and identifying environmental thyroid disrupting chemicals has significant public health implications. As such, some developmental and reproductive toxicology studies now require or suggest serum total thyroxine (T4) measurements in pregnant, lactating, and developing rats. However, serum T4 concentrations are normally low in the fetus and pup which makes accurate quantification difficult. These challenges can be circumvented by technologies like mass spectrometry, but these approaches are expensive and not always widely available. To demonstrate the feasibility of measuring serum T4 using a commercially available kit we compare T4 concentrations in pregnant, fetal, and neonatal rats, as measured by both liquid chromatography mass spectrometry (LC/MS/MS) and radioimmunoassay (RIA). The sera samples analyzed were obtained from rats on gestational day 20 (dams and fetuses) or postnatal day 5 (pups), following a maternal exposure to the goitrogen propylthiouracil (0-3 ppm) to incrementally decrease T4. We show that with optimization, it is possible to measure serum T4 using low sample volumes (25-50μL) by RIA and the relative control values obtained are comparable to LC/MS/MS. This work demonstrates that low concentrationT4 quantification is feasible for toxicological studies, but attention to technical detail is pertinent.

Data set for the neurodevelopmental and somatic impacts of a perinatal exposure to stress coupled with Mn exposure on dams and their offspring.

Cognitive tests included in this assessment. Novel object recognition (NOR) test data: habituation trial, training trial and test trial. Morris water maze (MWM): Acquisition, reference probe, and reversal challenge Differential reinforcement of low rates (DRL): Autoshaping and efficiency data from DRL Cued and uncued choice reaction time (CRT): Accuracy, Anticipatory responding, decision and movement time.