Thyroid-Hormone–Disrupting Chemicals: Evidence for Dose-Dependent Additivity or Synergism

Endocrine disruption from environmental contaminants has been linked to a broad spectrum of adverse outcomes. One concern about endocrine-disrupting xenobiotics is the potential for additive or synergistic (i.e., greater-than-additive) effects of mixtures. A short-term dosing model to examine the effects of environmental mixtures on thyroid homeostasis has been developed. Prototypic thyroid-disrupting chemicals (TDCs) such as dioxins, polychlorinated biphenyls (PCBs), and poly-brominated diphenyl ethers have been shown to alter thyroid hormone homeostasis in this model primarily by up-regulating hepatic catabolism of thyroid hormones via at least two mechanisms. Our present effort tested the hypothesis that a mixture of TDCs will affect serum total thyroxine (T(4)) concentrations in a dose-additive manner. Young female Long-Evans rats were dosed via gavage with 18 different polyyhalogenated aromatic hydrocarbons [2 dioxins, 4 dibenzofurans, and 12 PCBs, including dioxin-like and non-dioxin-like PCBs] for 4 consecutive days. Serum total T(4) was measured via radioimmunoassay in samples collected 24 hr after the last dose. Extensive dose–response functions (based on seven to nine doses per chemical) were determined for individual chemicals. A mixture was custom synthesized with the ratio of chemicals based on environmental concentrations. Serial dilutions of this mixture ranged from approximately background levels to 100-fold greater than background human daily intakes. Six serial dilutions of the mixture were tested in the same 4-day assay. Doses of individual chemicals that were associated with a 30% TH decrease from control (ED(30)), as well as predicted mixture outcomes were calculated using a flexible single-chemical-required method applicable to chemicals with differing dose thresholds and maximum-effect asymptotes. The single-chemical data were modeled without and with the mixture data to determine, respectively, the expected mixture response (the additivity model) and the experimentally observed mixture response (the empirical model). A likelihood-ratio test revealed statistically significant departure from dose additivity. There was no deviation from additivity at the lowest doses of the mixture, but there was a greater-than-additive effect at the three highest mixtures doses. At high doses the additivity model underpredicted the empirical effects by 2- to 3-fold. These are the first results to suggest dose-dependent additivity and synergism in TDCs that may act via different mechanisms in a complex mixture. The results imply that cumulative risk approaches be considered when assessing the risk of exposure to chemical mixtures that contain TDCs

Incorporating New Technologies Into Toxicity Testing and Risk Assessment: Moving From 21st Century Vision to a Data-Driven Framework

Based on existing data and previous work, a series of studies is proposed as a basis toward a pragmatic early step in transforming toxicity testing. These studies were assembled into a data-driven framework that invokes successive tiers of testing with margin of exposure (MOE) as the primary metric. The first tier of the framework integrates data from high-throughput in vitro assays, in vitro-to-in vivo extrapolation (IVIVE) pharmacokinetic modeling, and exposure modeling. The in vitro assays are used to separate chemicals based on their relative selectivity in interacting with biological targets and identify the concentration at which these interactions occur. The IVIVE modeling converts in vitro concentrations into external dose for calculation of the point of departure (POD) and comparisons to human exposure estimates to yield a MOE. The second tier involves short-term in vivo studies, expanded pharmacokinetic evaluations, and refined human exposure estimates. The results from the second tier studies provide more accurate estimates of the POD and the MOE. The third tier contains the traditional animal studies currently used to assess chemical safety. In each tier, the POD for selective chemicals is based primarily on endpoints associated with a proposed mode of action, whereas the POD for nonselective chemicals is based on potential biological perturbation. Based on the MOE, a significant percentage of chemicals evaluated in the first 2 tiers could be eliminated from further testing. The framework provides a risk-based and animal-sparing approach to evaluate chemical safety, drawing broadly from previous experience but incorporating technological advances to increase efficiency

Methylphenidate Normalizes Fronto-Striatal Underactivation During Interference Inhibition in Medication-Naïve Boys with Attention-Deficit Hyperactivity Disorder

Youth with attention deficit hyperactivity disorder (ADHD) have deficits in interference inhibition, which can be improved with the indirect catecholamine agonist methylphenidate (MPH). Functional magnetic resonance imaging was used to investigate the effects of a single dose of MPH on brain activation during interference inhibition in medication-naïve ADHD boys. Medication-naïve boys with ADHD were scanned twice, in a randomized, double-blind design, under either a single clinical dose of MPH or placebo, while performing a Simon task that measures interference inhibition and controls for the oddball effect of low-frequency appearance of incongruent trials. Brain activation was compared within patients under either drug condition. To test for potential normalization effects of MPH, brain activation in ADHD patients under either drug condition was compared with that of healthy age-matched comparison boys. During incongruent trials compared with congruent–oddball trials, boys with ADHD under placebo relative to controls showed reduced brain activation in typical areas of interference inhibition, including right inferior prefrontal cortex, left striatum and thalamus, mid-cingulate/supplementary motor area, and left superior temporal lobe. MPH relative to placebo upregulated brain activation in right inferior prefrontal and premotor cortices. Under the MPH condition, patients relative to controls no longer showed the reduced activation in right inferior prefrontal and striato-thalamic regions. Effect size comparison, furthermore, showed that these normalization effects were significant. MPH significantly normalized the fronto-striatal underfunctioning in ADHD patients relative to controls during interference inhibition, but did not affect medial frontal or temporal dysfunction. MPH therefore appears to have a region-specific upregulation effect on fronto-striatal activation

Facebook Family Values: A News Feed Hierarchy Of Needs

Algorithmic curation is a growing influence on our information flows as it complements and sometimes supplants traditional mass media and personal information sharing. One of the primary agents of this rise in algorithmically-curated information flows is the Facebook News Feed, a onetime source of primarily entertainment that has, as of late, taken large strides towards the news business. It is fair to say that Facebook has a huge influence on our information, one that will likely expand in the future; even if not Facebook, similar systems will rule our information. Yet, we know next to nothing about how they work, as the algorithms that power them are sealed inside a black box. This thesis approaches the Facebook News Feed through a mix of qualitative and quantitative methods in a process dubbed “Negative Reverse Engineering” in an attempt to gain access to the contents of the black box not through traditional technical means, but through an analysis of Facebook’s values structure and needs. Components include an extensive, cross-disciplinary review of the literature, an experiment based around the generation of filter bubbles through the application of negative pressure, a grounded content analysis of Facebook’s statements and documents, an autoethnography of Facebook use, and a regression analysis of Facebook under duress. From this data, a Hierarchy of Needs for the News Feed is created, rejecting the model of News Feed filtering as an equation in favor of a holistic, values-based model