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Globally, industries and regulatory authorities are faced with an urgent need to assess the potential adverse effects of chemicals more efficiently by embracing new approach methodologies (NAMs). NAMs include cell and tissue methods (in vitro), structure-based/toxicokinetic models (in silico), methods that assess toxicant interactions with biological macromolecules (in chemico), and alternative models. Increasing knowledge on chemical toxicokinetics (what the body does with chemicals) and toxicodynamics (what the chemicals do with the body) obtained from in silico and in vitro systems continues to provide opportunities for modernizing chemical risk assessments. However, directly leveraging in vitro and in silico data for derivation of human health-based reference values has not received regulatory acceptance due to uncertainties in extrapolating NAM results to human populations, including metabolism, complex biological pathways, multiple exposures, interindividual susceptibility and vulnerable populations. The objective of this article is to provide a standardized pragmatic framework that applies integrated approaches with a focus on quantitative in vitro to in vivo extrapolation (QIVIVE) to extrapolate in vitro cellular exposures to human equivalent doses from which human reference values can be derived. The proposed framework intends to systematically account for the complexities in extrapolation and data interpretation to support sound human health safety decisions in diverse industrial sectors (food systems, cosmetics, industrial chemicals, pharmaceuticals etc.). Case studies of chemical entities, using new and existing data, are presented to demonstrate the utility of the proposed framework while highlighting potential sources of human population bias and uncertainty, and the importance of Good Method and Reporting Practices.

Sodium-ion storage technologies are promising candidates for large-scale grid systems owing to the abundance and low cost of sodium. However, compared to well-understood lithium-ion storage mechanisms, sodium-ion storage remains relatively unexplored. Herein, we systematically determine the sodium-ion storage properties of anatase titanium dioxide (TiO2(A)). During the initial sodiation process, a thin surface layer (~3 to 5 nm) of crystalline TiO2(A) becomes amorphous but still undergoes Ti4+/Ti3+ redox reactions. A model explaining the role of the amorphous layer and the dependence of the specific capacity on the size of TiO2(A) nanoparticles is proposed. Amorphous nanoparticles of ~10 nm seem to be optimum in terms of achieving high specific capacity, on the order of 200 mAh g-1, at high charge/discharge rates. Kinetic studies of TiO2(A) nanoparticles indicate that sodium-ion storage is due to a surface-redox, capacitor-like reaction mechanism that is not dependent on nanoparticle size in contrast to the lithiation of TiO2(A) which is a diffusion-limited intercalation process. The surface-redox properties of TiO2(A) result in excellent rate capability, cycling stability and low overpotentials. Moreover, the surface-redox mechanism is instrumental in enabling thick electrodes of TiO2(A) retain high rate properties, and represent a promising direction for high-power sodium-ion storage.

Sodium-ion storage technologies are promising candidates for large-scale grid systems due to the abundance and low cost of sodium. However, compared to well-understood lithium-ion storage mechanisms, sodium-ion storage remains relatively unexplored. Herein, we systematically determine the sodium-ion storage properties of anatase titanium dioxide (TiO2(A)). During the initial sodiation process, a thin surface layer (~3 to 5 nm) of crystalline TiO2(A) becomes amorphous but still undergoes Ti4+/Ti3+ redox reactions. A model explaining the role of the amorphous layer and the dependence of the specific capacity on the size of TiO2(A) nanoparticles is proposed. Amorphous nanoparticles of ~10 nm seem to be optimum in terms of achieving high specific capacity, on the order of 200 mAh g−1, at high charge/discharge rates. Kinetic studies of TiO2(A) nanoparticles indicate that sodium-ion storage is due to a surface-redox mechanism that is not dependent on nanoparticle size in contrast to the lithiation of TiO2(A) which is a diffusion-limited intercalation process. The surface-redox properties of TiO2(A) result in excellent rate capability, cycling stability and low overpotentials. Moreover, tailoring the surface-redox mechanism enables thick electrodes of TiO2(A) to retain high rate properties, and represents a promising direction for high-power sodium-ion storage.

The developmental toxicity potential (dTP) concentration from the devTOX quickPredict (devTOXVPA and a series of structural analogues were tested with the devTOXThe EAD estimates for the VPA analogues based on different PK/PBPK models were quantitatively similar to in vivo data from both rats and humans, where available, and the derived rank order of the chemicals was consistent with observed in vivo developmental toxicity. Different models were identified that provided accurate predictions for rat prenatal LELs and conservative estimates of human safe exposure. The impact of in vitro kinetics on EAD estimates is chemical-dependent. EADs from this study were within range of predicted doses from other in vitro and model organism data.This study highlights the importance of pharmacokinetic considerations when using in vitro assays and demonstrates the utility of the devTOX

Engineered nanomaterials (ENMs) come in a wide array of shapes, sizes, surface coatings, and compositions, and often possess novel or enhanced properties compared to larger sized particles of the same elemental composition. To ensure the safe commercialization of products containing ENMs, it is important to thoroughly understand their potential risks. Given that ENMs can be created in an almost infinite number of variations, it is not feasible to conduct in vivo testing on each type of ENM. Instead, new approach methodologies (NAMs) such as in vitro or in chemico test methods may be needed, given their capacity for higher throughput testing, lower cost, and ability to provide information on toxicological mechanisms. However, the different behaviors of ENMs compared to dissolved chemicals may challenge safety testing of ENMs using NAMs. In this study, member agencies within the Interagency Coordinating Committee on the Validation of Alternative Methods were queried about what types of ENMs are of agency interest and whether there is agency-specific guidance for ENM toxicity testing. To support the ability of NAMs to provide robust results in ENM testing, two key issues in the usage of NAMs, namely dosimetry and interference/bias controls, are thoroughly discussed.

The formation of the soluble polysulfides (Na2Sn, 4 ≤ n ≤ 8) causes poor cycling performance for room temperature sodium–sulfur (RT Na–S) batteries. Moreover, the formation of insoluble polysulfides (Na2Sn, 2 ≤ n < 4) can slow down the reaction kinetics and terminate the discharge reaction before it reaches the final product. In this work, coffee residue derived activated ultramicroporous coffee carbon (ACC) material loading with small sulfur molecules (S2–4) as cathode material for RT Na–S batteries is reported. The first principle calculations indicate the space confinement of the slit ultramicropores can effectively suppress the formation of polysulfides (Na2Sn, 2 ≤ n ≤ 8). Combining with in situ UV/vis spectroscopy measurements, one‐step reaction RT Na–S batteries with Na2S as the only and final discharge product without polysulfides formation are demonstrated. As a result, the ultramicroporous carbon loaded with 40 wt% sulfur delivers a high reversible specific capacity of 1492 mAh g−1 at 0.1 C (1 C = 1675 mA g−1). When cycled at 1 C rate, the carbon–sulfur composite electrode exhibits almost no capacity fading after 2000 cycles with 100% coulombic efficiency, revealing excellent cycling stability and reversibility. The superb cycling stability and rate performance demonstrate ultramicropore confinement can be an effective strategy to develop high performance cathode for RT Na–S batteries., The coffee residue derived ultramicroporous carbon material loading with small sulfur molecules (S2–4) as cathode material for room temperature (RT) Na–S batteries can effectively suppress the formation of polysulfides (Na2Sn, 2 ≤ n ≤ 8). Due to the special reaction mechanism, the ultramicroporous carbon loaded with 40 wt% sulfur (ACC‐40S) exhibits good rate capability, low‐self discharge, and excellent cycling stability.

Moving towards species-relevant chemical safety assessments and away from animal testing requires access to reliable data to develop and build confidence in new approaches. The Integrated Chemical Environment (ICE) provides tools and curated data centered around chemical safety assessment. This article describes updates to ICE, including improved accessibility and interpretability of in vitro data via mechanistic target mapping and enhanced interactive tools for in vitro to in vivo extrapolation (IVIVE). Mapping of in vitro assay targets to toxicity endpoints of regulatory importance uses literature-based mode-of-action information and controlled terminology from existing knowledge organization systems to support data interoperability with external resources. The most recent ICE update includes Tox21 high-throughput screening data curated using analytical chemistry data and assay-specific parameters to eliminate potential artifacts or unreliable activity. Also included are physicochemical/ADME parameters for over 800,000 chemicals predicted by quantitative structure-activity relationship models. These parameters are used by the new ICE IVIVE tool in combination with the U.S. Environmental Protection Agency’s httk R package to estimate in vivo exposures corresponding to in vitro bioactivity concentrations from stored or user-defined assay data. These new ICE features allow users to explore the applications of an expanded data space and facilitate building confidence in non-animal approaches.

In the elevator main engine room, turning gear is one of the indispensable safety devices. The elevator turning gear is used to drive the main engine to rotate when the elevator is closed, and then stop the car at the corresponding position for rescue. The elevator turning mainly includes a disc and a drive shaft, wherein the drive shaft is provided with a gear, which is used to cooperate with the gear on the traction wheel of the main engine to drive the elevator traction wheel to rotate. The turning gear needs to be suspended when not in use. Because the disc is perpendicular to the drive shaft, when the drive shaft is normally installed on the disc, the drive shaft is horizontal, which will affect the space in the main engine room. Of course, there is also a separate design between the drive shaft and the disc. When the drive shaft needs to be installed on the disc through tools, the installation process is more troublesome. In order to solve the above technical problems, this paper studies a foldable manual turning of elevator, which saves space and is easy to install.

Recently, explanations of the sub-synchronous oscillation (SSO) caused by wind farms based on direct-driven wind generators (DDWGs) have been published in the literatures, in which the controller parameters of DDWGs and the system equivalent parameters play an important role. However, more than one set of parameters can cause weakly damped sub-synchronous modes. The most vulnerable and highly possible scenario is still unknown. To find scenarios that have potential oscillation risks, this paper proposes a small disturbance model of wind farms with DDWGs connected to the grid using a state-space modeling technique. Taguchi’s orthogonal array testing is introduced to generate different scenarios. Multiple scenarios with different parameter settings that may lead to SSOs are found. A probabilistic analysis method based on the Gaussian mixture model is employed to evaluate the consistency of these scenarios with the actual accidents. Electromagnetic transient simulations are performed to verify the findings.

In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.

Physiologically Based Pharmacokinetic (PBPK) models are often developed using animal data and applied to predict chemical movement and concentration in humans. However, differences in physiology and exposure routes between animal experiments and human exposures may impact the predictions and interpretation of PBPK model results. Data are needed to parameterize PBPK models, potentially requiring chemical-specific adjustment to model inputs. Since data may be limited for a chemical or exposure of interest, in silico approaches such as chemical structure-based modeling can help fill the gaps. This case study assesses generalized, open-source PBPK models for interspecies kinetic extrapolation of nicotine using both in vivo data from a rat oral gavage study and in silico predictions. Nicotine is used as a data-rich example chemical because PK data are available from different exposure routes in both humans and animals. Rat nicotine plasma data were obtained after oral gavage dosing of nicotine (up to 8 mg/kg/day over 7 days) and used to develop human nicotine models for both oral ingestion and buccal (mouth tissue) absorption. As an open-source buccal tissue absorption model was not available, we mimicked a buccal exposure by modifying the open-source model for the intravenous exposure route. An 8 mg/kg/day human dose using oral ingestion and buccal absorption resulted in an approximately 2- and 4-fold higher predicted maximum plasma concentration (Cmax) than an 8 mg/kg/day gavage exposure in rats, respectively, highlighting the impact of species and exposure route on model predictions. This study demonstrates that a generalized and open-source PBPK model can extrapolate the plasma kinetic profiles of nicotine between species using in vivo and in silico data after accounting for differences in exposure routes. In silico-informed model parameterizations provided similar results to rat in vivo-based parameterizations, highlighting the potential use of in silico approaches when data are limited.

New approach methodologies (NAMs) for toxicological applications such as in vitro assays and in silico models generate data that can be useful for assessing potential health impacts of chemicals. The National Toxicology Program’s (NTP’s) Integrated Chemical Environment (ICE; https://ice.ntp.niehs.nih.gov/ ) provides user-friendly access to NAM data and tools to explore and contextualize chemical bioactivity and molecular properties. ICE contains curated in vivo and in vitro toxicity testing data and experimental physicochemical property data gathered from different literature sources. ICE also contains computationally generated toxicity data and physicochemical parameter predictions. ICE provides interactive computational tools that characterize, analyze, and predict bioactivity for user-defined chemicals. ICE Search allows users to select and merge data sets for lists of chemicals and mixtures, yielding summary-level information, curated reference data, and bioactivity details mapped to mechanistic targets and modes of action. With the Curve Surfer tool, the user can explore concentration–response relationships of curated high-throughput screening assays. The Physiologically Based Pharmacokinetics (PBPK) tool predicts tissue-level concentrations resulting from in vivo doses, while the In Vitro–In Vivo Extrapolation (IVIVE) tool translates in vitro activity concentrations to equivalent in vivo dose estimates. The Chemical Characterization tool displays distributions of physicochemical properties, bioactivity- and structure-based projections, and consumer product use information. Chemical Quest, the newest ICE tool, allows users to search for structurally similar chemicals to a target chemical or substructure from within the extensive ICE database. Retrieved information on target chemicals and those with similar structures can then be used to query other ICE tools and datasets, greatly expanding data available to address the user’s question. ICE links to other NTP and U.S. Environmental Protection Agency data sources, expanding ICE’s capacity to examine chemicals based on physicochemical properties, bioactivity, and product use categories.

Chemicals that alter normal function of farnesoid X receptor (FXR) have been shown to affect the homeostasis of bile acids, glucose, and lipids. Several structural classes of environmental chemicals and drugs that modulated FXR transactivation were previously identified by quantitative high-throughput screening (qHTS) of the Tox21 10K chemical collection. In the present study, we validated the FXR antagonist activity of selected structural classes, including avermectin anthelmintics, dihydropyridine calcium channel blockers, 1,3-indandione rodenticides, and pyrethroid pesticides, using in vitro assay and quantitative structural-activity relationship (QSAR) analysis approaches. (Z)-Guggulsterone, chlorophacinone, ivermectin, and their analogs were profiled for their ability to alter CDCA-mediated FXR binding using a panel of 154 coregulator motifs and to induce or inhibit transactivation and coactivator recruitment activities of constitutive androstane receptor (CAR), liver X receptor alpha (LXRα), or pregnane X receptor (PXR). Our results showed that chlorophacinone and ivermectin had distinct modes of action (MOA) in modulating FXR-coregulator interactions and compound selectivity against the four aforementioned functionally-relevant nuclear receptors. These findings collectively provide mechanistic insights regarding compound activities against FXR and possible explanations for in vivo toxicological observations of chlorophacinone, ivermectin, and their analogs.

In vitro to in vivo extrapolation (IVIVE) leverages in vitro biological activities to predict corresponding in vivo exposures, therefore potentially reducing the need for animal safety testing that are traditionally performed to support the hazard and risk assessment. Interpretation of IVIVE predictions are affected by various factors including the model type, exposure route and kinetic assumptions for the test article, and choice of in vitro assay(s) that are relevant to clinical outcomes. Exposure scenarios are further complicated for mixtures where the in vitro activity may stem from one or more components in the mixture. In this study, we used electronic cigarette (EC) aerosols, a complex mixture, to explore impacts of these factors on the use of IVIVE in hazard identification, using open-source pharmacokinetic models of varying complexity and publicly available data. Results suggest in vitro assay selection has a greater impact on exposure estimates than modeling approaches. Using cytotoxicity assays, high exposure estimates (>1000 EC cartridges (pods) or > 700 mL EC liquid per day) would be needed to obtain the in vivo plasma levels that are corresponding to in vitro assay data, suggesting acute toxicity would be unlikely in typical usage scenarios. When mechanistic (Tox21) assays were used, the exposure estimates were much lower for the low end, but the range of exposure estimate became wider across modeling approaches. These proof-of-concept results highlight challenges and complexities in IVIVE for mixtures.

Endocrine-disrupting chemicals have the ability to interfere with and alter functions of the hormone system, leading to adverse effects on reproduction, growth and development. Despite growing concerns over their now ubiquitous presence in the environment, endocrine-related human health effects remain largely outside of comparative human toxicity characterization frameworks as applied for example in life cycle impact assessments. In this paper, we propose a new methodological framework to consistently integrate endocrine-related health effects into comparative human toxicity characterization. We present two quantitative and operational approaches for extrapolating towards a common point of departure from both in vivo and dosimetry-adjusted in vitro endocrine-related effect data and deriving effect factors as well as corresponding characterization factors for endocrine-active/endocrine-disrupting chemicals. Following the proposed approaches, we calculated effect factors for 323 chemicals, reflecting their endocrine potency, and related characterization factors for 157 chemicals, expressing their relative endocrine-related human toxicity potential. Developed effect and characterization factors are ready for use in the context of chemical prioritization and substitution as well as life cycle impact assessment and other comparative assessment frameworks. Endocrine-related effect factors were found comparable to existing effect factors for cancer and non-cancer effects, indicating that (1) the chemicals' endocrine potency is not necessarily higher or lower than other effect potencies and (2) using dosimetry-adjusted effect data to derive effect factors does not consistently overestimate the effect of potential endocrine disruptors. Calculated characterization factors span over 8-11 orders of magnitude for different substances and emission compartments and are dominated by the range in endocrine potencies.

A novel poly(catechol-diethylenetriamine-pphenylenediamine)(PCEA) adsorbent was synthesized in methanol, with chelating groups supplied by catechol and diethylenetriamine, which showed a strong removal performance and efficient adsorption toward Cu(II) ions in aqueous solution. The adsorbent was characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). Besides, factors such as adsorbent dosage, pH, initial ionic and metal concentrations, contact time, and temperature on the adsorption of Cu(II) were studied. The data revealed that the adsorption followed a pseudo-second order kinetic model and the adsorption rate was influenced by the intra-particle diffusion. Furthermore, the adsorption process followed the Langmuir isotherm model, and the maximum adsorption capacity (Qm) was 44.2 mg/g at 298 K in simulated wastewater. The value of ΔG (kJ/mol) and ΔH (kJ/mol) also demonstrated that the adsorption process was spontaneous and endothermic. Studies revealed that PCEA particles were powerful and stable for the removal of Cu(II) in water, and it could be directly applied to the Cu(II)-contaminated water.

d-Methionine and chitosan have been used for fabrication of nitrogen/sulfur-codoped carbon materials by a hydrothermal process followed by carbonization at 750°C for 3 h. The as-prepared carbon materials showed enhanced electrochemical performance, combining electrical double-layer capacitance with pseudocapacitance owing to the doping with sulfur and nitrogen. The specific capacitance of the obtained carbon material reached 135 F g−1 at current density of 1 A g−1, which is much higher than undoped chitosan (67 F g−1). The capacitance retention of the carbon material was almost 97.2% after 5000 cycles at current density of 1 A g−1. With such improved electrochemical performance, the nitrogen/sulfur-codoped carbon material may have promising potential for use in energy-storage electrodes of supercapacitors.

Background: Novel in vitro methods are being developed to identify chemicals that may interfere with estrogen receptor (ER) signaling, but the results are difficult to put into biological context because of reliance on reference chemicals established using results from other in vitro assays and because of the lack of high-quality in vivo reference data. The Organisation for Economic Co-operation and Development (OECD)-validated rodent uterotrophic bioassay is considered the “gold standard” for identifying potential ER agonists. Objectives: We performed a comprehensive literature review to identify and evaluate data from uterotrophic studies and to analyze study variability. Methods: We reviewed 670 articles with results from 2,615 uterotrophic bioassays using 235 unique chemicals. Study descriptors, such as species/strain, route of administration, dosing regimen, lowest effect level, and test outcome, were captured in a database of uterotrophic results. Studies were assessed for adherence to six criteria that were based on uterotrophic regulatory test guidelines. Studies meeting all six criteria (458 bioassays on 118 unique chemicals) were considered guideline-like (GL) and were subsequently analyzed. Results: The immature rat model was used for 76% of the GL studies. Active outcomes were more prevalent across rat models (74% active) than across mouse models (36% active). Of the 70 chemicals with at least two GL studies, 18 (26%) had discordant outcomes and were classified as both active and inactive. Many discordant results were attributable to differences in study design (e.g., injection vs. oral dosing). Conclusions: This uterotrophic database provides a valuable resource for understanding in vivo outcome variability and for evaluating the performance of in vitro assays that measure estrogenic activity. Citation: Kleinstreuer NC, Ceger PC, Allen DG, Strickland J, Chang X, Hamm JT, Casey WM. 2016. A curated database of rodent uterotrophic bioactivity. Environ Health Perspect 124:556–562; http://dx.doi.org/10.1289/ehp.1510183

Background: To effectively incorporate in vitro data into regulatory use, confidence must be established in the quantitative extrapolation of in vitro activity to relevant end points in animals or humans. Objective: Our goal was to evaluate and optimize in vitro to in vivo extrapolation (IVIVE) approaches using in vitro estrogen receptor (ER) activity to predict estrogenic effects measured in rodent uterotrophic studies. Methods: We evaluated three pharmacokinetic (PK) models with varying complexities to extrapolate in vitro to in vivo dosimetry for a group of 29 ER agonists, using data from validated in vitro [U.S. Environmental Protection Agency (U.S. EPA) ToxCast™ ER model] and in vivo (uterotrophic) methods. In vitro activity values were adjusted using mass-balance equations to estimate intracellular exposure via an enrichment factor (EF), and steady-state model calculations were adjusted using fraction of unbound chemical in the plasma (fu) to approximate bioavailability. Accuracy of each model-adjustment combination was assessed by comparing model predictions with lowest effect levels (LELs) from guideline uterotrophic studies. Results: We found little difference in model predictive performance based on complexity or route-specific modifications. Simple adjustments, applied to account for in vitro intracellular exposure (EF) or chemical bioavailability (fu), resulted in significant improvements in the predictive performance of all models. Conclusion: Computational IVIVE approaches accurately estimate chemical exposure levels that elicit positive responses in the rodent uterotrophic bioassay. The simplest model had the best overall performance for predicting both oral (PPK_EF) and injection (PPK_fu) LELs from guideline uterotrophic studies, is freely available, and can be parameterized entirely using freely available in silico tools. https://doi.org/10.1289/EHP1655

Background: To effectively incorporate in vitro data into regulatory use, confidence must be established in the quantitative extrapolation of in vitro activity to relevant end points in animals or ...

Transient voltages in the power grid are the key for the fault analysis of a power grid, optimized insulation design, and the standardization of the high-voltage testing method. The traditional measuring equipment, based on electrical engineering, normally has a limited bandwidth and response speed, which are also featured by a huge size and heavy weight. In this paper, an integrated optical electric-field sensor based on the Pockels effect was developed and applied to measure the transient voltages on the high-voltage conductors in a non-contact measuring mode. The measuring system has a response speed faster than 6 ns and a wide bandwidth ranging from 5 Hz to 100 MHz. Moreover, the sensors have the dimensions of 18 mm by 18 mm by 48 mm and a light weight of dozens of grams. The measuring systems were employed to monitor the lightning transient voltages on a 220 kV overhead transmission line. The switching transient voltages were also measured by the measuring system during the commissioning of the 500 kV middle Tibet power grid. In 2017, 307 lightning transient voltages caused by induction stroke were recorded. The characteristics of these voltage waveforms are different from the standard lightning impulse voltage proposed by IEC standards. Three types of typical switching transient voltage in 500 kV AC power grid were measured, and the peak values of these overvoltages can reach 1.73 times rated voltage.

Using in vitro data in human cell lines, several research groups have investigated changes in gene expression in cellular systems following exposure to extremely low frequency (ELF) and radiofrequency (RF) electromagnetic fields (EMF). For ELF EMF, we obtained five studies with complete microarray data and three studies with only lists of significantly altered genes. Likewise, for RF EMF, we obtained 13 complete microarray datasets and 5 limited datasets. Plausible linkages between exposure to ELF and RF EMF and human diseases were identified using a three-step process: (a) linking genes associated with classes of human diseases to molecular pathways, (b) linking pathways to ELF and RF EMF microarray data, and (c) identifying associations between human disease and EMF exposures where the pathways are significantly similar. A total of 60 pathways were associated with human diseases, mostly focused on basic cellular functions like JAK–STAT signaling or metabolic functions like xenobiotic metabolism by cytochrome P450 enzymes. ELF EMF datasets were sporadically linked to human diseases, but no clear pattern emerged. Individual datasets showed some linkage to cancer, chemical dependency, metabolic disorders, and neurological disorders. RF EMF datasets were not strongly linked to any disorders but strongly linked to changes in several pathways. Based on these analyses, the most promising area for further research would be to focus on EMF and neurological function and disorders.

Testicular necrosis is a sensitive endpoint for cadmium (Cd 2+ , Cd) toxicity across all species tested. Resistance to Cd-induced testicular damage is a recessive trait assigned to the Cdm locus on mouse chromosome 3. We first narrowed the Cdm -gene-containing region to 880 kb. SNP analysis of this region from two sensitive and two resistant inbred strains demonstrated a 400-kb haplotype block consistent with the Cd-induced toxicity phenotype; in this region is the Slc39a8 gene encoding a member of the solute-carrier superfamily. Slc39a8 encodes SLC39A8 (ZIP8), whose homologs in plant and yeast are putative zinc transporters. We show here that ZRT-, IRT-like protein (ZIP)8 expression in cultured mouse fetal fibroblasts leads to a >10-fold increase in the rate of intracellular Cd influx and accumulation and 30-fold increase in sensitivity to Cd-induced cell death. The complete ZIP8 mRNA and intron-exon splice junctions have no nucleotide differences between two sensitive and two resistant strains of mice; by using situ hybridization, we found that ZIP8 mRNA is prominent in the vascular endothelial cells of the testis of the sensitive strains of mice but absent in these cells of resistant strains. Slc39a8 is therefore the Cdm gene, defining sensitivity to Cd toxicity specifically in vascular endothelial cells of the testis.

Nuclear magnetic resonance (NMR) spectroscopy reveals that higher-order aggregates of glucagon-like peptide-1-(7–36)-amide (GLP-1) in pure water at pH 2.5 are disrupted by 35% 2,2,2-trifluoroethanol (TFE), and form a stable and highly symmetric helical self-aggregate. NMR spectra show that the helical structure is identical to that formed by monomeric GLP-1 under the same experimental conditions [Chang et al., Magn. Reson. Chem. 37 (2001) 477–483; Protein Data Bank at RCSB code: 1D0R], while amide proton exchange rates reveal a dramatic increase of the stability of the helices of the self-aggregate. Pulsed-field gradient NMR diffusion experiments show that the TFE-induced helical self-aggregate is a dimer. The experimental data and model calculations indicate that the dimer is a parallel coiled coil, with a few hydrophobic residues on the surface that may cause aggregation in pure water. The results suggest that the coiled coil dimer is an intermediate state towards the formation of higher aggregates, e.g. fibrils.

The influx of genomic sequence information has led to the concept of structural proteomics, the determination of protein structures on a genome-wide scale. Here we describe an approach to structural proteomics of small proteins using NMR spectroscopy. Over 500 small proteins from several organisms were cloned, expressed, purified, and evaluated by NMR. Although there was variability among proteomes, overall 20% of these proteins were found to be readily amenable to NMR structure determination. NMR sample preparation was centralized in one facility, and a distributive approach was used for NMR data collection and analysis. Twelve structures are reported here as part of this approach, which allowed us to infer putative functions for several conserved hypothetical proteins.

The farnesoid X receptor (FXR) regulates the homeostasis of bile acids, lipids and glucose. Because endogenous chemicals bind and activate FXR, it is important to examine which xenobiotic compounds would disrupt normal receptor function. We used a cell-based human FXR β-lactamase (Bla) reporter gene assay to profile the Tox21 10K compound collection of environmental chemicals and drugs. Structure-activity relationships of FXR-active compounds revealed by this screening were then compared against the androgen receptor, estrogen receptor α, peroxisome proliferator-activated receptors δ and γ and the vitamin D receptor. We identified several FXR-active structural classes including anthracyclines, benzimidazoles, dihydropyridines, pyrethroids, retinoic acids and vinca alkaloids. Microtubule inhibitors potently decreased FXR reporter gene activity. Pyrethroids specifically antagonized FXR transactivation. Anthracyclines affected reporter activity in all tested assays, suggesting non-specific activity. These results provide important information to prioritize chemicals for further investigation and suggest possible modes of action of compounds in FXR signaling.

Crystallographic and NMR studies of insulin have revealed a highly flexible molecule with a range of different aggregation and structural states; the importance of these states for the function of the hormone is still unclear. To address this question, we have studied the solution structure of the insulin R6 symmetric hexamer using NMR spectroscopy. Structure determination of symmetric oligomers by NMR is complicated due to `symmetry ambiguity' between intra- and intermonomer NOEs, and between different classes of intermonomer NOEs. Hence, to date, only two symmetric tetramers and one symmetric pentamer (VTB, B subunit of verotoxin) have been solved by NMR; there has been no other symmetric hexamer or higher-order oligomer. Recently, we reported a solution structure for R6 insulin hexamer. However, in that study, a crystal structure was used as a reference to resolve ambiguities caused by the threefold symmetry; the same method was used in solving VTB. Here, we have successfully recalculated R6 insulin using the symmetry-ADR method, a computational strategy in which ambiguities are resolved using the NMR data alone. Thus the obtained structure is a refinement of the previous R6 solution structure. Correlated motions in the final structural ensemble were analysed using a recently developed principal component method; this suggests the presence of two major conformational substates. The study demonstrates that the solution structure of higher-order symmetric oligomers can be determined unambiguously from NMR data alone, using the symmetry-ADR method. This success bodes well for future NMR studies of higher-order symmetric oligomers. The correlated motions observed in the structural ensemble suggest a new insight into the mechanism of phenol exchange and the T 6 ↔ R 6 transition of insulin in solution.

Background The data from DNA microarrays are increasingly being used in order to understand effects of different conditions, exposures or diseases on the modulation of the expression of various genes in a biological system. This knowledge is then further used in order to generate molecular mechanistic hypotheses for an organism when it is exposed to different conditions. Several different methods have been proposed to analyze these data under different distributional assumptions on gene expression. However, the empirical validation of these assumptions is lacking. Results Best fit hypotheses tests, moment-ratio diagrams and relationships between the different moments of the distribution of the gene expression was used to characterize the observed distributions. The data are obtained from the publicly available gene expression database, Gene Expression Omnibus (GEO) to characterize the empirical distributions of gene expressions obtained under varying experimental situations each of which providing relatively large number of samples for hypothesis testing. All data were obtained from either of two microarray platforms - the commercial Affymetrix mouse 430.2 platform and a non-commercial Rosetta/Merck one. The data from each platform were preprocessed in the same manner. Conclusions The null hypotheses for goodness of fit for all considered univariate theoretical probability distributions (including the Normal distribution) are rejected for more than 50% of probe sets on the Affymetrix microarray platform at a 95% confidence level, suggesting that under the tested conditions a priori assumption of any of these distributions across all probe sets is not valid. The pattern of null hypotheses rejection was different for the data from Rosetta/Merck platform with only around 20% of the probe sets failing the logistic distribution goodness-of-fit test. We find that there are statistically significant (at 95% confidence level based on the F-test for the fitted linear model) relationships between the mean and the logarithm of the coefficient of variation of the distributions of the logarithm of gene expressions. An additional novel statistically significant quadratic relationship between the skewness and kurtosis is identified. Data from both microarray platforms fail to identify with any one of the chosen theoretical probability distributions from an analysis of the l-moment ratio diagram.

Cellular stress by DNA damage induces checkpoint kinase-2 (CHK2)-mediated phosphorylation and stabilization of the E2F1 transcription factor, leading to induction of apoptosis by activation of a subset of proapoptotic E2F1 target genes, including Apaf1 and p73. This report characterizes an interaction between the aryl hydrocarbon (Ah) receptor (AHR), a ligand-activated transcription factor, and E2F1 that results in the attenuation of E2F1-mediated apoptosis. In Ahr−/− fibroblasts stably transfected with a doxycycline-regulated AHR expression vector, inhibition of AHR expression causes a significant elevation of oxidative stress, γH2A.X histone phosphorylation, and E2F1-dependent apoptosis, which can be blocked by small interfering RNA-mediated knockdown of E2F1 expression. In contrast, ligand-dependent AHR activation protects these cells from etoposide-induced cell death. In cells expressing both proteins, AHR and E2F1 interact independently of the retinoblastoma protein (RB), because AHR and E2F1 coimmunoprecipitate from extracts of RB-negative cells. Additionally, chromatin immunoprecipitation assays indicate that AHR and E2F1 bind to the Apaf1 promoter at a region containing a consensus E2F1 binding site but no AHR binding sites. AHR activation represses Apaf1 and TAp73 mRNA induction by a constitutively active CHK2 expression vector. Furthermore, AHR overexpression blocks the transcriptional induction of Apaf1 and p73 and the accumulation of sub-G0/G1 cells resulting from ectopic overexpression of E2F1. These results point to a proproliferative, antiapoptotic function of the Ah receptor that likely plays a role in tumor progression.

The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor that mediates the toxic effects of its xenobiotic ligands and acts as an environmental checkpoint during the cell cycle. We expressed stably integrated, Tet-Off-regulated AHR variants in fibroblasts from AHR-null mice to further investigate the AHR role in cell cycle regulation. Ahr+/+ fibroblasts proliferated significantly faster than Ahr-/- fibroblasts did, and exposure to a prototypical AHR ligand or deletion of the ligand-binding domain did not change their proliferation rates, indicating that the AHR function in cell cycle was ligand independent. Growth-promoting genes, such as cyclin and cyclin-dependent kinase genes, were significantly down-regulated in Ahr-/- cells, whereas growth-arresting genes, such as the transforming growth factor beta1 (TGF-beta1) gene, extracellular matrix (ECM)-related genes, and cyclin-dependent kinase inhibitor genes, were up-regulated. Ahr-/- fibroblasts secreted significantly more TGF-beta1 into the culture medium than Ahr+/+ fibroblasts did, and Ahr-/- showed increased levels of activated Smad4 and TGF-beta1 mRNA. Inhibition of TGF-beta1 signaling by overexpression of Smad7 reversed the proliferative and gene expression phenotype of Ahr-/- fibroblasts. Changes in TGF-beta1 mRNA accumulation were due to stabilization resulting from decreased activity of TTP, the tristetraprolin RNA-binding protein responsible for mRNA destabilization through AU-rich motifs. These results show that the Ah receptor possesses interconnected intrinsic cellular functions, such as ECM formation, cell cycle control, and TGF-beta1 regulation, that are independent of activation by either exogenous or endogenous ligands and that may play a crucial role during tumorigenesis.

Core 2 beta1,6-N-acetylglucosaminyltransferase I (C2GnT-I) plays a pivotal role in the biosynthesis of mucin-type O-glycans that serve as ligands in cell adhesion. To elucidate the three-dimensional structure of the enzyme for use in computer-aided design of therapeutically relevant enzyme inhibitors, we investigated the participation of cysteine residues in disulfide linkages in a purified murine recombinant enzyme. The pattern of free and disulfide-bonded Cys residues was determined by liquid chromatography/electrospray ionization tandem mass spectrometry in the absence and presence of dithiothreitol. Of nine highly conserved Cys residues, under both conditions, one (Cys217) is a free thiol, and eight are engaged in disulfide bonds, with pairs formed between Cys59-Cys413, Cys100-Cys172, Cys151-Cys199, and Cys372-Cys381. The only non-conserved residue within the beta1,6-N-acetylglucosaminyltransferase family, Cys235, is also a free thiol in the presence of dithiothreitol; however, in the absence of reductant, Cys235 forms an intermolecular disulfide linkage. Biochemical studies performed with thiolreactive agents demonstrated that at least one free cysteine affects enzyme activity and is proximal to the UDP-GlcNAc binding site. A Cys217 --Ser mutant enzyme was insensitive to thiol reactants and displayed kinetic properties virtually identical to those of the wild-type enzyme, thereby showing that Cys217, although not required for activity per se, represents the only thiol that causes enzyme inactivation when modified. Based on the pattern of free and disulfide-linked Cys residues, and a method of fold recognition/threading and homology modeling, we have computed a three-dimensional model for this enzyme that was refined using the T4 bacteriophage beta-glucosyltransferase fold.