Transparency in Modeling through Careful Application of OECD's QSAR/QSPR Principles via a Curated Water Solubility Data Set

The need for careful assembly, training, and validation of quantitative structure-activity/property models (QSAR/QSPR) is more significant than ever as data sets become larger and sophisticated machine learning tools become increasingly ubiquitous and accessible to the scientific community. Regulatory agencies such as the United States Environmental Protection Agency must carefully scrutinize each aspect of a resulting QSAR/QSPR model to determine its potential use in environmental exposure and hazard assessment. Herein, we revisit the goals of the Organisation for Economic Cooperation and Development (OECD) in our application and discuss the validation principles for structure-activity models. We apply these principles to a model for predicting water solubility of organic compounds derived using random forest regression, a common machine learning approach in the QSA/PR literature. Using public sources, we carefully assembled and curated a data set consisting of 10,200 unique chemical structures with associated water solubility measurements. This data set was then used as a focal narrative to methodically consider the OECD's QSA/PR principles and how they can be applied to random forests. Despite some expert, mechanistically informed supervision of descriptor selection to enhance model interpretability, we achieved a model of water solubility with comparable performance to previously published models (5-fold cross validated performance 0.81 R2 and 0.98 RMSE). We hope this work will catalyze a necessary conversation around the importance of cautiously modernizing and explicitly leveraging OECD principles while pursuing state-of-the-art machine learning approaches to derive QSA/PR models suitable for regulatory consideration.

Detection and toxicity modeling of anthraquinone dyes and chlorinated side products from a colored smoke pyrotechnic reaction

"Green" pyrotechnics seek to remove known environmental pollutants and health hazards from their formulations. This chemical engineering approach often focuses on maintaining performance effects upon replacement of objectionable ingredients, yet neglects the chemical products formed by the exothermic reaction. In this work, milligram quantities of a lab-scale pyrotechnic red smoke composition were functioned within a thermal probe for product identification by pyrolysis-gas chromatography-mass spectrometry. Thermally decomposed ingredients and new side product derivatives were identified at lower relative abundances to the intact organic dye (as the engineered sublimation product). Side products included chlorination of the organic dye donated by the chlorate oxidizer. Machine learning quantitative structure-activity relationship models computed impacts to health and environmental hazards. High to very high toxicities were predicted for inhalation, mutagenicity, developmental, and endocrine disruption for common military pyrotechnic dyes and their analogous chlorinated side products. These results underscore the need to revise objectives of "green" pyrotechnic engineering.

Integrating publicly available information to screen potential candidates for chemical prioritization under the Toxic Substances Control Act: A proof of concept case study using genotoxicity and carcinogenicity

The Toxic Substances Control Act (TSCA) became law in the U.S. in 1976 and was amended in 2016. The amended law requires the U.S. EPA to perform risk-based evaluations of existing chemicals. Here, we developed a tiered approach to screen potential candidates based on their genotoxicity and carcinogenicity information to inform the selection of candidate chemicals for prioritization under TSCA. The approach was underpinned by a large database of carcinogenicity and genotoxicity information that had been compiled from various public sources. Carcinogenicity data included weight-of-evidence human carcinogenicity evaluations and animal cancer data. Genotoxicity data included bacterial gene mutation data from the Salmonella (Ames) and Escherichia coli WP2 assays and chromosomal mutation (clastogenicity) data. Additionally, Ames and clastogenicity outcomes were predicted using the alert schemes within the OECD QSAR Toolbox and the Toxicity Estimation Software Tool (TEST). The evaluation workflows for carcinogenicity and genotoxicity were developed along with associated scoring schemes to make an overall outcome determination. For this case study, two sets of chemicals, the TSCA Active Inventory non-confidential portion list available on the EPA CompTox Chemicals Dashboard (33,364 chemicals, 'TSCA Active List') and a representative proof-of-concept (POC) set of 238 chemicals were profiled through the two workflows to make determinations of carcinogenicity and genotoxicity potential. Of the 33,364 substances on the 'TSCA Active List', overall calls could be made for 20,371 substances. Here 46.67%% (9507) of substances were non-genotoxic, 0.5% (103) were scored as inconclusive, 43.93% (8949) were predicted genotoxic and 8.9% (1812) were genotoxic. Overall calls for genotoxicity could be made for 225 of the 238 POC chemicals. Of these, 40.44% (91) were non-genotoxic, 2.67% (6) were inconclusive, 6.22% (14) were predicted genotoxic, and 50.67% (114) genotoxic. The approach shows promise as a means to identify potential candidates for prioritization from a genotoxicity and carcinogenicity perspective.

Evaluation of Existing QSAR Models and Structural Alerts and Development of New Ensemble Models for Genotoxicity Using a Newly Compiled Experimental Dataset

Regulatory agencies world-wide face the challenge of performing risk-based prioritization of thousands of substances in commerce. In this study, a major effort was undertaken to compile a large genotoxicity dataset (54,805 records for 9299 substances) from several public sources (e.g., TOXNET, COSMOS, eChemPortal). The names and outcomes of the different assays were harmonized, and assays were annotated by type: gene mutation in Salmonella bacteria (Ames assay) and chromosome mutation (clastogenicity) in vitro or in vivo (chromosome aberration, micronucleus, and mouse lymphoma Tk ^+/- assays). This dataset was then evaluated to assess genotoxic potential using a categorization scheme, whereby a substance was considered genotoxic if it was positive in at least one Ames or clastogen study. The categorization dataset comprised 8442 chemicals, of which 2728 chemicals were genotoxic, 5585 were not and 129 were inconclusive. QSAR models (TEST and VEGA) and the OECD Toolbox structural alerts/profilers (e.g., OASIS DNA alerts for Ames and chromosomal aberrations) were used to make in silico predictions of genotoxicity potential. The performance of the individual QSAR tools and structural alerts resulted in balanced accuracies of 57-73%. A Naïve Bayes consensus model was developed using combinations of QSAR models and structural alert predictions. The 'best' consensus model selected had a balanced accuracy of 81.2%, a sensitivity of 87.24% and a specificity of 75.20%. This in silico scheme offers promise as a first step in ranking thousands of substances as part of a prioritization approach for genotoxicity.

An automated framework for compiling and integrating chemical hazard data

Comparative chemical hazard assessment, which compares hazards for several endpoints across several chemicals, can be used for a variety of purposes including alternatives assessment and the prioritization of chemicals for further assessment. A new framework was developed to compile and integrate chemical hazard data for several human health and ecotoxicity endpoints from public online sources including hazardous chemical lists, Globally Harmonized System hazard codes (H-codes) or hazard categories from government health agencies, experimental quantitative toxicity values, and predicted values using Quantitative Structure-Activity Relationship (QSAR) models. QSAR model predictions were obtained using EPA's Toxicity Estimation Software Tool. Java programming was used to download hazard data, convert data from each source into a consistent score record format, and store the data in a database. Scoring criteria based on the EPA's Design for the Environment Program Alternatives Assessment Criteria for Hazard Evaluation were used to determine ordinal hazard scores (i.e., low, medium, high, or very high) for each score record. Different methodologies were assessed for integrating data from multiple sources into one score for each hazard endpoint for each chemical. The chemical hazard assessment (CHA) Database developed in this study currently contains more than 990,000 score records for more than 85,000 chemicals. The CHA Database and the methods used in its development may contribute to several cheminformatics, public health, and environmental activities.

The Next Generation Blueprint of Computational Toxicology at the U.S. Environmental Protection Agency

The U.S. Environmental Protection Agency (EPA) is faced with the challenge of efficiently and credibly evaluating chemical safety often with limited or no available toxicity data. The expanding number of chemicals found in commerce and the environment, coupled with time and resource requirements for traditional toxicity testing and exposure characterization, continue to underscore the need for new approaches. In 2005, EPA charted a new course to address this challenge by embracing computational toxicology (CompTox) and investing in the technologies and capabilities to push the field forward. The return on this investment has been demonstrated through results and applications across a range of human and environmental health problems, as well as initial application to regulatory decision-making within programs such as the EPA's Endocrine Disruptor Screening Program. The CompTox initiative at EPA is more than a decade old. This manuscript presents a blueprint to guide the strategic and operational direction over the next 5 years. The primary goal is to obtain broader acceptance of the CompTox approaches for application to higher tier regulatory decisions, such as chemical assessments. To achieve this goal, the blueprint expands and refines the use of high-throughput and computational modeling approaches to transform the components in chemical risk assessment, while systematically addressing key challenges that have hindered progress. In addition, the blueprint outlines additional investments in cross-cutting efforts to characterize uncertainty and variability, develop software and information technology tools, provide outreach and training, and establish scientific confidence for application to different public health and environmental regulatory decisions.

Linking Molecular Structure via Functional Group to Chemical Literature for Establishing a Reaction Lineage for Application to Alternatives Assessment

The evaluation of potential alternatives for chemicals of concern (CoC) requires an understanding of their potential human health and environmental impacts during the manufacture, use, recycle and disposal life stages. During the manufacturing phase, the processes used to produce a desired chemical are defined based on the sequence of chemical reactions and unit operations required to produce the molecule and separate it from other materials used or produced during its manufacture. This paper introduces and demonstrates a tool that links a chemical's structure to information about its synthesis route and the manufacturing process for that chemical. The structure of the chemical is entered using either a SMILES string or the molecule MOL file, and the molecule is searched to identify functional groups present. Based on those functional groups present, the respective named reactions that can be used in its synthesis routes are identified. This information can be used to identify input and output materials for each named reaction, along with reaction conditions, solvents, and catalysts that participate in the reaction. Additionally, the reaction database contains links to internet references and appropriate reaction-specific keywords, further increasing its comprehensiveness. The tool is designed to facilitate the cataloging and use of the chemical literature in a way that allows user to identify and evaluate information about the reactions, such as alternative solvents, catalysts, reaction conditions and other reaction products which enable the comparison of various reaction pathways for the manufacture of the subject chemical. The chemical manufacturing processing steps can be linked to a chemical process ontology to estimate releases and exposures occurring during the manufacturing phase of a chemical.

Prediction of pesticide acute toxicity using two-dimensional chemical descriptors and target species classification

Previous modelling of the median lethal dose (oral rat LD₅₀) has indicated that local class-based models yield better correlations than global models. We evaluated the hypothesis that dividing the dataset by pesticidal mechanisms would improve prediction accuracy. A linear discriminant analysis (LDA) based-approach was utilized to assign indicators such as the pesticide target species, mode of action, or target species - mode of action combination. LDA models were able to predict these indicators with about 87% accuracy. Toxicity is predicted utilizing the QSAR model fit to chemicals with that indicator. Toxicity was also predicted using a global hierarchical clustering (HC) approach which divides data set into clusters based on molecular similarity. At a comparable prediction coverage (~94%), the global HC method yielded slightly higher prediction accuracy (r² = 0.50) than the LDA method (r² ~ 0.47). A single model fit to the entire training set yielded the poorest results (r² = 0.38), indicating that there is an advantage to clustering the dataset to predict acute toxicity. Finally, this study shows that whilst dividing the training set into subsets (i.e. clusters) improves prediction accuracy, it may not matter which method (expert based or purely machine learning) is used to divide the dataset into subsets.

A framework for an alternatives assessment dashboard for evaluating chemical alternatives applied to flame retardants for electronic applications

The goal of alternatives assessment (AA) is to facilitate a comparison of alternatives to a chemical of concern, resulting in the identification of safer alternatives. A two stage methodology for comparing chemical alternatives was developed. In the first stage, alternatives are compared using a variety of human health effects, ecotoxicity, and physicochemical properties. Hazard profiles are completed using a variety of online sources and quantitative structure activity relationship models. In the second stage, alternatives are evaluated utilizing an exposure/risk assessment over the entire life cycle. Exposure values are calculated using screening-level near-field and far-field exposure models. The second stage allows one to more accurately compare potential exposure to each alternative and consider additional factors that may not be obvious from separate binned persistence, bioaccumulation, and toxicity scores. The methodology was utilized to compare phosphate-based alternatives for decabromodiphenyl ether (decaBDE) in electronics applications.

A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by identifying a subset of the key chemical descriptors associated with broad aquatic toxicity MoAs, and by providing a computational chemistry-based network classification model with reasonable prediction accuracy.

Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER binding. In vitro classification models yielded balanced accuracies ranging from 0.65 to 0.85 for the external prediction set. In vivo ER classification models yielded balanced accuracies ranging from 0.72 to 0.83. If used as additional biological descriptors for in vivo models, in vitro scores were found to increase the prediction accuracy of in vivo ER models. If in vitro activity was used directly as a surrogate for in vivo activity, the results were poor (balanced accuracy ranged from 0.49 to 0.72). Under-sampling negative compounds in the training set was found to increase the coverage (fraction of chemicals which can be predicted) and increase prediction sensitivity.

MOAtox: A comprehensive mode of action and acute aquatic toxicity database for predictive model development

The mode of toxic action (MOA) has been recognized as a key determinant of chemical toxicity and as an alternative to chemical class-based predictive toxicity modeling. However, the development of quantitative structure activity relationship (QSAR) and other models has been limited by the availability of comprehensive high quality MOA and toxicity databases. The current study developed a dataset of MOA assignments for 1213 chemicals that included a diversity of metals, pesticides, and other organic compounds that encompassed six broad and 31 specific MOAs. MOA assignments were made using a combination of high confidence approaches that included international consensus classifications, QSAR predictions, and weight of evidence professional judgment based on an assessment of structure and literature information. A toxicity database of 674 acute values linked to chemical MOA was developed for fish and invertebrates. Additionally, species-specific measured or high confidence estimated acute values were developed for the four aquatic species with the most reported toxicity values: rainbow trout (Oncorhynchus mykiss), fathead minnow (Pimephales promelas), bluegill (Lepomis macrochirus), and the cladoceran (Daphnia magna). Measured acute toxicity values met strict standardization and quality assurance requirements. Toxicity values for chemicals with missing species-specific data were estimated using established interspecies correlation models and procedures (Web-ICE; http://epa.gov/ceampubl/fchain/webice/), with the highest confidence values selected. The resulting dataset of MOA assignments and paired toxicity values are provided in spreadsheet format as a comprehensive standardized dataset available for predictive aquatic toxicology model development.

Comparison of global and mode of action-based models for aquatic toxicity

The ability to estimate aquatic toxicity is a critical need for ecological risk assessment and chemical regulation. The consensus in the literature is that mode of action (MOA) based toxicity models yield the most toxicologically meaningful and, theoretically, the most accurate results. In this study, a two-step prediction methodology was developed to estimate acute aquatic toxicity from molecular structure. In the first step, one-against-the-rest linear discriminant analysis (LDA) models were used to predict the MOA. The LDA models were able to predict the MOA with 85.8-88.8% accuracy for broad and specific MOAs, respectively. In the second step, a multiple linear regression (MLR) model corresponding to the predicted MOA was used to predict the acute aquatic toxicity value. The MOA-based approach was found to yield similar external prediction accuracy (r(2) = 0.529-0.632) to a single global MLR model (r(2) = 0.551-0.562) fit to the entire training set. Overall, the global hierarchical clustering approach yielded a higher combination of accuracy and prediction coverage (r(2) = 0.572, coverage = 99.3%) than the other approaches. Utilizing multiple two-dimensional chemical descriptors in MLR models yielded comparable results to using only the octanol-water partition coefficient (log K(ow)).

Does rational selection of training and test sets improve the outcome of QSAR modeling?

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

Gender and laterality affect recurrences of acute anterior uveitis

AIM

Acute anterior uveitis (AAU) associated with HLA-B27 or axial spondyloarthritis (axial SpA) is primarily unilateral and recurrent. We tested the hypotheses that disease laterality and gender affected recurrences of AAU.

METHODS

We studied 207 AAU subjects who were either HLA-B27 positive or had a verified history of axial SpA with documentation of the first uveitis episode. We recorded gender, laterality, duration, and time between episodes.

RESULTS

Of 207 subjects, 126 (60.9%) had axial spondyloarthritis. Of the 179 with known HLA-B27 status, 174 (97.2%) were HLA-B27 positive. The initial episode of AAU occurred slightly more often in the right eye, 109 (52.6%), than in the left, 91 (44.0%) or bilaterally, 7 (3.4%), but the difference between right and left was not significant (p=0.23). Interestingly, 69.4% of subsequent episodes occurred in the same eye affected previously (95% CI 59.3%, 78.3%, p=0.0001). In subjects with recurrent AAU, the probability of being disease-free for one year was 38.9% (95% CI 29.1%, 52.0%) using Kaplan-Meier estimates. Univariate analyses showed that male gender (p=0.03) and AAU which recurred in the same eye (p=0.04) was associated with a shorter time interval between episodes. Multivariate analysis by the Cox proportional hazards model showed similar results.

CONCLUSIONS

The initial episode of unilateral AAU associated with HLA-B27 or axial SpA randomly affects either eye. Subsequent episodes occur more often in the same eye previously affected. Male gender and history of unilateral AAU in the same eye are associated with a shortened time interval between relapses.

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

Predictive models for carcinogenicity and mutagenicity: frameworks, state-of-the-art, and perspectives

Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include Vitotox, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-throughput assays combined with innovative data-mining and in silico methods. Various initiatives in this regard have begun, including CAESAR, OSIRIS, CHEMOMENTUM, CHEMPREDICT, OpenTox, EPAA, and ToxCast. In silico methods can be used for priority setting, mechanistic studies, and to estimate potency. Ultimately, such efforts should lead to improvements in application of in silico methods for predicting carcinogenicity to assist industry and regulators and to enhance protection of public health.

Activation of nucleotide oligomerization domain 2 exacerbates a murine model of proteoglycan-induced arthritis

In addition to its role in innate immunity, nucleotide oligomerization domain 2 (NOD2) has been shown to play a suppressive role in models of colitis. Notably, mutations in NOD2 cause the inherited granulomatous disease of the joints called Blau syndrome, thereby linking NOD2 with joint disease as well. However, the role of NOD2 in joint inflammation has not been clarified. We demonstrate here that NOD2 is functional within the mouse joint and promotes inflammation, as locally or systemically administered muramyl dipeptide (MDP; the NOD2 agonist) resulted in significant joint inflammation that was abolished in NOD2-deficient mice. We then sought to investigate the role of NOD2 in a mouse model of inflammatory arthritis dependent on adaptive immunity using TCR-transgenic mice whose T cells recognized the dominant epitope of proteoglycan (PG). Mice immunized with PG in the presence of MDP developed a more severe inflammatory arthritis and histopathology within the joints. Antigen-specific activation of splenocytes was enhanced by MDP with respect to IFN-gamma production, which would be consistent with the Th1-mediated disease in vivo. Intriguingly, NOD2 deficiency did not alter the PG-induced arthritis, indicating that NOD2 does not play an essential role in this model of joint disease when it is not activated by MDP. In conclusion, we demonstrate that in a model of inflammatory arthritis dependent on T and B cell priming, NOD2 activation potentiates disease. However, the absence of NOD2 does not alter the course of inflammatory arthritis, in contrast to models of intestinal inflammation.

Activation of NOD2 in vivo induces IL-1beta production in the eye via caspase-1 but results in ocular inflammation independently of IL-1 signaling

Nucleotide-binding and oligomerization domain 2 (NOD2) belongs to the emerging Nod-like receptor (NLR) family considered important in innate immunity. Mutations in NOD2 cause Blau syndrome, an inherited inflammation of eye, joints, and skin. Mutations in a homologous region of another NLR member, NALP3, cause autoinflammation, wherein IL-1beta plays a critical role. Here, we tested the hypothesis that IL-1beta is a downstream mediator of NOD2-dependent ocular inflammation. We used a mouse model of NOD2-dependent ocular inflammation induced by muramyl dipeptide (MDP), the minimal bacterial motif sensed by NOD2. We report that MDP-induced ocular inflammation generates IL-1beta and IL-18 within the eye in a NOD2- and caspase-1-dependent manner. Surprisingly, two critical measures of ocular inflammation, leukocyte rolling and leukocyte intravascular adherence, appear to be completely independent of IL-1 signaling effects, as caspase-1 and IL-1R1-deficient mice still developed ocular inflammation in response to MDP. In contrast to the eye, a diminished neutrophil response was observed in an in vivo model of MDP-induced peritonitis in caspase-1-deficient mice, suggesting that IL-1beta is not essential in NOD2-dependent ocular inflammation, but it is involved, in part, in systemic inflammation triggered by NOD2 activation. This disparity may be influenced by IL-1R antagonist (IL-1Ra), as we observed differential IL-1Ra levels in the eye versus plasma at baseline levels and in response to MDP treatment. This report reveals a new in vivo function of NOD2 within the eye yet importantly, distinguishes NOD2-dependent from NALP3-dependent inflammation, as ocular inflammation in mice occurred independently of IL-1beta.

Anterior uveitis accompanies joint disease in a murine model resembling ankylosing spondylitis

BACKGROUND

Uveitis is often associated with a systemic inflammatory disease such as ankylosing spondylitis. Our understanding of the eye's susceptibility to immune-mediated uveitis as in the apparent absence of infection has been limited by a relative lack of experimental models. Here we sought to assess whether ocular inflammation occurs in a previously described murine model of proteoglycan-induced spondylitis, wherein mice develop progressive spondylitis, sacroiliitis and peripheral arthritis--features common to the clinical presentations of ankylosing spondylitis.

METHODS

Using intravital microscopy we examined the ocular inflammatory response after the onset of arthritis in mice that overexpressed the T cell receptor (TCR) specific for a dominant arthritogenic epitope of cartilage proteoglycan [TCR-Tg (transgenic) mice] or BALB/c controls.

RESULTS

Immunized TCR-Tg mice showed a significant increase in the number of rolling and adhering cells within the iris vasculature compared to adjuvant control mice. Cellular infiltration within the iris tissue, as assessed by intravital microscopy and histology, was also increased. Our initial temporal analysis has revealed that immunized TCR-Tg mice show a significant increase in intravascular inflammation by 2 weeks after immunization, but it diminishes at 4 weeks after immunization.

CONCLUSIONS

Although these data are preliminary, this model has the potential to clarify the mechanisms accounting for the coexistence of eye and sacroiliac inflammation as occurs in patients with ankylosing spondylitis.

Evolutionary genomics: codon volatility does not detect selection

Plotkin et al. introduce a method to detect selection that is based on an index called codon volatility and that uses only the sequence of a single genome, claiming that this method is applicable to a large range of sequenced organisms. Volatility for a given codon is the ratio of non-synonymous codons to all sense codons accessible by one point mutation. The significance of each gene's volatility is assessed by comparison with a simulated distribution of 10(6) synonymous versions of each gene, with synonymous codons drawn randomly from average genome frequencies. Here we re-examine their method and data and find that codon volatility does not detect selection, and that, even if it did, the genomes of Mycobacterium tuberculosis and Plasmodium falciparum, as well as those of most sequenced organisms, do not meet the assumptions necessary for application of their method.

Cloning, sequencing and expression analysis of the mouse NOD2/CARD15 gene

BACKGROUND

Mutations in the human NOD2/CARD15 gene have been associated with Crohn's disease and Blau syndrome. The objective of the present study was to clone the murine form of NOD2 and characterize its tissue distribution, function and response to inflammatory stimuli.

METHODS

Murine NOD2 was isolated using anchored polymerize chain reaction (PCR). Sequence analysis confirmed the identification of full-length cDNA representing the murine NOD2 gene. Using this sequence to search a Mus musculus supercontig database, NOD2 genomic DNA was identified. NOD2 was transfected into human embryonic kidney (HEK) cells and nuclear factor kappa B (NF-kappaB) activation was measured using a reporter assay. Tissue distribution and changes in transcription in mouse monocytes in response to inflammatory stimuli was determined by real time PCR.

RESULTS

The NOD2 gene spans 39 KB and contains 12 coding exons on chromosome 8. Expression of mouse NOD2 into HEK cells resulted in NF-kappaB activation. NOD2 was found to be expressed in all mouse tissues analyzed except skin, with highest levels in lung, thymus and spleen. NOD2 mRNA levels increased greater than two-fold in a monocyte cell line in response to lipopolysaccharide, lipoteichoic acid, interferon-g and tumor necrosis factor-alpha.

CONCLUSIONS

Common structural and functional features between human and mouse NOD2 were identified. This should allow for development of relevant animal models to evaluate the role of NOD2 in chronic inflammatory disorders.

Preparation of budesonide and budesonide-PLA microparticles using supercritical fluid precipitation technology

The objective of this study was to prepare and characterize microparticles of budesonide alone and budesonide and polylactic acid (PLA) using supercritical fluid (SCF) technology. A precipitation with a compressed antisolvent (PCA) technique employing supercritical CO2 and a nozzle with 100- microm internal diameter was used to prepare microparticles of budesonide and budesonide-PLA. The effect of various operating variables (temperature and pressure of CO2 and flow rates of drug-polymer solution and/or CO2) and formulation variables (0.25%, 0.5%, and 1% budesonide in methylene chloride) on the morphology and size distribution of the microparticles was determined using scanning electron microscopy. In addition, budesonide-PLA particles were characterized for their surface charge and drug-polymer interactions using a zeta meter and differential scanning calorimetry (DSC), respectively. Furthermore, in vitro budesonide release from budesonide-PLA microparticles was determined at 37 degrees C. Using the PCA process, budesonide and budesonide-PLA microparticles with mean diameters of 1 to 2 microm were prepared. An increase in budesonide concentration (0.25%-1% wt/vol) resulted in budesonide microparticles that were fairly spherical and less agglomerated. In addition, the size of the microparticles increased with an increase in the drug-polymer solution flow rate (1.4-4.7 mL/min) or with a decrease in the CO2 flow rate (50-10 mL/min). Budesonide-PLA microparticles had a drug loading of 7.94%, equivalent to approximately 80% encapsulation efficiency. Budesonide-PLA microparticles had a zeta potential of -37 +/- 4 mV, and DSC studies indicated that SCF processing of budesonide-PLA microparticles resulted in the loss of budesonide crystallinity. Finally, in vitro drug release studies at 37 degrees C indicated 50% budesonide release from the budesonide-PLA microparticles at the end of 28 days. Thus, the PCA process was successful in producing budesonide and budesonide-PLA microparticles. In addition, budesonide-PLA microparticles sustained budesonide release for 4 weeks.

Prediction of the acute toxicity (96-h LC50) of organic compounds to the fathead minnow (Pimephales promelas) using a group contribution method

A group contribution method has been developed to correlate the acute toxicity (96-h LC50) to the fathead minnow (Pimephales promelas) for 397 organic chemicals. Multilinear regression and computational neural networks (CNNs) were used for model building. The models were able to achieve a fairly good correlation of the data (r2 > 0.9). The linear model, which included four specific interaction terms, provided a rapid means of predicting the toxicity of a compound. The CNN model was able to yield virtually the same predictions with or without the four interaction terms that were included in the multilinear model.

Intraocular in vivo imaging of activated T-lymphocytes expressing green-fluorescent protein after stimulation with endotoxin

BACKGROUND

Intravital microscopy allows imaging of specific cell populations in vivo. The value of this technique is well established, but would be enhanced if one could distinguish functional states of cells in vivo. Interleukin-2 (IL-2) is expressed upon stimulation of T-cells and is a commonly used marker for T-cell activation. This study tests the use of enhanced green fluorescent protein (GFP) as a reporter gene for interleukin-2 (IL-2) expression in vivo.

METHODS

Characterization of mice that have the GFP gene under the control of IL-2 regulatory sequences has previously been published. Uveitis was induced by injection of E. coli endotoxin into the vitreous of these IL-2/GFPki transgenic mice. Four hours later, 3 microg of recombinant mouse IL-2 was injected into the anterior chambers of one group of mice. In vivo imaging of infiltrating cells in the iris stroma was performed with fluorescence microscopy at 6, 24, 48, and 72 h after endotoxin injection. The absolute number of fluorescent cells per mm2 was evaluated.

RESULTS

Eyes with endotoxin-induced uveitis had cells that expressed GFP and were identifiable by intravital microscopy. The fluorescent cells were exclusively seen in the subset of cells that had infiltrated the iris stroma or arrested along the vascular endothelium. The number of GFP-positive infiltrating cells in the iris increased from undetectable at baseline to 0.5 cells/mm2 at 6 h and 1.3 cells/mm2 at 72 h. The animals that received endotoxin as well as IL-2 tended to have more GFP-positive cells at the 48-h and 72-h time points, but these differences were not statistically significant

CONCLUSIONS

GFP is commonly used as a reporter gene for in vitro expression assays. The results presented here document that transgenic mice with GFP under the control of IL-2 regulatory elements can be used with intravital microscopy for in vivo expression assays that allow detection of activated T-cells at multiple time points within the same animal. This provides a novel method for temporal and spatial studies on the state of cell activation in inflammatory responses.

Inefficient assembly and intracellular accumulation of antibodies with mutations in V(H) CDR2

We previously described secretion defects in four mutants of the murine anti-phosphocholine Ab, T15. The mutant heavy (H) chains had amino acid replacements in the V(H) complementarity-determining region 2 (HCDR2) and were expressed at normal intracellular levels. Here, the intracellular fate of the secretion-defective mutant heavy chains was investigated. Metabolic labeling demonstrated that the T15 wild-type Ab was secreted within a 4-h chase. In contrast, the mutant H chains accumulated with intracellular t(1/2) values ranging from 10 to 24 h. The mutant H chains were associated with increased levels of the molecular chaperones BiP and GRP94, and remained endoglycosidase H sensitive, suggesting retention in the endoplasmic reticulum. Assembly of the mutant H chains with T15 light (L) chain was arrested at the H2 and H2L intermediate stages of the T15 wild-type pathway (H2 --> H2L --> H2L2). Even though some assembly with L chain occurred, it was not as a secretion-competent H2L2 Ig moiety. The T15 L chains coexpressed with mutant H chains were degraded efficiently except for a minor L chain population with a long t(1/2) that was apparently protected at the H2L stage. To our knowledge, this is the first study demonstrating that intracellular half-lives of Ig H and L chains can be influenced by somatic mutations in HCDR2.

Comparison of cuffed and uncuffed endotracheal tubes in young children during general anesthesia

BACKGROUND

Uncuffed endotracheal tubes are routinely used in young children. This study tests a formula for selecting appropriately sized cuffed endotracheal tubes and compares the use of cuffed versus uncuffed endotracheal tubes for patients whose lungs are mechanically ventilated during anesthesia.

METHODS

Full-term newborns and children (n = 488) through 8 yr of age who required general anesthesia and tracheal intubation were assigned randomly to receive either a cuffed tube sized by a new formula [size(mm internal diameter) = (age/4) + 3], or an uncuffed tube sized by the modified Cole's formula [size(mm internal diameter) = (age/4) + 4]. The number of intubations required to achieve an appropriately sized tube, the need to use more than 21.min-1 fresh gas flow, the concentration of nitrous oxide in the operating room, and the incidence of croup were compared.

RESULTS

Cuffed tubes selected by our formula were appropriate for 99% of patients. Uncuffed tubes selected by Cole's formula were appropriate for 77% of patients (P < 0.001). The lungs of patients with cuffed tubes were adequately ventilated with 2 1.min-1 fresh gas flow, whereas 11% of those with uncuffed tubes needed greater fresh gas flow (P < 0.001). Ambient nitrous oxide concentration exceeded 25 parts per million in 37% of cases with uncuffed tubes and in 0% of cases with cuffed tubes (P < 0.001). Three patients in each group were treated for croup symptoms (1.2% cuffed; 1.3% uncuffed).

CONCLUSIONS

Our formula for cuffed tube selection is appropriate for young children. Advantages of cuffed endotracheal tubes include avoidance of repeated laryngoscopy, use of low fresh gas flow, and reduction of the concentration of anesthetics detectable in the operating room. We conclude that cuffed endotracheal tubes may be used routinely during controlled ventilation in full-term newborns and children during anesthesia.

Deletion in HCDR3 rescues T15 antibody mutants from a secretion defect caused by mutations in HCDR2

We recently described mutants of the murine anti-phosphocholine Ab T15, with changes in heavy chain complementarity determining region 2 (HCDR2) that caused loss of secretion. Surprisingly, the T15 HCDR2 mutations did not alter secretion when placed into the related anti-phosphocholine Ab D16, which differs from T15 only in HCDR3 and light (L) chain. Here, we exploit the differences between these two Abs to assess the basis of the secretion defect. The T15 L chain is not secreted in the absence of heavy (H) chain. In contrast, D16 L chain is secreted in the absence of H chain, as are most L chains. We co-expressed the T15 wild-type (wt) and mutant H chains with the D16 L chain, as well as with another secreted L chain, J558L. The mutant H chains were not secreted when expressed with either heterologous L chain. These results establish that the T15 L chain is not uniquely associated with the defect. The T15 and D16 Abs also differ in HCDR3 length in that D16 lacks four amino acid residues (Ser99, Ser100, Tyr100a, Trp100b) present in T15. We deleted these four residues from T15 wt and mutant H chains. Secretion of T15 wt was unaffected by the deletion, but shortening HCDR3 restored secretion in the HCDR2 mutants regardless of L chain association. Together these data demonstrate that both the HCDR2 and HCDR3 domains contain structural information that may affect the secretion competence of Abs.

Deletion in HCDR3 rescues T15 antibody mutants from a secretion defect caused by mutations in HCDR2

We recently described mutants of the murine anti-phosphocholine Ab T15, with changes in heavy chain complementarity determining region 2 (HCDR2) that caused loss of secretion. Surprisingly, the T15 HCDR2 mutations did not alter secretion when placed into the related anti-phosphocholine Ab D16, which differs from T15 only in HCDR3 and light (L) chain. Here, we exploit the differences between these two Abs to assess the basis of the secretion defect. The T15 L chain is not secreted in the absence of heavy (H) chain. In contrast, D16 L chain is secreted in the absence of H chain, as are most L chains. We co-expressed the T15 wild-type (wt) and mutant H chains with the D16 L chain, as well as with another secreted L chain, J558L. The mutant H chains were not secreted when expressed with either heterologous L chain. These results establish that the T15 L chain is not uniquely associated with the defect. The T15 and D16 Abs also differ in HCDR3 length in that D16 lacks four amino acid residues (Ser99, Ser100, Tyr100a, Trp100b) present in T15. We deleted these four residues from T15 wt and mutant H chains. Secretion of T15 wt was unaffected by the deletion, but shortening HCDR3 restored secretion in the HCDR2 mutants regardless of L chain association. Together these data demonstrate that both the HCDR2 and HCDR3 domains contain structural information that may affect the secretion competence of Abs.

Binding of phenylphosphocholine-carrier conjugates to the combining site of antibodies maintains a conformation of the hapten

The structural basis of the binding of phenylphosphocholine haptens to antibodies was studied. This was done by preparing antibodies and testing binding to conjugates of phenylphosphocholine. The choice of haptens was made in order to evaluate the contribution of the carrier to binding, and its effect on hapten conformation in the active site. Thus, phosphocholine (PC) was diazophenyl-linked to tyrosine or histidine as single amino acid carriers and to tripeptides or octapeptides containing tyrosine or histidine as central amino acids to which PC was attached. Relative affinity was assessed by inhibition enzyme-linked immunosorbent assay (ELISA) and binding constants were determined by fluorescence quenching. Fluorinated haptens were used to determine the kinetics of binding using 19F nuclear magnetic resonance. The transferred nuclear Overhauser effect was used to characterize conformation of the bound hapten. We had previously shown that nitrophenylphosphocholine unlinked to carrier is bound in the active site as a bent structure [Bruderer, U., Peyton, D. H., Barbar, E., Fellman, J. H., & Rittenberg, M. B. (1992) Biochemistry 31, 584-589]. We show here that this same bent conformation is retained in the active site regardless of the neighboring carrier or the conformation of the hapten in the unbound conjugate. The presence of the carrier residues in the bound state does, however, influence affinity.

Posttonsillectomy vomiting. Ondansetron or metoclopramide during paediatric tonsillectomy: are two doses better than one?

This randomized, double blinded, placebo controlled, prospective study compared the anti-emetic efficacy of one preoperative dose of metoclopramide 0.25 mg.kg-1 intravenously or ondansetron 0.15 mg.kg-1 intravenously with two doses of the same drugs (second dose administered one h postoperatively) in 200 preadolescent children undergoing tonsillectomy with either isoflurane or propofol anaesthesia. The incidence of posttonsillectomy vomiting was significantly reduced (P < 0.005) by two doses of either metoclopramide or ondansetron (18% and 8%, respectively) compared with placebo (50%). No difference in posttonsillectomy vomiting exists between the children who received isoflurane and those who received a propofol infusion. Our results suggest that two doses of metoclopramide 0.25 mg.kg-1 intravenously, like two doses of ondansetron 0.15 mg.kg-1, are effective in reducing vomiting after tonsillectomy in children who have received either isoflurane or propofol anaesthesia.

Ondansetron reduces the incidence and severity of poststrabismus repair vomiting in children

This prospective, randomized, placebo-controlled, double-blinded study evaluated the antiemetic efficacy of ondansetron and metoclopramide in 90 ASA physical status I or II children, 2-17 yr of age, undergoing strabismus repair. After anesthetic induction and prior to eye muscle manipulation, subjects received normal saline 0.3 mL/kg (Group 1), metoclopramide 0.25 mg/kg (Group 2), or ondansetron 0.15 mg/kg (Group 3), intravenously. There were no differences between groups with respect to age, weight, gender, fluids received, number of eye muscles repaired, anesthetic technique, or time in the operating room. The incidence of vomiting in Groups 1, 2, and 3 was 50%, 27%, and 10% prior to discharge, and 67%, 53%, and 30% during the 24 h after surgery, respectively. The number of children vomiting prior to discharge and within 24 h of surgery was significantly reduced in Group 3 compared with Group 1 (P < 0.003 and P < 0.015, respectively). The number of vomiting episodes per patient in Groups 1, 2, and 3 was 1.1, 0.5, and 0.1 prior to discharge, and 4.5, 2.6, and 1.2 during the 24 h after surgery (P < 0.0005 and P < 0.004, respectively). Ondansetron 0.15 mg/kg intravenously after the induction of anesthesia reduces the incidence and severity of vomiting after strabismus repair both prior to discharge from the hospital and during the 24 h after surgery.

Defective secretion of an immunoglobulin caused by mutations in the heavy chain complementarity determining region 2

We have investigated four secretion-deficient antibodies (Abs) derived from a panel of 46 mutant T15 anti-phosphocholine Abs, all of which have point mutations in the heavy chain (H) complementarity determining region 2 (CDR2). The level of secretion for these four Abs was < 10% of wild type when expressed together with the T15 light chain (L) in either SP2/0 or P3X63Ag8.653 myeloma cells although normal levels of H and L chain mRNA were produced. Moreover, abundant intracellular H and L chain proteins were detected. Three of the four mutants had little or no assembled H and L complexes intracellularly whereas one had a significant amount of intracellular immunoglobulin (Ig) which was shown to be capable of binding Ag. Thus, we demonstrate for the first time that point mutations confined to CDR2 of the H chain variable (V) region can impede Ab assembly and secretion. We then introduced the same CDR2 mutations into a related H chain which is encoded by the same T15 VH gene but different diversity (D) and joining (J) genes. When these H chains were expressed with a non-T15 L chain, the resulting Abs were secreted normally. The results thus suggest that the effects of the CDR2 mutations on Ab secretion are dependent on their interactions with L and/or H chain D-J sequences. These results also reveal a novel mechanism that could contribute to B cell wastage.

PKA-dependent regulation of mKv1.1, a mouse Shaker-like potassium channel gene, when stably expressed in CHO cells

Potassium (K) channels are important regulators of cellular physiology and can themselves be modulated by phosphorylation. We have investigated the potential protein kinase A (PKA) regulation of mKv1.1, a mouse Shaker-like K channel gene, when it is expressed in stably transfected Chinese hamster ovary (CHO) cell lines. Whole-cell patch-clamp records show that expression of mKv1.1 gives rise to a rapidly activating, sustained K+ current, referred to classically as a delayed rectifier-type current. In order to study the effects of PKA, we compared cell lines transfected with mKv1.1 alone with lines cotransfected with both mKv1.1 and a plasmid encoding a dominant negative mutation in the regulatory subunit of PKA. These mutant regulatory subunits bind to endogenous catalytic subunits of PKA but do not respond to cAMP, thereby causing a chronic reduction in the basal PKA activity in these cells. We found that mKv1.1 current kinetics are unaltered but current density is 3.4-fold higher in the cell lines expressing mutant regulatory subunit than in lines expressing only mKv1.1. RNase protection assays indicate that levels of the specific RNA for mKv1.1 are increased almost twofold in the lines expressing mutant regulatory subunit over the lines expressing mKv1.1 only. Further, the levels of mKv1.1 protein, assayed using an mKv1.1 channel-specific antibody, are increased by almost a factor of 3 between the two types of cell lines. These results suggest that PKA can regulate mKv1.1 channel expression by changing steady-state levels of RNA and by other posttranscriptional mechanisms.

Heteromultimeric K+ channels in terminal and juxtaparanodal regions of neurons

Voltage-gated potassium (K+) channels display a wide variety of conductances and gating properties in vivo. This diversity can be attributed not only to the presence of many K(+)-channel gene products, but also to the possibility that different K(+)-channel subunits co-assemble to form heteromultimeric channels in vivo. When expressed in Xenopus oocytes or transfected cells, K(+)-channel polypeptides assemble to form tetramers. Certain combinations of Shaker-like subunits have been shown to co-assemble, forming heteromultimeric channels with distinct properties. It is not known, however, whether K(+)-channel polypeptides form heteromultimeric channels in vivo. Here we describe the co-localization of two Shaker-like voltage-gated K(+)-channel proteins, mKv1.1 and mKv1.2, in the juxtaparanodal regions of nodes of Ranvier in myelinated axons, and in terminal fields of basket cells in mouse cerebellum. We also show that mKv1.1 and mKv1.2 can be coimmunoprecipitated with specific antibodies that recognize only one of them. These data indicate that the two polypeptides occur in subcellular regions where rapid membrane repolarization may be important and that they form heteromultimeric channels in vivo.

Propofol anesthesia reduces emesis and airway obstruction in pediatric outpatients

This study was an authors comparison of the effects of and recovery from anesthesia in healthy, premedicated pediatric outpatients who received either inhaled anesthetics (group 1) or propofol (group 2). Group 1 (n = 68) averaged 3.8 +/- 0.2 yr and weighed 17.7 +/- 0.8 kg, whereas group 2 (n = 75) averaged 3.3 +/- 0.2 yr and weighed 16.3 +/- 0.6 kg. The incidence of vomiting in the Postanesthetic Care Unit (PACU) and from discharge to the first postoperative morning was lower in the group receiving propofol (0% and 18%) than in the group receiving volatile agents (7% and 34%, P < 0.05). The incidence of airway obstruction during induction of anesthesia was higher (34% vs 10%, P < 0.01) in children receiving inhaled agent. Withdrawal of the extremity with propofol injection occurred in 14 (19%) patients. Arterial blood pressure was higher at loss of consciousness, laryngoscopy, and tracheal intubation in group 2 (P < 0.01). The length of time from the end of surgery to extubation of the trachea, recovery scores, and length of time spent in the PACU and the Day Surgery Unit were the same in the two groups. Pain scores obtained in the PACU were not different. The data indicate that propofol can be used safely to induce and maintain anesthesia in healthy pediatric outpatients. This coupled with the low incidence of vomiting and airway obstruction in the propofol group suggests distinct and compelling reasons to consider using the drug in this patient population.