Health effects of toxicants: Online knowledge support

Research in toxicology generates vast quantities of data which reside on the Web and are subsequently appropriated and utilized to support further research. This data includes a broad spectrum of information about chemical, biological and radiological agents which can affect health, the nature of the effects, treatment, regulatory measures, and more. Information is structured in a variety of formats, including traditional databases, portals, prediction models, and decision making support tools. Online resources are created and housed by a variety of institutions, including libraries and government agencies. This paper focuses on three such institutions and the tools they offer to the public: the National Library of Medicine (NLM) and its Toxicology and Environmental Health Information Program, the United States Environmental Protection Agency (EPA), and the Organisation for Economic Co-operation and Development (OECD). Reference is also made to other relevant organizations.

Toxicokinetic Triage for Environmental Chemicals

Toxicokinetic (TK) models link administered doses to plasma, blood, and tissue concentrations. High-throughput TK (HTTK) performs in vitro to in vivo extrapolation to predict TK from rapid in vitro measurements and chemical structure-based properties. A significant toxicological application of HTTK has been "reverse dosimetry," in which bioactive concentrations from in vitro screening studies are converted into in vivo doses (mg/kg BW/day). These doses are predicted to produce steady-state plasma concentrations that are equivalent to in vitro bioactive concentrations. In this study, we evaluate the impact of the approximations and assumptions necessary for reverse dosimetry and develop methods to determine whether HTTK tools are appropriate or may lead to false conclusions for a particular chemical. Based on literature in vivo data for 87 chemicals, we identified specific properties (eg, in vitro HTTK data, physico-chemical descriptors, and predicted transporter affinities) that correlate with poor HTTK predictive ability. For 271 chemicals we developed a generic HT physiologically based TK (HTPBTK) model that predicts non-steady-state chemical concentration time-courses for a variety of exposure scenarios. We used this HTPBTK model to find that assumptions previously used for reverse dosimetry are usually appropriate, except most notably for highly bioaccumulative compounds. For the thousands of man-made chemicals in the environment that currently have no TK data, we propose a 4-element framework for chemical TK triage that can group chemicals into 7 different categories associated with varying levels of confidence in HTTK predictions. For 349 chemicals with literature HTTK data, we differentiated those chemicals for which HTTK approaches are likely to be sufficient, from those that may require additional data.

High throughput heuristics for prioritizing human exposure to environmental chemicals

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the hazard presented by the chemical and the extent of exposure. However, many chemicals lack estimates of exposure intake, limiting the understanding of health risks. We aim to develop a rapid heuristic method to determine potential human exposure to chemicals for application to the thousands of chemicals with little or no exposure data. We used Bayesian methodology to infer ranges of exposure consistent with biomarkers identified in urine samples from the U.S. population by the National Health and Nutrition Examination Survey (NHANES). We performed linear regression on inferred exposure for demographic subsets of NHANES demarked by age, gender, and weight using chemical descriptors and use information from multiple databases and structure-based calculators. Five descriptors are capable of explaining roughly 50% of the variability in geometric means across 106 NHANES chemicals for all the demographic groups, including children aged 6-11. We use these descriptors to estimate human exposure to 7968 chemicals, the majority of which have no other quantitative exposure prediction. For thousands of chemicals with no other information, this approach allows forecasting of average exposure intake of environmental chemicals.

In vitro and modelling approaches to risk assessment from the U.S. Environmental Protection Agency ToxCast programme

A significant challenge in toxicology is the 'too many chemicals' problem. Human beings and environmental species are exposed to tens of thousands of chemicals, only a small percentage of which have been tested thoroughly using standard in vivo test methods. This study reviews several approaches that are being developed to deal with this problem by the U.S. Environmental Protection Agency, under the umbrella of the ToxCast programme (http://epa.gov/ncct/toxcast/). The overall approach is broken into seven tasks: (i) identifying biological pathways that, when perturbed, can lead to toxicity; (ii) developing high-throughput in vitro assays to test chemical perturbations of these pathways; (iii) identifying the universe of chemicals with likely human or ecological exposure; (iv) testing as many of these chemicals as possible in the relevant in vitro assays; (v) developing hazard models that take the results of these tests and identify chemicals as being potential toxicants; (vi) generating toxicokinetics data on these chemicals to predict the doses at which these hazard pathways would be activated; and (vii) developing exposure models to identify chemicals for which these hazardous dose levels could be achieved. This overall strategy is described and briefly illustrated with recent examples from the ToxCast programme.

Dosimetric anchoring of in vivo and in vitro studies for perfluorooctanoate and perfluorooctanesulfonate

In order to compare between in vivo toxicity studies, dosimetry is needed to translate study-specific dose regimens into dose metrics such as tissue concentration. These tissue concentrations may then be compared with in vitro bioactivity assays to perhaps identify mechanisms relevant to the lowest observed effect level (LOEL) dose group and the onset of the observed in vivo toxicity. Here, we examine the perfluorinated compounds (PFCs) perfluorooctanoate (PFOA) and perfluorooctanesulfonate (PFOS). We analyzed 9 in vivo toxicity studies for PFOA and 13 in vivo toxicity studies for PFOS. Both PFCs caused multiple effects in various test species, strains, and genders. We used a Bayesian pharmacokinetic (PK) modeling framework to incorporate data from 6 PFOA PK studies and 2 PFOS PK studies (conducted in 3 species) to predict dose metrics for the in vivo LOELs and no observed effect levels (NOELs). We estimated PK parameters for 11 combinations of chemical, species, strain, and gender. Despite divergent study designs and species-specific PK, for a given effect, we found that the predicted dose metrics corresponding to the LOELs (and NOELs where available) occur at similar concentrations. In vitro assay results for PFOA and PFOS from EPA's ToxCast project were then examined. We found that most in vitro bioactivity occurs at concentrations lower than the predicted concentrations for the in vivo LOELs and higher than the predicted concentrations for the in vivo NOELs (where available), for a variety of nonimmunological effects. These results indicate that given sufficient PK data, the in vivo LOELs dose regimens, but not necessarily the effects, could have been predicted from in vitro studies for these 2 PFCs.

Evidence-based toxicology for the 21st century: opportunities and challenges

The Evidence-based Toxicology Collaboration (EBTC) was established recently to translate evidence-based approaches from medicine and health care to toxicology in an organized and sustained effort. The EBTC held a workshop on "Evidence-based Toxicology for the 21st Century: Opportunities and Challenges" in Research Triangle Park, North Carolina, USA on January 24-25, 2012. The presentations largely reflected two EBTC priorities: to apply evidence-based methods to assessing the performance of emerging pathway-based testing methods consistent with the 2007 National Research Council report on "Toxicity Testing in the 21st Century" as well as to adopt a governance structure and work processes to move that effort forward. The workshop served to clarify evidence-based approaches and to provide food for thought on substantive and administrative activities for the EBTC. Priority activities include conducting pilot studies to demonstrate the value of evidence-based approaches to toxicology, as well as conducting educational outreach on these approaches.

Perspectives on validation of high-throughput assays supporting 21st century toxicity testing

In vitro high-throughput screening (HTS) assays are seeing increasing use in toxicity testing. HTS assays can simultaneously test many chemicals but have seen limited use in the regulatory arena, in part because of the need to undergo rigorous, time-consuming formal validation. Here we discuss streamlining the validation process, specifically for prioritization applications. By prioritization, we mean a process in which less complex, less expensive, and faster assays are used to prioritize which chemicals are subjected first to more complex, expensive, and slower guideline assays. Data from the HTS prioritization assays is intended to provide a priori evidence that certain chemicals have the potential to lead to the types of adverse effects that the guideline tests are assessing. The need for such prioritization approaches is driven by the fact that there are tens of thousands of chemicals to which people are exposed, but the yearly throughput of most guideline assays is small in comparison. The streamlined validation process would continue to ensure the reliability and relevance of assays for this application. We discuss the following practical guidelines: (1) follow current validation practice to the extent possible and practical; (2) make increased use of reference compounds to better demonstrate assay reliability and relevance; (3) de-emphasize the need for cross-laboratory testing; and (4) implement a web-based, transparent, and expedited peer review process.

Update on EPA's ToxCast program: providing high throughput decision support tools for chemical risk management

The field of toxicology is on the cusp of a major transformation in how the safety and hazard of chemicals are evaluated for potential effects on human health and the environment. Brought on by the recognition of the limitations of the current paradigm in terms of cost, time, and throughput, combined with the ever increasing power of modern biological tools to probe mechanisms of chemical-biological interactions at finer and finer resolutions, 21st century toxicology is rapidly taking shape. A key element of the new approach is a focus on the molecular and cellular pathways that are the targets of chemical interactions. By understanding toxicity in this manner, we begin to learn how chemicals cause toxicity, as opposed to merely what diseases or health effects they might cause. This deeper understanding leads to increasing confidence in identifying which populations might be at risk, significant susceptibility factors, and key influences on the shape of the dose-response curve. The U. S. Environmental Protection Agency (EPA) initiated the ToxCast, or "toxicity forecaster", program 5 years ago to gain understanding of the strengths and limitations of the new approach by starting to test relatively large numbers (hundreds) of chemicals against an equally large number of biological assays. Using computational approaches, the EPA is building decision support tools based on ToxCast in vitro screening results to help prioritize chemicals for further investigation, as well as developing predictive models for a number of health outcomes. This perspective provides a summary of the initial, proof of concept, Phase I of ToxCast that has laid the groundwork for the next phases and future directions of the program.

The exposure data landscape for manufactured chemicals

The U.S. Environmental Protection Agency is developing chemical screening and prioritization programs to evaluate environmental chemicals for potential risk to human health in a rapid and efficient manner. As part of these efforts, it is important to catalog available information on chemical toxicity and exposure from widely dispersed sources. The main objective of this analysis is to define important aspects of the exposure space and to catalog the available exposure information for chemicals being considered for analysis as part of the U.S. EPA ToxCast™ screening and prioritization program. Publicly available exposure data have been extracted into ACToR (Aggregated Computational Toxicology Resource), which combines information for hundreds of thousands of chemicals from >600 public sources. We use data from ACToR to assess the exposure data landscape for environmental chemicals. Of the roughly 100,000 chemicals that have at least limited toxicity information available, less than one-fifth also have exposure information - and for most of these the information is of limited utility (e.g., production volume). Readily accessible data on concentrations in exposure-related media are only available for a much smaller fraction. Among these, the largest number of chemicals is measured in water with over 1150 unique compounds, followed by 788 substances measured in soil, and 670 in air. These small numbers clearly reflect a focus of resources on those substances previously identified as possibly posing a hazard to human health. Exposure to a much broader number of chemicals will need to be measured in order to fully realize the envisioned goal of using exposure information to guide toxicity testing.

Public databases supporting computational toxicology

A major goal of the emerging field of computational toxicology is the development of screening-level models that predict potential toxicity of chemicals from a combination of mechanistic in vitro assay data and chemical structure descriptors. In order to build these models, researchers need quantitative in vitro and ideally in vivo data for large numbers of chemicals for common sets of assays and endpoints. A number of groups are compiling such data sets into publicly available web-based databases. This article (1) reviews some of the underlying challenges to the development of the databases, (2) describes key technologies used (relational databases, ontologies, and knowledgebases), and (3) summarizes several major database efforts that are widely used in the computational toxicology field.

Evaluation of high-throughput genotoxicity assays used in profiling the US EPA ToxCast chemicals

Three high-throughput screening (HTS) genotoxicity assays-GreenScreen HC GADD45a-GFP (Gentronix Ltd.), CellCiphr p53 (Cellumen Inc.) and CellSensor p53RE-bla (Invitrogen Corp.)-were used to analyze the collection of 320 predominantly pesticide active compounds being tested in Phase I of US. Environmental Protection Agency's ToxCast research project. Between 9% and 12% of compounds were positive for genotoxicity in the assays. However, results of the varied tests only partially overlapped, suggesting a strategy of combining data from a battery of assays. The HTS results were compared to mutagenicity (Ames) and animal tumorigenicity data. Overall, the HTS assays demonstrated low sensitivity for rodent tumorigens, likely due to: screening at a low concentration, coverage of selected genotoxic mechanisms, lack of metabolic activation and difficulty detecting non-genotoxic carcinogens. Conversely, HTS results demonstrated high specificity, >88%. Overall concordance of the HTS assays with tumorigenicity data was low, around 50% for all tumorigens, but increased to 74-78% (vs. 60% for Ames) for those compounds producing tumors in rodents at multiple sites and, thus, more likely genotoxic carcinogens. The aim of the present study was to evaluate the utility of HTS assays to identify potential genotoxicity hazard in the larger context of the ToxCast project, to aid prioritization of environmentally relevant chemicals for further testing and assessment of carcinogenicity risk to humans.

The toxicity data landscape for environmental chemicals

OBJECTIVE

Thousands of chemicals are in common use, but only a portion of them have undergone significant toxicologic evaluation, leading to the need to prioritize the remainder for targeted testing. To address this issue, the U.S. Environmental Protection Agency (EPA) and other organizations are developing chemical screening and prioritization programs. As part of these efforts, it is important to catalog, from widely dispersed sources, the toxicology information that is available. The main objective of this analysis is to define a list of environmental chemicals that are candidates for the U.S. EPA screening and prioritization process, and to catalog the available toxicology information.

DATA SOURCES

We are developing ACToR (Aggregated Computational Toxicology Resource), which combines information for hundreds of thousands of chemicals from > 200 public sources, including the U.S. EPA, National Institutes of Health, Food and Drug Administration, corresponding agencies in Canada, Europe, and Japan, and academic sources.

DATA EXTRACTION

ACToR contains chemical structure information; physical-chemical properties; in vitro assay data; tabular in vivo data; summary toxicology calls (e.g., a statement that a chemical is considered to be a human carcinogen); and links to online toxicology summaries. Here, we use data from ACToR to assess the toxicity data landscape for environmental chemicals.

DATA SYNTHESIS

We show results for a set of 9,912 environmental chemicals being considered for analysis as part of the U.S. EPA ToxCast screening and prioritization program. These include high-and medium-production-volume chemicals, pesticide active and inert ingredients, and drinking water contaminants.

CONCLUSIONS

Approximately two-thirds of these chemicals have at least limited toxicity summaries available. About one-quarter have been assessed in at least one highly curated toxicology evaluation database such as the U.S. EPA Toxicology Reference Database, U.S. EPA Integrated Risk Information System, and the National Toxicology Program.

ACToR--Aggregated Computational Toxicology Resource

ACToR (Aggregated Computational Toxicology Resource) is a database and set of software applications that bring into one central location many types and sources of data on environmental chemicals. Currently, the ACToR chemical database contains information on chemical structure, in vitro bioassays and in vivo toxicology assays derived from more than 150 sources including the U.S. Environmental Protection Agency (EPA), Centers for Disease Control (CDC), U.S. Food and Drug Administration (FDA), National Institutes of Health (NIH), state agencies, corresponding government agencies in Canada, Europe and Japan, universities, the World Health Organization (WHO) and non-governmental organizations (NGOs). At the EPA National Center for Computational Toxicology, ACToR helps manage large data sets being used in a high-throughput environmental chemical screening and prioritization program called ToxCast.

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

BACKGROUND

Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex in vitro/in vivo datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.

RESULTS

The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated in vitro assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.

CONCLUSION

We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.

Bayesian meta-analysis of genetic association studies with different sets of markers

Robust assessment of genetic effects on quantitative traits or complex-disease risk requires synthesis of evidence from multiple studies. Frequently, studies have genotyped partially overlapping sets of SNPs within a gene or region of interest, hampering attempts to combine all the available data. By using the example of C-reactive protein (CRP) as a quantitative trait, we show how linkage disequilibrium in and around its gene facilitates use of Bayesian hierarchical models to integrate informative data from all available genetic association studies of this trait, irrespective of the SNP typed. A variable selection scheme, followed by contextualization of SNPs exhibiting independent associations within the haplotype structure of the gene, enhanced our ability to infer likely causal variants in this region with population-scale data. This strategy, based on data from a literature based systematic review and substantial new genotyping, facilitated the most comprehensive evaluation to date of the role of variants governing CRP levels, providing important information on the minimal subset of SNPs necessary for comprehensive evaluation of the likely causal relevance of elevated CRP levels for coronary-heart-disease risk by Mendelian randomization. The same method could be applied to evidence synthesis of other quantitative traits, whenever the typed SNPs vary among studies, and to assist fine mapping of causal variants.

Spectrum and prevalence of cardiac sodium channel variants among black, white, Asian, and Hispanic individuals: implications for arrhythmogenic susceptibility and Brugada/long QT syndrome genetic testing

OBJECTIVES

The purpose of this study was to determine the prevalence and spectrum of nonsynonymous polymorphisms (amino acid variants) in the cardiac sodium channel among healthy subjects.

BACKGROUND

Pathogenic mutations in the cardiac sodium channel gene, SCN5A, cause approximately 15 to 20% of Brugada syndrome (BrS1), 5 to 10% of long QT syndrome (LQT3), and 2 to 5% of sudden infant death syndrome.

METHODS

Using single-stranded conformation polymorphism, denaturing high-performance liquid chromatography, and/or direct DNA sequencing, mutational analysis of the protein-encoding exons of SCN5A was performed on 829 unrelated, anonymous healthy subjects: 319 black, 295 white, 112 Asian, and 103 Hispanic.

RESULTS

In addition to the four known common polymorphisms (R34C, H558R, S1103Y, and R1193Q), four relatively ethnic-specific polymorphisms were identified: R481W, S524Y, P1090L, and V1951L. Overall, 39 distinct missense variants (28 novel) were elucidated. Nineteen variants (49%) were found only in the black cohort. Only seven variants (18%) localized to transmembrane-spanning domains. Four variants (F1293S, R1512W, and V1951L cited previously as BrS1-causing mutations and S1787N previously published as a possible LQT3-causing mutation) were identified in this healthy cohort.

CONCLUSIONS

This study provides the first comprehensive determination of the prevalence and spectrum of cardiac sodium channel variants in healthy subjects from four distinct ethnic groups. This compendium of SCN5A variants is critical for proper interpretation of SCN5A genetic testing and provides an essential hit list of targets for future functional studies to determine whether or not any of these variants mediate genetic susceptibility for arrhythmias in the setting of either drugs or disease.

New and confirmatory evidence of an association between APOE genotype and baseline C-reactive protein in dyslipidemic individuals

We have investigated the association between APOE genotypes and C-reactive protein (CRP) levels in a cohort of approximately 600 individuals who were candidates for statin therapy. An association had been previously reported between the APOE3 allele and elevated CRP levels. That study only examined men. We have reproduced that association in men and have extended the finding to women. We also investigated the effect of the interaction between APOE genotype and hormone replacement therapy (HRT) status on CRP levels, adjusting for body mass index (BMI) and other covariates. BMI and HRT are also significant predictors of CRP, as previously reported. The effect of HRT is strong enough that the contribution of APOE genotype is no longer statistically significant among women on HRT. We also demonstrate that the presence or absence of the single SNP Cysl30Arg (which distinguishes APOE4 from APOE2 and APOE3) is sufficient to determine whether an individual is predisposed to higher or lower CRP levels. Essentially, the presence of one or two copies of APOE4 is associated with a reduction of CRP levels by approximately 34% relative to individuals with zero copies (1.73 mg/L for subjects with one or two copies versus 2.63 mg/L for subjects with zero copies of APOE4). We also tested previously reported associations between CRP levels and polymorphisms in the CRP and IL6 genes. These associations were not reproduced in our cohort.

Genome-wide evaluation of the public SNP databases

The public SNP databases are an important resource for groups performing genetic association and linkage studies. Both academic and commercial groups are developing large numbers of genotyping assays for SNPs in candidate genes or spread across the genome. These databases now contain in excess of 6 million SNPs that have been generated using a large number of methods and cohorts. Today, however, only a small fraction of these SNPs are well characterized and validated. The latest release of dbSNP contains ∼ 3.7 million non-redundant entries, only 0.5 million of which are validated, and 0.2 million of which have frequency information. Users of these databases have several common questions. How many of the SNPs are real? What is the frequency spectrum of the SNPs in these databases? What is the distribution picture of these SNPs across different ethnic and geographical populations? What fraction of the total number of SNPs is already captured by these databases? In order to address these questions, we compared the public SNPs against a well-characterized collection of gene-centric SNPs that we have developed. From this comparison, we find that > 50% of high frequency SNPs in the genome (> 20% minor allele frequency) have already been captured by these databases. The coverage drops dramatically below frequencies of 10%. At high frequencies, there is no sampling bias with respect to ethnicity or to regions of the genome. Finally, a relatively large fraction (> 40%) of SNPs in these databases were not seen in our study, which means that they are either of very low frequency, mismapped, or not polymorphic at all.

Using multiple drug exposure levels to optimize power in pharmacogenetic trials

Large-scale pharmacogenetic trials testing tens to hundreds of thousands of single-nucleotide polymorphisms (SNPs) will become possible in the near future given rapidly decreasing costs of genotyping. Devising optimal designs for these trials will be a significant challenge. The author demonstrates how the level of drug exposure may strongly affect the power to detect true associations between genetic polymorphisms and drug response. An analytic model of drug response is described that is used to simulate pharmacogenetic trials. Analytical and numerical sensitivity analyses are performed on the model to demonstrate possible exposure-sensitivity behaviors. This model shows that the power to detect an association can be a nonlinear, nonmonotonic function of drug exposure. This model is further investigated using two clinical trial designs. The conclusion is that trial designs that use more than one drug exposure or dose will have an increased likelihood of discovering statistically significant pharmacogenetic associations.

How many SNPs does a genome-wide haplotype map require?

We derive and compare several estimates of the number of SNPs that would be required to form the basis of a complete haplotype survey of the human genome. Our estimates make use of reports published by Stephens et al. [1], Patil et al. [2] and Daly et al. [3]. The estimated number of SNPs required for a genome-wide haplotype survey ranges from 180K (based on a European sample of 16 chromosomes) to 600K (based on an ethnically diverse sample of 164 chromosomes). We discuss the implications of using cohorts of different size and ethnic composition and the usefulness of public SNP databases for this effort. Finally, we estimate the experimental effort and cost required to complete a genome-wide haplotype survey.

Notes from the SNP vs. haplotype front

Single nucleotide polymorphisms (SNPs) and haplotypes are commonly used genetic markers in clinical studies. We provide some broad guidelines for deciding which of the two is most appropriate in particular circumstances. Molecular haplotyping techniques are also briefly reviewed and contrasted with electronic approaches.

The predictive power of haplotypes in clinical response

A variety of approaches have been proposed to find genetic markers that can be used in a clinical setting. Single nucleotide polymorphisms (SNPs) are the basis of the most commonly used approaches. Here we describe an approach using gene-based haplotypes, which are collections of SNPs located throughout the ftinctional regions of candidate genes, and organised as they occur separately on an individual's two chromosomes. The main point of this review is that the haplotype has greater power than any individual SNP to track an unobsenrved, but evolutionarily linked, variable site.

Computational evolution of a model polymer that folds to a specified target conformation

A method is described for folding polymers to specific target conformations. The approach uses a fast but approximate dynamics algorithm, coupled with a genetic algorithm that is used to evolve the large number of free parameters needed. The dynamics algorithm uses a state transition matrix approach. At each time step, the distances between pairs of atoms are adjusted by shifting them from Dij to Dij + Sij where Sij is an element of the state transition matrix S. Atom pairs that are attractive have Sij < 0 and pairs that are repulsive have S ij > 0. The atomic movement is carried out by gradient minimizing the molecular mechanics energy of the molecule subject to harmonic distance constraints. The method is applied to a simple test case, a 19 atom 2-D polymer. The paper also show that the S matrices can correctly fold a limited variety of initial conformations that differ from the one used during the evolution phase.

Minor burns. Modern management techniques

No matter how trivial a burn injury may appear, to the sufferer it is associated with pain and disability disproportionate to its size. Unless appropriately managed, even minor burns may become infected leading to a progression of local tissue damage and spreading cellulitis, with risks of septicaemia. Infection of the burn will not only delay healing but may produce significant local scarring with marked functional and cosmetic consequences. The management of any burn injury should provide: relief of the distressing symptoms; and the optimum environment for the healing of the damaged tissue. Formulation of this plan follows accurate assessment of the extent of the injury and an understanding of the processes of wound healing.

An intra-thyroidal branchial cyst: a case report

Branchial cleft cysts were previously thought not to occur in the thyroid but have recently been described in two patients with Hashimoto's disease. This case report describes a patient with a branchial cleft cyst in an otherwise normal thyroid gland and could provide further evidence that thyroidal follicular cells are derived from the branchial clefts as well as from the primitive gut.

Corynebacterium pseudotuberculosis: in vitro susceptibility to 39 antimicrobial agents

The minimal inhibitory concentrations of 39 antimicrobial agents for 54 isolates of Corynebacterium pseudotuberculosis in vitro have been determined. The most active agents were penicillins, macrolides, tetracyclines, cephalosporins, lincomycin, chloramphenicol, and rifampicin. Most isolates were resistant to aminoglycosides, nitrofurans, polymyxins, nalidixic acid, and cycloheximide.

Solitary liver abscess: a continuing medicosurgical problem

The management problems of 22 patients with solitary liver abscess are reviewed. To achieve earlier diagnosis, and reduce the high mortality rate of this condition (32% in this series), clinicians need to change their data base of the clinical presentation and also to incorporate liver imaging as part of the routine investigation of a patient with pyrexia of uncertain origin. The problems associated with operative diagnosis, and with methods of surgical drainage are discussed. The need for careful bacteriological cultures is emphasized, and the use of the most appropriate antibiotics is described. While in many cases the cause of the liver abscess remains unknown, in Australia the possibility of the abscess being amoebic or an infected hydatid cyst should be kept in mind.

Zollinger-Ellison syndrome caused by a duodenal wall tumour

An isolated benign duodenal wall gastrinoma is reported. The place of conservative gastrinoma excision versus total gastrectomy is briefly discussed in the light of present knowledge and recent advances in management.