What made you wait so long? Delays in presentation of retinal detachment: knowledge is related to an attached macula.

PURPOSE: In rhegmatogenous retinal detachment, the time between first symptoms and reattachment surgery is critical to prevent macular detachment. We explored which determinants discriminate between 'macula-ON' and 'macula-OFF' retinal detachments to improve timely treatment. METHODS: Eight-hundred patients with rhegmatogenous retinal detachment admitted for surgery at the Rotterdam Eye Hospital in the Netherlands were eligible to complete a questionnaire to explore the following determinants: (i) patient's delay and doctor's delay; (ii) patient-reported causes for delay; (iii) symptoms as early warning signals; (iv) patient's prior knowledge about retinal detachment; and (v) trait anxiety. RESULTS: Five hundred and twenty-one questionnaires (65%) were analysed. Median interval between first symptoms and surgery was 14 days. Macula-ON/OFF ratio was 46/54. Patient's delay in macula-ON patients (median 3 days) was shorter than in macula-OFF (5 days, p = 0.026). No difference was found in doctor's delay except for 'waiting time for surgery': macula-ON patients were operated on faster (median 1 day) than macula-OFF (median 5 days, p < 0.001). Macula-ON patients more often attributed symptoms to retinal problems. Except floaters, no symptoms were determined as early warning signals for macula-ON. Macula-ON patients more often reported knowing that prognosis would be worse when treated later, even when controlled for previous experience with retinal detachment. CONCLUSION: Macula-ON patients seem to self-refer faster to a healthcare provider, seem more sensitive to floaters and seem more informed. This suggests that increasing awareness, especially about floaters, might increase the proportion of patients with macula still on at the moment of referral to the ophthalmologist.

Prediction of adverse drug reactions using decision tree modeling.

Drug safety is of great importance to public health. The detrimental effects of drugs not only limit their application but also cause suffering in individual patients and evoke distrust of pharmacotherapy. For the purpose of identifying drugs that could be suspected of causing adverse reactions, we present a structure-activity relationship analysis of adverse drug reactions (ADRs) in the central nervous system (CNS), liver, and kidney, and also of allergic reactions, for a broad variety of drugs (n = 507) from the Swiss drug registry. Using decision tree induction, a machine learning method, we determined the chemical, physical, and structural properties of compounds that predispose them to causing ADRs. The models had high predictive accuracies (78.9-90.2%) for allergic, renal, CNS, and hepatic ADRs. We show the feasibility of predicting complex end-organ effects using simple models that involve no expensive computations and that can be used (i) in the selection of the compound during the drug discovery stage, (ii) to understand how drugs interact with the target organ systems, and (iii) for generating alerts in postmarketing drug surveillance and pharmacovigilance.

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.

Prediction of chemical toxicity with local support vector regression and activity-specific kernels.

We propose a new kernel, based on 2-D structural chemical similarity, that integrates activity-specific information from the training data, and a new approach to applicability domain estimation that takes feature significances and activity distributions into consideration. The new kernel provides superior results than the well-established Tanimoto kernel, and activity-sensitive feature selection enhances prediction quality. Validation of local support vector regression models based on this kernel has been preformed with three publicly available datasets from the DSSTox project. One of them (Fathead Minnow Acute Toxicity) has been already modelled by other groups, and serves as a benchmark dataset, the other two (Maximum Recommended Therapeutic Dose, IRIS Lifetime Cancer Risk) have been modelled for the first time according to the knowledge of the authors. For all three models predictive accuracies increase with the prediction confidences that indicate the applicability domain. Depending on the confidence cutoff for acceptable predictions we were able to achieve > 90% predictions within 1 log unit of the experimental data for all datasets.

Genetic diversity among Botulinum Neurotoxin-producing clostridial strains.

Clostridium botulinum is a taxonomic designation for many diverse anaerobic spore-forming rod-shaped bacteria that have the common property of producing botulinum neurotoxins (BoNTs). The BoNTs are exoneurotoxins that can cause severe paralysis and death in humans and other animal species. A collection of 174 C. botulinum strains was examined by amplified fragment length polymorphism (AFLP) analysis and by sequencing of the 16S rRNA gene and BoNT genes to examine the genetic diversity within this species. This collection contained representatives of each of the seven different serotypes of botulinum neurotoxins (BoNT/A to BoNT/G). Analysis of the16S rRNA gene sequences confirmed previous identifications of at least four distinct genomic backgrounds (groups I to IV), each of which has independently acquired one or more BoNT genes through horizontal gene transfer. AFLP analysis provided higher resolution and could be used to further subdivide the four groups into subgroups. Sequencing of the BoNT genes from multiple strains of serotypes A, B, and E confirmed significant sequence variation within each serotype. Four distinct lineages within each of the BoNT A and B serotypes and five distinct lineages of serotype E strains were identified. The nucleotide sequences of the seven toxin genes of the serotypes were compared and showed various degrees of interrelatedness and recombination, as was previously noted for the nontoxic nonhemagglutinin gene, which is linked to the BoNT gene. These analyses contribute to the understanding of the evolution and phylogeny within this species and assist in the development of improved diagnostics and therapeutics for the treatment of botulism.

Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study.

The OECD has proposed five principles for validation of QSAR models used for regulatory purposes. Here we present a case study investigating how these principles can be applied to models based on Kohonen and counter propagation neural networks. The study is based on a counter propagation network model that has been built using toxicity data in fish fathead minnow for 541 compounds. The study demonstrates that most, if not all, of the OECD criteria may be met when modeling using this neural network approach.

Data mining and knowledge discovery in predictive toxicology.

This article describes the knowledge discovery process in predictive toxicology. This process consists of five major steps (i) feature calculation, (ii) feature selection, (iii) model induction, (iv) model validation and (v) interpretation of predictions and models. Data mining is a part of the knowledge discovery process and consists of the application of data analysis and discovery algorithms, which can be useful in all of the above steps. A brief review of suitable algorithms and their advantages and disadvantages is given for each knowledge discovery step, followed by a more detailed description of a problem-specific implementation of the lazar prediction system.

A survey of the Predictive Toxicology Challenge 2000-2001.

MOTIVATION: The Predictive Toxicology Challenge (PTC) was initiated to stimulate the development of advanced techniques for predictive toxicology models. The goal of this challenge was to compare different approaches for the prediction of rodent carcinogenicity, based on the experimental results of the US National Toxicology Program (NTP). RESULTS: 111 sets of predictions for 185 compounds have been evaluated on quantitative and qualitative scales to select the most predictive models and those with the highest toxicological relevance. The accuracy of the submitted predictions was between 25 and 79 %. An evaluation of the most accurate models by toxicological experts showed, that it is still hard for domain experts to interpret the submitted models and to put them into relation with toxicological knowledge. AVAILABILITY: PTC details and data can be found at: http://www.predictive-toxicology.org/ptc/.

Fragment generation and support vector machines for inducing SARs.

We present a new approach to the induction of SARs based on the generation of structural fragments and support vector machines (SVMs). It is tailored for bio-chemical databases, where the examples are two-dimensional descriptions of chemical compounds. The fragment generator finds all fragments (i.e. linearly connected atoms) that satisfy user-specified constraints regarding their frequency and generality. In this paper, we are querying for fragments within a minimum and a maximum frequency in the dataset. After fragment generation, we propose to apply SVMs to the problem of inducing SARs from these fragments. We conjecture that the SVMs are particularly useful in this context, as they can deal with a large number of features. Experiments in the domains of carcinogenicity and mutagenicity prediction show that the minimum and the maximum frequency queries for fragments can be answered within a reasonable time, and that the predictive accuracy obtained using these fragments is satisfactory. However, further experiments will have to confirm that this is a viable approach to inducing SARs.

Data quality in predictive toxicology: reproducibility of rodent carcinogenicity experiments.

We compared 121 replicate rodent carcinogenicity assays from the two parts (National Cancer Institute/National Toxicology Program and literature) of the Carcinogenic Potency Database (CPDB) to estimate the reliability of these experiments. We estimated a concordance of 57% between the overall rodent carcinogenicity classifications from both sources. This value did not improve substantially when additional biologic information (species, sex, strain, target organs) was considered. These results indicate that rodent carcinogenicity assays are much less reproducible than previously expected, an effect that should be considered in the development of structure-activity relationship models and the risk assessment process.

Data quality in predictive toxicology: identification of chemical structures and calculation of chemical properties.

Every technique for toxicity prediction and for the detection of structure-activity relationships relies on the accurate estimation and representation of chemical and toxicologic properties. In this paper we discuss the potential sources of errors associated with the identification of compounds, the representation of their structures, and the calculation of chemical descriptors. It is based on a case study where machine learning techniques were applied to data from noncongeneric compounds and a complex toxicologic end point (carcinogenicity). We propose methods applicable to the routine quality control of large chemical datasets, but our main intention is to raise awareness about this topic and to open a discussion about quality assurance in predictive toxicology. The accuracy and reproducibility of toxicity data will be reported in another paper.

Knowledge discovery and data mining in toxicology.

Knowledge discovery and data mining tools are gaining increasing importance for the analysis of toxicological databases. This paper gives a survey of algorithms, capable to derive interpretable models from toxicological data, and presents the most important application areas. The majority of techniques in this area were derived from symbolic machine learning, one commercial product was developed especially for toxicological applications. The main application area is presently the detection of structure-activity relationships, very few authors have used these techniques to solve problems in epidemiological and clinical toxicology. Although the discussed algorithms are very flexible and powerful, further research is required to adopt the algorithms to the specific learning problems in this area, to develop improved representations of chemical and biological data and to enhance the interpretability of the derived models for toxicological experts.

Evaluation of the single cell gel electrophoresis assay with human hepatoma (Hep G2) cells.

Human Hep G2 cells have retained the activities of phase I and phase II enzymes which are involved in the metabolism of environmental genotoxins. The present study describes the results of single cell gel electrophoresis (SCGE) assays with a panel of different model compounds with these cells. With genotoxic carcinogens such as aflatoxin B(1) (AFB(1)), benzo(a)pyrene (B(a)P), nitrosodimethylamine (NDMA) and cyclophosphamide (CP), statistically significant dose dependent induction of DNA migration was measured. With the two heterocyclic amines, 2-amino-3-methyl-3H-imidazo[4, 5-f]quinoline (IQ) and 3-amino-1,4-dimethyl-5H-pyrido[4,3-b]indole (Trp-P-1), and also with rodent carcinogens such as safrole, hexamethylphosphoramide (HMPA) and the pyrrolizidine alkaloid isatidine, which give negative results in other in vitro genotoxicity tests, positive results were obtained in Hep G2/SCGE assays. Nitrosomethylurea (NMU) was the only directly acting compound tested in the study and was by far (ca. 10(3)-fold) more active than the corresponding nitrosamine. The exposure concentrations required to cause significant effects varied over a broad range. The most pronounced effect was seen with AFB(1) (0.008 microM) followed by HMPA (15 microM), B(a)P (25 microM), NMU (100 microM), isatidin (500 microM), CP (900 microM), IQ (1200 microM), safrol (4000 microM), and NDMA (90x10(3) microM). Numbers in parenthesis give the lowest concentrations, which caused a significant increase of DNA migration. With two compounds, namely, the non-carcinogen pyrene and the synthetic hormone tamoxifen (TF), negative results were obtained under all test conditions. These findings are in agreement with the results of recent investigations which indicated that human hepatocytes are unable to convert TF to DNA reactive metabolites, whereas it is activated by rat liver cells and causes DNA adducts in these cells. Comparisons of the present results with data from earlier experiments indicate that the Hep G2/SCGE assay enables the detection of genotoxins including compounds which give misleading results in other in vitro genotoxicity tests and appears to be an alternative to tests with primary liver cells from laboratory animals.

A public domain image-analysis program for the single-cell gel-electrophoresis (comet) assay.

The single-cell gel electrophoresis (or comet) assay has gained widespread acceptance as a cheap and simple genotoxicity test, but it requires a computer-assisted image-analysis system. As commercial programs are expensive and inflexible, we decided to develop an image-analysis system based on public domain programs and make it publicly available for the scientific community. Our system is based on the scientific image-processing program NIH Image, and was written in its Pascal-like macro language. User interaction was kept as simple as possible, to enable the measurement of a large number of cells with a few keystrokes. Therefore, the time for image analysis is very low, even on slow computers. The comet macro can be obtained from http://mailbox.univie.ac.at/christoph.helma++ +/comet/, NIH Image is available at http://rsb.info.nih.gov/nih-image/. Both programs are free of charge.

Single-cell gel electrophoresis assays with human-derived hepatoma (Hep G2) cells.

The purpose of the present study was the development of a protocol for detecting chemically-induced DNA damage, using the alkaline single-cell gel electrophoresis (SCGE) assay with human-derived, metabolically competent hepatoma (Hep G2) cells. Previous studies indicated that Hep G2 cells have retained the activities of certain phase I and phase II enzymes and reflect the metabolism of genotoxins in mammals better than other in vitro models which require addition of exogenous activation mixtures. The optimal trypsin concentration for the removal of the cells from the plates were found to be 0.1%. Dimethylsulfoxide, at concentrations up to 2%, was an appropriate solvent for water-insoluble compounds. To determine the optimal exposure periods for mutagen treatment, the time kinetics of comet formation was investigated with genotoxic chemicals representing various classes of promutagens namely benzo[a]pyrene (B[a]P), 2-amino-3-methylimidazo[4,5-f]quinoline (IQ), and N-nitrosodimethylamine (NDMA) and with N-nitrosomethylurea (NMU). All compounds caused a statistically significant induction in DNA damage. With the promutagens, comet formation increased gradually as a function of the exposure duration, and reached maximum values between 20-24 h. With NMU, comet induction maximized already after a short exposure (1 h) and remained at a constant level for up to 24 h. Based on these results, the Hep G2/SCGE assay appears to be a suitable approach for investigating DNA damaging potential of chemicals. Further experiments with IQ and B[a]P showed that the assays are highly reproducible. Comparisons of the present results with those from earlier experiments in which other endpoints (induction of sister chromatid exchanges, micronuclei and chromosomal aberrations) were measured in Hep G2 cells, indicated that the sensitivity of the SCGE assays is more or less identical. Since the SCGE assay is less time consuming than other genotoxicity assays we anticipate that it might be a suitable approach to investigate DNA damaging effects of chemicals in the human-derived, metabolically competent cell line.

Genotoxic effects of heavy metals: comparative investigation with plant bioassays.

The potential use of micronucleus assays in plants for the detection of genotoxic effects of heavy-metal ions was investigated. Three different plant systems were comparatively investigated in micronucleus tests with Tradescantia pollen mother cells (Trad MCN) and micronucleus tests with meristematic root tip cells of Allium cepa and Vicia faba (Allium/ Vicia MCN). As3+, Pb2+, Cd2+, Zn2+ caused a dose-dependent increase of MCN frequencies in all three test systems. Cu2+ gave consistently negative responses in all three tests; Zn2+ caused only a moderate, statistically not significant increase of MCN frequencies in Vicia. The ranking of genotoxic potencies in all three tests was in the descending order: As3+ > Pb2+ > Cd2+ > Zn2+ Cu2+. In experiments with Tradescantia, induction of MCN was observed in a concentration range between 1 and 10 mM, whereas in tests with root tip cells, higher concentrations (10-1,000 mM) were required to show significant effects. Further increase of the exposure levels caused toxic effects (reduction of root growth), cell division delays, and a decrease of MCN frequencies. Comparisons by linear regression analyses indicated that the sensitivity of the three bioassays for heavy metals decreases in the order: Trad MCN > Vicia root MCN > Allium root MCN. In further experimental series, a soil sample which contained high concentrations of the five metals and a control soil were investigated. Aqueous soil extracts induced only weak effects in Trad MCN tests and no effects in the root tip assays, whereas cultivation of the plants in the soils resulted in a pronounced induction of MCN in the Tradescantia system and moderate effects in Vicia and Allium. In conclusion, the results of the study indicate that the Trad MCN assay detects the genotoxic effects of heavy metals and can be used for biomonitoring metal-contaminated soils.

Investigations on genotoxic effects of groundwater from the Mitterndorfer Senke and from the vicinity of Wiener Neustadt.

INTRODUCTION: This report describes the first study on genotoxic effects of Austrian ground- and drinking waters. Samples from the Mitterndorfer Senke (MS) and the vicinity of Wiener Neustadt were tested over a three years period. The MS is the largest aquifer in Austria. Due to deposition of industrial and community wastes, chemicals have polluted the groundwater in this area. Aim of the present study was to elucidate if consumption of these waters might pose a carcinogenic risk to humans. METHODS: 43 Water samples were tested in a test battery which consisted of bacterial gene mutation assays (Salmonella strains TA100 and TA98), micronucleus (MN) assays with cultures of primary rat hepatocytes and plant bioassays (MN tests with Tradescantia and Vicia faba). For the bacterial assays, the water samples were extracted with XAD resins. RESULTS: In total, 27.9% of the samples caused positive effects; 8 samples were active in Salmonella microsome assays, Strain TA100 was particularly sensitive upon addition of metabolic activation mix (6 positive samples). Four samples were positive exclusively in MN assays with cultures of primary rat hepatocytes; one sample gave positive results in all three bioassays. Finished waters from waterworks were consistently devoid of mutagenic activity under all experimental conditions. DISCUSSION: Overall, only a small fraction of the groundwaters caused mutagenic effects and in all cases the activities were moderate. Comparison of the results of the present study with data obtained in other investigations under similar experimental conditions shows that the genotoxicity of groundwaters of the MS area are lower than the effects caused by ground- and drinking waters from other countries. The fact that no genotoxic activity was detected in any of the finished drinking waters can be taken as an indication that consumption of these waters does not pose a health hazard arising from contamination with genotoxic carcinogens to humans.

Toxic effects of griseofulvin: disease models, mechanisms, and risk assessment.

Griseofulvin (GF) has been in use for more than 30 years as a pharmaceutical drug in humans for the treatment of dermatomycoses. Animal studies give clear evidence that it causes a variety of acute and chronic toxic effects, including liver and thyroid cancer in rodents, abnormal germ cell maturation, teratogenicity, and embroyotoxicity in various species. No sufficient data from human studies are available at present to exclude a risk in humans: therefore, attempts were made to elucidate the mechanisms responsible for the toxic effects of GF and to address the question whether such effects might occur in humans undergoing GF therapy. It is well documented that GF acts as a spindle poison and its reproductive toxicity as well as the induction of numerical chromosome aberrations and of micronuclei in somatic cells possibly may result from disturbance of microtubuli formation. Likewise, a causal relationship between aneuploidy and cancer has been repeatedly postulated. However, a critical survey of the data available on aneuploidogenic chemicals revealed insufficient evidence for such an association. Conceivably, other mechanisms may be responsible for the carcinogenic effects of the drug. The induction of thyroid tumors in rats by GF is apparently a consequence of the decrease of thyroxin levels and it is unlikely that such effects occur in GF-exposed humans. The appearance of hepatocellular carcinomas (HCC) in mice on GF-supplemented diet is preceded by various biochemical and morphological changes in the liver. Among these, hepatic porphyria is prominent, it may result from inhibition of ferrochelatase and (compensatory) induction of ALA synthetase. GF-induced accumulation of porphyrins in mouse liver is followed by cell damage and necrotic and inflammatory processes. Similar changes are known from certain human porphyrias which are also associated with an increased risk for HCC. However, the porphyrogenic effect of GF therapy in humans is moderate compared with that in the mouse model, although more detailed studies should be performed in order to clarify this relationship on a quantitative basis. A further important effect of GF-feeding in mice is the formation of Mallory bodies (MBs) in hepatocytes. These cytoskeletal abnormalities occur also in humans, although under different conditions; their appearance is associated with the induction of liver disease and HCC. Chronic liver damage associated with porphyria and MB formation, enhanced cell proliferation, liver enlargement, and enzyme induction all may contribute to the hepatocarcinogenic effect of GF in mice. In conclusion, further investigation is required for adequate assessment of health risks to humans under GF therapy.

Genotoxic effects of the chlorinated hydroxyfuranones 3-chloro-4-(dichloromethyl)-5-hydroxy-2[5H]-furanone and 3,4-dichloro-5-hydroxy-2[5H]-furanone in Tradescantia micronucleus assays.

This is the first report of clastogenic effects of chlorinated hydroxyfuranones (CHFs) in plants. Two byproducts of water chlorination, 3-chloro-4-(dichloromethyl)-5-hydroxy-2[5H]-furanone (MX) and 3,4-dichloro-5-hydroxy-2[5H]-furanone (MA) induced a dose dependent increase of micronuclei (MN) in pollen mother cells of Tradescantia when doses up to 100 micrograms MX and 500 micrograms MA were applied directly to the inflorescences. In contrast, exposure of the stems in aqueous solutions containing up to 1 mg/l MX and 10 mg/l MA did not cause a positive response.

Enhanced clastogenicity of contaminated groundwater following UV irradiation detected by the Tradescantia micronucleus assay.

The Tradescantia micronucleus (Trad-MCN) assay was used to determine clastogenic effects of contaminated groundwater collected near a hazardous waste landfill. Water samples were taken from a purification plant (activated charcoal filtration, UV irradiation) which was built to avoid groundwater contamination by this landfill. Five series of experiments were conducted during approximately 4 months. In addition, water samples were irradiated under laboratory conditions with increasing doses of UV light. Several field water samples gave positive, dose-dependent effects before filtration and irradiation. Maximal values (6.1 +/- 4.7 micronuclei (MCN)/100 tetrads) were six-fold above controls. UV irradiation of activated charcoal-filtered water resulted in an enhancement of MCN frequencies. Exposure of groundwater to UV irradiation in the laboratory led to a dose-dependent increase of micronuclei. At the highest dose (1500 J/m2) the MCN frequency was more than six times higher than in the unirradiated sample (5.4 +/- 1.0 vs. 0.8 +/- 0.4 MCN/100 tetrads). The clastogenicity of UV-irradiated samples decreased with a half-life of approximately 1 day. Irradiation of tap water did not increase the MCN frequency. Our results indicate that irradiation of water with UV light for disinfection purposes might lead to a transiently increased genotoxicity of chemically polluted water samples.