Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice.

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.

Analysis of metabolome changes in the bile acid pool in feces and plasma of antibiotic-treated rats.

The bile acid-liver-gut microbiota axis plays an important role in the host's health. The gut microbiota has an impact on the bile acid pool, but also the bile acids themselves can influence the gut microbiota composition. In this study, six antibiotics from five different classes (i.e. lincosamides, glycopeptides, macrolides, fluoroquinolones, aminoglycosides) were used to modulate microbial communities of Wistar rats to elucidate changes in the bile acid metabolism and to identify key metabolites in the bile acid pool related to gut microbial changes. 20 primary and secondary bile acids were analyzed in plasma and feces of control and treated animals. Antibiotics treatment induced significant changes in primary and secondary bile acids in both matrices. Taurine-conjugated primary bile acids significantly increased in plasma and feces. Contrary, cholic acid and most of the analyzed secondary bile acids significantly decreased in plasma, and cholic acid accumulated in the feces after treatment with all antibiotics but roxithromycin. Despite the different activity spectra of the antibiotics applied against gut microbes, the overall effect on the bile acid pool tended to be similar in both matrices except for streptomycin. These results show that changes in the gut microbial community affect the bile acid pool in plasma and feces and that changes in the bile acid profile can be indicative of alterations of the gut microbiome. Due to the important role of bile acids for the host, changes in the bile acid pool can have severe consequences for the host.

Metabolomics as read-across tool: An example with 3-aminopropanol and 2-aminoethanol.

Read-across and grouping is one of the most commonly used alternative approaches for data gap filling in registrations submitted under the REACH Regulation as defined by the European Chemicals Agency (ECHA) in their 'Read-Across Assessment Framework' (RAAF, 2017). At the same time, the application of read-across is rejected by ECHA frequently due to various reasons. As a major reason hereof, applicants fail to reduce the level of 'remaining uncertainty' intrinsical to every read-across approach compared to testing a substance experimentally. Recently, the use of metabolomics to support read-across cases with biological information has been reported in a case study with phenoxy herbicides (Ravenzwaay et al., 2016). In the present case-study a 'weight-of-evidence' read-across approach from 2-aminoethanol (MEA = 'source') to 3-aminopropanol (3AP = 'target') with metabolomics as 'supporting evidence' reducing the remaining uncertainties is reported. We demonstrate the high structural similarity of the two analogous substances based on the available data and we report how metabolome data add confidence concerning mechanistic similarity in this read-across approach. Finally, the herein described read-across case supported by metabolomics is used to cover the data gaps in repeated dose and reproductive toxicity endpoint of 3AP via weight of evidence for the REACH-registration.

Microbiome-related metabolite changes in gut tissue, cecum content and feces of rats treated with antibiotics.

The metabolic functionality of the gut microbiota contributes to the metabolism and well-being of its host, although detailed insight in the microbiota's metabolism is lacking. Omics technologies could facilitate unraveling metabolism by the gut microbiota. In this study, we performed metabolite profiling of different matrices of the gut, after antibiotic treatment of rats in order to evaluate metabolite changes observed at different dose levels and in different sexes, and to identify the best tissue matrix for further investigations regarding an assessment of metabolic effects of new compounds with antibiotic activity. Three different antibiotics (vancomycin, streptomycin and roxithromycin) were administered orally to rats for 28 days according to the OECD 407 guideline with a subsequent metabolic profiling in feces, cecum content and gut tissue (jejunum, ileum, cecum, colon and rectum). The data were analyzed in the MetaMap®Tox database. Treatment-related effects could be observed in the metabolite profile of feces and cecum content, but not of the different gut tissues. The metabolite profile showed compound specific effects on the microbiome. In line with the activity spectra of the antibiotics tested, vancomycin showed the largest effects, followed by roxithromycin and then by streptomycin for which changes were modest. In general, for all antibiotics the largest changes were observed for the classes of lipids (increase up to 94-fold), bile acids (increase up to 33-fold), amino acids (increase up to 200-fold) and amino acid related (increase up to 348-fold). The most relevant changes in metabolite values were similar in feces and cecum content and among sexes. The results of this targeted analysis indicate that the metabolic profiles of male and female animals in the gut microbiome are comparable. Concluding, taking other samples than feces does not add any extra information. Thus, as a non-invasive sampling method, feces provide a suitable matrix for studies on metabolism by the gut microbiota.

Gut microbiome-related metabolic changes in plasma of antibiotic-treated rats.

The intestinal microbiota contributes to the metabolism of its host. Adequate identification of the microbiota's impact on the host plasma metabolites is lacking. As antibiotics have a profound effect on the microbial composition and hence on the mammalian-microbiota co-metabolism, we studied the effects of antibiotics on the "functionality of the microbiome"-defined as the production of metabolites absorbed by the host. This metabolomics study presents insights into the mammalian-microbiome co-metabolism of endogenous metabolites. To identify plasma metabolites related to microbiome changes due to antibiotic treatment, we have applied broad-spectrum antibiotics belonging to the class of aminoglycosides (neomycin, gentamicin), fluoroquinolones (moxifloxacin, levofloxacin) and tetracyclines (doxycycline, tetracycline). These were administered orally for 28 days to male rats including blood sampling for metabolic profiling after 7, 14 and 28 days. Fluoroquinolones and tetracyclines can be absorbed from the gut; whereas, aminoglycosides are poorly absorbed. Hippuric acid, indole-3-acetic acid and glycerol were identified as key metabolites affected by antibiotic treatment, beside changes mainly concerning amino acids and carbohydrates. Inter alia, effects on indole-3-propionic acid were found to be unique for aminoglycosides, and on 3-indoxylsulfate for tetracyclines. For each class of antibiotics, specific metabolome patterns could be established in the MetaMap®Tox data base, which contains metabolome data for more than 550 reference compounds. The results suggest that plasma-based metabolic profiling (metabolomics) could be a suitable tool to investigate the effect of antibiotics on the functionality of the microbiome and to obtain insight into the mammalian-microbiome co-metabolism.

Metabolomics as read-across tool: A case study with phenoxy herbicides.

New technologies, such as metabolomics, can address chemical grouping and read across from a biological perspective. In a virtual case study, we selected MCPP as target substance and MCPA and 2,4-DP as source substances with the goal to waive a 90-day study with MCPP. In order to develop a convincing case to show how biological data can substantiate read across, we used metabolomics on blood samples from the 28-day studies to show the qualitative and quantitative similarity of the substances. The 28-day metabolome evaluation of source substances and the target substance indicate liver and kidneys as target organs. 2,4-DP was identified as the best source substance. Using the information of the 90-day 2,4-DP study, we predicted MCPP's toxicity profile at 2500 ppm: reduced food consumption and body weight gain, liver and kidney weight increases with clinical-pathology changes and a moderate red blood cell parameter reduction. NOEL prediction for MCPP was below that of 2,4-DP (<500 ppm), and similar to that of MCPA (≥150 ppm). Qualitatively, these predictions are comparable to the results of the real MCPP 90-day study in rats (reduced food consumption and body weight gain, weight increases and clinical-pathology changes in liver and kidneys, reduced red blood cells values). Quantitatively, the predicted NOAEL (150 ppm) is similar to the actual study (NOEL = 75 ppm, NOAEL ≤ 500 ppm). Thus, the 90-day rat toxicity study of MCPP could have been waived and substituted by the 90-day results of 2,4-DP by using metabolome data of 28 day studies.

Metabolomics: a tool for early detection of toxicological effects and an opportunity for biology based grouping of chemicals-from QSAR to QBAR.

BASF has developed a Metabolomics database (MetaMap(®) Tox) containing approximately 500 data rich chemicals, agrochemicals and drugs. This metabolome-database has been built based upon 28-day studies in rats (adapted to OECD 407 guideline) with blood sampling and metabolic profiling after 7, 14 and 28 days of test substance treatment. Numerous metabolome patterns have been established for different toxicological targets (liver, kidney, thyroid, testes, blood, nervous system and endocrine system) which are specific for different toxicological modes of action. With these patterns early detection of toxicological effects and the underlying mechanism can now be obtained from routine studies. Early recognition of toxicological mode of action will help to develop new compounds with a more favourable toxicological profile and will also help to reduce the number of animal studies necessary to do so. Thus this technology contributes to animal welfare by means of reduction through refinement (2R), but also has potential as a replacement method by analyzing samples from in vitro studies. With respect to the REACH legislation for which a large number of animal studies will need to be performed, one of the most promising methods to reduce the number of animal experiments is grouping of chemicals and read-across to those which are data rich. So far mostly chemical similarity or QSAR models are driving the selection process of chemical grouping. However, "omics" technologies such as metabolomics may help to optimize the chemical grouping process by providing biologically based criteria for toxicological equivalence. "From QSAR to QBAR" (quantitative biological activity relationship).

Succinate dehydrogenase inhibitors: in silico flux analysis and in vivo metabolomics investigations show no severe metabolic consequences for rats and humans.

Succinate dehydrogenase complex II inhibitors (SDHIs) are widely used fungicides since the 1960s. Recently, based on published in vitro cell viability data, potential health effects via disruption of the mitochondrial respiratory chain and tricarboxylic acid cycle have been postulated in mammalian species. As primary metabolic impact of SDH inhibition, an increase in succinate, and compensatory ATP production via glycolysis resulting in excess lactate levels was hypothesized. To investigate these hypotheses, genome-scale metabolic models of Rattus norvegicus and Homo sapiens were used for an in silico analysis of mammalian metabolism. Moreover, plasma samples from 28-day studies with the SDHIs boscalid and fluxapyroxad were subjected to metabolome analyses, to assess in vivo metabolite changes induced by SDHIs. The outcome of in silico analyses indicated that mammalian metabolic networks are robust and able to compensate different types of metabolic perturbation, e.g., partial or complete SDH inhibition. Additionally, the in silico comparison of rat and human responses suggested no noticeable differences between both species, evidencing that the rat is an appropriate testing organism for toxicity of SDHIs. Since no succinate or lactate accumulation were found in rats, such an accumulation is also not expected in humans as a result of SDHI exposure.

Added value of plasma metabolomics to describe maternal effects in rat maternal and prenatal toxicity studies.

For regulatory purposes prenatal developmental toxicity (OECD No. 414) studies are routinely performed in our laboratories. The suitability of metabolomics as technology to identify maternal toxicity in such studies was investigated. Plasma was sampled from pregnant, non-fasted rats on gestation day 20 before cesarean section. Metabolite profiling was performed by gas- and liquid-chromatography-tandem mass spectrometry techniques. The sensitivity of routinely examined maternal toxicity parameters (OECD No. 414) was compared to those of metabolome analysis. Evaluating 44 studies, the metabolome-derived NOEL was more sensitive in 45% of the cases in detecting maternal toxicity than the maternal NOAEL. Metabolome patterns indicative for liver effects and 4-hydroxyphenylpyruvate dioxygenase (HPPD) enzyme-inhibition were established in pregnant rats based on regulated metabolites using reference compounds. The HPPD inhibition and liver toxicity patterns in pregnant rats were reasonably comparable to the ones established in non-pregnant, fasted rats. Metabolomics is a useful tool for an improved and mechanism-based identification of maternal toxicity in maternal and prenatal toxicity studies. The data suggest that the current classical maternal toxicity parameters may underestimate the extent of effects of compounds on the dams.

Impact of lincosamides antibiotics on the composition of the rat gut microbiota and the metabolite profile of plasma and feces.

The importance of the gut microorganisms and their wide range of interactions with the host are well-acknowledged. In this study, lincomycin and clindamycin were used to modulate microbial communities of Wistar rats to gain a comprehensive understanding of the implications of microbiome alterations. A metabolomics approach and taxonomic profiling were applied to characterize the effects of these antibiotics on the functionality of the microbiome and to identify microbiome-related metabolites. After treatment, the diversity of the microbial community was drastically reduced. Bacteroidetes and Verrucomicrobia were drastically reduced, Tenericutes and Deferribacteres completely disappeared, while abundance of Firmicutes and Proteobacteria were highly increased. Changes in plasma and feces metabolites were observed for metabolites belonging mainly to the class of complex lipids, fatty acids and related metabolites as well as amino acids and related compounds. Bile acid metabolism was markedly affected: taurocholic acid, glycochenodeoxycholic acid and cholic acid presented abrupt changes showing a specific metabolite pattern indicating disruption of the microbial community. In both plasma and feces taurocholic acid was highly upregulated upon treatment whereas glycochenodeoxycholic acid was downregulated. Cholic acid was upregulated in feces but downregulated in plasma. These results show that changes in the gut microbial community lead to alterations of the metabolic profile in blood and feces of the host and can be used to identify potentially microbiome-related metabolites. This implies that metabolomics could be a suitable tool to estimate the extent of changes induced in the intestinal microbiome with respect to consequences for the host.

The use of metabolomics for the discovery of new biomarkers of effect.

Will metabolomics have a greater chance of success in toxicology and biomarker assessment than genomics and proteomics? Metabolomics has the advantage that (1) it analyses the last step in a series of changes following a toxic insult, (2) many of the metabolites have a known function and (3) changes are detectable in blood. If the analysis of a great number of individual organs can be replaced by one matrix then this will provide significant advantages (less invasive method, no need to kill animals, time course analysis possible). We have chosen to perform the analysis of blood metabolites in such a way as to minimize the risk of artifacts and to have a high number of known metabolites. We have also reduced the amount of variation in the biological system as well as during analysis. In a series of proof of concept studies it could be demonstrated that (1) the metabolome of control animals was stable of a period of nearly 1 year, with a remarkable differentiation between males and females, (2) a dose response relationship in metabolome changes was induced by phenobarbital and that (3) different modes of action could be distinguished by blood metabolome analysis. To investigate the potential of metabolomics to find biomarkers or specific patterns of change we have analyzed the blood metabolome of rats treated with HPPD inhibitors, a novel class of herbicides. The results demonstrated that a single metabolite, tyrosine, can be used as a biomarker. In addition to tyrosine we also found a specific pattern of change that involved nine metabolites. Though the extent of change was less than for tyrosine the consistent change of these metabolites is diagnostic for this (toxicological) mode of action.

Metabolite profiles of rats in repeated dose toxicological studies after oral and inhalative exposure.

The MetaMap(®)-Tox database contains plasma-metabolome and toxicity data of rats obtained from oral administration of 550 reference compounds following a standardized adapted OECD 407 protocol. Here, metabolic profiles for aniline (A), chloroform (CL), ethylbenzene (EB), 2-methoxyethanol (ME), N,N-dimethylformamide (DMF) and tetrahydrofurane (THF), dosed inhalatively for six hours/day, five days a week for 4 weeks were compared to oral dosing performed daily for 4 weeks. To investigate if the oral and inhalative metabolome would be comparable statistical analyses were performed. Best correlations for metabolome changes via both routes of exposure were observed for toxicants that induced profound metabolome changes. e.g. CL and ME. Liver and testes were correctly identified as target organs. In contrast, route of exposure dependent differences in metabolic profiles were noted for low profile strength e.g. female rats dosed inhalatively with A or THF. Taken together, the current investigations demonstrate that plasma metabolome changes are generally comparable for systemic effects after oral and inhalation exposure. Differences may result from kinetics and first pass effects. For compounds inducing only weak changes, the differences between both routes of exposure are visible in the metabolome.

Identification of peptides from autoantigens GAD65 and IA-2 that bind to HLA class II molecules predisposing to or protecting from type 1 diabetes.

Type 1 diabetes is a T-cell-mediated disease in which presentation of autoantigens to CD4+ T-cells is thought to play a crucial role. Polymorphism of HLA class II genes accounts for 50% of the genetic risk of contracting type 1 diabetes. HLA-DQ and -DR molecules predisposing to or protecting from type 1 diabetes have been identified, but the molecular basis controlling these associations is as yet undefined. Apart from distinct thymic selection of autoreactive T-cells by susceptible and protective HLA molecules, exclusive presentation of autoantigenic peptides by type 1 diabetes-predisposing HLA molecules or, alternatively, induction of regulatory T-cells by protective alleles are potential mechanisms for modification of type 1 diabetes risk by HLA polymorphism. As a first step in exploring the role of HLA molecules in autoantigen-specific cellular responses in type 1 diabetes, we have screened peptides covering the sequence of two major autoantigens targeted by humoral and cellular immune responses, GAD65 and islet associated-2 (IA-2), for binding to class II molecules. We developed a sensitive novel competition binding assay allowing us to measure peptide binding on intact cells to 10 HLA-DR and 4 HLA-DQ molecules. For all tested alleles, multiple peptides binding with high affinity were identified. We report clustering of binding peptides in the COOH-terminal regions of GAD65 and IA-2, as well as highly promiscuous binding patterns of some peptides. Our results demonstrate that most peptides derived from the GAD and IA-2 autoantigens can bind to both type 1 diabetes-predisposing and type 1 diabetes-protective HLA molecules, although some exceptions were observed. The binding inventory presented here for GAD and IA-2 peptides can be useful for mapping natural epitopes and predicting peptide-specific responses induced by preventive immunization.

Structural analysis of two HLA-DR-presented autoantigenic epitopes: crucial role of peripheral but not central peptide residues for T-cell receptor recognition.

Specific and major histocompatibility complex (MHC)-restricted T-cell recognition of antigenic peptides is based on interactions of the T-cell receptor (TCR) with the MHC alpha helices and solvent exposed peptide residues termed TCR contacts. In the case of MHC class II-presented peptides, the latter are located in the positions p2/3, p5 and p7/8 between MHC anchor residues. For numerous epitopes, peptide substitution studies have identified the central residue p5 as primary TCR contact characterized by very low permissiveness for peptide substitution, while the more peripheral positions generally represent auxiliary TCR contacts. In structural studies of TCR/peptide/MHC complexes, this has been shown to be due to intimate contact between the TCR complementarity determining region (CDR) three loops and the central peptide residue. We asked whether this model also applied to two HLA-DR presented epitopes derived from an antigen targeted in type 1 diabetes. Large panels of epitope variants with mainly conservative single substitutions were tested for human leukocyte antigen (HLA) class II binding affinity and T cell stimulation. Both epitopes bind with high affinity to the presenting HLA-DR molecules. However, in striking contrast to the standard distribution of TCR contacts, recognition of the central p5 residue displayed high permissiveness even for non-conservative substitutions, while the more peripheral p2 and p8 TCR contacts showed very low permissiveness for substitution. This suggests that intimate TCR interaction with the central peptide residue is not always required for specific antigen recognition and can be compensated by interactions with positions normally acting as auxiliary contacts.

Establishment of T cell lines to bovine beta-casein and beta-casein-derived epitopes in patients with type 1 diabetes.

Enhanced cellular immune response to bovine beta-casein has been reported in patients with type 1 diabetes. In this study we aimed to establish beta-casein-specific T cell lines from newly diagnosed type 1 diabetic patients and to characterise these cell lines in terms of phenotype and epitope specificity. Furthermore, since sequence homologies exist between beta-casein and putative beta-cell autoantigens, reactivity to the latter was also investigated. T cell lines were generated from the peripheral blood of nine recent onset type 1 diabetic patients with different HLA-DQ and -DR genotypes, after stimulation with antigen pulsed autologous irradiated antigen presenting cells (APCs) and recombinant human interleukin-2 (rhIL-2). T cell line reactivity was evaluated in response to bovine beta-casein, to 18 overlapping peptides encompassing the whole sequence of beta-casein and to beta-cell antigens, including the human insulinoma cell line, CM, and a peptide from the beta-cell glucose transporter, GLUT-2. T cell lines specific to beta-casein could not be isolated from HLA-matched and -unmatched control subjects. beta-Casein T cell lines reacted to different sequences of the protein, however a higher frequency of T cell reactivity was observed towards the C-terminal portion (peptides B05-14, and B05-17 in 5/9 and 4/9 T cell lines respectively). Furthermore, we found that 1 out of 9 beta-casein-specific T cell lines reacted also to the homologous peptide from GLUT-2, and that 3 out of 4 of tested cell lines reacted also to extracts of the human insulinoma cell line, CM. We conclude that T cell lines specific to bovine beta-casein can be isolated from the peripheral blood of patients with type 1 diabetes; these cell lines react with multiple and different sequences of the protein particularly towards the C-terminal portion. In addition, reactivity of beta-casein T cell lines to human insulinoma extracts and GLUT-2 peptide was detected, suggesting that the potential cross-reactivity with beta-cell antigens deserves further investigation.

Plasma dehydroepiandrosterone in pregnant and nonpregnant women.

From 157 plasma samples taken randomly throughout normal pregnancy and from 42 plasma samples of nonpregnant women, total plasma dehydroepiandrosterone was measured by a method using Amberlite XAD-2 column chromatography at 45degreesC, enzyme hydrolysis, radioactive internal standard, thin-layer chromatography and gas-liquid chromatography after trimethylsilyl ether derivative formation. The following values for dehydroepiandrosterone were obtained: from individual, nonpregnant samples, (n = 25) 69.6 +/- 10.6 mug/100 ml (S.E.M.); from the pool of nonpregnant samples (n = 17) 67.7 mug/100 ml; from individual samples, 6-12 weeks of gestation (n = 32) 48.5 +/- 5.7 mug/100 ml (S.E.M.); from individual samples, 13-18 weeks of gestation (n = 13) 45.9 +/- 7.7 mug/100 ml (S.E.M.); from individual samples, 19-24 weeks of gestation (n = 20) 42.9 +/- 6.9 mug/100 ml (S.E.M.); from individual samples, 25-30 weeks of gestation (n = 22) 41.7 +/- 6.8 mug/100 ml (S.E.M.); from individual samples, 31-36 weeks of gestation (n = 31) 39.5 +/- 6.1 mug/100 ml (S.E.M.); from individual samples, 37-43 weeks of gestation (n = 29) 37.6 +/- 3.6 mug/100 ml (S.E.M.); and from the pool sample, 37-43 weeks of gestation (n = 10) 25.4 mug/100 ml. This study demonstrates a significant decrease of total plasma dehydroepiandrosterone throughout the course of normal pregnancy in individual and pooled plasma samples, thus confirming previous reports. These plasma hormone changes are discussed in relation to production and utilization of this steroid in pregnancy.

Is Change in Electrical Potential or pH a Hatching Signal for Heterodera glycines?

ABSTRACT This study explored the possibilities that changes in the egg shell/lipid layer electrical potential or pH communicate external hatching conditions to the Heterodera glycines second-stage juvenile (J2) within the mature egg and that electrophysiology could measure effects of chemicals on emergence. Potentials were measured following application of the emergence inducers (ZnSO(4) and ZnCl(2)), ions that do not affect emergence, or synthetic emergence inhibitors. Results were compared with pH measurements and emergence bioassays. Healthy appearing eggs had negative resting potentials. Application of ZnSO(4) caused a smooth depolarization. However, eggs containing J2 and immature eggs depolarized to a similar degree when ZnSO(4) was added. In addition, ZnSO(4), synthetic emergence inhibitors, and CaCl(2) caused similar depolarization, and some depolarization was measured in dye-permeable eggs and empty shells. Results suggest that change in cation surface charge contributed to depolarization and that Cl penetrated the egg shell/lipid layer without causing potential changes. In bioassays, zinc consistently stimulated emergence to a greater degree than H(2)O, other cations, or buffers, and counteracted emergence inhibitors. Zinc-caused emergence stimulation was independent of pH. In summary, it is concluded that depolarization and pH are not emergence signals and electrophysiology is unlikely to measure effectiveness of emergence stimulators or inhibitors.

Adequate dialysis? Measurement of KT/V in a pediatric peritoneal dialysis population.

OBJECTIVE: To measure the urea and creatinine kinetics in a pediatric population. PATIENTS AND METHODS: In 19 children treated with peritoneal dialysis (PD) KT/V, urea and creatinine clearances (Ccr) were measured. Thirteen children were on continuous ambulatory peritoneal dialysis (CAPD) and 6 on highly intermittent peritoneal dialysis (NIPD). RESULTS: Mean KT/V per week was 2.31 +/- 0.78 and mean creatinine clearance 74 +/- 47 L/week/1.73 m2. There was no difference in dialytic KT/V between patients treated with CAPD and NIPD (1.75 +/- 0.21 vs 1.76 +/- 0.50). The correlation between KT/V urea and creatinine clearance was 0.9 (p < 0.001). There was a clear relationship of these parameters with residual renal function, but not with age or blood urea level. A weak positive correlation was found with serum albumin and protein intake. CONCLUSIONS: Mean KT/V in this patient group was higher than the values reported for most adult patient groups. Residual renal function considerably contributes to this high KT/V. It is not clearly defined which KT/V should be aimed for, since criteria for adequate dialysis are multifactorially determined and therefore difficult to interpret.

Flow Cytometric Analysis and Sorting of Heterodera glycines Eggs.

A nondestructive technique was developed to characterize and separate eggs of soybean cyst nematode, Heterodera glycines, by developmental stage using flow cytometry. Eggs from cysts cultured on susceptible soybean roots were suspended in 0.1% xanthan gum or 59% sucrose and loaded into either a Coulter EPICS 752 or EPICS 753 flow cytometer. Eggs were analyzed and sorted according to forward angle and 90 degrees light scatter, flow cytometric parameters that are relative measures of object size and granularity, respectively. Mature eggs containing vermiform juveniles were less granular and slightly larger than eggs in earlier stages of embryogeny, allowing for separation of mature eggs from immature eggs. The effectiveness of flow cytometric sorting was evaluated by comparing the developmental stages of subpopulations of unsorted and sorted eggs. Of a subpopulation of unsorted eggs, 62% contained vermiform juveniles, whereas 85 to 95% of sorted subpopulations of larger, less granular eggs contained vermiform juveniles. Suspending H. glycines eggs in 0.1% xanthan gum or 59% sucrose for flow cytometric analysis had no effect on subsequent egg hatch in vitro. This technique is an efficient and effective means to collect large, relatively homogeneous quantities of H. glycines eggs in early or late embryogeny, and would likely be useful for analyzing and sorting eggs of other nematode species for use in developmental, genetic, or physiological research, or for identification and collection of parasitized eggs.

The sensitivity of metabolomics versus classical regulatory toxicology from a NOAEL perspective.

The identification of the no observed adverse effect level (NOAEL) is the key regulatory outcome of toxicity studies. With the introduction of "omics" technologies into toxicological research, the question arises as to how sensitive these technologies are relative to classical regulatory toxicity parameters. BASF SE and metanomics developed the in vivo metabolome database MetaMap®Tox containing metabolome data for more than 500 reference compounds. For several years metabolome analysis has been routinely performed in regulatory toxicity studies (REACH mandated testing or new compound development), mostly in the context of 28 day studies in rats (OECD 407 guideline). For those chemicals for which a toxicological NOAEL level was obtained at either high or mid-dose level, we evaluated the associated metabolome to investigate the sensitivity of metabolomics versus classical toxicology with respect to the NOAEL. For the definition of a metabolomics NOAEL the ECETOC criteria (ECETOC, 2007) were used. In this context we evaluated 104 cases. Comparable sensitivity was noted in 75% of the cases, increased sensitivity of metabolomics in 8%, and decreased sensitivity in 18% of the cases. In conclusion, these data suggest that metabolomics profiling has a similar sensitivity to the classical toxicological study (e.g. OECD 407) design.