Chemical synthesis and NMR spectroscopy of long stable isotope labelled RNA.

We showcase the high potential of the 2'-cyanoethoxymethyl (CEM) methodology to synthesize RNAs with naturally occurring modified residues carrying stable isotope (SI) labels for NMR spectroscopic applications. The method was applied to synthesize RNAs with sizes ranging between 60 to 80 nucleotides. The presented approach gives the possibility to selectively modify larger RNAs (>60 nucleotides) with atom-specifically 13C/15N-labelled building blocks. The method harbors the unique potential to address structural as well as dynamic features of these RNAs with NMR spectroscopy but also using other biophysical methods, such as mass spectrometry (MS), or small angle neutron/X-ray scattering (SANS, SAXS).

Partial break in tolerance of NKG2A-/LIR-1- single KIR+ NK cells early in the course of HLA-matched, KIR-mismatched hematopoietic cell transplantation.

Natural killer (NK) cell subpopulations from 8 HLA-matched but killer cell immunoglobulin-like receptor (KIR)/HLA-ligand-mismatched patient-donor pairs were analyzed in the course of allogeneic hematopoietic stem cell transplantation (HCT). The patients' post-transplantation NKG2A-/LIR-1- NK cells, which expressed only inhibitory KIRs for which the patient had no HLA class I ligands, showed higher cytotoxic capacity than the NKG2A-/LIR-1- NK cells lacking any inhibitory KIRs that remained tolerant throughout the course of HCT. The NKG2A+ NK cell subpopulations displayed the highest levels of cytotoxic activation, which appeared to be significantly enhanced in comparison with that in allogeneic graft's donors. LIR-1- NK cells were much more frequent after HCT than LIR-1+ NK cells and LIR-1 expression on NKG2A+ or NKG2A- NK cells was associated with significantly lower cytotoxic activities. Thus NKG2A-/LIR-1- NK cells expressing only HLA-mismatched KIRs show a partial break in tolerance in the first year following HCT. The failure to exclude LIR-1+ cells within the NKG2A- NK cell subset in previous studies could explain the earlier conflicting results. Thus systemic immune activation in patients following HCT augments the GvL effect through both increasing overall NK cell activities and partially breaking tolerance of unlicensed NK cells.

Influence of urban area on the water quality of the Campo River basin, Paraná State, Brazil.

The Campo River basin is located on the third plateau of the Paraná State or trap plateau of Paraná, at the middle portion between the rivers Ivaí and Piquiri, southern Brazil, between the coordinates 23° 53 and 24° 10' South Latitude and 52° 15' and 52° 31' West Longitude. The basin has 384 Km² area, being 247 km² in the municipality of Campo Mourão and 137 km² in the municipality of Peabiru, in Paraná State. The Campo River is a left bank tributary of the Mourão River, which flows into the Ivaí River. The objective of this study was to monitor water quality in the Km 119 River and the Campo River, tributaries of the Mourão River, with monthly collection of water samples to determine pH, temperature, turbidity, biochemical oxygen demand, dissolved oxygen, fecal coliforms, total solids, total nitrogen, ammoniacal nitrogen, nitrite, nitrate and total phosphorus. The results obtained were compared with the indices established by the environmental legislation and applied in the determination of the Water Quality Index (WQI) used by the Water Institute of Paraná State, regulating environmental agency. Poor water quality in these rivers presents a worrying scenario for the region, since this river is the main source of water supply for the public system. Results of organic matter, fecal coliforms and total phosphorus were higher than the limits established by Resolution CONAMA 357/2005 to river class 2, specially at downstream of the Km 119 River and the Campo River, due to the significant influence of the urban anthropic activity by the lack of tertiary treatment and also rural by the lack of basic sanitation in this area. Results of WQI of Km 119 River and do Campo River indicated that water quality can be classified as average in 71% and good in 29% of the sites evaluated.

Influence of urban area on the water quality of the Campo River basin, Paraná State, Brazil / Influência da área urbana na qualidade das águas na Bacia do Rio do Campo River, estado do Paraná, Brasil

The Campo River basin is located on the third plateau of the Paraná State or trap plateau of Paraná, at the middle portion between the rivers Ivaí and Piquiri, southern Brazil, between the coordinates 23° 53 and 24° 10’ South Latitude and 52° 15’ and 52° 31’ West Longitude. The basin has 384 Km² area, being 247 km2 in the municipality of Campo Mourão and 137 km2 in the municipality of Peabiru, in Paraná State. The Campo River is a left bank tributary of the Mourão River, which flows into the Ivaí River. The objective of this study was to monitor water quality in the Km 119 River and the Campo River, tributaries of the Mourão River, with monthly collection of water samples to determine pH, temperature, turbidity, biochemical oxygen demand, dissolved oxygen, fecal coliforms, total solids, total nitrogen, ammoniacal nitrogen, nitrite, nitrate and total phosphorus. The results obtained were compared with the indices established by the environmental legislation and applied in the determination of the Water Quality Index (WQI) used by the Water Institute of Paraná State, regulating environmental agency. Poor water quality in these rivers presents a worrying scenario for the region, since this river is the main source of water supply for the public system. Results of organic matter, fecal coliforms and total phosphorus were higher than the limits established by Resolution CONAMA 357/2005 to river class 2, specially at downstream of the Km 119 River and the Campo River, due to the significant influence of the urban anthropic activity by the lack of tertiary treatment and also rural by the lack of basic sanitation in this area. Results of WQI of Km 119 River and do Campo River indicated that water quality can be classified as average in 71% and good in 29% of the sites evaluated.

Resumo A Bacia Hidrográfica Rio do Campo está situada no terceiro planalto paranaense, na porção média entre os rios Ivaí e Piquiri, Sul do Brasil, entre as coordenadas 23° 53’ e 24°10’ de Latitude Sul e 52°15’ e 52°31’ de Longitude Oeste. A bacia ocupa área de 384 Km2, sendo 247 km2 no município de Campo Mourão e 137 km2 no município de Peabiru, no estado do Paraná. O Rio do Campo é um afluente da margem esquerda do Rio Mourão, que deságua no Rio Ivaí. O objetivo deste trabalho foi monitorar a qualidade da água do rio Km 119 e rio do Campo, afluentes do Rio Mourão, com coletas mensais de amostras de água para determinação do pH, temperatura, turbidez, demanda bioquímica de oxigênio, oxigênio dissolvido, coliformes fecais, sólidos totais, nitrogênio total, nitrogênio amoniacal, nitrito, nitrato e fósforo total. Os resultados obtidos foram comparados aos limites estabelecidos na legislação ambiental vigente para poluentes na água e aplicados na determinação do Índice de Qualidade das Águas (IQA) usado pelo Instituto das Águas do Paraná, órgão ambiental fiscalizador. A má qualidade observada nestes rios é preocupante para a região que usufruiu destas águas como principal fonte de abastecimento público. Resultados de matéria orgânica, coliformes totais e fósforo total extrapolaram os padrões estabelecidos na Resolução CONAMA 357/2005 para rio classe 2, especialmente à jusante do rio Km 119 e do Rio do Campo, devido à influência significativa da atividade antrópica urbana pela falta de tratamento terciário e rural pela falta de saneamento básico nesta área. Os resultados do IQA do Rio Km 119 e Rio do Campo indicam que as águas podem ser classificadas com qualidade média em 71% e boa em 29% nos pontos avaliados.

Influence of urban area on the water quality of the Campo River basin, Paraná State, Brazil

The Campo River basin is located on the third plateau of the Paraná State or trap plateau of Paraná, at the middle portion between the rivers Ivaí and Piquiri, southern Brazil, between the coordinates 23° 53 and 24° 10 South Latitude and 52° 15 and 52° 31 West Longitude. The basin has 384 Km² area, being 247 km2 in the municipality of Campo Mourão and 137 km2 in the municipality of Peabiru, in Paraná State. The Campo River is a left bank tributary of the Mourão River, which flows into the Ivaí River. The objective of this study was to monitor water quality in the Km 119 River and the Campo River, tributaries of the Mourão River, with monthly collection of water samples to determine pH, temperature, turbidity, biochemical oxygen demand, dissolved oxygen, fecal coliforms, total solids, total nitrogen, ammoniacal nitrogen, nitrite, nitrate and total phosphorus. The results obtained were compared with the indices established by the environmental legislation and applied in the determination of the Water Quality Index (WQI) used by the Water Institute of Paraná State, regulating environmental agency. Poor water quality in these rivers presents a worrying scenario for the region, since this river is the main source of water supply for the public system. Results of organic matter, fecal coliforms and total phosphorus were higher than the limits established by Resolution CONAMA 357/2005 to river class 2, specially at downstream of the Km 119 River and the Campo River, due to the significant influence of the urban anthropic activity by the lack of tertiary treatment and also rural by the lack of basic sanitation in this area. Results of WQI of Km 119 River and do Campo River indicated that water quality can be classified as average in 71% and good in 29% of the sites evaluated.

Resumo A Bacia Hidrográfica Rio do Campo está situada no terceiro planalto paranaense, na porção média entre os rios Ivaí e Piquiri, Sul do Brasil, entre as coordenadas 23° 53 e 24°10 de Latitude Sul e 52°15 e 52°31 de Longitude Oeste. A bacia ocupa área de 384 Km2, sendo 247 km2 no município de Campo Mourão e 137 km2 no município de Peabiru, no estado do Paraná. O Rio do Campo é um afluente da margem esquerda do Rio Mourão, que deságua no Rio Ivaí. O objetivo deste trabalho foi monitorar a qualidade da água do rio Km 119 e rio do Campo, afluentes do Rio Mourão, com coletas mensais de amostras de água para determinação do pH, temperatura, turbidez, demanda bioquímica de oxigênio, oxigênio dissolvido, coliformes fecais, sólidos totais, nitrogênio total, nitrogênio amoniacal, nitrito, nitrato e fósforo total. Os resultados obtidos foram comparados aos limites estabelecidos na legislação ambiental vigente para poluentes na água e aplicados na determinação do Índice de Qualidade das Águas (IQA) usado pelo Instituto das Águas do Paraná, órgão ambiental fiscalizador. A má qualidade observada nestes rios é preocupante para a região que usufruiu destas águas como principal fonte de abastecimento público. Resultados de matéria orgânica, coliformes totais e fósforo total extrapolaram os padrões estabelecidos na Resolução CONAMA 357/2005 para rio classe 2, especialmente à jusante do rio Km 119 e do Rio do Campo, devido à influência significativa da atividade antrópica urbana pela falta de tratamento terciário e rural pela falta de saneamento básico nesta área. Os resultados do IQA do Rio Km 119 e Rio do Campo indicam que as águas podem ser classificadas com qualidade média em 71% e boa em 29% nos pontos avaliados.

Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.

UNLABELLED: Modeling of dynamical systems using ordinary differential equations is a popular approach in the field of systems biology. Two of the most critical steps in this approach are to construct dynamical models of biochemical reaction networks for large datasets and complex experimental conditions and to perform efficient and reliable parameter estimation for model fitting. We present a modeling environment for MATLAB that pioneers these challenges. The numerically expensive parts of the calculations such as the solving of the differential equations and of the associated sensitivity system are parallelized and automatically compiled into efficient C code. A variety of parameter estimation algorithms as well as frequentist and Bayesian methods for uncertainty analysis have been implemented and used on a range of applications that lead to publications. AVAILABILITY AND IMPLEMENTATION: The Data2Dynamics modeling environment is MATLAB based, open source and freely available at http://www.data2dynamics.org. CONTACT: andreas.raue@fdm.uni-freiburg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

[Differential diagnosis of myeloproliferative neoplasms. Quantitative NF-E2 immunohistochemistry for differentiating between essential thrombocythemia and primary myelofibrosis]. / Differenzialdiagnose myelproliferativer Neoplasien. Quantitative NF-E2-Immunhistochemie zur Unterscheidung zwischen essenzieller Thrombozythämie und primärer Myelofibrose.

BACKGROUND: Besides essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) the myeloproliferative neoplasms (MPN) defined by the World Health Organization (WHO) comprise the entity of unclassifiable MPNs (MPN, U). The exact differential diagnosis of the specific MPN entities can be challenging particularly at early stages of the diseases. So far, pathologists have had to rely only on histomorphological evaluation of bone marrow biopsies in combination with laboratory data because helpful ancillary tests are not yet available. Even molecular tests, such as JAK2 mutation analysis are not helpful particularly in the differential diagnosis of ET and PMF because both entities are associated with the V617F mutation in 50 % of the cases. Recently overexpression of the transcription factor NF-E2 in MPN was described. MATERIALS AND METHODS: A collective of samples consisting of 163 bone marrow biopsies including 139 MPN cases was stained immunohistochemically for NF-E2 and analyzed regarding the subcellular localization of NF-E2 in erythroid progenitor cells. The results were compared between the MPN entities as well as the controls and statistical analyses were conducted. RESULTS AND DISCUSSION: This study showed that NF-E2 immunohistochemistry and analysis of the proportion of nuclear positive erythroblasts of all erythroid precursor cells can help to distinguish between ET and PMF even in early stages of the diseases. An MPN, U case showing a proportion of more than 20 % nuclear positive erythroblasts can be classified as a PMF with 92 % accuracy.

Comprehensive estimation of input signals and dynamics in biochemical reaction networks.

MOTIVATION: Cellular information processing can be described mathematically using differential equations. Often, external stimulation of cells by compounds such as drugs or hormones leading to activation has to be considered. Mathematically, the stimulus is represented by a time-dependent input function. Parameters such as rate constants of the molecular interactions are often unknown and need to be estimated from experimental data, e.g. by maximum likelihood estimation. For this purpose, the input function has to be defined for all times of the integration interval. This is usually achieved by approximating the input by interpolation or smoothing of the measured data. This procedure is suboptimal since the input uncertainties are not considered in the estimation process which often leads to overoptimistic confidence intervals of the inferred parameters and the model dynamics. RESULTS: This article presents a new approach which includes the input estimation into the estimation process of the dynamical model parameters by minimizing an objective function containing all parameters simultaneously. We applied this comprehensive approach to an illustrative model with simulated data and compared it to alternative methods. Statistical analyses revealed that our method improves the prediction of the model dynamics and the confidence intervals leading to a proper coverage of the confidence intervals of the dynamic parameters. The method was applied to the JAK-STAT signaling pathway. AVAILABILITY: MATLAB code is available on the authors' website http://www.fdmold.uni-freiburg.de/~schelker/. CONTACT: max.schelker@fdm.uni-freiburg.de SUPPLEMENTARY INFORMATION: Additional information is available at Bioinformatics Online.

TSSi--an R package for transcription start site identification from 5' mRNA tag data.

UNLABELLED: High-throughput sequencing has become an essential experimental approach for the investigation of transcriptional mechanisms. For some applications like ChIP-seq, several approaches for the prediction of peak locations exist. However, these methods are not designed for the identification of transcription start sites (TSSs) because such datasets contain qualitatively different noise. In this application note, the R package TSSi is presented which provides a heuristic framework for the identification of TSSs based on 5' mRNA tag data. Probabilistic assumptions for the distribution of the data, i.e. for the observed positions of the mapped reads, as well as for systematic errors, i.e. for reads which map closely but not exactly to a real TSS, are made and can be adapted by the user. The framework also comprises a regularization procedure which can be applied as a preprocessing step to decrease the noise and thereby reduce the number of false predictions. AVAILABILITY: The R package TSSi is available from the Bioconductor web site: www.bioconductor.org/packages/release/bioc/html/TSSi.html.

Addressing parameter identifiability by model-based experimentation.

Mathematical description of biological processes such as gene regulatory networks or signalling pathways by dynamic models utilising ordinary differential equations faces challenges if the model parameters like rate constants are estimated from incomplete and noisy experimental data. Typically, biological networks are only partially observed. Only a fraction of the modelled molecular species is measurable directly. This can result in structurally non-identifiable model parameters. Furthermore, practical non-identifiability can arise from limited amount and quality of experimental data. In the challenge of growing model complexity on one side, and experimental limitations on the other side, both types of non-identifiability arise frequently in systems biological applications often prohibiting reliable prediction of system dynamics. On theoretical grounds this article summarises how and why both types of non-identifiability arise. It exemplifies pitfalls where models do not yield reliable predictions of system dynamics because of non-identifiabilities. Subsequently, several approaches for identifiability analysis proposed in the literature are discussed. The aim is to provide an overview of applicable methods for detecting parameter identifiability issues. Once non-identifiability is detected, it can be resolved either by experimental design, measuring additional data under suitable conditions; or by model reduction, tailoring the size of the model to the information content provided by the experimental data. Both strategies enhance model predictability and will be elucidated by an example application. [Includes supplementary material].

Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood.

MOTIVATION: Mathematical description of biological reaction networks by differential equations leads to large models whose parameters are calibrated in order to optimally explain experimental data. Often only parts of the model can be observed directly. Given a model that sufficiently describes the measured data, it is important to infer how well model parameters are determined by the amount and quality of experimental data. This knowledge is essential for further investigation of model predictions. For this reason a major topic in modeling is identifiability analysis. RESULTS: We suggest an approach that exploits the profile likelihood. It enables to detect structural non-identifiabilities, which manifest in functionally related model parameters. Furthermore, practical non-identifiabilities are detected, that might arise due to limited amount and quality of experimental data. Last but not least confidence intervals can be derived. The results are easy to interpret and can be used for experimental planning and for model reduction. AVAILABILITY: An implementation is freely available for MATLAB and the PottersWheel modeling toolbox at http://web.me.com/andreas.raue/profile/software.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An error model for protein quantification.

MOTIVATION: Quantitative experimental data is the critical bottleneck in the modeling of dynamic cellular processes in systems biology. Here, we present statistical approaches improving reproducibility of protein quantification by immunoprecipitation and immunoblotting. RESULTS: Based on a large data set with more than 3600 data points, we unravel that the main sources of biological variability and experimental noise are multiplicative and log-normally distributed. Therefore, we suggest a log-transformation of the data to obtain additive normally distributed noise. After this transformation, common statistical procedures can be applied to analyze the data. An error model is introduced to account for technical as well as biological variability. Elimination of these systematic errors decrease variability of measurements and allow for a more precise estimation of underlying dynamics of protein concentrations in cellular signaling. The proposed error model is relevant for simulation studies, parameter estimation and model selection, basic tools of systems biology. AVAILABILITY: Matlab and R code is available from the authors on request. The data can be downloaded from our website www.fdm.uni-freiburg.de/~ckreutz/data.

Data-based identifiability analysis of non-linear dynamical models.

MOTIVATION: Mathematical modelling of biological systems is becoming a standard approach to investigate complex dynamic, non-linear interaction mechanisms in cellular processes. However, models may comprise non-identifiable parameters which cannot be unambiguously determined. Non-identifiability manifests itself in functionally related parameters, which are difficult to detect. RESULTS: We present the method of mean optimal transformations, a non-parametric bootstrap-based algorithm for identifiability testing, capable of identifying linear and non-linear relations of arbitrarily many parameters, regardless of model size or complexity. This is performed with use of optimal transformations, estimated using the alternating conditional expectation algorithm (ACE). An initial guess or prior knowledge concerning the underlying relation of the parameters is not required. Independent, and hence identifiable parameters are determined as well. The quality of data at disposal is included in our approach, i.e. the non-linear model is fitted to data and estimated parameter values are investigated with respect to functional relations. We exemplify our approach on a realistic dynamical model and demonstrate that the variability of estimated parameter values decreases from 81 to 1% after detection and fixation of structural non-identifiabilities.

Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells.

Sesquiterpene lactones are known for their anti-inflammatory activity which has been proven in various assays on DNA, mRNA and protein level. Here we report on the change in the gene expression profile in TNF-alpha stimulated human 293 cells after treatment with parthenolide using a cDNA microarray analysis. Twenty-one of 7028 genes were found to be up- and 18 down-regulated. They encode for chemoattractants, immune system proteins, glycoproteins, metabolism, serine proteinases, and transcription factors. Confirmatory analyses were carried out using quantitative real-time RT-PCR (TaqMan). Additional studies with selected genes revealed the concentration-dependent influence of parthenolide on the expression of these genes.

Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways.

Complex cellular networks regulate regeneration, detoxification and differentiation of hepatocytes. By combining experimental data with mathematical modelling, systems biology holds great promises to elucidate the key regulatory mechanisms involved and predict targets for efficient intervention. For the generation of high-quality quantitative data suitable for mathematical modelling a standardised in vitro system is essential. Therefore the authors developed standard operating procedures for the preparation and cultivation of primary mouse hepatocytes. To reliably monitor the dynamic induction of signalling pathways, the authors established starvation conditions and evaluated the extent of starvation-associated stress by quantifying several metabolic functions of cultured primary hepatocytes, namely activities of glutathione-S-transferase, glutamine synthetase, CYP3A as well as secretion of lactate and urea into the culture medium. Establishment of constant metabolic activities after an initial decrease compared with freshly isolated hepatocytes showed that the cultured hepatocytes achieve a new equilibrium state that was not affected by our starving conditions. To verify the highly reproducible dynamic activation of signalling pathways in the in vitro system, the authors examined the JAK-STAT, SMAD, PI3 kinase, MAP kinase, NF-kappaB and Wnt/beta-catenin signalling pathways. For the induction of gp130, JAK1 and STAT3 phosphorylation IL6 was used, whereas TGFbeta was applied to activate the phosphorylation of SMAD1, SMAD2 and SMAD3. Both Akt/PKB and ERK1/2 phosphorylation were stimulated by the addition of hepatocyte growth factor. The time-dependent induction of a pool of signalling competent beta-catenin was monitored in response to the inhibition of GSK3beta. To analyse whether phosphorylation is actually leading to transcriptional responses, luciferase reporter gene constructs driven by multiple copies of TGFbeta-responsive motives were applied, demonstrating a dose-dependent increase in luciferase activity. Moreover, the induction of apoptosis by the TNF-like cytokine Fas ligand was studied in the in vitro system. Thus, the mouse hepatocyte in vitro system provides an important basis for the generation of high-quality quantitative data under standardised cell culture conditions that is essential to elucidate critical hepatocellular functions by the systems biology approach.

Quantitative data generation for systems biology: the impact of randomisation, calibrators and normalisers.

Systems biology is an approach to the analysis and prediction of the dynamic behaviour of biological networks through mathematical modelling based on experimental data. The current lack of reliable quantitative data, especially in the field of signal transduction, means that new methodologies in data acquisition and processing are needed. Here, we present methods to advance the established techniques of immunoprecipitation and immunoblotting to more accurate and quantitative procedures. We propose randomisation of sample loading to disrupt lane correlations and the use of normalisers and calibrators for data correction. To predict the impact of each method on improving the data quality we used simulations. These studies showed that randomisation reduces the standard deviation of a smoothed signal by 55% +/- 10%, independently from most experimental settings. Normalisation with appropriate endogenous or external proteins further reduces the deviation from the true values. As the improvement strongly depends on the quality of the normaliser measurement, a criteria-based normalisation procedure was developed. Our approach was experimentally verified by application of the proposed methods to time course data obtained by the immunoblotting technique. This analysis showed that the procedure is robust and can significantly improve the quality of experimental data.

Molecular, immunological and clinical properties of mutated hepatitis B viruses.

Hepatitis B virus (HBV) is at the origin of severe liver diseases like chronic active hepatitis, liver cirrhosis and hepatocellular carcinoma. There are some groups of patients with high risk of generation of HBV mutants: infected infants, immunosuppressed individuals (including hemodialysis patients), patients treated with interferon and lamivudine for chronic HBV infection. These groups are the target for molecular investigations reviewed in this paper. The emergence of lamivudine- or other antiviral-resistant variants, rises concern regarding long term use of these drugs. Infection or immunization with one HBV subtype confers immunity to all subtypes. However, reinfection or reactivation of latent HBV infection with HBV mutants have been reported in patients undergoing transplant and those infected with HIV. Mutations of the viral genome which are not replicative incompetent can be selected in further course of infection or under prolonged antiviral treatment and might maintain the liver disease. Four open reading frames (ORF) which are called S-gene, C-gene, X-gene and P-gene were identified within the HBV genome. Mutations may affect each of the ORFs. Mutated S-genes were described to be responsible for HBV-infections in successfully vaccinated persons, mutated C-genes were found to provoke severe chronic liver diseases, mutated X-genes could cause serious medical problems in blood donors by escaping the conventional test systems and mutated P-genes were considered to be the reason for chemotherapeutic drug resistance. This paper reviews molecular, immunological and clinical aspects of the HBV mutants.

Fibronectin and laminin binding of eighteen Clostridium species.

The ability of Clostridium difficile, Clostridium perfringens, Clostridium sporogenes and fifteen other Clostridium species to bind to human serum fibronectin or laminin was tested by using protein-coated latex particles. Three groups of Clostridium species were formed, namely the pseudomembranous colitis-causing species Clostridium difficile, the gas gangrene-causing Clostridium species and other Clostridium species, which are infrequently found in human infections. Significantly more strains of gas gangrene-causing Clostridium species, and strains of Clostridium species other than Clostridium difficile recognized fibronectin or laminin than did Clostridium difficile. Experiments with monoclonal antibodies revealed the specificity of the bacterial binding to fibronectin or laminin.