Characterization and classification of matrix effects in biological samples analyses.

An exhaustive classification of matrix effects occurring when a sample preparation is performed prior to liquid-chromatography coupled to mass spectrometry (LC-MS) analyses was proposed. A total of eight different situations were identified allowing the recognition of the matrix effect typology via the calculation of four recovery values. A set of 198 compounds was used to evaluate matrix effects after solid phase extraction (SPE) from plasma or urine samples prior to LC-ESI-MS analysis. Matrix effect identification was achieved for all compounds and classified through an organization chart. Only 17% of the tested compounds did not present significant matrix effects.

Using toxicokinetic modeling approach to determine biological reference values (BRVs) and to assess human exposure to pesticides

Exposure to various pesticides has been characterized in workers and the general population, but interpretation and assessment of biomonitoring data from a health risk perspective remains an issue. For workers, a Biological Exposure Index (BEI®) has been proposed for some substances, but most BEIs are based on urinary biomarker concentrations at Threshold Limit Value - Time Weighted Average (TLV-TWA) airborne exposure while occupational exposure can potentially occurs through multiple routes, particularly by skin contact (i.e.captan, chlorpyrifos, malathion). Similarly, several biomonitoring studies have been conducted to assess environmental exposure to pesticides in different populations, but dose estimates or health risks related to these environmental exposures (mainly through the diet), were rarely characterized. Recently, biological reference values (BRVs) in the form of urinary pesticide metabolites have been proposed for both occupationally exposed workers and children. These BRVs were established using toxicokinetic models developed for each substance, and correspond to safe levels of absorption in humans, regardless of the exposure scenario. The purpose of this chapter is to present a review of a toxicokinetic modeling approach used to determine biological reference values. These are then used to facilitate health risk assessments and decision-making on occupational and environmental pesticide exposures. Such models have the ability to link absorbed dose of the parent compound to exposure biomarkers and critical biological effects. To obtain the safest BRVs for the studied population, simulations of exposure scenarios were performed using a conservative reference dose such as a no-observed-effect level (NOEL). The various examples discussed in this chapter show the importance of knowledge on urine collections (i.e. spot samples and complete 8-h, 12-h or 24-h collections), sampling strategies, metabolism, relative proportions of the different metabolites in urine, absorption fraction, route of exposure and background contribution of prior exposures. They also show that relying on urinary measurements of specific metabolites appears more accurate when applying this approach to the case of occupational exposures. Conversely, relying on semi-specific metabolites (metabolites common to a category of pesticides) appears more accurate for the health risk assessment of environmental exposures given that the precise pesticides to which subjects are exposed are often unknown. In conclusion, the modeling approach to define BRVs for the relevant pesticides may be useful for public health authorities for managing issues related to health risks resulting from environmental and occupational exposures to pesticides.

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways.

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

Characterization for plant height and flowering date in the biological species oat

The use of wild oat races in artificial hybridization with cultivated oat (Avena sativa L.) has been used as a way of increasing the variability. This work aimed to identify the variability for plant height and flowering date of groups of cultivated oat genotypes, wild introductions of A. fatua L. and segregating populations of natural crosses between A. sativa and A. fatua. Wide genetic variability was observed for both traits in the groups and between them. The wild group of A. fatua L. showed high plants with early maturity, but in the segregating group there was reduced plant height and early maturity. The wild introductions of A. fatua L. studied in this work can be used in oat breeding programs to increase genetic variability by transferring specific characters into the cultivated germ plasm.

Molecular biology of baculovirus and its use in biological control in Brazil

Baculoviruses are insect viruses found mainly in Lepidoptera. The family Baculoviridae is taxonomically divided in two genera, Nucleopolyhedrovirus and Granulovirus, which differ by occlusion body morphology. NPVs (Nucleopolyhedroviruses) have polyhedrical inclusion bodies (PIBs) containing multiple viral particles, while GVs (Granuloviruses) appear to be generally single particles occluded in oval shaped occlusion bodies. During the life cycle, two different viral progenies are produced: BV (Budded Virus) and PDV (Polyhedra Derived Virus), which are essential for the infectious process and virus propagation in host cells. Baculoviruses are being used for pest control and they are especially safe due to their specificity and invertebrate-restricted host range. Baculoviruses have been used as vectors for high level protein expression ofheterologous genes from prokaryotic and eukaryotic organisms. Also, recombinant DNA techniques have allowed the production of genetically modified viral insecticides. This study is a review on the taxonomy, structure, replication and molecular biology of baculoviruses, as well as their use as bioinsecticides in Brazil.

Biological embedding of early-life exposures and disease risk in humans : a role for DNA methylation

BACKGROUND: Following wider acceptance of 'the thrifty phenotype' hypothesis and the convincing evidence that early-life exposures can influence adult health even decades after the exposure, much interest has been placed on the mechanisms through which early-life exposures become biologically embedded. MATERIALS AND METHODS: In this review, we summarize the current literature regarding biological embedding of early-life experiences. To this end, we conducted a literature search to identify studies investigating early-life exposures in relation to DNA methylation changes. In addition, we summarize the challenges faced in investigations of epigenetic effects, stemming from the peculiarities of this emergent and complex field. A proper systematic review and meta-analyses were not feasible given the nature of the evidence. RESULTS: We identified seven studies on early-life socio-economic circumstances, 10 studies on childhood obesity and six studies on early-life nutrition all relating to DNA methylation changes that met the stipulated inclusion criteria. The pool of evidence gathered, albeit small, favours a role of epigenetics and DNA methylation in biological embedding, but replication of findings, multiple comparison corrections, publication bias and causality are concerns remaining to be addressed in future investigations. CONCLUSIONS: Based on these results, we hypothesize that epigenetics, in particular DNA methylation, is a plausible mechanism through which early-life exposures are biologically embedded. This review describes the current status of the field and acts as a stepping stone for future, better designed investigations on how early-life exposures might become biologically embedded through epigenetic effects.

Growth and yield of common bean cultivars at two soil phosphorus levels under biological nitrogen fixation

The genotypic differences on growth and yield of common bean (Phaseolus vulgaris L.) in response to P supply were evaluated in a field experiment under biological N2 fixation. Eight cultivars were grown at two levels of applied P (12 and 50 kg ha-1 of P -- P1 and P2 respectively), in randomized block design in factorial arrangement. Vegetative biomass was sampled at three ontogenetic stages. The effects of genotype and phosphorus were significant for most traits, but not the genotype ´ phosphorus interaction. The cultivars presented different patterns of biomass production and nutrient accumulation, particularly on root system. At P1, P accumulation persisted after the beginning of pod filling, and P translocation from roots to shoots was lower. The nodule senescence observed after flowering might have reduced N2 fixation during pod filling. The responses of vegetative growth to the higher P supply did not reflect with the same magnitude on yield, which increased only 6% at P2; hence the harvest index was lower at P2. The cultivars with highest yields also presented lower grain P concentrations. A sub-optimal supply of N could have limited the expression of the yield potential of cultivars, reducing the genotypic variability of responses to P levels.

Generation of biological association networks: A novel strategy to detect new targets in cancer therapy

The aim of this work was to design a novel strategy to detect new targets for anticancer treatments. The rationale was to build Biological Association Networks from differentially expressed genes in drug-resistant cells to identify important nodes within the Networks. These nodes may represent putative targets to attack in cancer therapy, as a way to destabilize the gene network developed by the resistant cells to escape from the drug pressure. As a model we used cells resistant to methotrexate (MTX), an inhibitor of DHFR. Selected node-genes were analyzed at the transcriptional level and from a genotypic point of view. In colon cancer cells, DHFR, the AKR1 family, PKC¿, S100A4, DKK1, and CAV1 were overexpressed while E-cadherin was lost. In breast cancer cells, the UGT1A family was overexpressed, whereas EEF1A1 was overexpressed in pancreatic cells. Interference RNAs directed against these targets sensitized cells towards MTX.

Minimal analytical characterization of engineered nanomaterials needed for hazard assessment in biological matrices.

Abstract This paper presents the outcomes from a workshop of the European Network on the Health and Environmental Impact of Nanomaterials (NanoImpactNet). During the workshop, 45 experts in the field of safety assessment of engineered nanomaterials addressed the need to systematically study sets of engineered nanomaterials with specific metrics to generate a data set which would allow the establishment of dose-response relations. The group concluded that international cooperation and worldwide standardization of terminology, reference materials and protocols are needed to make progress in establishing lists of essential metrics. High quality data necessitates the development of harmonized study approaches and adequate reporting of data. Priority metrics can only be based on well-characterized dose-response relations derived from the systematic study of the bio-kinetics and bio-interactions of nanomaterials at both organism and (sub)-cellular levels. In addition, increased effort is needed to develop and validate analytical methods to determine these metrics in a complex matrix.

Biomedical and biological applications of scanning electron microscopy

This article summarizes the basic principles of scanning electron microscopy and the capabilities of the technique with different examples ofapplications in biomedical and biological research.

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases

AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Pathway databases and tools for their exploitation: benefits, current limitations and challenges

In past years, comprehensive representations of cell signalling pathways have been developed by manual curation from literature, which requires huge effort and would benefit from information stored in databases and from automatic retrieval and integration methods. Once a reconstruction of the network of interactions is achieved, analysis of its structural features and its dynamic behaviour can take place. Mathematical modelling techniques are used to simulate the complex behaviour of cell signalling networks, which ultimately sheds light on the mechanisms leading to complex diseases or helps in the identification of drug targets. A variety of databases containing information on cell signalling pathways have been developed in conjunction with methodologies to access and analyse the data. In principle, the scenario is prepared to make the most of this information for the analysis of the dynamics of signalling pathways. However, are the knowledge repositories of signalling pathways ready to realize the systems biology promise? In this article we aim to initiate this discussion and to provide some insights on this issue.

Biological monitoring of chemical exposure : toxicokinetic differences due to age and sex

Human biomonitoring is a widely used method in the assessment of occupational exposure to chemical substances and recommended biological limits are published periodically for interpretation and decision-making. However, it is increasingly recognized that a large variability is associated with biological monitoring, making interpretation less efficient than assumed. In order to improve the applicability of biological monitoring, specific factors responsible for this variability should be identified and their contribution quantified. Among these factors, age and sex are easily identifiable, and present knowledge about pharmaceutical chemicals suggests that they play an important role on the toxicokinetics of occupational chemical agents, and therefore on the biological monitoring results.The aim of the present research project was to assess the influence of age and sex on biological indicators corresponding to organic solvents. This has been done experimentally and by toxicokinetic computer simulation. Another purpose was to explore the effect of selected CYP2E1 polymorphisms on the toxicokinetic profile.Age differences were identified by numerical simulations using a general toxicokinetic model from a previous study which was applied to 14 chemicals, representing 21 specific biological entities, with, among others, toluene, phenol, lead and mercury. These models were runn with the modified parameters, indicating in some cases important differences due to age. The expected changes are mostly of the order of 10-20 %, but differences up to 50 % were observed in some cases. These differences appear to depend on the chemical and on the biological entity considered.Sex differences were quantified by controlled human exposures, which were carried out in a 12 m3 exposure chamber for three organic solvents separately: methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1-trichloroethane. The human volunteer groups were composed 12 of ten young men and fifteen young women, the latter subdivided into those with and without hormonal contraceptive. They were exposed during six hours at rest and at half of the threshold limit value. The kinetics of the parent compounds (organic volatiles) and their metabolite(s) were followed in blood, urine and expired air over time. Analyses of the solvent and their metabolites were performed by using headspace gas chromatography, CYP2E1 genotypes by using PCR-based RFLP methods. Experimental data were used to calibrate the toxicokinetic models developed for the three solvents. The results obtained for the different biomarkers of exposure mainly showed an effect on the urinary levels of several biomarkers among women due to the use of hormonal contraceptive, with an increase of about 50 % in the metabolism rate. The results also showed a difference due to the genotype CYP2E1*6, when exposed to methyl ethyl ketone, with a tendency to increase CYP2E1 activity when volunteers were carriers of the mutant allele. Simulations showed that it is possible to use simple toxicokinetic tools in order to predict internal exposure when exposed to organic solvents. Our study suggests that not only physiological differences but also exogenous sex hormones could influence CYP2E1 enzyme activity. The variability among the urinary biological indicators levels gives evidence of an interindividual susceptibility, an aspect that should have its place in the approaches for setting limits of occupational exposure.