1000 resultados para Biological characters


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AIM: Specific factors responsible for interindividual variability should be identified and their contribution quantified to improve the usefulness of biological monitoring. Among others, age is an easily identifiable determinant, which could play an important impact on biological variability. MATERIALS AND METHODS: A compartmental toxicokinetic model developed in previous studies for a series of metallic and organic compounds was applied to the description of age differences. Young male physiological and metabolic parameters, based on Reference Man information, were taken from preceding studies and were modified to take into account age based on available information about age differences. RESULTS: Numerical simulation using the kinetic model with the modified parameters indicates 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. CONCLUSION: These differences appear to depend on the chemical and on the biological entity considered. Further work should be done to improve our estimates of these parameters, by considering for example uncertainty and variability in these parameters. [Authors]

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Selostus: Ruokohelven siementuotanto-ominaisuudet ja itävyys Suomessa

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Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34,216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10(-7)). These findings replicate in a second large data set (N=127,274, thereof 76,242 smokers) for both SI (P=1.2 × 10(-5)) and CPD (P=9.3 × 10(-5)). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.

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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.

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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.

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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.

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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.

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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.

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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.

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Primary sensory neurons were grown under four conditions of culture. The influence of nonneuronal cells, horse serum or both was studied on the phenotypic expression of certain neuronal subpopulations. The number of neurons expressing acetylcholinesterase, alpha-bungarotoxin-binding sites or a high uptake capacity for glutamine was enhanced by nonneuronal cells. The horse serum increases the neuronal subpopulation exhibiting a carbonic anhydrase activity. Certain phenotypic changes fit conditions consistent with an epigenetic induction rather than a cell selection.