178 research outputs found

    Recommendations for the design of laboratory studies on non-target arthropods for risk assessment of genetically engineered plants

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    This paper provides recommendations on experimental design for early-tier laboratory studies used in risk assessments to evaluate potential adverse impacts of arthropod-resistant genetically engineered (GE) plants on non-target arthropods (NTAs). While we rely heavily on the currently used proteins from Bacillus thuringiensis (Bt) in this discussion, the concepts apply to other arthropod-active proteins. A risk may exist if the newly acquired trait of the GE plant has adverse effects on NTAs when they are exposed to the arthropod-active protein. Typically, the risk assessment follows a tiered approach that starts with laboratory studies under worst-case exposure conditions; such studies have a high ability to detect adverse effects on non-target species. Clear guidance on how such data are produced in laboratory studies assists the product developers and risk assessors. The studies should be reproducible and test clearly defined risk hypotheses. These properties contribute to the robustness of, and confidence in, environmental risk assessments for GE plants. Data from NTA studies, collected during the analysis phase of an environmental risk assessment, are critical to the outcome of the assessment and ultimately the decision taken by regulatory authorities on the release of a GE plant. Confidence in the results of early-tier laboratory studies is a precondition for the acceptance of data across regulatory jurisdictions and should encourage agencies to share useful information and thus avoid redundant testing

    Sensitivity of RT-PCR method in samples shown to be positive for Zika virus by RT-qPCR in vector competence studies

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    Abstract Tissue samples from mosquitoes artificially infected with Zika virus and shown to be positive by RT-qPCR were reexamined by RT-PCR. Using these samples we compared the two methods employed in virus RNA detection for vector competence studies. Results demonstrated that, albeit useful, RT-PCR gave false negatives with low viral loads (< 106 RNA copies/ml)

    Quantitative Assessment of Whole-Body Tumor Burden in Adult Patients with Neurofibromatosis

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    Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis are at risk for multiple nerve sheath tumors and premature mortality. Traditional magnetic resonance imaging (MRI) has limited ability to assess disease burden accurately. The aim of this study was to establish an international cohort of patients with quantified whole-body internal tumor burden and to correlate tumor burden with clinical features of disease.We determined the number, volume, and distribution of internal nerve sheath tumors in patients using whole-body MRI (WBMRI) and three-dimensional computerized volumetry. We quantified the distribution of tumor volume across body regions and used unsupervised cluster analysis to group patients based on tumor distribution. We correlated the presence and volume of internal tumors with disease-related and demographic factors.WBMRI identified 1286 tumors in 145/247 patients (59%). Schwannomatosis patients had the highest prevalence of tumors (P = 0.03), but NF1 patients had the highest median tumor volume (P = 0.02). Tumor volume was unevenly distributed across body regions with overrepresentation of the head/neck and pelvis. Risk factors for internal nerve sheath tumors included decreasing numbers of café-au-lait macules in NF1 patients (P = 0.003) and history of skeletal abnormalities in NF2 patients (P = 0.09). Risk factors for higher tumor volume included female gender (P = 0.05) and increasing subcutaneous neurofibromas (P = 0.03) in NF1 patients, absence of cutaneous schwannomas in NF2 patients (P = 0.06), and increasing age in schwannomatosis patients (p = 0.10).WBMRI provides a comprehensive phenotype of neurofibromatosis patients, identifies distinct anatomic subgroups, and provides the basis for investigating molecular biomarkers that correlate with unique disease manifestations

    Association and interaction of PPAR-complex gene variants with latent traits of left ventricular diastolic function

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    <p>Abstract</p> <p>Background</p> <p>Abnormalities in myocardial metabolism and/or regulatory genes have been implicated in left ventricular systolic dysfunction. However, the extent to which these modulate left ventricular diastolic function (LVDF) is uncertain.</p> <p>Methods</p> <p>Independent component analysis was applied to extract latent LVDF traits from 14 measured echocardiography-derived endophenotypes of LVDF in 403 Caucasians. Genetic association was assessed between measured and latent LVDF traits and 64 single nucleotide polymorphisms (SNPs) in three peroxisome proliferator-activated receptor <it>(PPAR)</it>-complex genes involved in the transcriptional regulation of fatty acid metabolism.</p> <p>Results</p> <p>By linear regression analysis, 7 SNPs (4 in <it>PPARA</it>, 2 in <it>PPARGC1A</it>, 1 in <it>PPARG</it>) were significantly associated with the latent LVDF trait, whereas a range of 0-4 SNPs were associated with each of the 14 measured echocardiography-derived endophenotypes. Frequency distribution of <it>P </it>values showed a greater proportion of significant associations with the latent LVDF trait than for the measured endophenotypes, suggesting that analyses of the latent trait improved detection of the genetic underpinnings of LVDF. Ridge regression was applied to investigate within-gene and gene-gene interactions. In the within-gene analysis, there were five significant pair-wise interactions in <it>PPARGC1A </it>and none in <it>PPARA </it>or <it>PPARG</it>. In the gene-gene analysis, significant interactions were found between rs4253655 in <it>PPARA </it>and rs1873532 (p = 0.02) and rs7672915 (p = 0.02), both in <it>PPARGC1A</it>, and between rs1151996 in <it>PPARG </it>and rs4697046 in <it>PPARGC1A </it>(p = 0.01).</p> <p>Conclusions</p> <p>Myocardial metabolism <it>PPAR</it>-complex genes, including within and between genes interactions, may play an important role modulating left ventricular diastolic function.</p

    Serotonergic chemosensory neurons modify the <i>C. elegans</i> immune response by regulating G-protein signaling in epithelial cells

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    The nervous and immune systems influence each other, allowing animals to rapidly protect themselves from changes in their internal and external environment. However, the complex nature of these systems in mammals makes it difficult to determine how neuronal signaling influences the immune response. Here we show that serotonin, synthesized in Caenorhabditis elegans chemosensory neurons, modulates the immune response. Serotonin released from these cells acts, directly or indirectly, to regulate G-protein signaling in epithelial cells. Signaling in these cells is required for the immune response to infection by the natural pathogen Microbacterium nematophilum. Here we show that serotonin signaling suppresses the innate immune response and limits the rate of pathogen clearance. We show that C. elegans uses classical neurotransmitters to alter the immune response. Serotonin released from sensory neurons may function to modify the immune system in response to changes in the animal's external environment such as the availability, or quality, of food

    Persistence of dissolved organic matter explained by molecular changes during its passage through soil

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    Dissolved organic matter affects fundamental biogeochemical processes in the soil such as nutrient cycling and organic matter storage. The current paradigm is that processing of dissolved organic matter converges to recalcitrant molecules (those that resist degradation) of low molecular mass and high molecular diversity through biotic and abiotic processes. Here we demonstrate that the molecular composition and properties of dissolved organic matter continuously change during soil passage and propose that this reflects a continual shifting of its sources. Using ultrahigh-resolution mass spectrometry and nuclear magnetic resonance spectroscopy, we studied the molecular changes of dissolved organic matter from the soil surface to 60 cm depth in 20 temperate grassland communities in soil type Eutric Fluvisol. Applying a semi-quantitative approach, we observed that plant-derived molecules were first broken down into molecules containing a large proportion of low-molecular-mass compounds. These low-molecular-mass compounds became less abundant during soil passage, whereas larger molecules, depleted in plant-related ligno-cellulosic structures, became more abundant. These findings indicate that the small plant-derived molecules were preferentially consumed by microorganisms and transformed into larger microbial-derived molecules. This suggests that dissolved organic matter is not intrinsically recalcitrant but instead persists in soil as a result of simultaneous consumption, transformation and formation

    Serotonin synthesis, release and reuptake in terminals: a mathematical model

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    <p>Abstract</p> <p>Background</p> <p>Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding of serotonergic systems in the central nervous system involves genomics, neurochemistry, electrophysiology, and behavior. Though associations have been found between functions at these different levels, in most cases the causal mechanisms are unknown. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders in the serotonergic signaling system.</p> <p>Methods</p> <p>We construct a mathematical model of serotonin synthesis, release, and reuptake in a single serotonergic neuron terminal. The model includes the effects of autoreceptors, the transport of tryptophan into the terminal, and the metabolism of serotonin, as well as the dependence of release on the firing rate. The model is based on real physiology determined experimentally and is compared to experimental data.</p> <p>Results</p> <p>We compare the variations in serotonin and dopamine synthesis due to meals and find that dopamine synthesis is insensitive to the availability of tyrosine but serotonin synthesis is sensitive to the availability of tryptophan. We conduct <it>in silico </it>experiments on the clearance of extracellular serotonin, normally and in the presence of fluoxetine, and compare to experimental data. We study the effects of various polymorphisms in the genes for the serotonin transporter and for tryptophan hydroxylase on synthesis, release, and reuptake. We find that, because of the homeostatic feedback mechanisms of the autoreceptors, the polymorphisms have smaller effects than one expects. We compute the expected steady concentrations of serotonin transporter knockout mice and compare to experimental data. Finally, we study how the properties of the the serotonin transporter and the autoreceptors give rise to the time courses of extracellular serotonin in various projection regions after a dose of fluoxetine.</p> <p>Conclusions</p> <p>Serotonergic systems must respond robustly to important biological signals, while at the same time maintaining homeostasis in the face of normal biological fluctuations in inputs, expression levels, and firing rates. This is accomplished through the cooperative effect of many different homeostatic mechanisms including special properties of the serotonin transporters and the serotonin autoreceptors. Many difficult questions remain in order to fully understand how serotonin biochemistry affects serotonin electrophysiology and vice versa, and how both are changed in the presence of selective serotonin reuptake inhibitors. Mathematical models are useful tools for investigating some of these questions.</p

    Development and evaluation of a rapid molecular diagnostic test for Zika virus infection by reverse transcription loop-mediated isothermal amplification

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    The recent outbreak of Zika virus (ZIKV) disease caused an enormous number of infections in Central and South America, and the unusual increase in the number of infants born with microcephaly associated with ZIKV infection aroused global concern. Here, we developed a reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay using a portable device for the detection of ZIKV. The assay specifically detected ZIKV strains of both Asian and African genotypes without cross-reactivity with other arboviruses, including Dengue and Chikungunya viruses. The assay detected viral RNA at 14.5 TCID50/mL in virus-spiked serum or urine samples within 15?min, although it was slightly less sensitive than reference real time RT-PCR assay. We then evaluated the utility of this assay as a molecular diagnostic test using 90 plasma or serum samples and 99 urine samples collected from 120 suspected cases of arbovirus infection in the states of Paraiba and Pernambuco, Brazil in 2016. The results of this assay were consistent with those of the reference RT-PCR test. This portable RT-LAMP assay was highly specific for ZIKV, and enable rapid diagnosis of the virus infection. Our results provide new insights into ZIKV molecular diagnostics and may improve preparedness for future outbreaks

    A thermosensitive electromechanical model for detecting biological particles

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    Miniature electromechanical systems form a class of bioMEMS that can provide appropriate sensitivity. In this research, a thermo-electro-mechanical model is presented to detect biological particles in the microscale. Identification in the model is based on analyzing pull-in instability parameters and frequency shifts. Here, governing equations are derived via the extended Hamilton’s principle. The coupled effects of system parameters such as surface layer energy, electric field correction, and material properties are incorporated in this thermosensitive model. Afterward, the accuracy of the present model and obtained results are validated with experimental, analytical, and numerical data for several cases. Performing a parametric study reveals that mechanical properties of biosensors can significantly affect the detection sensitivity of actuated ultra-small detectors and should be taken into account. Furthermore, it is shown that the number or dimension of deposited particles on the sensing zone can be estimated by investigating the changes in the threshold voltage, electrode deflection, and frequency shifts. The present analysis is likely to provide pertinent guidelines to design thermal switches and miniature detectors with the desired performance. The developed biosensor is more appropriate to detect and characterize viruses in samples with different temperatures
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