707 research outputs found

    Cd, Pb and Hg Biomonitoring in Fish of the Mediterranean Region and Risk Estimations on Fish Consumption

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    Cadmium (Cd), lead (Pb) and mercury (Hg) are toxic metals with increasing interest due to their tendency to bioaccumulate in fish tissue which may pose a threat to human health via fish consumption. This review of the recent literature on Cd, Pb, Hg levels summarizes data of fish biomonitoring studies in the Mediterranean Sea in order to determine potential risks due to dietary intake of metals. The analytical methods applied are described, with Atomic Absorption Spectroscopy and Inductively Coupled Plasma Mass Spectroscopy being the most popular. Most of the literature reviewed is focused on the Eastern Mediterranean. Results from the studies indicate that metals mostly accumulate in liver, followed by muscle. Although there are few studies reporting metal levels in fish exceeding the maximum residue levels (MRLs), the bulk of the studies cite levels below the MRLs. The hazard index (HI) of fish consumption, namely the ratio of estimated weekly intake to provisional tolerable weekly intake (EWI/PTWI) was estimated for adult consumers and no risk emerged. The EWI/PTWI ratios of lead and mercury for Italy (0.14 and 0.22 respectively) represent the highest HI levels estimated. In view of maximizing the benefits while minimizing the risks of fish consumption, a more detailed fish-specific database on intakes for consumers is required and extended bimonitoring in as many regions as possible

    Developing a scalable model of recombinant protein yield from Pichia pastoris: the influence of culture conditions, biomass and induction regime

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    <p>Abstract</p> <p>Background</p> <p>The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors.</p> <p>Results</p> <p>Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from <it>Pichia pastoris</it>, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism.</p> <p>Conclusion</p> <p>We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.</p

    A quantitative risk assessment for skin sensitizing plant protection products: Linking derived No-Effect levels (DNELs) with agricultural exposure models.

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    Chemical skin sensitizers produce allergic contact dermatitis, which is one of the most frequent occupational diseases associated with chemical exposures. Skin exposure is the major route of exposure when using plant protection products (PPPs). Therefore, skin sensitization is an important factor to be addressed during the regulatory risk assessment of PPPs. The main regulatory decision criterion considered when performing risk assessment for skin sensitizers is the dose applied. The equally important criteria "potency of the substance" is insufficiently considered by two potency categories as potency may vary up to five orders of magnitude. "Frequency of exposure" to the skin sensitizer is not considered at all. Consequently, an improved risk assessment methodology is essential to adequately assess health risks from skin sensitizers, especially for agricultural operators using PPPs. A quantitative risk assessment (QRA) approach for addressing PPPs sensitizing potential is proposed here. This QRA combines a methodology to derive a substance-specific threshold for skin sensitizers, a Derived No-Effect Level (DNEL), and an agricultural exposure model used for assessing chronic health risks of PPPs. The proposed QRA for skin sensitizing PPPs is a clear improvement over current risk assessment to ensure the safe use of skin sensitizers in an occupational context

    Poly(3,4-ethylenedioxythiophene) as a Micro-Neural Interface Material for Electrostimulation

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    Chronic microstimulation-based devices are being investigated to treat conditions such as blindness, deafness, pain, paralysis, and epilepsy. Small-area electrodes are desired to achieve high selectivity. However, a major trade-off with electrode miniaturization is an increase in impedance and charge density requirements. Thus, the development of novel materials with lower interfacial impedance and enhanced charge storage capacity is essential for the development of micro-neural interface-based neuroprostheses. In this report, we study the use of conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) as a neural interface material for microstimulation of small-area iridium electrodes on silicon-substrate arrays. Characterized by electrochemical impedance spectroscopy, electrodeposition of PEDOT results in lower interfacial impedance at physiologically relevant frequencies, with the 1 kHz impedance magnitude being 23.3 ± 0.7 kΩ, compared to 113.6 ± 3.5 kΩ for iridium oxide (IrOx) on 177 μm2 sites. Further, PEDOT exhibits enhanced charge storage capacity at 75.6 ± 5.4 mC/cm2 compared to 28.8 ± 0.3 mC/cm2 for IrOx, characterized by cyclic voltammetry (50 mV/s). These improvements at the electrode interface were corroborated by observation of the voltage excursions that result from constant current pulsing. The PEDOT coatings provide both a lower amplitude voltage and a more ohmic representation of the applied current compared to IrOx. During repetitive pulsing, PEDOT-coated electrodes show stable performance and little change in electrical properties, even at relatively high current densities which cause IrOx instability. These findings support the potential of PEDOT coatings as a micro-neural interface material for electrostimulation

    Transcriptome analysis of a respiratory Saccharomyces cerevisiae strain suggests the expression of its phenotype is glucose insensitive and predominantly controlled by Hap4, Cat8 and Mig1

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    BACKGROUND: We previously described the first respiratory Saccharomyces cerevisiae strain, KOY.TM6*P, by integrating the gene encoding a chimeric hexose transporter, Tm6*, into the genome of an hxt null yeast. Subsequently we transferred this respiratory phenotype in the presence of up to 50 g/L glucose to a yeast strain, V5 hxt1-7Delta, in which only HXT1-7 had been deleted. In this study, we compared the transcriptome of the resultant strain, V5.TM6*P, with that of its wild-type parent, V5, at different glucose concentrations. RESULTS: cDNA array analyses revealed that alterations in gene expression that occur when transitioning from a respiro-fermentative (V5) to a respiratory (V5.TM6*P) strain, are very similar to those in cells undergoing a diauxic shift. We also undertook an analysis of transcription factor binding sites in our dataset by examining previously-published biological data for Hap4 (in complex with Hap2, 3, 5), Cat8 and Mig1, and used this in combination with verified binding consensus sequences to identify genes likely to be regulated by one or more of these. Of the induced genes in our dataset, 77% had binding sites for the Hap complex, with 72% having at least two. In addition, 13% were found to have a binding site for Cat8 and 21% had a binding site for Mig1. Unexpectedly, both the up- and down-regulation of many of the genes in our dataset had a clear glucose dependence in the parent V5 strain that was not present in V5.TM6*P. This indicates that the relief of glucose repression is already operable at much higher glucose concentrations than is widely accepted and suggests that glucose sensing might occur inside the cell. CONCLUSION: Our dataset gives a remarkably complete view of the involvement of genes in the TCA cycle, glyoxylate cycle and respiratory chain in the expression of the phenotype of V5.TM6*P. Furthermore, 88% of the transcriptional response of the induced genes in our dataset can be related to the potential activities of just three proteins: Hap4, Cat8 and Mig1. Overall, our data support genetic remodelling in V5.TM6*P consistent with a respiratory metabolism which is insensitive to external glucose concentrations

    Statistical coverage for supersymmetric parameter estimation: a case study with direct detection of dark matter

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    Models of weak-scale supersymmetry offer viable dark matter (DM) candidates. Their parameter spaces are however rather large and complex, such that pinning down the actual parameter values from experimental data can depend strongly on the employed statistical framework and scanning algorithm. In frequentist parameter estimation, a central requirement for properly constructed confidence intervals is that they cover true parameter values, preferably at exactly the stated confidence level when experiments are repeated infinitely many times. Since most widely-used scanning techniques are optimised for Bayesian statistics, one needs to assess their abilities in providing correct confidence intervals in terms of the statistical coverage. Here we investigate this for the Constrained Minimal Supersymmetric Standard Model (CMSSM) when only constrained by data from direct searches for dark matter. We construct confidence intervals from one-dimensional profile likelihoods and study the coverage by generating several pseudo-experiments for a few benchmark sets of pseudo-true parameters. We use nested sampling to scan the parameter space and evaluate the coverage for the benchmarks when either flat or logarithmic priors are imposed on gaugino and scalar mass parameters. The sampling algorithm has been used in the configuration usually adopted for exploration of the Bayesian posterior. We observe both under- and over-coverage, which in some cases vary quite dramatically when benchmarks or priors are modified. We show how most of the variation can be explained as the impact of explicit priors as well as sampling effects, where the latter are indirectly imposed by physicality conditions. For comparison, we also evaluate the coverage for Bayesian credible intervals, and observe significant under-coverage in those cases.Comment: 30 pages, 5 figures; v2 includes major updates in response to referee's comments; extra scans and tables added, discussion expanded, typos corrected; matches published versio

    The synthesis of recombinant membrane proteins in yeast for structural studies

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    Historically, recombinant membrane protein production has been a major challenge meaning that many fewer membrane protein structures have been published than those of soluble proteins. However, there has been a recent, almost exponential increase in the number of membrane protein structures being deposited in the Protein Data Bank. This suggests that empirical methods are now available that can ensure the required protein supply for these difficult targets. This review focuses on methods that are available for protein production in yeast, which is an important source of recombinant eukaryotic membrane proteins. We provide an overview of approaches to optimize the expression plasmid, host cell and culture conditions, as well as the extraction and purification of functional protein for crystallization trials in preparation for structural studies
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