136 research outputs found

    Protective role of vitamin B6 (PLP) against DNA damage in Drosophila models of type 2 diabetes

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    Growing evidence shows that improper intake of vitamin B6 increases cancer risk and several studies indicate that diabetic patients have a higher risk of developing tumors. We previously demonstrated that in Drosophila the deficiency of Pyridoxal 5' phosphate (PLP), the active form of vitamin B6, causes chromosome aberrations (CABs), one of cancer prerequisites, and increases hemolymph glucose content. Starting from these data we asked if it was possible to provide a link between the aforementioned studies. Thus, we tested the effect of low PLP levels on DNA integrity in diabetic cells. To this aim we generated two Drosophila models of type 2 diabetes, the first by impairing insulin signaling and the second by rearing flies in high sugar diet. We showed that glucose treatment induced CABs in diabetic individuals but not in controls. More interestingly, PLP deficiency caused high frequencies of CABs in both diabetic models demonstrating that hyperglycemia, combined to reduced PLP level, impairs DNA integrity. PLP-depleted diabetic cells accumulated Advanced Glycation End products (AGEs) that largely contribute to CABs as α-lipoic acid, an AGE inhibitor, rescued not only AGEs but also CABs. These data, extrapolated to humans, indicate that low PLP levels, impacting on DNA integrity, may be considered one of the possible links between diabetes and cancer

    Risk, balanced skills and entrepreneurship

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    This paper proposes that risk aversion encourages individuals to invest in balanced skill profiles, making them more likely to become entrepreneurs. By not taking this possible linkage into account, previous research has underestimated the impacts of both risk aversion and balanced skills on the likelihood individuals choose entrepreneurship. Data on Dutch university graduates provide an illustration supporting our contention. We raise the possibility that even risk-averse people might be suited to entrepreneurship; and it may also help explain why prior research has generated somewhat mixed evidence about the effects of risk aversion on selection into entrepreneurship

    Large scale variation in the rate of germ-line de novo mutation, base composition, divergence and diversity in humans

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    It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. However, it is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We investi- gate a number of questions pertaining to the distribution of mutations using more than 130,000 DNMs from three large datasets. We demonstrate that the amount and pattern of variation differs between datasets at the 1MB and 100KB scales probably as a consequence of differences in sequencing technology and processing. In particular, datasets show differ- ent patterns of correlation to genomic variables such as replication time. Never-the-less there are many commonalities between datasets, which likely represent true patterns. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that can- not be explained by variation at smaller scales, however the level of this variation is modest at large scales–at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome. We demonstrate that variation in the mutation rate does not generate large-scale variation in GC-content, and hence that mutation bias does not maintain the isochore struc- ture of the human genome. We find that genomic features explain less than 40% of the explainable variance in the rate of DNM. As expected the rate of divergence between spe- cies is correlated to the rate of DNM. However, the correlations are weaker than expected if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered

    Mediated behavioural change in human-machine networks: exploring network characteristics, trust and motivation

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    Human-machine networks pervade much of contemporary life. Network change is the product of structural modifications along with differences in participant be-havior. If we assume that behavioural change in a human-machine network is the result of changing the attitudes of participants in the network, then the question arises whether network structure can affect participant attitude. Taking citizen par-ticipation as an example, engagement with relevant stakeholders reveals trust and motivation to be the major objectives for the network. Using a typology to de-scribe network state based on multiple characteristic or dimensions, we can pre-dict possible behavioural outcomes in the network. However, this has to be medi-ated via attitude change. Motivation for the citizen participation network can only increase in line with enhanced trust. The focus for changing network dynamics, therefore, shifts to the dimensional changes needed to encourage increased trust. It turns out that the coordinated manipulation of multiple dimensions is needed to bring about the desired shift in attitude.Comment: Paper submitted to SocInfo, organised by the Oxford Internet Institute, September 201

    Immunological properties of Oxygen-Transport Proteins: Hemoglobin, Hemocyanin and Hemerythrin

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    Environmental Constraints Guide Migration of Malaria Parasites during Transmission

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    Migrating cells are guided in complex environments mainly by chemotaxis or structural cues presented by the surrounding tissue. During transmission of malaria, parasite motility in the skin is important for Plasmodium sporozoites to reach the blood circulation. Here we show that sporozoite migration varies in different skin environments the parasite encounters at the arbitrary sites of the mosquito bite. In order to systematically examine how sporozoite migration depends on the structure of the environment, we studied it in micro-fabricated obstacle arrays. The trajectories observed in vivo and in vitro closely resemble each other suggesting that structural constraints can be sufficient to guide Plasmodium sporozoites in complex environments. Sporozoite speed in different environments is optimized for migration and correlates with persistence length and dispersal. However, this correlation breaks down in mutant sporozoites that show adhesion impairment due to the lack of TRAP-like protein (TLP) on their surfaces. This may explain their delay in infecting the host. The flexibility of sporozoite adaption to different environments and a favorable speed for optimal dispersal ensures efficient host switching during malaria transmission

    Ultrafast evolution and transient phases of a prototype out-of-equilibrium Mott-Hubbard material

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    The study of photoexcited strongly correlated materials is attracting growing interest since their rich phase diagram often translates into an equally rich out-of-equilibrium behaviour. With femtosecond optical pulses, electronic and lattice degrees of freedom can be transiently decoupled, giving the opportunity of stabilizing new states inaccessible by quasi-adiabatic pathways. Here we show that the prototype Mott-Hubbard material V2O3 presents a transient non-thermal phase developing immediately after ultrafast photoexcitation and lasting few picoseconds. For both the insulating and the metallic phase, the formation of the transient configuration is triggered by the excitation of electrons into the bonding a1g orbital, and is then stabilized by a lattice distortion characterized by a hardening of the A1g coherent phonon, in stark contrast with the softening observed upon heating. Our results show the importance of selective electron-lattice interplay for the ultrafast control of material parameters, and are relevant for the optical manipulation of strongly correlated systems. \ua9 The Author(s) 2017

    Relationship between amino acid composition and gene expression in the mouse genome

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    <p>Abstract</p> <p>Background</p> <p>Codon bias is a phenomenon that refers to the differences in the frequencies of synonymous codons among different genes. In many organisms, natural selection is considered to be a cause of codon bias because codon usage in highly expressed genes is biased toward optimal codons. Methods have previously been developed to predict the expression level of genes from their nucleotide sequences, which is based on the observation that synonymous codon usage shows an overall bias toward a few codons called major codons. However, the relationship between codon bias and gene expression level, as proposed by the translation-selection model, is less evident in mammals.</p> <p>Findings</p> <p>We investigated the correlations between the expression levels of 1,182 mouse genes and amino acid composition, as well as between gene expression and codon preference. We found that a weak but significant correlation exists between gene expression levels and amino acid composition in mouse. In total, less than 10% of variation of expression levels is explained by amino acid components. We found the effect of codon preference on gene expression was weaker than the effect of amino acid composition, because no significant correlations were observed with respect to codon preference.</p> <p>Conclusion</p> <p>These results suggest that it is difficult to predict expression level from amino acid components or from codon bias in mouse.</p

    Transcriptome analysis and comparison reveal divergence between two invasive whitefly cryptic species

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    <p>Abstract</p> <p>Background</p> <p>Invasive species are valuable model systems for examining the evolutionary processes and molecular mechanisms associated with their specific characteristics by comparison with closely related species. Over the past 20 years, two species of the whitefly <it>Bemisia tabaci </it>species complex, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED), have both spread from their origin Middle East/Mediterranean to many countries despite their apparent differences in many life history parameters. Previously, we have sequenced the transcriptome of MED. In this study, we sequenced the transcriptome of MEAM1 and took a comparative genomic approach to investigate the transcriptome evolution and the genetic factors underlying the differences between MEAM1 and MED.</p> <p>Results</p> <p>Using Illumina sequencing technology, we generated 17 million sequencing reads for MEAM1. These reads were assembled into 57,741 unique sequences and 15,922 sequences were annotated with an E-value above 10<sup>-5</sup>. Compared with the MED transcriptome, we identified 3,585 pairs of high quality orthologous genes and inferred their sequence divergences. The average differences in coding, 5' untranslated and 3' untranslated region were 0.83%, 1.66% and 1.43%, respectively. The level of sequence divergence provides additional support to the proposition that MEAM1 and MED are two species. Based on the ratio of nonsynonymous and synonymous substitutions, we identified 24 sequences that have evolved in response to positive selection. Many of those genes are predicted to be involved in metabolism and insecticide resistance which might contribute to the divergence of the two whitefly species.</p> <p>Conclusions</p> <p>Our data present a comprehensive sequence comparison between the two invasive whitefly species. This study will provide a road map for future investigations on the molecular mechanisms underlying their biological differences.</p
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