5,357 research outputs found

    High refractive index of melanin in shiny occipital feathers of a bird of paradise

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    Male Lawes's Parotia, a bird of paradise, use the highly directional reflection of the structurally colored, brilliant-silvery occipital feathers in their courtship display. As in other birds, the structural coloration is produced by ordered melanin pigmentation. The barbules of the Parotia's occipital feathers, with thickness ~3 µm, contain 6–7 layers of densely packed melanin rodlets (diameter ~0.25 µm, length ~2 µm). The effectively ~0.2 µm thick melanin layers separated by ~0.2 µm thick keratin layers create a multilayer interference reflector. Reflectance measurements yielded peak wavelengths in the near-infrared at ~1.3 µm, i.e., far outside the visible wavelength range. With the Jamin-Lebedeff interference microscopy method recently developed for pigmented media, we here determined the refractive index of the intact barbules. We thus derived the wavelength dependence of the refractive index of the barbules' melanin to be 1.7–1.8 in the visible wavelength range. Implementing the anatomical and refractive index data in an optical multilayer model, we calculated the barbules' reflectance, transmittance and absorptance spectra, thereby confirming measured spectra

    Microtubule dynamics in cell division : exploring living cells with polarized light microscopy

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    Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Annual Reviews for personal use, not for redistribution. The definitive version was published in Annual Review of Cell and Developmental Biology 24 (2008): 1-28, doi:10.1146/annurev.cellbio.24.110707.175323.This Perspective is an account of my early experience while I studied the dynamic organization and behavior of the mitotic spindle and its submicroscopic filaments using polarized light microscopy. The birefringence of spindle filaments in normally dividing plant and animal cells, and those treated by various agents, revealed: A) the reality of spindle fibers and fibrils in healthy living cells; B) the labile, dynamic nature of the molecular filaments making up the spindle fibers; C) the mode of fibrogenesis and action of orienting centers; and D) force-generating properties based on the disassembly and assembly of the fibrils. These studies, which were carried out directly on living cells using improved polarizing microscopes, in fact, predicted the reversible assembly properties of isolated microtubules

    Synthesis and characterization of hybrid organic-inorganic materials based on sulphonated polyamideimide and silica

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    The preparation of hybrid organic–inorganic membrane materials based on a sulphonated polyamideimide resin and silica filler has been studied. The method allows the sol–gel process to proceed in the presence of a high molecular weight polyamideimide, resulting in well dispersed silica nanoparticles (<50 nm) within the polymer matrix with chemical bonding between the organic and inorganic phases. Tetraethoxysilane (TEOS) was used as the silica precursor and the organosilicate networks were bonded to the polymer matrix via a coupling agent aminopropyltriethoxysilane (APTrEOS). The structure and properties of these hybrid materials were characterized via a range of techniques including FTIR, TGA, DSC, SEM and contact angle analysis. It was found that the compatibility between organic and inorganic phases has been greatly enhanced by the incorporation of APTrEOS. The thermal stability and hydrophilic properties of hybrid materials have also been significantly improved

    <i>Trypanosoma brucei rhodesiense</i> transmitted by a single tsetse fly bite in vervet monkeys as a model of human African trypanosomiasis

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    Sleeping sickness is caused by a species of trypanosome blood parasite that is transmitted by tsetse flies. To understand better how infection with this parasite leads to disease, we provide here the most detailed description yet of the course of infection and disease onset in vervet monkeys. One infected tsetse fly was allowed to feed on each host individual, and in all cases infections were successful. The characteristics of infection and disease were similar in all hosts, but the rate of progression varied considerably. Parasites were first detected in the blood 4-10 days after infection, showing that migration of parasites from the site of fly bite was very rapid. Anaemia was a key feature of disease, with a reduction in the numbers and average size of red blood cells and associated decline in numbers of platelets and white blood cells. One to six weeks after infection, parasites were observed in the cerebrospinal fluid (CSF), indicating that they had moved from the blood into the brain; this was associated with a white cell infiltration. This study shows that fly-transmitted infection in vervets accurately mimics human disease and provides a robust model to understand better how sleeping sickness develops

    Metallopanstimulin as a marker for head and neck cancer

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    BACKGROUND: Metallopanstimulin (MPS-1) is a ribosomal protein that is found in elevated amounts in the sera of patients with head and neck squamous cell carcinoma (HNSCC). We used a test, denoted MPS-H, which detects MPS-1 and MPS-1-like proteins, to determine the relationship between MPS-H serum levels and clinical status of patients with, or at risk for, HNSCC. PATIENTS AND METHODS: A total of 125 patients were prospectively enrolled from a university head and neck oncology clinic. Participants included only newly diagnosed HNSCC patients. Two control groups, including 25 non-smokers and 64 smokers, were studied for comparison. A total of 821 serum samples collected over a twenty-four month period were analyzed by the MPS-H radioimmunoassay. RESULTS: HNSCC, non-smokers, and smokers had average MPS-H values of 41.5 ng/mL, 10.2 ng/mL, and 12.8 ng/mL, respectively (p = 0.0001). CONCLUSION: We conclude that MPS-1 and MPS-1-like proteins are elevated in patients with HNSCC, and that MPS-H appears to be a promising marker of presence of disease and response to treatment in HNSCC patients

    A novel approach to simulate gene-environment interactions in complex diseases

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    Background: Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results: We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions: By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study

    Temporal perception deficits in schizophrenia: integration is the problem, not deployment of attentions

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    Patients with schizophrenia are known to have impairments in sensory processing. In order to understand the specific temporal perception deficits of schizophrenia, we investigated and determined to what extent impairments in temporal integration can be dissociated from attention deployment using Attentional Blink (AB). Our findings showed that there was no evident deficit in the deployment of attention in patients with schizophrenia. However, patients showed an increased temporal integration deficit within a hundred-millisecond timescale. The degree of such integration dysfunction was correlated with the clinical manifestations of schizophrenia. There was no difference between individuals with/without schizotypal personality disorder in temporal integration. Differently from previous studies using the AB, we did not find a significant impairment in deployment of attention in schizophrenia. Instead, we used both theoretical and empirical approaches to show that previous findings (using the suppression ratio to correct for the baseline difference) produced a systematic exaggeration of the attention deficits. Instead, we modulated the perceptual difficulty of the task to bring the baseline levels of target detection between the groups into closer alignment. We found that the integration dysfunction rather than deployment of attention is clinically relevant, and thus should be an additional focus of research in schizophrenia

    Comparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of high-scoring genes

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    <p>Abstract</p> <p>Background</p> <p>A major goal of the analysis of high-dimensional RNA expression data from tumor tissue is to identify prognostic signatures for discriminating patient subgroups. For this purpose genome-wide identification of bimodally expressed genes from gene array data is relevant because distinguishability of high and low expression groups is easier compared to genes with unimodal expression distributions.</p> <p>Recently, several methods for the identification of genes with bimodal distributions have been introduced. A straightforward approach is to cluster the expression values and score the distance between the two distributions. Other scores directly measure properties of the distribution. The kurtosis, e.g., measures divergence from a normal distribution. An alternative is the outlier-sum statistic that identifies genes with extremely high or low expression values in a subset of the samples.</p> <p>Results</p> <p>We compare and discuss scores for bimodality for expression data. For the genome-wide identification of bimodal genes we apply all scores to expression data from 194 patients with node-negative breast cancer. Further, we present the first comprehensive genome-wide evaluation of the prognostic relevance of bimodal genes. We first rank genes according to bimodality scores and define two patient subgroups based on expression values. Then we assess the prognostic significance of the top ranking bimodal genes by comparing the survival functions of the two patient subgroups. We also evaluate the global association between the bimodal shape of expression distributions and survival times with an enrichment type analysis.</p> <p>Various cluster-based methods lead to a significant overrepresentation of prognostic genes. A striking result is obtained with the outlier-sum statistic (<it>p </it>< 10<sup>-12</sup>). Many genes with heavy tails generate subgroups of patients with different prognosis.</p> <p>Conclusions</p> <p>Genes with high bimodality scores are promising candidates for defining prognostic patient subgroups from expression data. We discuss advantages and disadvantages of the different scores for prognostic purposes. The outlier-sum statistic may be particularly valuable for the identification of genes to be included in prognostic signatures. Among the genes identified as bimodal in the breast cancer data set several have not yet previously been recognized to be prognostic and bimodally expressed in breast cancer.</p
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