A systematic investigation of production of synthetic prions from recombinant prion protein

According to the protein-only hypothesis, infectious mammalian prions, which exist as distinct strains with discrete biological properties, consist of multichain assemblies of misfolded cellular prion protein (PrP). A critical test would be to produce prion strains synthetically from defined components. Crucially, high-titre 'synthetic' prions could then be used to determine the structural basis of infectivity and strain diversity at the atomic level. While there have been multiple reports of production of prions from bacterially expressed recombinant PrP using various methods, systematic production of high-titre material in a form suitable for structural analysis remains a key goal. Here, we report a novel high-throughput strategy for exploring a matrix of conditions, additives and potential cofactors that might generate high-titre prions from recombinant mouse PrP, with screening for infectivity using a sensitive automated cell-based bioassay. Overall, approximately 20 000 unique conditions were examined. While some resulted in apparently infected cell cultures, this was transient and not reproducible. We also adapted published methods that reported production of synthetic prions from recombinant hamster PrP, but again did not find evidence of significant infectious titre when using recombinant mouse PrP as substrate. Collectively, our findings are consistent with the formation of prion infectivity from recombinant mouse PrP being a rare stochastic event and we conclude that systematic generation of prions from recombinant PrP may only become possible once the detailed structure of authentic ex vivo prions is solved

A note on the Kutta condition in Glauert's solution of the thin aerofoil problem

Glauert's classical solution of the thin aerofoil problem (a coordinate transformation, and splitting the solution into a sum of a singular part and an assumed regular part written as a Fourier sine series) is usually presented in textbooks on aerodynamics without a great deal of attention being paid to the rôle of the Kutta condition. Sometimes the solution is merely stated, apparently satisfying the Kutta condition automatically. Quite often, however, it is misleadingly suggested that it is by the choice of a sine series that the Kutta condition is satisfied. It is shown here that if Glauert's approach is interpreted in the context of generalised functions, (1) the whole solution, i.e. both the singular part and any non-Kutta condition solution, can be written as a sine-series, and (2) it is really the coordinate transformation which compels the Kutta condition to be satisfied, as it enhances the edge singularities from integrable to non-integrable, and so sifts out solutions not normally representable by a Fourier series. Furthermore, the present method provides a very direct way to construct other, more singular solutions. A practical consequence is that (at least, in principle) in numerical solutions based on Glauert's method, more is needed for the Kutta condition than a sine series expansion

Enhanced Eyelashes: Prescription and Over-the-Counter Options

Women have long strived to possess long, thick, and dark eyelashes. Prominent eyes and eyelashes are often considered a sign of beauty and can be associated with increased levels of attractiveness, confidence, and well-being. Numerous options may improve the appearance of eyelashes. Mascara aims to temporarily darken, lengthen, and thicken eyelashes using a combination of waxes, pigments, and resins. Artificial eyelashes can be adhered either to the dermal margin or to individual eyelashes. Individuals may even use eyelash transplantations to improve the appearance of their eyelashes. The unique properties of eyelashes (e.g., relatively long telogen and short anagen phases compared with scalp hairs, slow rate of growth, and a lack of influence by androgens) may allow for specific aesthetic interventions to improve the appearance of natural eyelashes. Some over-the-counter (OTC) products may contain prostaglandin analogs that can affect eyelash growth, but neither the safety nor efficacy of these OTC cosmetics has been fully studied. Originally indicated for the reduction of intraocular pressure, the synthetic prostaglandin analog bimatoprost was recently approved for the treatment of hypotrichosis of the eyelashes. In a double-blinded, randomized, vehicle-controlled trial, bimatoprost safely and effectively grew natural eyelashes, making them longer, thicker, and darker. Bimatoprost was generally safe and well tolerated and appears to provide an additional option for individuals looking to improve the appearance of their eyelashes

The Dispersal Ecology of Rhodesian Sleeping Sickness Following Its Introduction to a New Area

Tsetse-transmitted human and animal trypanosomiasis are constraints to both human and animal health in sub-Saharan Africa, and although these diseases have been known for over a century, there is little recent evidence demonstrating how the parasites circulate in natural hosts and ecosystems. The spread of Rhodesian sleeping sickness (caused by Trypanosoma brucei rhodesiense) within Uganda over the past 15 years has been linked to the movement of infected, untreated livestock (the predominant reservoir) from endemic areas. However, despite an understanding of the environmental dependencies of sleeping sickness, little research has focused on the environmental factors controlling transmission establishment or the spatially heterogeneous dispersal of disease following a new introduction. In the current study, an annually stratified case-control study of Rhodesian sleeping sickness cases from Serere District, Uganda was used to allow the temporal assessment of correlations between the spatial distribution of sleeping sickness and landscape factors. Significant relationships were detected between Rhodesian sleeping sickness and selected factors, including elevation and the proportion of land which was “seasonally flooding grassland” or “woodlands and dense savannah.” Temporal trends in these relationships were detected, illustrating the dispersal of Rhodesian sleeping sickness into more ‘suitable’ areas over time, with diminishing dependence on the point of introduction in concurrence with an increasing dependence on environmental and landscape factors. These results provide a novel insight into the ecology of Rhodesian sleeping sickness dispersal and may contribute towards the implementation of evidence-based control measures to prevent its further spread

Mining metabolites: extracting the yeast metabolome from the literature

Text mining methods have added considerably to our capacity to extract biological knowledge from the literature. Recently the field of systems biology has begun to model and simulate metabolic networks, requiring knowledge of the set of molecules involved. While genomics and proteomics technologies are able to supply the macromolecular parts list, the metabolites are less easily assembled. Most metabolites are known and reported through the scientific literature, rather than through large-scale experimental surveys. Thus it is important to recover them from the literature. Here we present a novel tool to automatically identify metabolite names in the literature, and associate structures where possible, to define the reported yeast metabolome. With ten-fold cross validation on a manually annotated corpus, our recognition tool generates an f-score of 78.49 (precision of 83.02) and demonstrates greater suitability in identifying metabolite names than other existing recognition tools for general chemical molecules. The metabolite recognition tool has been applied to the literature covering an important model organism, the yeast Saccharomyces cerevisiae, to define its reported metabolome. By coupling to ChemSpider, a major chemical database, we have identified structures for much of the reported metabolome and, where structure identification fails, been able to suggest extensions to ChemSpider. Our manually annotated gold-standard data on 296 abstracts are available as supplementary materials. Metabolite names and, where appropriate, structures are also available as supplementary materials

Retrospective head motion estimation in structural brain MRI with 3D CNNs

Head motion is one of the most important nuisance variables in neuroimaging, particularly in studies of clinical or special populations, such as children. However, the possibility of estimating motion in structural MRI is limited to a few specialized sites using advanced MRI acquisition techniques. Here we propose a supervised learning method to retrospectively estimate motion from plain MRI. Using sparsely labeled training data, we trained a 3D convolutional neural network to assess if voxels are corrupted by motion or not. The output of the network is a motion probability map, which we integrate across a region of interest (ROI) to obtain a scalar motion score. Using cross-validation on a dataset of n=48 healthy children scanned at our center, and the cerebral cortex as ROI, we show that the proposed measure of motion explains away 37% of the variation in cortical thickness. We also show that the motion score is highly correlated with the results from human quality control of the scans. The proposed technique can not only be applied to current studies, but also opens up the possibility of reanalyzing large amounts of legacy datasets with motion into consideration: we applied the classifier trained on data from our center to the ABIDE dataset (autism), and managed to recover group differences that were confounded by motion

Multimodality Imaging of Abnormal Vascular Perfusion and Morphology in Preclinical 9L Gliosarcoma Model

This study demonstrates that a dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) perfusion parameter may indicate vascular abnormality in a brain tumor model and reflects an effect of dexamethasone treatment. In addition, X-ray computed tomography (CT) measurements of vascular tortuosity and tissue markers of vascular morphology were performed to investigate the underpinnings of tumor response to dexamethasone.One cohort of Fisher 344 rats (N = 13), inoculated intracerebrally with 9L gliosarcoma cells, was treated with dexamethasone (i.p. 3 mg/kg/day) for five consecutive days, and another cohort (N = 11) was treated with equal volume of saline. Longitudinal DSC-MRI studies were performed at the first (baseline), third and fifth day of treatments. Relative cerebral blood volume (rCBV) was significantly reduced on the third day of dexamethasone treatment (0.65 ± .13) as compared to the fifth day during treatment (1.26 ±.19, p < 0.05). In saline treated rats, relative CBV gradually increased during treatment (0.89 ±.13, 1.00 ± .21, 1.13 ± .23) with no significant difference on the third day of treatment (p>0.05). In separate serial studies, microfocal X-ray CT of ex vivo brain specimens (N = 9) and immunohistochemistry for endothelial cell marker anti-CD31 (N = 8) were performed. Vascular morphology of ex vivo rat brains from micro-CT analysis showed hypervascular characteristics in tumors, and both vessel density (41.32 ± 2.34 branches/mm(3), p<0.001) and vessel tortuosity (p<0.05) were significantly reduced in tumors of rats treated with dexamethasone compared to saline (74.29 ± 3.51 branches/mm(3)). The vascular architecture of rat brain tissue was examined with anti-CD31 antibody, and dexamethasone treated tumor regions showed reduced vessel area (16.45 ± 1.36 µm(2)) as compared to saline treated tumor regions (30.83 ± 4.31 µm(2), p<0.001) and non-tumor regions (22.80 ± 1.11 µm(2), p<0.01).Increased vascular density and tortuosity are culprit to abnormal perfusion, which is transiently reduced during dexamethasone treatment

Asteroseismology and Interferometry

Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36

Structure-based classification and ontology in chemistry

<p>Abstract</p> <p>Background</p> <p>Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving <it>relevant </it>results from the available information, and <it>organising </it>those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures), while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies.</p> <p>Results</p> <p>We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches.</p> <p>Conclusion</p> <p>Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational utilities including algorithmic, statistical and logic-based tools. For the task of automatic structure-based classification of chemical entities, essential to managing the vast swathes of chemical data being brought online, systems which are capable of hybrid reasoning combining several different approaches are crucial. We provide a thorough review of the available tools and methodologies, and identify areas of open research.</p