Intractable policy failure: the case of bovine TB and badgers

The failure to eliminate bovine TB from the English and Welsh cattle herd represents a long-term intractable policy failure. Cattle-to-cattle transmission of the disease has been underemphasised in the debate compared with transmission from badgers despite a contested evidence base. Archival evidence shows that mythical constructions of the badger have shaped the policy debate. Relevant evidence was incomplete and contested; alternative framings of the policy problem were polarised and difficult to reconcile; and this rendered normal techniques of stakeholder management through co-option and mediation of little assistance

Time in a Bottle: The Evolutionary Fate of Species Discrimination in Sibling Drosophila Species

Disadvantageous hybridization favors the evolution of prezygotic isolating behaviors, generating a geographic pattern of interspecific mate discrimination where members of different species drawn from sympatric populations exhibit stronger preference for members of their own species than do individuals drawn from allopatric populations. Geographic shifts in species' boundaries can relax local selection against hybridization; under such scenarios the fate of enhanced species preference is unknown. Lineages established from populations in the region of sympatry that have been maintained as single-species laboratory cultures represent cases where allopatry has been produced experimentally. Using such cultures dating from the 1950s, we assess how Drosophila pseudoobscura and D. persimilis mate preferences respond to relaxed natural selection against hybridization. We found that the propensity to hybridize generally declines with increasing time in experimental allopatry, suggesting that maintaining enhanced preference for conspecifics may be costly. However, our data also suggest a strong role for drift in determining mating preferences once secondary allopatry has been established. Finally, we discuss the interplay between populations in establishing the presence or absence of patterns consistent with reinforcement

The effect of drinking milk containing conjugated linoleic acid on fecal microbiological profile, enzymatic activity, and fecal characteristics in humans

<p>Abstract</p> <p>Background</p> <p>The primary objective was to determine whether consumption of conjugated linoleic acids (CLAs) affected the fecal microbiota composition, fecal enzyme activity or fecal composition.</p> <p>Methods</p> <p>Human subjects consumed (1 <it>L</it>/day) cows' milk (4% fat) containing (5 mg/g fat) <it>cis</it>-9, <it>trans</it>-11 CLA (CONT), (32 mg/g fat) cis-9, <it>trans</it>-11 CLA (NAT) and (32 mg/g fat) <it>trans</it>-10, <it>cis</it>-12 CLA and <it>cis</it>-9, <it>trans</it>-11 CLA (SYN) for 8 weeks, in addition to their normal diet. Milk feeding periods were separated by 4 week washout periods. Fecal samples were obtained at the beginning (day 0) and the end (day 56) of each milk feeding period. Fecal samples were analysed for microbiological profile, enzyme activity, pH and short chain fatty acid content.</p> <p>Results</p> <p>Samples taken at day 0 and day 56 indicated that the numbers of <it>lactobacilli </it>and <it>bifidobacteria </it>significantly decreased after consumption of all experimental milks; total aerobes, total anaerobes, enterobacteria, and enterococci + streptococci did not change. At day 56, the activities of β-glucosidase, nitroreductase, and urease enzymes had decreased compared to samples taken on day 0 for all treatments. β-glucuronidase activity did not change. Fecal pH and ammonia content did not change.</p> <p>Conclusion</p> <p>It was concluded that observed changes could have been attributed to increased milk intake; no differences could be attributed to consumption of the different CLAs.</p

A personalized real-time virtual model of whole heart electrophysiology

Computer models capable of representing the intrinsic personal electrophysiology (EP) of the heart in silico are termed virtual heart technologies. When anatomy and EP are tailored to individual patients within the model, such technologies are promising clinical and industrial tools. Regardless of their vast potential, few virtual technologies simulating the entire organ-scale EP of all four-chambers of the heart have been reported and widespread clinical use is limited due to high computational costs and difficulty in validation. We thus report on the development of a novel virtual technology representing the electrophysiology of all four-chambers of the heart aiming to overcome these limitations. In our previous work, a model of ventricular EP embedded in a torso was constructed from clinical magnetic resonance image (MRI) data and personalized according to the measured 12 lead electrocardiogram (ECG) of a single subject under normal sinus rhythm. This model is then expanded upon to include whole heart EP and a detailed representation of the His-Purkinje system (HPS). To test the capacities of the personalized virtual heart technology to replicate standard clinical morphological ECG features under such conditions, bundle branch blocks within both the right and the left ventricles under two different conduction velocity settings are modeled alongside sinus rhythm. To ensure clinical viability, model generation was completely automated and simulations were performed using an efficient real-time cardiac EP simulator. Close correspondence between the measured and simulated 12 lead ECG was observed under normal sinus conditions and all simulated bundle branch blocks manifested relevant clinical morphological features

Complex oxide nanostructures by pulsed laser deposition through nanostencils

We achieved parallel nanoscale patterning of ferroelectric complex oxides by pulsed laser deposition through a nanostencil (i.e., through a pattern of apertures in a thin free-standing membrane). Ordered arrays of nanostructured barium titanate (BaTiO3) were obtained onto different substrates in a single deposition step, at room temperature, replicating accurately the aperture patterns in the stencil membrane. After a postdeposition annealing treatment, x-ray diffraction pattern showed a nanocrystalline BaTiO3 structure close to the perovskite cubic phase with grains 30-35 nm in size. Their local ferroelectric properties were detected using piezoresponse force microscopy

Metal-Organic Framework-Enhanced ELISA Platform for Ultrasensitive Detection of PD-L1

© 2020 American Chemical Society. The programmed cell death ligand 1 (PD-L1) protein has emerged as a predictive cancer biomarker and sensitivity to immune checkpoint blockade-based cancer immunotherapies. Current technologies for the detection of protein-based biomarkers, including the enzyme-linked immunosorbent assay (ELISA), have limitations such as low sensitivity and limit of detection (LOD) in addition to degradation of antibodies in exposure to environmental changes such as temperature and pH. To address these issues, we have proposed a metal-organic framework (MOF)-based ELISA for the detection of the PD-L1. A protective coating based on Zeolitic Imidazolate Framework 8 (ZIF-8) MOF thin film and polydopamine-polyethylenimine (PDA-PEI) was introduced on an ELISA plate for the improvement of antibody immobilization. Sensitivity and LOD of the resulting platform were compared with a conventional ELISA kit, and the bioactivity of the antibody in the proposed immunoassay was investigated in response to various pH and temperature values. The LOD and sensitivity of the MOF-based PD-L1 ELISA were 225 and 15.12 times higher, respectively, compared with those of the commercial ELISA kit. The antibody@ZIF-8/PDA-PEI was stable up to 55 °C and the pH range 5-10. The proposed platform can provide sensitive detection for target proteins, in addition to being resistant to elevated temperature and pH. The proposed MOF-based ELISA has significant potential for the clinical and diagnostic studies

Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient

Background: Investigation of the functioning of the brain in living systems has been a major effort amongst scientists and medical practitioners. Amongst the various disorder of the brain, epilepsy has drawn the most attention because this disorder can affect the quality of life of a person. In this paper we have reinvestigated the EEGs for normal and epileptic patients using surrogate analysis, probability distribution function and Hurst exponent. Results: Using random shuffled surrogate analysis, we have obtained some of the nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys Rev E 2001, 64:061907], for the epileptic patients during seizure. Probability distribution function shows that the activity of an epileptic brain is nongaussian in nature. Hurst exponent has been shown to be useful to characterize a normal and an epileptic brain and it shows that the epileptic brain is long term anticorrelated whereas, the normal brain is more or less stochastic. Among all the techniques, used here, Hurst exponent is found very useful for characterization different cases. Conclusions: In this article, differences in characteristics for normal subjects with eyes open and closed, epileptic subjects during seizure and seizure free intervals have been shown mainly using Hurst exponent. The H shows that the brain activity of a normal man is uncorrelated in nature whereas, epileptic brain activity shows long range anticorrelation.Comment: Keywords:EEG, epilepsy, Correlation dimension, Surrogate analysis, Hurst exponent. 9 page

Security of data science and data science for security

In this chapter, we present a brief overview of important topics regarding the connection of data science and security. In the first part, we focus on the security of data science and discuss a selection of security aspects that data scientists should consider to make their services and products more secure. In the second part about security for data science, we switch sides and present some applications where data science plays a critical role in pushing the state-of-the-art in securing information systems. This includes a detailed look at the potential and challenges of applying machine learning to the problem of detecting obfuscated JavaScripts