Chinese herbal medicine in the treatment of acute upper respiratory tract infection: a randomised, double blind, placebo-controlled clinical trial.

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Local variation of hashtag spike trains and popularity in Twitter

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamics, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media.Comment: 7 pages, 7 figure

A demonstration of 'broken' visual space

It has long been assumed that there is a distorted mapping between real and ‘perceived’ space, based on demonstrations of systematic errors in judgements of slant, curvature, direction and separation. Here, we have applied a direct test to the notion of a coherent visual space. In an immersive virtual environment, participants judged the relative distance of two squares displayed in separate intervals. On some trials, the virtual scene expanded by a factor of four between intervals although, in line with recent results, participants did not report any noticeable change in the scene. We found that there was no consistent depth ordering of objects that can explain the distance matches participants made in this environment (e.g. A > B > D yet also A < C < D) and hence no single one-to-one mapping between participants’ perceived space and any real 3D environment. Instead, factors that affect pairwise comparisons of distances dictate participants’ performance. These data contradict, more directly than previous experiments, the idea that the visual system builds and uses a coherent 3D internal representation of a scene

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Liver-Targeting of Interferon-Alpha with Tissue-Specific Domain Antibodies

PMCID: PMC3581439This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Financial time series prediction using spiking neural networks

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments. © 2014 Reid et al

The costs, resource use, and cost-effectiveness of Clinical Nurse Specialist (CNSs) led interventions for patients with palliative care needs: a systematic review of international evidence

Background: Patients with palliative care (PC) needs do not access specialist palliative care services according to their necessities. Clinical Nurse Specialists (CNS) working across a variety of fields are playing an increasingly important role in the care of such patients, but there is limited knowledge of the extent to which their interventions are cost-effective. Objectives: To present results from a systematic review of the international evidence on the costs, resource use and cost effectiveness of CNS led interventions for patients palliative care needs, defined as seriously ill patients and those with advanced disease or frailty who are unlikely to be cured, recover, or stabilize. Design: Systematic review following PRISMA methodology. Data sources: Medline, Embase, Cinahl and Cochrane library up to 2015. Studies focusing on the outcomes of CNS interventions for patients with PC needs, and including at least one economic outcome, were considered. The quality of studies was assessed using tools from the Joanna-Briggs-Institute. Results: A total of 79 papers were included: 37 RCTs, 22 quasi-experimental studies, 7 service evaluations and other studies, and 13 economic analyses. The studies included a wide variety of interventions including clinical, support and education, as well as care coordination activities. The quality of the studies varied greatly. Conclusions: CNSs interventions may be effective in reducing specific resource use such as hospitalizations /re-hospitalizations/admissions, length of stay, and health care costs. There is mixed evidence regarding their cost-effectiveness. Future studies should ensure that clinical nurse specialists’ roles and activities are clearly described and evaluated

Indigenous Populations of Three Closely Related Lysobacter spp. in Agricultural Soils Using Real-Time PCR

Previous research had shown that three closely related species of Lysobacter, i.e., Lysobacter antibioticus, Lysobacter capsici, and Lysobacter gummosus, were present in different Rhizoctonia-suppressive soils. However, the population dynamics of these three Lysobacter spp. in different habitats remains unknown. Therefore, a specific primer–probe combination was designed for the combined quantification of these three Lysobacter spp. using TaqMan. Strains of the three target species were efficiently detected with TaqMan, whereas related non-target strains of Lysobacter enzymogenes and Xanthomonas campestris were not or only weakly amplified. Indigenous Lysobacter populations were analyzed in soils of 10 organic farms in the Netherlands during three subsequent years with TaqMan. These soils differed in soil characteristics and crop rotation. Additionally, Lysobacter populations in rhizosphere and bulk soil of different crops on one of these farms were studied. In acid sandy soils low Lysobacter populations were present, whereas pH neutral clay soils contained high populations (respectively, <4.0–5.87 and 6.22–6.95 log gene copy numbers g−1 soil). Clay content, pH and C/N ratio, but not organic matter content in soil, correlated with higher Lysobacter populations. Unexpectedly, different crops did not significantly influence population size of the three Lysobacter spp. and their populations were barely higher in rhizosphere than in bulk soil

A Mouse Model of Heritable Cerebrovascular Disease

The study of animal models of heritable cerebrovascular diseases can improve our understanding of disease mechanisms, identify candidate genes for related human disorders, and provide experimental models for preclinical trials. Here we describe a spontaneous mouse mutation that results in reproducible, adult-onset, progressive, focal ischemia in the brain. The pathology is not the result of hemorrhage, embolism, or an anatomical abnormality in the cerebral vasculature. The mutation maps as a single site recessive locus to mouse Chromosome 9 at 105 Mb, a region of shared synteny with human chromosome 3q22. The genetic interval, defined by recombination mapping, contains seven protein-coding genes and one processed transcript, none of which are changed in their expression level, splicing, or sequence in affected mice. Targeted resequencing of the entire interval did not reveal any provocative changes; thus, the causative molecular lesion has not been identified

Inflammatory cytokines and biofilm production sustain Staphylococcus aureus outgrowth and persistence: A pivotal interplay in the pathogenesis of Atopic Dermatitis

Individuals with Atopic dermatitis (AD) are highly susceptible to Staphylococcus aureus colonization. However, the mechanisms driving this process as well as the impact of S. aureus in AD pathogenesis are still incompletely understood. In this study, we analysed the role of biofilm in sustaining S. aureus chronic persistence and its impact on AD severity. Further we explored whether key inflammatory cytokines overexpressed in AD might provide a selective advantage to S. aureus. Results show that the strength of biofilm production by S. aureus correlated with the severity of the skin lesion, being significantly higher (P < 0.01) in patients with a more severe form of the disease as compared to those individuals with mild AD. Additionally, interleukin (IL)-β and interferon γ (IFN-γ), but not interleukin (IL)-6, induced a concentration-dependent increase of S. aureus growth. This effect was not observed with coagulase-negative staphylococci isolated from the skin of AD patients. These findings indicate that inflammatory cytokines such as IL1-β and IFN-γ, can selectively promote S. aureus outgrowth, thus subverting the composition of the healthy skin microbiome. Moreover, biofilm production by S. aureus plays a relevant role in further supporting chronic colonization and disease severity, while providing an increased tolerance to antimicrobials