8,188 research outputs found
Synergistic Effect of Chlorogenic Acid and Caffeic Acid with Fosfomycin on Growth Inhibition of a Resistant Listeria monocytogenes Strain
Listeria monocytogenes, a human foodborne pathogen that causes listeriosis with high-rate mortality, has been reported to be resistant to commonly used antibiotics. New antibiotics or cocktails of existing antibiotics with synergistic compounds are in high demand for treating this multi-drug-resistant pathogen. Fosfomycin is one of the novel and promising therapeutic antibiotics for the treatment of listeriosis. However, some L. monocytogenes strains with the FosX gene were recently reported to survive from the fosfomycin treatment. This work aims to identify FosX inhibitors that can revive fosfomycin in treating resistant L. monocytogenes. Since structures and activities of the FosX protein in L. monocytogenes have been well studied, we used an integrated computational and experimental approach to identify FosX inhibitors that show synergistic effect with fosfomycin in treating resistant L. monocytogenes. Specifically, automated ligand docking was implemented to perform virtual screening of the Indofine natural-product database and FDA-approved drugs to identify potential inhibitors. An in vitro bacterial growth inhibition test was then utilized to verify the effectiveness of identified compounds combined with fosfomycin in inhibiting the resistant L. monocytogenes strains. Two phenolic acids, i.e., caffeic acid and chlorogenic acid, were predicted as high-affinity FosX inhibitors from the ligand-docking platform. Experiments with these compounds indicated that the cocktail of either caffeic acid (1.5 mg/mL) or chlorogenic acid (3 mg/mL) with fosfomycin (50 mg/L) was able to significantly inhibit the growth of the pathogen. The finding of this work implies that the combination of fosfomycin with either caffeic acid or chlorogenic acid is of potential to be used in the clinical treatment of Listeria infections
A paired neural network model for tourist arrival forecasting
Tourist arrival and tourist demand forecasting are a crucial issue in tourism economy and the community economic development as well. Tourist demand forecasting has attracted much attention from tourism academics as well as industries. In recent year, it attracts increasing attention in the computational literature as advances in machine learning method allow us to construct models that significantly improve the precision of tourism prediction. In this paper, we draw upon both strands of the literature and propose a novel paired neural network model. The tourist arrival data is decomposed by two low-pass filters into long-term trend and short-term seasonal components, which are then modelled by a pair of autoregressive neural network models as a parallel structure. The proposed model is evaluated by the tourist arrival data to United States from twelve source markets. The empirical studies show that our proposed paired neural network model outperforming the selected benchmark model across all error measures and over different horizons
Superconducting gap structure and pinning in disordered MgB2 films
We have performed a comparative study of two thin films of magnesium diboride
(MgB2) grown by different techniques. The critical current density at different
temperatures and magnetic fields was evaluated from magnetisation curves, the
structure of superconducting order parameter was obtained from point-contact
spectroscopy, and the scattering rates were evaluated by fitting the
temperature dependent normal-state resistivity to the two-band model. The films
have similar critical temperatures close to 39 K, but the upper critical fields
were different by a factor of 2 (5.2T and 2.5 T at 20 K). We have found that
the film with higher Hc2 also had stronger scattering in the sigma band and
smaller value of the superconducting gap in this band. As the scattering in
sigma band is primarily due to the defects in boron plane, our results are
consistent with the assumption that disordering the boron planes leads to
enhanced Hc2 and better pinning properties in magnetic field.Comment: Paper presented at EUCAS'0
Assessment tools measuring health-related empowerment in psychosocially vulnerable populations: a systematic review.
BackgroundMany programs are undertaken to facilitate the empowerment of vulnerable populations across the world. However, an overview of appropriate empowerment measurements to evaluate such initiatives remains incomplete to date. This systematic review aims to describe and summarise psychometric properties, feasibility and clinical utility of the available tools for measuring empowerment in psychosocially vulnerable populations.MethodsA systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was completed. A descriptive approach was used for data analysis. Papers were eligible if they explored the development, validation, cross-cultural translation or the utility of an empowerment measurement tool in the context of psychosocially vulnerable populations.ResultsTwenty-six included articles described twenty-six separate studies in which 16 empowerment measurement tools were developed, validated/translated, or used. There was heterogeneity in empowerment constructs, samples targeted, and psychometric properties measured. The measurement of reliability of the included instruments was satisfactory in most cases. However, the validity, responsiveness, interpretability, feasibility and clinical utility of the identified measurement tools were often not adequately described or measured.ConclusionThis systematic review provides a useful snapshot of the strengths as well as limitations of existing health related empowerment measurement tools used with psychosocially vulnerable populations in terms of their measurement properties, and constructs captured. It highlights significant gaps in empowerment tool measurement, development and evaluation processes. In particular, the results suggest that in addition to systematic assessments of psychometric properties, the inclusion of feasibility and clinical utility as outcome measures are important to assess relevance to clinical practice
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