A two-stage SVM method to predict membrane protein types by incorporating amino acid classifications and physicochemical properties into a general form of Chou's PseAAC

Membrane proteins play important roles in many biochemical processes and are also attractive targets of drug discovery for various diseases. The elucidation of membrane protein types provides clues for understanding the structure and function of proteins. Recently we developed a novel system for predicting protein subnuclear localizations. In this paper, we propose a simplified version of our system for predicting membrane protein types directly from primary protein structures, which incorporates amino acid classifications and physicochemical properties into a general form of pseudo-amino acid composition. In this simplified system, we will design a two-stage multi-class support vector machine combined with a two-step optimal feature selection process, which proves very effective in our experiments. The performance of the present method is evaluated on two benchmark datasets consisting of five types of membrane proteins. The overall accuracies of prediction for five types are 93.25% and 96.61% via the jackknife test and independent dataset test, respectively. These results indicate that our method is effective and valuable for predicting membrane protein types. A web server for the proposed method is available at http://www.juemengt.com/jcc/memty_page.php

Combined NIR/MIR analysis: A novel method for the classification of complex substances such as Illicium verum Hook. F. and its adulterants

A novel combined near- and mid-infrared (NIR and MIR) spectroscopic method has been researched and developed for the analysis of complex substances such as the Traditional Chinese Medicine (TCM), Illicium verum Hook. F. (IVHF), and its noxious adulterant, Iuicium lanceolatum A.C. Smith (ILACS). Three types of spectral matrix were submitted for classification with the use of the linear discriminant analysis (LDA) method. The data were pretreated with either the successive projections algorithm (SPA) or the discrete wavelet transform (DWT) method. The SPA method performed somewhat better, principally because it required less spectral features for its pretreatment model. Thus, NIR or MIR matrix as well as the combined NIR/MIR one, were pretreated by the SPA method, and then analysed by LDA. This approach enabled the prediction and classification of the IVHF, ILACS and mixed samples. The MIR spectral data produced somewhat better classification rates than the NIR data. However, the best results were obtained from the combined NIR/MIR data matrix with 95–100% correct classifications for calibration, validation and prediction. Principal component analysis (PCA) of the three types of spectral data supported the results obtained with the LDA classification method.

Determination of tricyclazole in water using solid phase extraction and liquid chromatography

A method for determination of tricyclazole in water using solid phase extraction and high performance liquid chromatography (HPLC) with UV detection at 230nm and a mobile phase of acetonitrile:water (20:80, v/v) was developed. A performance comparison between two types of solid phase sorbents, the C18 sorbent of Supelclean ENVI-18 cartridge and the styrene-divinyl benzene copolymer sorbent of Sep-Pak PS2-Plus cartridge was conducted. The Sep-Pak PS2-Plus cartridges were found more suitable for extracting tricyclazole from water samples than the Supelclean ENVI-18 cartridges. For this cartridge, both methanol and ethyl acetate produced good results. The method was validated with good linearity and with a limit of detection of 0.008gL-1 for a 500-fold concentration through the SPE procedure. The recoveries of the method were stable at 80% and the precision was from 1.1-6.0% within the range of fortified concentrations. The validated method was also applied to measure the concentrations of tricyclazole in real paddy water.

Multimodal polymer nanoparticles with combined 19F magnetic resonance and optical detection for tunable, targeted, multimodal imagingin vivo

Understanding the complex nature of diseased tissue in vivo requires development of more advanced nanomedicines, where synthesis of multifunctional polymers combines imaging multimodality with a biocompatible, tunable, and functional nanomaterial carrier. Here we describe the development of polymeric nanoparticles for multimodal imaging of disease states in vivo. The nanoparticle design utilizes the abundant functionality and tunable physicochemical properties of synthetically robust polymeric systems to facilitate targeted imaging of tumors in mice. For the first time, high-resolution 19F/1H magnetic resonance imaging is combined with sensitive and versatile fluorescence imaging in a polymeric material for in vivo detection of tumors. We highlight how control over the chemistry during synthesis allows manipulation of nanoparticle size and function and can lead to very high targeting efficiency to B16 melanoma cells, both in vitro and in vivo. Importantly, the combination of imaging modalities within a polymeric nanoparticle provides information on the tumor mass across various size scales in vivo, from millimeters down to tens of micrometers.

Combined analysis of three whole genome linkage scans for Ankylosing Spondylitis

Objective. Ankylosing spondylitis (AS) is a debilitating chronic inflammatory condition with a high degree of familiality (λs=82) and heritability (>90%) that primarily affects spinal and sacroiliac joints. Whole genome scans for linkage to AS phenotypes have been conducted, although results have been inconsistent between studies and all have had modest sample sizes. One potential solution to these issues is to combine data from multiple studies in a retrospective meta-analysis. Methods: The International Genetics of Ankylosing Spondylitis Consortium combined data from three whole genome linkage scans for AS (n=3744 subjects) to determine chromosomal markers that show evidence of linkage with disease. Linkage markers typed in different centres were integrated into a consensus map to facilitate effective data pooling. We performed a weighted meta-analysis to combine the linkage results, and compared them with the three individual scans and a combined pooled scan. Results: In addition to the expected region surrounding the HLA-B27 gene on chromosome 6, we determined that several marker regions showed significant evidence of linkage with disease status. Regions on chromosome 10q and 16q achieved 'suggestive' evidence of linkage, and regions on chromosomes 1q, 3q, 5q, 6q, 9q, 17q and 19q showed at least nominal linkage in two or more scans and in the weighted meta-analysis. Regions previously associated with AS on chromosome 2q (the IL-1 gene cluster) and 22q (CYP2D6) exhibited nominal linkage in the meta-analysis, providing further statistical support for their involvement in susceptibility to AS. Conclusion: These findings provide a useful guide for future studies aiming to identify the genes involved in this highly heritable condition. . Published by on behalf of the British Society for Rheumatology.

Acoustic feature extraction using perceptual wavelet packet decomposition for frog call classification

Frog protection has become increasingly essential due to the rapid decline of its biodiversity. Therefore, it is valuable to develop new methods for studying this biodiversity. In this paper, a novel feature extraction method is proposed based on perceptual wavelet packet decomposition for classifying frog calls in noisy environments. Pre-processing and syllable segmentation are first applied to the frog call. Then, a spectral peak track is extracted from each syllable if possible. Track duration, dominant frequency and oscillation rate are directly extracted from the track. With k-means clustering algorithm, the calculated dominant frequency of all frog species is clustered into k parts, which produce a frequency scale for wavelet packet decomposition. Based on the adaptive frequency scale, wavelet packet decomposition is applied to the frog calls. Using the wavelet packet decomposition coefficients, a new feature set named perceptual wavelet packet decomposition sub-band cepstral coefficients is extracted. Finally, a k-nearest neighbour (k-NN) classifier is used for the classification. The experiment results show that the proposed features can achieve an average classification accuracy of 97.45% which outperforms syllable features (86.87%) and Mel-frequency cepstral coefficients (MFCCs) feature (90.80%).

Evaluation of ion exchange as a pre-treatment option for coal seam gas water

The Coal Seam Gas (CSG) industry in Australia has grown significantly in recent years. During the gas extraction process, water is also recovered which is brackish in character. In order to facilitate beneficial reuse of the water, the CSG industry has primarily invested in Reverse Osmosis (RO) as the primary method for associated water desalination. However, the presence of alkaline earth ions in the water combined with the inherent alkalinity of the water may result in RO membrane scaling. Consequently, weak acid cation (WAC) synthetic ion exchange resins were investigated as a potential solution to this potential problem. It was shown that resins were indeed highly efficient at treating single and multi-component solutions of alkaline earth ions. The interaction of the ions with the resin was found to be considerably more complex that previously reported.

Combined PET-FDG and USPIO-enhanced MR imaging in patients with symptomatic moderate carotid artery stenosis

Introduction: PET-FDG and USPIO-enhanced MRI are increasingly being used in depicting carotid atheroma inflammation - a risk factor for the high risk plaque. Their combined use has not been previously reported. Report: Two patients presenting with stroke and identified with 50% carotid stenosis on duplex ultrasonography, underwent PET FDG and USPIO-enhanced MR imaging. Results were concordant and complementary suggesting that both techniques reflect similar metabolic processes. Discussion: The selection of patients for carotid revascularisation has largely been based on the severity of luminal stenosis alone. The two imaging modalities, which identify inflammatory activity, may be potential surrogate risk markers in the selection of patients eligible for carotid surgery, if plaque inflammation can be correlated with risk of developing clinical symptoms.

Analysis of word embeddings and sequence features for clinical information extraction

This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence that the corpora used to generate such features have. We also demonstrate the promise of sequence-based unsupervised features for further improving concept extraction.

Evaluate traffic noise level based on traffic microsimulation combined with a refined classic noise prediction method

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sized trucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Plasma-enhanced synthesis of bioactive polymeric coatings from monoterpene alcohols: A combined experimental and theoretical study

This paper describes the synthesis and characterization of a novel organic polymer coating for the prevention of the growth of Pseudomonas aeruginosa on the solid surface of three-dimensional objects. Substrata were encapsulated with polyterpenol thin films prepared from terpinen-4-ol using radio frequency plasma enhanced chemical vapor deposition. Terpinen-4-ol is a constituent of tea tree oil with known antibacterial properties. The influence of deposition power on the chemical structure, surface composition, and ultimately the antibacterial inhibitory activity of the resulting polyterpenol thin films was studied using X-ray photoelectron spectroscopy (XPS), water contact angle measurement, atomic force microscopy (AFM), and 3-D interactive visualization and statistical approximation of the topographic profiles. The experimental results were consistent with those predicted by molecular simulations. The extent of bacterial attachment and extracellular polymeric substances (EPS) production was analyzed using scanning electron microscopy (SEM) and confocal scanning laser microscopy (CSLM). Polyterpenol films deposited at lower power were particularly effective against P. aeruginosa due to the preservation of original terpinen-4-ol molecules in the film structure. The proposed antimicrobial and antifouling coating can be potentially integrated into medical and other clinically relevant devices to prevent bacterial growth and to minimize bacteria-associated adverse host responses.

Low-frequency electrical stimulation combined with a cooling vest improves recovery of elite kayakers following a simulated 1000-m race in a hot environment

This study compared the effects of a low-frequency electrical stimulation (LFES; Veinoplus® Sport, Ad Rem Technology, Paris, France), a low-frequency electrical stimulation combined with a cooling vest (LFESCR) and an active recovery combined with a cooling vest (ACTCR) as recovery strategies on performance (racing time and pacing strategies), physiologic and perceptual responses between two sprint kayak simulated races, in a hot environment (∼32 wet-bulb-globe temperature). Eight elite male kayakers performed two successive 1000-m kayak time trials (TT1 and TT2), separated by a short-term recovery period, including a 30-min of the respective recovery intervention protocol, in a randomized crossover design. Racing time, power output, and stroke rate were recorded for each time trial. Blood lactate concentration, pH, core, skin and body temperatures were measured before and after both TT1 and TT2 and at mid- and post-recovery intervention. Perceptual ratings of thermal sensation were also collected. LFESCR was associated with a very likely effect in performance restoration compared with ACTCR (99/0/1%) and LFES conditions (98/0/2%). LFESCR induced a significant decrease in body temperature and thermal sensation at post-recovery intervention, which is not observed in ACTCR condition. In conclusion, the combination of LFES and wearing a cooling vest (LFESCR) improves performance restoration between two 1000-m kayak time trials achieved by elite athletes, in the heat.

Assessing the combined effect of asbestos exposure and smoking on lung cancer: a Bayesian approach

We review the literature on the combined association between lung cancer and two environmental exposures, asbestos exposure and smoking, and explore a Bayesian approach to assess evidence of interaction between the exposures. The meta-analysis combines separate indices of additive and multiplicative relationships and multivariate relative risk estimates. By making inferences on posterior probabilities we can explore both the form and strength of interaction. This analysis may be more informative than providing evidence to support one relation over another on the basis of statistical significance. Overall, we find evidence for a more than additive and less than multiplicative relation.

The effectiveness of the teach-back method on adherence and self-management in health education for people with chronic disease: A systematic review

- BACKGROUND Chronic diseases are increasing worldwide and have become a significant burden to those affected by those diseases. Disease-specific education programs have demonstrated improved outcomes, although people do forget information quickly or memorize it incorrectly. The teach-back method was introduced in an attempt to reinforce education to patients. To date, the evidence regarding the effectiveness of health education employing the teach-back method in improved care has not yet been reviewed systematically. - OBJECTIVES This systematic review examined the evidence on using the teach-back method in health education programs for improving adherence and self-management of people with chronic disease. - INCLUSION CRITERIA Types of participants: Adults aged 18 years and over with one or more than one chronic disease. Types of intervention: All types of interventions which included the teach-back method in an education program for people with chronic diseases. The comparator was chronic disease education programs that did not involve the teach-back method. Types of studies: Randomized and non-randomized controlled trials, cohort studies, before-after studies and case-control studies. Types of outcomes: The outcomes of interest were adherence, self-management, disease-specific knowledge, readmission, knowledge retention, self-efficacy and quality of life. - SEARCH STRATEGY Searches were conducted in CINAHL, MEDLINE, EMBASE, Cochrane CENTRAL, Web of Science, ProQuest Nursing and Allied Health Source, and Google Scholar databases. Search terms were combined by AND or OR in search strings. Reference lists of included articles were also searched for further potential references. - METHODOLOGICAL QUALITY Two reviewers conducted quality appraisal of papers using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument. - DATA EXTRACTION Data were extracted using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument data extraction instruments. - DATA SYNTHESIS There was significant heterogeneity in selected studies, hence a meta-analysis was not possible and the results were presented in narrative form. - RESULTS Of the 21 articles retrieved in full, 12 on the use of the teach-back method met the inclusion criteria and were selected for analysis. Four studies confirmed improved disease-specific knowledge in intervention participants. One study showed a statistically significant improvement in adherence to medication and diet among type 2 diabetics patients in the intervention group compared to the control group (p < 0.001). Two studies found statistically significant improvements in self-efficacy (p = 0.0026 and p < 0.001) in the intervention groups. One study examined quality of life in heart failure patients but the results did not improve from the intervention (p = 0.59). Five studies found a reduction in readmission rates and hospitalization but these were not always statistically significant. Two studies showed improvement in daily weighing among heart failure participants, and in adherence to diet, exercise and foot care among those with type 2 diabetes. - CONCLUSION Overall, the teach-back method showed positive effects in a wide range of health care outcomes although these were not always statistically significant. Studies in this systematic review revealed improved outcomes in disease-specific knowledge, adherence, self-efficacy and the inhaler technique. There was a positive but inconsistent trend also seen in improved self-care and reduction of hospital readmission rates. There was limited evidence on improvement in quality of life or disease related knowledge retention.