Independent Test Results Research Articles

DeepEfflux: a 2D convolutional neural network model for identifying families of efflux proteins in transporters

Efflux protein plays a key role in pumping xenobiotics out of the cells. The prediction of efflux family proteins involved in transport process of compounds is crucial for understanding family structures, functions and energy dependencies. Many methods have been proposed to classify efflux pump transporters without considerations of any pump specific of efflux protein families. In other words, efflux proteins protect cells from extrusion of foreign chemicals. Moreover, almost all efflux protein families have the same structure based on the analysis of significant motifs. The motif sequences consisting of the same amount of residues will have high degrees of residue similarity and thus will affect the classification process. Consequently, it is challenging but vital to recognize the structures and determine energy dependencies of efflux protein families. In order to efficiently identify efflux protein families with considering about pump specific, we developed a 2 D convolutional neural network (2 D CNN) model called DeepEfflux. DeepEfflux tried to capture the motifs of sequences around hidden target residues to use as hidden features of families. In addition, the 2 D CNN model uses a position-specific scoring matrix (PSSM) as an input. Three different datasets, each for one family of efflux protein, was fed into DeepEfflux, and then a 5-fold cross validation approach was used to evaluate the training performance. The model evaluation results show that DeepEfflux outperforms traditional machine learning algorithms. Furthermore, the accuracy of 96.02%, 94.89% and 90.34% for classes A, B and C, respectively, in the independent test results show that our model can perform well and can be used as a reliable tool for identifying families of efflux proteins in transporters. The online version of deepefflux is available at http://deepefflux.irit.fr. The source code of deepefflux is available both on the deepefflux website and at http://140.138.155.216/deepefflux/. Supplementary data are available at Bioinformatics online.

Space-based vegetation health for wheat yield modeling and prediction in Australia

An early warning of crop losses in response to weather fluctuations helps farmers, governments, traders, and policy makers better monitor global food supply and demand and identifies nations in need of aid. This paper discusses the utility of vegetation health (VH) indices, derived from the advance very high-resolution radiometer (AVHRR) and visible infrared imaging radiometer suite (VIIRS), as a proxy for modeling Australian wheat from the National Oceanic and Atmospheric Administration (NOAA) operational afternoon polar-orbiting satellites. These models are used to assess wheat production and to provide an early warning of drought-related losses. The NOAA AVHRR- and VIIRS-based VH indices were used to model wheat yield in Australia. A strong correlation (≥0.7) between wheat yield and VH indices was found during the critical reproductive stage of development (enhanced crops sensitivity to weather), which starts 2 to 3 weeks before and ends 2 to 3 weeks after wheat heading. The results of modeling and independent testing proved that the VH indices (especially those estimating thermal and health conditions) are a good proxy providing 1 to 2 months before harvest yield prediction (with 3% to 6% error). With the new generation of NOAA-20 operational polar-orbiting satellites, launched in November 2017, the VH method will be improved considerably both in an advanced crop/pasture prediction, spatial resolution, and accuracy.

Annotating activation/inhibition relationships to protein-protein interactions using gene ontology relations

BackgroundSignaling pathways can be reconstructed by identifying ‘effect types’ (i.e. activation/inhibition) of protein-protein interactions (PPIs). Effect types are composed of ‘directions’ (i.e. upstream/downstream) and ‘signs’ (i.e. positive/negative), thereby requiring directions as well as signs of PPIs to predict signaling events from PPI networks. Here, we propose a computational method for systemically annotating effect types to PPIs using relations between functional information of proteins.ResultsWe used regulates, positively regulates, and negatively regulates relations in Gene Ontology (GO) to predict directions and signs of PPIs. These relations indicate both directions and signs between GO terms so that we can project directions and signs between relevant GO terms to PPIs. Independent test results showed that our method is effective for predicting both directions and signs of PPIs. Moreover, our method outperformed a previous GO-based method that did not consider the relations between GO terms. We annotated effect types to human PPIs and validated several highly confident effect types against literature. The annotated human PPIs are available in Additional file 2 to aid signaling pathway reconstruction and network biology research.ConclusionsWe annotated effect types to PPIs by using regulates, positively regulates, and negatively regulates relations in GO. We demonstrated that those relations are effective for predicting not only signs, but also directions of PPIs. The usefulness of those relations suggests their potential applications to other types of interactions such as protein-DNA interactions.

The effect of sleep hygiene and brain gym on increasing elderly comfort and sleep quality

Introduction: Quality of life is one of the important things to consider, with the increasing number of elderly people, the number of problems and the number of elderly people living in nursing homes also increased. The greatest need for the elderly is the level of health, so that one can live a prosperous life by applying a healthy sleep pattern and carrying out physical exercise. The purpose of this study was to determine the effect of sleep hygiene and brain gym on increasing comfort in the elderly. Method: This type of research is a pretest posttest with control group design quasy experiment. The sampling method used was purposive sampling as many as 50 people and had fulfilled the inclusion and exclusion criteria. Sleep hygiene intervention was applied every day for 30 days, and the brain gym was held as many as 16x meetings for 4 weeks. The statistical test used is the independent t-test to test the hypothesis. Result: The independent t-test hypothesis test results are 0,000. This study showed significant results on the treatment group, which means that there is an effect of sleep hygiene and brain gym on increasing comfort and sleep quality in the elderly. Conclusion: Intervention of sleep hygiene and brain gym can improve comfort and sleep quality in the elderly. © 2018, Indian Journal of Public Health Research and Development. All rights reserved.

PTM-ssMP: A Web Server for Predicting Different Types of Post-translational Modification Sites Using Novel Site-specific Modification Profile.

Protein post-translational modifications (PTMs) are chemical modifications of a protein after its translation. Owing to its play an important role in deep understanding of various biological processes and the development of effective drugs, PTM site prediction have become a hot topic in bioinformatics. Recently, many online tools are developed to prediction various types of PTM sites, most of which are based on local sequence and some biological information. However, few of existing tools consider the relations between different PTMs for their prediction task. Here, we develop a web server called PTM-ssMP to predict PTM site, which adopts site-specific modification profile (ssMP) to efficiently extract and encode the information of both proximal PTMs and local sequence simultaneously. In PTM-ssMP we provide efficient prediction of multiple types of PTM site including phosphorylation, lysine acetylation, ubiquitination, sumoylation, methylation, O-GalNAc, O-GlcNAc, sulfation and proteolytic cleavage. To assess the performance of PTM-ssMP, a large number of experimentally verified PTM sites are collected from several sources and used to train and test the prediction models. Our results suggest that ssMP consistently contributes to remarkable improvement of prediction performance. In addition, results of independent tests demonstrate that PTM-ssMP compares favorably with other existing tools for different PTM types. PTM-ssMP is implemented as an online web server with user-friendly interface, which is freely available at http://bioinformatics.ustc.edu.cn/PTM-ssMP/index/.

NIAT BERWIRAUSAHA MAHASISWA DAN KETERHUBUNGANNYA DENGAN KECERDASAN-HADAPI-RINTANGAN

<p>Entrepreneurial Intention can be influenced by demographic factors (gender, age, work experience) and external factors, such as family background. One characteristic of an entrepreneur looked when he faces obstacles in managing the business, he is likely to survive and find a way out and not stop halfway. Individual ability to transform obstacles into opportunities is known as the Adversity Quotient (AQ/ adversity intelligence). Connectedness between adversity intelligence with the intention of entrepreneurship, as well as differences in the intentions of entrepreneurship by differences in gender, work experience and family background (family business and non-family business) are described in this study. Sampling technique used is purposive sampling of 126 students of the Ciputra University. Results showed the Sig. coefficient of Spearman’s rank correlationis 0.000 and the correlation coefficient is0.502; which means that there are significant linkages between adversity intelligence with the entrepreneurial intention. Independent sample test results show that the intention of entrepreneurship do not differ between male student with the girls. However, the intention of entrepreneurship students who have not experienced lower job than work experience. In addition, students who have a background in family business have higher entrepreneurial intention than students of non-family business.<br />Keywords: entrepreneurial intention, adversity intelligence, family business</p>

Computing Prediction and Functional Analysis of Prokaryotic Propionylation.

Identification and systematic analysis of candidates for protein propionylation are crucial steps for understanding its molecular mechanisms and biological functions. Although several proteome-scale methods have been performed to delineate potential propionylated proteins, the majority of lysine-propionylated substrates and their role in pathological physiology still remain largely unknown. By gathering various databases and literatures, experimental prokaryotic propionylation data were collated to be trained in a support vector machine with various features via a three-step feature selection method. A novel online tool for seeking potential lysine-propionylated sites (PropSeek) ( http://bioinfo.ncu.edu.cn/PropSeek.aspx ) was built. Independent test results of leave-one-out and n-fold cross-validation were similar to each other, showing that PropSeek is a stable and robust predictor with satisfying performance. Meanwhile, analyses of Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathways, and protein-protein interactions implied a potential role of prokaryotic propionylation in protein synthesis and metabolism.

Risk of false decision on conformity of a multicomponent material when test results of the components’ content are correlated

The probability of a false decision on conformity of a multicomponent material due to measurement uncertainty is discussed when test results are correlated. Specification limits of the components’ content of such a material generate a multivariate specification interval/domain. When true values of components’ content and corresponding test results are modelled by multivariate distributions (e.g. by multivariate normal distributions), a total global risk of a false decision on the material conformity can be evaluated based on calculation of integrals of their joint probability density function. No transformation of the raw data is required for that. A total specific risk can be evaluated as the joint posterior cumulative function of true values of a specific batch or lot lying outside the multivariate specification domain, when the vector of test results, obtained for the lot, is inside this domain. It was shown, using a case study of four components under control in a drug, that the correlation influence on the risk value is not easily predictable. To assess this influence, the evaluated total risk values were compared with those calculated for independent test results and also with those assuming much stronger correlation than that observed. While the observed statistically significant correlation did not lead to a visible difference in the total risk values in comparison to the independent test results, the stronger correlation among the variables caused either the total risk decreasing or its increasing, depending on the actual values of the test results.

Regulasi Tekanan Darah pada Penderita Hipertensi Primer dengan Smoothie Pisang (Musa Paradisiaca)

Introduction: Hypertension is a major problem that often happen in Indonesia. Hypertension can cause many complications. In Indonesia almost patients with hypertension got farmacologic therapy, but there is no difference. Banana smoothie is one of nonfarmacologic therapy that can be used to lower blood pressure. The purpose of this study was to analyze the effect of banana smoothie on regulation in patients with primary hypertension.Method: This study used quasy experimental design. The population in this study were patients with primary hypertension in Kedungturi village Taman Sidoarjo. The sampling technique used nonprobability sampling type of purposive sampling. The total number of sample were 16 respondents who were selected based on inclusion and exclusion criteria.Result:The Result of paired t-test at the systolic blood pressure and diastolic blood pressure in experiment group showed p value = 0.000. Independent t test between experiment group post-test and control group post-test showed p value = 0.000 for systolic blood pressure and p value = 0.002 for diastolic blood pressure. This result showed that there was a difference value of pretest and post-test systolic and diastolic blood pressure. With the result of independen t-test we know that there is a difference value between exsperiment and control blood pressure.Discussion: This study explain that there was significant effect of banana smoothie to regulate blood pressure in patients with primary hypertention. Banana smoothie can regulate the blood pressure because of high kalium substance. The function of kalium is to reduce the effect of natrium so the blood pressure can down. It can be conclude that banana smoothie can regulate the blood pressure in patients with primary hypertention. In further day patients with hypertension can choose banana smoothie to regulate their blood pressure.

Evaluating Educational Groups’ Function of High Schools in Tehran on the Basis of Krek Patrick

Nowadays, checking human sciences situation in valuation educational system in Iran is very important. They who educated in Iran’s educational system, then tested higher education one of the most sophisticated countries, find well that one of the most important distinctions between two systems is difference of situation and human science value. The aim of this research is evaluating educational groups’ function of human sciences area in high schools in Tehran due to Krek Patrick Model in 4 levels (reaction, behavior, learning an results). Statistical population of all teachers of educational groups of schools in Tehran by number… and sample volume according to Cochran formula is 359 that selected by clustered sampling among teachers who are members of educational groups of human sciences area. To collect data from questionnaire, researcher uses four above levels. Formal and content validity are accepted by 15 authorities and reliability that is calculated by using Cronbach Alpha in 4 levels (reaction, behavior, learning and results) is 0.823, 0.795, 0.861, and 0.742 respectively. Study method is descriptive and survey and adding to descriptive indexes, to analyze data, one group t, independent t, analyzing multivariable variance and regression are used. Results of one group t test showed that educational groups’ function of human sciences area is suitable due to Krek Patrick Model in four studied levels. Also results of independent test t and analyzing multivariable variance showed that there is a meaningful difference in educational groups’ function according to Krek Patrick Model and also in various levels among women and men. Finally, results of regression showed that history of work predicts educational groups’ function according to Krek Patrick model.

Implementation of Evidence-Based Nursing Guidelines and Sleep Quality in Patients With Acute Coronary Syndrome

Background: Sleep disorder is a common problem in patients hospitalized in cardiac care unit (CCU) and it may lead to irreversible consequences. Evaluating sleep quality is an important indicator in care quality. A new method to improve quality of nurses’ clinical practice is implementation of evidence-based nursing guidelines. Objectives: This study aimed to evaluate the effect of implementation of evidence-based nursing guidelines on quality of sleep in patients with acute coronary syndrome (ACS) admitted to the coronary care unit. Patients and Methods: This before and after clinical trial was performed in Hazrat Fatima (sa) hospital in Kerman city, Iran, during 2012 - 2013. Interventions included training evidence-based nursing guidelines to nurses working in CCU and the implementation of these guidelines. Sampling was done through the convenience nonprobability method and 45 patients were placed in the before group and 45 in the after group. Patients’ quality of sleep was evaluated using the Pittsburgh sleep quality standardized questionnaire before and after the interventions and data were analyzed using SPSS software version 19, mean descriptive statistics, standard deviation statistics, inferential statistics, an independent t-test and chi-square test Results: The total mean score of adequate sleep was 6.71 (3.54) in the intervention group and 5.26 (2.58) in the control group. The difference was statistically significant (P = 0.03). Conclusions: Implementation of evidence-based nursing guidelines improved the quality of sleep; therefore, it is recommended to administrators and managers of hospitals and health education centers to consider educating evidence-based nursing guidelines in their agenda.

Real-Time TaqMan PCR Assay for the Detection of Heat-Labile and Heat-Stable Enterotoxin Genes in a Geographically Diverse Collection of Enterotoxigenic Escherichia coli Strains and Stool Specimens.

Enterotoxigenic Escherichia coli (ETEC) are an important cause of diarrhea in children under the age of 5 years in developing countries and are the leading bacterial agent of traveler's diarrhea in persons traveling to these countries. ETEC strains secrete heat-labile (LT) and/or heat-stable (ST) enterotoxins that induce diarrhea by causing water and electrolyte imbalance. We describe the validation of a real-time TaqMan PCR (RT-PCR) assay to detect LT, ST1a, and ST1b enterotoxin genes in E. coli strains and in stool specimens. We validated LT/ST1b duplex and ST1a single-plex RT-PCR assay using a conventional PCR assay as a gold standard with 188 ETEC strains and 42 non-ETEC strains. We validated LT/ST1b duplex and ST1a single-plex RT-PCR assay in stool specimens (n = 106) using traditional culture as the gold standard. RT- PCR assay sensitivities for LT, ST1a, and ST1b detection in strains were 100%, 100%, and 98%; specificities were 95%, 98%, and 99%, and Pearson correlation coefficient r was 0.9954 between RT-PCR assay and the gold standard. In stool specimens, RT-PCR assay sensitivities for LT, ST1a, and ST1b detection were 97%, 100%, and 97%; and specificities were 99%, 94%, and 97%. Pearson correlation coefficient r was 0.9975 between RT-PCR results in stool specimens and the gold standard. Limits of detection of LT, ST1a, and ST1b by RT-PCR assay were 0.1 to1.0 pg/μL and by conventional PCR assay were 100 to1000 pg/μL. The accuracy, rapidity and sensitivity of this RT-PCR assay is promising for ETEC detection in public health/clinical laboratories and for laboratories in need of an independent method to confirm results of other culture independent diagnostic tests.

Accuracy of the One-Stage and Two-Stage Impression Techniques: A Comparative Analysis.

Introduction. One of the main steps of impression is the selection and preparation of an appropriate tray. Hence, the present study aimed to analyze and compare the accuracy of one- and two-stage impression techniques. Materials and Methods. A resin laboratory-made model, as the first molar, was prepared by standard method for full crowns with processed preparation finish line of 1 mm depth and convergence angle of 3-4°. Impression was made 20 times with one-stage technique and 20 times with two-stage technique using an appropriate tray. To measure the marginal gap, the distance between the restoration margin and preparation finish line of plaster dies was vertically determined in mid mesial, distal, buccal, and lingual (MDBL) regions by a stereomicroscope using a standard method. Results. The results of independent test showed that the mean value of the marginal gap obtained by one-stage impression technique was higher than that of two-stage impression technique. Further, there was no significant difference between one- and two-stage impression techniques in mid buccal region, but a significant difference was reported between the two impression techniques in MDL regions and in general. Conclusion. The findings of the present study indicated higher accuracy for two-stage impression technique than for the one-stage impression technique.

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites.

BackgroundProtein S-sulfenylation is a type of post-translational modification (PTM) involving the covalent binding of a hydroxyl group to the thiol of a cysteine amino acid. Recent evidence has shown the importance of S-sulfenylation in various biological processes, including transcriptional regulation, apoptosis and cytokine signaling. Determining the specific sites of S-sulfenylation is fundamental to understanding the structures and functions of S-sulfenylated proteins. However, the current lack of reliable tools often limits researchers to use expensive and time-consuming laboratory techniques for the identification of S-sulfenylation sites. Thus, we were motivated to develop a bioinformatics method for investigating S-sulfenylation sites based on amino acid compositions and physicochemical properties.ResultsIn this work, physicochemical properties were utilized not only to identify S-sulfenylation sites from 1,096 experimentally verified S-sulfenylated proteins, but also to compare the effectiveness of prediction with other characteristics such as amino acid composition (AAC), amino acid pair composition (AAPC), solvent-accessible surface area (ASA), amino acid substitution matrix (BLOSUM62), position-specific scoring matrix (PSSM), and positional weighted matrix (PWM). Various prediction models were built using support vector machine (SVM) and evaluated by five-fold cross-validation. The model constructed from hybrid features, including PSSM and physicochemical properties, yielded the best performance with sensitivity, specificity, accuracy and MCC measurements of 0.746, 0.737, 0.738 and 0.337, respectively. The selected model also provided a promising accuracy (0.693) on an independent testing dataset. Additionally, we employed TwoSampleLogo to help discover the difference of amino acid composition among S-sulfenylation, S-glutathionylation and S-nitrosylation sites.ConclusionThis work proposed a computational method to explore informative features and functions for protein S-sulfenylation. Evaluation by five-fold cross validation indicated that the selected features were effective in the identification of S-sulfenylation sites. Moreover, the independent testing results demonstrated that the proposed method could provide a feasible means for conducting preliminary analyses of protein S-sulfenylation. We also anticipate that the uncovered differences in amino acid composition may facilitate future studies of the extensive crosstalk among S-sulfenylation, S-glutathionylation and S-nitrosylation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2299-1) contains supplementary material, which is available to authorized users.

Block shear failure planes of bolted connections — Direct experimental verifications

This paper presents direct experimental verifications of the active shear planes in bolted connections, previously identified by the first author for determining the block shear capacity. The laboratory test results were obtained by independent researchers for specimens where the applied loads were resisted by the “block” in shear only. The first set consists of five bolted connection specimens in the webs of wide flange sections where the tensile resistance planes had been sawn off. The second set consists of ten bolted connection specimens each in one leg of an angle section that had fractured completely along the net tensile plane through a block shear failure. Comparisons among the gross, net, and active shear planes against the independent laboratory test results showed that the critical shear planes of bolted connections were best represented by the active shear planes rather than either the gross or the net shear planes. It is also pointed out that full or almost full shear strain hardening was generally achieved at the ultimate limit state of block shear failure of bolted connections in hot-rolled steel plates or sections, irrespective of the connection length. Verification against independent laboratory test results of tee sections bolted at the web reinforces this point.

Prediction of Protein-Protein Interaction Sites Based on Naive Bayes Classifier.

Protein functions through interactions with other proteins and biomolecules and these interactions occur on the so-called interface residues of the protein sequences. Identifying interface residues makes us better understand the biological mechanism of protein interaction. Meanwhile, information about the interface residues contributes to the understanding of metabolic, signal transduction networks and indicates directions in drug designing. In recent years, researchers have focused on developing new computational methods for predicting protein interface residues. Here we creatively used a 181-dimension protein sequence feature vector as input to the Naive Bayes Classifier- (NBC-) based method to predict interaction sites in protein-protein complexes interaction. The prediction of interaction sites in protein interactions is regarded as an amino acid residue binary classification problem by applying NBC with protein sequence features. Independent test results suggested that Naive Bayes Classifier-based method with the protein sequence features as input vectors performed well.

Ultimate Shear-Out Capacities of Structural-Steel Bolted Connections

Based on the previous research results of the authors, this paper presents an accurate and consistent equation for determining the ultimate shear-out capacity of a structural steel bolted connection. The equation is verified against independent laboratory test results obtained by other researchers around the world. Comparisons against alternative equations found in the design specifications and literature are also included. The paper explains why certain equations appear to be accurate for particular configurations, but are grossly inaccurate for others. This paper describes the various assumptions embedded in the existing equations, some optimistic and others pessimistic. It shows that the current code equations lead to very significant errors on either side of conservatism, while the proposed equation is consistently accurate for all test specimens known to fail in shear-out. A resistance factor of 0.85 is recommended for the proposed equation in order to achieve a reliability index of 4.0. The use of the proposed equation instead of the current AISC specification’s equation will facilitate structural designs that are more economical yet reliable.

Sand–pipeline–trench lateral interaction effects for shallow buried pipelines

A large-deformation numerical methodology is applied to simulate the interaction effects for a pipeline installed in a trench backfilled with loosely deposited dry sand, focusing on shallow buried pipelines subjected to lateral displacements relative to the surrounding soil. Based on the backfill–pipeline deformation mode under shallow embedment conditions, described in previous experimental studies, analyses are performed while considering only the critical state shear strength parameters of the backfill. The numerical methodology is validated against experimental full-scale test measurements from the literature, for pipelines buried in uniform dry loose and medium sand. Parametric analyses are performed to generate approximate formulas and charts for calculating (i) the maximum force on the pipeline and (ii) the minimum trench dimensions to eliminate interaction with the surrounding natural ground. Application of the proposed approach in the prediction of independent full-scale test results for a pipeline embedded in a shallow trench demonstrates its effectiveness, and underlines the effect of trench dimensioning on the response of the pipeline.

Determination of size-independent specific fracture energy of concrete mixes by two methods

The RILEM work-of-fracture method for measuring the specific fracture energy of concrete from notched three-point bend specimens is still the most common method used throughout the world, despite the fact that the specific fracture energy so measured is known to vary with the size and shape of the test specimen. The reasons for this variation have also been known for nearly two decades, and two methods have been proposed in the literature to correct the measured size-dependent specific fracture energy (Gf) in order to obtain a size-independent value (GF). It has also been proved recently, on the basis of a limited set of results on a single concrete mix with a compressive strength of 37 MPa, that when the size-dependent Gf measured by the RILEM method is corrected following either of these two methods, the resulting specific fracture energy GF is very nearly the same and independent of the size of the specimen. In this paper, we will provide further evidence in support of this important conclusion using extensive independent test results of three different concrete mixes ranging in compressive strength from 57 to 122 MPa.

Analytical approach for estimating ground deformation profile induced by normal faulting in undrained clay

Although theoretical models have been developed to predict the location of the failure surface in soil induced by bedrock faulting, no analytical tool is available to estimate subsurface ground deformation. In this paper, a newly developed semi-empirical approach is introduced and developed for calculating surface and subsurface deformations induced by normal faulting in undrained clay. Based on observations from centrifuge model tests, the ground deformation mechanisms are identified by three regions; namely, a stationary zone, a shearing zone, and a rigid body zone. By using an error function to represent vertical displacement continuously, the ground deformation profile can be described quantitatively. It is revealed that the ground deformation profile depends on vertical displacement of the bedrock hanging wall, soil thickness, dip angle of the bedrock fault plane, and a shape parameter that is a function of the undrained shear modulus normalized by the undrained shear strength. Validation and consistent agreement are obtained between calculated ground deformation profiles and other independent centrifuge test results and reported numerical data.