Power mapping-based stability analysis and order adjustment control for fractional-order multiple delayed systems.

This article investigates the asymptotic stability of a general class of fractional-order multiple delayed systems to evaluate the delay robustness. We establish a one-to-one spectral connection between the original fractional-order system and the transformed one under the power mapping. The applicability of the Cluster Treatment of Characteristic Roots paradigm to the transformed dynamics is proved by this connection. Then, we utilize the Dixon resultant-based frequency sweeping framework to create the complete stability map. The results demonstrate that the order adjustment control significantly enhances the control flexibility and brings unlimited possibilities for the improvement of the delay robustness. Finally, we inspect the stability preservation problem when using the integer-order approximations for practical implementation.

Experimental Investigation and Control of a Hot-Air Tunnel with Improved Performance and Energy Saving.

The paper is focused on the identification, control design, and experimental verification of a two-input two-output hot-air laboratory apparatus representing a small-scale version of appliances widely used in the industry. A decentralized multivariable controller design is proposed, satisfying control-loop decoupling and measurable disturbance rejection. The proposed inverted or equivalent noninverted decoupling controllers serve for the rejection of cross-interactions in controlled loops, whereas open-loop antidisturbance members satisfy the absolute invariance to the disturbances. Explicit controller-structure design formulae are derived, and their equivalence to other decoupling schemes is proven. Three tuning rules are used to set primary controller parameters, which are further discretized. All the control responses are simulated in the Matlab/Simulink environment. In the experimental part, two data-acquisition, communication, and control interfaces are set up. Namely, a programmable logic controller and a computer equipped with the peripheral component interconnect card commonly used in industrial practice are implemented. A simple supervisory control and data acquisition human-machine interface via the Control Web environment is developed. The laboratory experiments prove better temperature control performance measured by integral criteria by 35.3%, less energy consumption by up to 6%, and control effort of mechanical actuator parts by up to 17.1% for our method compared to the coupled or disturbance-ignoring design in practice. It was also observed that the use of a programmable logic controller gives better performance measures for both temperature and air-flow control.

Reporting patterns of adverse drug reactions over recent years in China: analysis from publications.

PURPOSE: The goal of this study was to clarify the reporting patterns of self-reported adverse drug reactions (ADRs) in China. METHODS: A variety of sources were searched, including the official website of China FDA, the national center for ADR monitoring center, publications from PubMed, and so on. We retrieved the relevant information and made descriptive and comparative analysis from the year 2009 to 2013. RESULTS: The ADR reporting numbers were 638,996, 692,904, 852,799, 1,200,000 and 1,317,000 from 2009 to 2013, respectively. Healthcare professionals contributed significantly, and their proportion always exceeded 80% before 2012. The average report per million inhabitants has increased from 479 to 983 from 2009 to 2013. However, the proportion of new or serious report was always below 25%. The reports mainly concern anti-infective agents and traditional Chinese medicine (TCM), especially TCM injection. The proportion of ADR reports in geriatric patients has increased for 4 consecutive years. CONCLUSIONS: ADR report numbers and reporting rates in China are on the rise. However, the proportion of new or serious reports as well as the proportion of reports contributed by consumers and pharmaceutical companies are still quite low. More attention should be paid to the elderly, anti-infective agents and TCM, especially TCM injections.

Classifying G-protein-coupled receptors to the finest subtype level.

G-protein-coupled receptors (GPCRs) constitute a remarkable protein family of receptors that are involved in a broad range of biological processes. A large number of clinically used drugs elicit their biological effect via a GPCR. Thus, developing a reliable computational method for predicting the functional roles of GPCRs would be very useful in the pharmaceutical industry. Nowadays, researchers are more interested in functional roles of GPCRs at the finest subtype level. However, with the accumulation of many new protein sequences, none of the existing methods can completely classify these GPCRs to their finest subtype level. In this paper, a pioneer work was performed trying to resolve this problem by using a hierarchical classification method. The first level determines whether a query protein is a GPCR or a non-GPCR. If it is considered as a GPCR, it will be finally classified to its finest subtype level. GPCRs are characterized by 170 sequence-derived features encapsulating both amino acid composition and physicochemical features of proteins, and support vector machines are used as the classification engine. To test the performance of the present method, a non-redundant dataset was built which are organized at seven levels and covers more functional classes of GPCRs than existing datasets. The number of protein sequences in each level is 5956, 2978, 8079, 8680, 6477, 1580 and 214, respectively. By 5-fold cross-validation test, the overall accuracy of 99.56%, 93.96%, 82.81%, 85.93%, 94.1%, 95.38% and 92.06% were observed at each level. When compared with some previous methods, the present method achieved a consistently higher overall accuracy. The results demonstrate the power and effectiveness of the proposed method to accomplish the classification of GPCRs to the finest subtype level.

Prediction of pattern recognition receptor family using pseudo-amino acid composition.

Pattern recognition receptors (PRRs) play a key role in the innate immune response by recognizing pathogen associated molecular patterns derived from a diverse collection of microbial pathogens. PRRs form a superfamily of proteins related to host health and disease. Thus, prediction of PRR family might supply biologically significant information for functional annotation of PRRs and development of novel drugs. In this paper, a computational method is proposed for predicting the families of PRRs. The prediction was performed on the basis of amino acid composition and pseudo-amino acid composition (PseAAC) from primary sequences of proteins using support vector machines. A non-redundant dataset consisted of 332 PRRs in seven families was constructed to do training and testing. It was demonstrated that different families of PRRs were quite closely correlated with amino acid composition as well as PseAAC. In the jackknife test, overall accuracies of amino acid composition-based and PseAAC-based classifiers reached 96.1% and 97.9%, respectively. The results indicate that families of PRRs are predictable with high accuracy. It is anticipated that this computational method might be a powerful tool for the automated assignment of families of PRRs.

Body mass index and health-related quality of life in adults: a population based study in five cities of China.

BACKGROUND: To investigate the relationship between obesity and health-related quality of life (HRQL) in a randomly selected Chinese sample. METHODS: A total of 3600 residents aged 18-80 years were sampled in five cities of China using a randomized stratified multiple-stage sampling method to receive the interview, with a self-completed questionnaire to collect demographic information, and the Mandarin version of Short Form 36 Health Survey questionnaire (SF-36) to assess HRQL, followed by height and weight measurements for calculating body mass index (BMI). Cross-sectional association between BMI and HRQL was analysed. RESULTS: Among the 3207 participants (mean age 42 years) suitable for analysis, BMI differed by age and gender. Based on the international or the Asian BMI categories, in women, meaningful impairments were seen between obese and normal weight participants in four physical health scales, and only one scale of the four mental health scales--vitality scale was affected by obesity; in men, impairments by obesity were not found in all of the eight SF-36 scales, and better HRQL in two mental health scales were observed in obese participants compared to normal weight ones; after adjusting related variables, several physical but not mental health scales were found impaired by obesity. CONCLUSION: Obesity impaired physical but not mental health, and the impairments varied between genders. Public health agencies and government should emphasize the impairments of obesity on physical health.

Misuse of statistical methods in 10 leading Chinese medical journals in 1998 and 2008.

Statistical methods are vital to biomedical research. Our aim was to find out whether progress has been made in the last decade in the use of statistical methods in Chinese medical research. We reviewed 10 leading Chinese medical journals published in 1998 and in 2008. Regarding statistical methods, using a multiple t-test for multiple group comparison was the most common error in the t-test in both years, which significantly decreased in 2008. In contingency tables, no significant level adjustment for multiple comparison significantly decreased in 2008. In ANOVA, over a quarter of articles misused the method of multiple pair-wise comparison in both years, and no significant difference was seen between the two years. In the rank transformation nonparametric test, the error of using multiple pair-wise comparison for multiple group comparison became less common. Many mistakes were found in the randomised controlled trial (56.3% in 1998; 67.9% in 2008), non- randomised clinical trial (57.3%; 58.6%), basic science study (72.9%; 65.5%), case study or case series study (48.4%; 47.2%), and cross-sectional study (57.1%; 44.2%). Progress has been made in the use of statistical methods in Chinese medical journals, but much is yet to be done.

Proton pump inhibitors therapy and risk of hip fracture: a systematic review and meta-analysis.

BACKGROUND AND AIMS: Previous studies have reported inconsistent findings that proton pump inhibitors (PPIs) therapy might increase the risk of hip fracture. We investigated the association between PPIs therapy and hip fracture by a systematic review and meta-analysis. METHODS: We systematically searched PubMed, EMBASE, and the Cochrane Library. We included studies assessing the effects of PPIs on hip fracture. Data from the studies about odds ratio and 95% confidence interval were gathered and summarized. RESULTS: Seven studies met the inclusion criteria. PPIs therapy was associated with a statistically significant increase of hip fracture risk (pooled odds ratio=1.24; 95% confidence interval: 1.15-1.34; P<0.00001) under a random model. Meanwhile, we found that the effect of PPIs on hip fracture differs in different duration groups. CONCLUSION: These results indicate that PPIs therapy might have the potential risk of hip fracture. Different effects on hip fracture in the subgroup analysis do not support a causal relationship between PPIs and hip fracture. Whether the risk exists warrants further investigation.

Steroids in the treatment of IgA nephropathy to the improvement of renal survival: a systematic review and meta-analysis.

BACKGROUND: Studies have shown that steroids can improve kidney survival and decrease the risk of proteinuria in patients with Immunoglobulin A nephropathy, but the overall benefit of steroids in the treatment of Immunoglobulin A nephropathy remains controversial. The aim of this study was to evaluate the benefits and risks of steroids for renal survival in adults with Immunoglobulin A nephropathy. METHODOLOGY AND PRINCIPAL FINDINGS: We searched the Cochrane Renal Group Specialized Register, Cochrane Controlled Trial Registry, MEDLINE and EMBASE databases. All eligible studies were measuring at least one of the following outcomes: end-stage renal failure, doubling of serum creatinine and urinary protein excretion. Fifteen relevant trials (n = 1542) that met our inclusion criteria were identified. In a pooled analysis, steroid therapy was associated with statistically significant reduction of the risk in end-stage renal failure (RR: 0.46, 95% CI: 0.27 to 0.79), doubling of serum creatinine (RR = 0.34, 95%CI = 0.15 to 0.77) and reduced urinary protein excretion (MD = -0.47 g/day, 95%CI = -0.64 to -0.31). CONCLUSIONS/SIGNIFICANCE: We identified that steroid therapy was associated with a decrease of proteinuria and with a statistically significant reduction of the risk in end-stage renal failure. Moreover, subgroup analysis also suggested that long-term steroid therapy had a higher efficiency than standard and short term therapy.

A retrospective survey of research design and statistical analyses in selected Chinese medical journals in 1998 and 2008.

BACKGROUND: High quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium. METHODOLOGY/PRINCIPAL FINDINGS: Ten (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, p<0.001), 59.8% (545/1,335) in 1998 compared to 52.2% (664/1,578) in 2008. The overall error/defect proportion of study design also decreased ( = 21.22, p<0.001), 50.9% (680/1,335) compared to 42.40% (669/1,578). In 2008, design with randomized clinical trials remained low in single digit (3.8%, 60/1,578) with two-third showed poor results reporting (defects in 44 papers, 73.3%). Nearly half of the published studies were retrospective in nature, 49.3% (658/1,335) in 1998 compared to 48.2% (761/1,578) in 2008. Decreases in defect proportions were observed in both results presentation ( = 93.26, p<0.001), 92.7% (945/1,019) compared to 78.2% (1023/1,309) and interpretation ( = 27.26, p<0.001), 9.7% (99/1,019) compared to 4.3% (56/1,309), some serious ones persisted. CONCLUSIONS/SIGNIFICANCE: Chinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative.

A computerized system for detecting signals due to drug-drug interactions in spontaneous reporting systems.

UNLABELLED: WHAT IS ALREADY KNOWN ABOUT THE SUBJECT: * Concomitant use of different drugs may yield excessive risk for adverse drug reactions and it is a challenging task to do surveillance on the safety profile of the interaction between different drugs. * Currently, several methods are used by pharmacoepidemiologists and statisticians to detect possible drug-drug interactions in spontaneous reporting systems. * However, with the increasing number of reports in the system, there is a growing need for a computerized system that could facilitate the process of data arrangement and detection of drug interaction. WHAT THIS STUDY ADDS: * We had already developed a computerized system to detect adverse drug reaction signals due to single drugs. * After the development of this system, interaction between different drugs could also be detected automatically and intelligently. AIMS: In spontaneous reporting systems (SRS), there is a growing need for the automated detection of adverse drug reactions (ADRs) resulting from drug-drug interactions. In addition, special attention is also needed for systems facilitating automated data preprocessing. In our study, we set up a computerized system to signal possible drug-drug interactions by which data acquisition and signal detection could be carried out automatically and the process of data preprocessing could also be facilitated. METHODS: This system was developed with Microsoft Visual Basic 6.0 and Microsoft Access was used as the database. Crude ADR reports submitted to Shanghai SRS from January 2007 to December 2008 were included in this study. The logistic regression method, the Omega shrinkage measure method, an additive model and a multiplicative model were used for automatic detection of drug-drug interactions where two drugs were used concomitantly. RESULTS: A total of 33 897 crude ADR reports were acquired from the SRS automatically. The 10 drug combinations most frequently reported were found and the 10 most suspicious drug-drug ADR combinations for each method were detected automatically after the performance of the system. CONCLUSIONS: Since the detection of drug-drug interaction depends upon the skills and memory of the professionals involved, is time consuming and the number of reports is increasing, this system might be a promising tool for the automated detection of possible drug-drug interactions in SRS.

Improving discrimination of outer membrane proteins by fusing different forms of pseudo amino acid composition.

Integral membrane proteins are central to many cellular processes and constitute approximately 50% of potential targets for novel drugs. However, the number of outer membrane proteins (OMPs) present in the public structure database is very limited due to the difficulties in determining structure with experimental methods. Therefore, discriminating OMPs from non-OMPs with computational methods is of medical importance as well as genome sequencing necessity. In this study, some sequence-derived structural and physicochemical features of proteins were incorporated with amino acid composition to discriminate OMPs from non-OMPs using support vector machines. The discrimination performance of the proposed method is evaluated on a benchmark dataset of 208 OMPs, 673 globular proteins, and 206 alpha-helical membrane proteins. A high overall accuracy of 97.8% was observed in the 5-fold cross-validation test. In addition, the current method distinguished OMPs from globular proteins and alpha-helical membrane proteins with overall accuracies of 98.2 and 96.4%, respectively. The prediction performance is superior to the state-of-the-art methods in the literature. It is anticipated that the current method might be a powerful tool for the discrimination of OMPs.

Improving the classification of nuclear receptors with feature selection.

Nuclear receptors are involved in multiple cellular signaling pathways that affect and regulate processes. Because of their physiology and pathophysiology significance, classification of nuclear receptors is essential for the proper understanding of their functions. Bhasin and Raghava have shown that the subfamilies of nuclear receptors are closely correlated with their amino acid composition and dipeptide composition [29]. They characterized each protein by a 400 dimensional feature vector. However, using high dimensional feature vectors for characterization of protein sequences will increase the computational cost as well as the risk of overfitting. Therefore, using only those features that are most relevant to the present task might improve the prediction system, and might also provide us with some biologically useful knowledge. In this paper a feature selection approach was proposed to identify relevant features and a prediction engine of support vector machines was developed to estimate the prediction accuracy of classification using the selected features. A reduced subset containing 30 features was accepted to characterize the protein sequences in view of its good discriminative power towards the classes, in which 18 are of amino acid composition and 12 are of dipeptide composition. This reduced feature subset resulted in an overall accuracy of 98.9% in a 5-fold cross-validation test, higher than 88.7% of amino acid composition based method and almost as high as 99.3% of dipeptide composition based method. Moreover, an overall accuracy of 93.7% was reached when it was evaluated on a blind data set of 63 nuclear receptors. On the other hand, an overall accuracy of 96.1% and 95.2% based on the reduced 12 dipeptide compositions was observed simultaneously in the 5-fold cross-validation test and the blind data set test, respectively. These results demonstrate the effectiveness of the present method.

Prediction of nuclear receptors with optimal pseudo amino acid composition.

Nuclear receptors are involved in multiple cellular signaling pathways that affect and regulate processes such as organ development and maintenance, ion transport, homeostasis, and apoptosis. In this article, an optimal pseudo amino acid composition based on physicochemical characters of amino acids is suggested to represent proteins for predicting the subfamilies of nuclear receptors. Six physicochemical characters of amino acids were adopted to generate the protein sequence features via web server PseAAC. The optimal values of the rank of correlation factor and the weighting factor about PseAAC were determined to get the appropriate descriptor of proteins that leads to the best performance. A nonredundant dataset of nuclear receptors in four subfamilies is constructed to evaluate the method using support vector machines. An overall accuracy of 99.6% was achieved in the fivefold cross-validation test as well as the jackknife test, and an overall accuracy of 98.4% was reached in a blind dataset test. The performance is very competitive with that of some previous methods.

Pharmacovigilance in Traditional Chinese Medicine safety surveillance.

PURPOSE: To give an overview of the current status including problems and efforts about pharmacovigilance in Traditional Chinese Medicine (TCM) safety surveillance. METHODS: It is based on literature review and publicly available data in China. RESULTS: TCM led to several adverse drug reactions (ADRs) during the past few years and pharmacovigilance about TCM remained as a problem though great effort had been made to improve it. CONCLUSIONS: Pharmacovigilance in TCM is still facing many challenges in playing critical roles in China. More attention should be paid to pharmacovigilance in TCM safety surveillance.

A computerized system for signal detection in spontaneous reporting system of Shanghai China.

PURPOSE: We developed a computerized system for signal detection in spontaneous reporting system (SRS) of Shanghai. Data acquisition, data mining could be carried out automatically and the process of data preprocessing and cleaning could be facilitated. This system was expected to detect signals from SRS after drug licensing with minimum patient exposure. METHODS: This system was developed by Microsoft visual basic (VB) 6.0. Data preprocessing, data cleaning, and data mining were based upon visual basic for application (VBA) in Microsoft Excel 2003. Database of drug generic name and adverse drug reaction (ADR) standard dictionary were set up initially for data cleaning and coding. Algorithms including reporting odds ratio (ROR), proportional reporting ratio (PRR), measure used by the Medicines and Healthcare Products Regulatory Agency (MHRA), Bayesian confidence propagation neural network (BCPNN) were employed in this system. Crude ADR reports submitted to Shanghai ADR SRS from December 2003 to April 2007 were used as a material in this study to test the feasibility and flexibility of this system. RESULTS: Thirty two thousand seven hundred and fourty six crude ADR reports were acquired from the SRS automatically. Two thousand one hundred and fourty seven drug generic name and 621 ADR name were kept in the database after data preprocessing and cleaning. A total of 1430, 1419, 868 and 997 possible drug-ADR signals were generated by ROR, PRR, BCPNN and MHRA, respectively. CONCLUSIONS: The results indicate that this computerized system is a flexible one that can help to detect possible drug-ADR signals intelligently in SRS of Shanghai now. It is a promising system for post-marketing surveillance on both chemical medicine and Chinese traditional medicine.

Classification of amine type G-protein coupled receptors with feature selection.

G-protein coupled receptors (GPCRs) are involved in various physiological processes. Therefore, classification of amine type GPCRs is important for proper understanding of their functions. Though some effective methods have been developed, it still remains unknown how many and which features are essential for this task. Empirical studies show that feature selection might address this problem and provide us with some biologically useful knowledge. In this paper, a feature selection technique is introduced to identify those relevant features of proteins which are potentially important for the prediction of amine type GPCRs. The selected features are finally accepted to characterize proteins in a more compact form. High prediction accuracy is observed on two data sets with different sequence similarity by 5-fold cross-validation test. The comparison with a previous method demonstrates the efficiency and effectiveness of the proposed method.

EZ-Entry: a clinical data management system.

In this paper, a new data management system named EZ-Entry is introduced. Five major functions are enclosed in this system: (1) user authentication; (2) database construction; (3) double data entry with instant alignment; (4) revision tracking; (5) query management. The practical application performed on two clinical trials indicates that EZ-Entry meets the requirements of clinical data management with high efficiency and security. This software is freely available on request from the authors for academic purposes.

Classification of G-protein coupled receptors at four levels.

G-protein coupled receptors (GPCRs) are transmembrane proteins which via G-proteins initiate some of the important signaling pathways in a cell and are involved in various physiological processes. Thus, computational prediction and classification of GPCRs can supply significant information for the development of novel drugs in pharmaceutical industry. In this paper, a nearest neighbor method has been introduced to discriminate GPCRs from non-GPCRs and subsequently classify GPCRs at four levels on the basis of amino acid composition and dipeptide composition of proteins. Its performance is evaluated on a non-redundant dataset consisted of 1406 GPCRs for six families and 1406 globular proteins using the jackknife test. The present method based on amino acid composition achieved an overall accuracy of 96.4% and Matthew's correlation coefficient (MCC) of 0.930 for correctly picking out the GPCRs from globular proteins. The overall accuracy and MCC were further enhanced to 99.8% and 0.996 by dipeptide composition-based method. On the other hand, the present method has successfully classified 1406 GPCRs into six families with an overall accuracy of 89.6 and 98.8% using amino acid composition and dipeptide composition, respectively. For the subfamily prediction of 1181 GPCRs of rhodopsin-like family, the present method achieved an overall accuracy of 76.7 and 94.5% based on the amino acid composition and dipeptide composition, respectively. Finally, GPCRs belonging to the amine subfamily and olfactory subfamily of rhodopsin-like family were further analyzed at the type level. The overall accuracy of dipeptide composition-based method for the classification of amine type and olfactory type of GPCRs reached 94.5 and 86.9%, respectively, while the overall accuracy of amino acid composition-based method was very low for both subfamilies. In comparison with existing methods in the literature, the present method also displayed great competitiveness. These results demonstrate the effectiveness of our method on identifying and classifying GPCRs correctly. GPCRsIdentifier, a corresponding stand-alone executable program for GPCR identification and classification was also developed, which can be acquired freely on request from the authors for academic purposes.

Using Nearest Feature Line and Tunable Nearest Neighbor methods for prediction of protein subcellular locations.

The subcellular location of a protein is closely correlated with it biological function. In this paper, two new pattern classification methods termed as Nearest Feature Line (NFL) and Tunable Nearest Neighbor (TNN) have been introduced to predict the subcellular location of proteins based on their amino acid composition alone. The simulation experiments were performed with the jackknife test on a previously constructed data set, which consists of 2,427 eukaryotic and 997 prokaryotic proteins. All protein sequences in the data set fall into four eukaryotic subcellular locations and three prokaryotic subcellular locations. The NFL classifier reached the total prediction accuracies of 82.5% for the eukaryotic proteins and 91.0% for the prokaryotic proteins. The TNN classifier reached the total prediction accuracies of 83.6 and 92.2%, respectively. It is clear that high prediction accuracies have been achieved. Compared with Support Vector Machine (SVM) and Nearest Neighbor methods, these two methods display similar or even higher prediction accuracies. Hence, we conclude that NFL and TNN can be used as complementary methods for prediction of protein subcellular locations.