Expression of His-tagged NADPH-dependent acetoacetyl-CoA reductase in recombinant Escherichia coli BL-21(DE3).

Poly-3-hydroxybutyrate (P(3HB)), a member of the polyhydroxyalkanoate (PHA) family, is a biodegradable polyester with diverse industrial applications. NADPH-dependent acetoacetyl-CoA reductase (phaB) is the enzyme which plays an essential role in P(3HB) synthesis by catalyzing the conversion of the intermediates. The expression of phaB enzyme using the recombinant Escherichia coli BL-21(DE3) and the purification of the synthesized enzyme were studied. The pET-B3 plasmid harbouring the phaB gene derived from Ralstonia eutropha H16, was driven by the lac promoter in E. coli BL-21(DE3). The enzyme was expressed with different induction time, temperatures and cell age. Results showed that the cell age of 4 h, induction time of 12 h at 37°C were identified as the optimal conditions for the enzyme reductase expression. A specific activity of 0.151 U mg-1 protein and total protein concentration of 0.518 mg mg-1 of dry cell weight (DCW) were attained. Affinity chromatography was performed to purify the His-tagged phaB enzyme, in which enhanced the specific activity (14.44 U mg-1) and purification fold (38-fold), despite relative low yield (44.6%) of the enzyme was obtained. The purified phaB showed an optimal enzyme activity at 30°C and pH 8.0. The findings provide an alternative for the synthesis of the reductase enzyme which can be used in the industrial-scale production of the biodegradable polymers.

Prediction of Diagnosis-Related Groups for Appendectomy Patients Using C4.5 and Neural Network.

Due to the increasing cost of health insurance, for decades, many countries have endeavored to constrain the cost of insurance by utilizing a DRG payment system. In most cases, under the DRG payment system, hospitals cannot exactly know which DRG code inpatients are until they are discharged. This paper focuses on the prediction of what DRG code appendectomy patients will be classified with when they are admitted to hospital. We utilize two models (or classifiers) constructed using the C4.5 algorithm and back-propagation neural network (BPN). We conducted experiments with the data collected from two hospitals. The results show that the accuracies of these two classification models can be up to 97.84% and 98.70%, respectively. According to the predicted DRG code, hospitals can effectively arrange medical resources with certainty, then, in turn, improve the quality of the medical care patients receive.

Effective Patient-Dentist Communication with a Simulation System for Orthodontics.

Orthodontic treatment is a common dental treatment. A complete treatment often takes several years and is costly. In order to increase the degree of satisfaction and reduce the gap between the expectations of the patient and the limitations of orthodontics, orthodontists and patients should have sufficient communication. A simulation system can provide a good channel for communication between orthodontists and patients. This paper proposes a 3D dentist-patient communication system for the simulation of orthodontics in advance. The system collects the clinical paradigms of orthodontic cases, which must contain photos from before, during, and after maxillofacial treatment. This research simulates treatment processes by tuning a 3D virtual model of the oral and maxillofacial areas, including the face, mouth, and teeth, to demonstrate the processes of clinical paradigms. These 3D models could be edited and synthesized to generate new 3D models for simulation with the 3DS Max tool. In addition, the proposed system provides a function for the orthodontist to manually operate the 3D virtual model, such as tooth arrangement, morphing of the gums with movement of the teeth, the placement (attachment) of arch-wires and brackets, and changes of facial appearance. The orthodontist can demonstrate the treatment processes, show movements of the teeth, and answer possible questions from the patient about the treatment processes by using the 3D model. To show the effectiveness of the proposed system, a questionnaire about the system was also used to demonstrate its acceptance, usability, and validity. Qualitative interviews with dentists and questionnaires for patients about the system are both performed. The results showed that the proposed system is an effective vehicle for communication between patients and orthodontists.

Implementation and Acceptance of Information and Communication Technology Incorporated into Long-Term Care.

Every country in the world is facing serious demographic aging, since the average life expectancy is consistently increasing. Agencies involved in the implementation of caregiving through long-term care institutions can develop more convenient approaches using information and communication technology to enhance overall efficiency. Communication technology has enabled the strengthening of physiological instruments, improving the efficiency and quality of services, while integrating management systems for optimum efficiency. This work conducted empirical studies, collecting responses to questionnaires from residents and caregivers in five institutions located in the south of Taiwan. The PZB model, proposed by Parasuraman, Zeithaml, and Berry, was used to construct the questionnaire to analyze the service quality following the incorporation of information and communication technology. The results of the empirical study show that 34% and 63% of the relatives of the residents agreed and strongly agreed that the system was practical and convenient, respectively. As for the caregivers, 77% of them agreed or strongly agreed that the system was mobile, practical, and convenient, and they agreed that the system could significantly increase working efficiency, reduce waiting time, and improve administration for chronic diseases among care-home residents.

Molecular Characteristics of Fat Body Protein 1 in the Oriental Fruit Fly, Bactrocera dorsalis.

Bactrocera dorsails fat body protein 1 (Bdfbp1) cDNA was cloned (GenBank accession no. MT514270), and the complete 3,749-bp cDNA encoded a 1,152-amino acid protein. The phylogenetic relationship of dipteran fbp1s was analyzed. The sequence XP_028900815 from the insect genome project for Zeugodacus cucurbitae (LOC105219342) was proposed that two fbp1 genes were present in the sequence. The developmental transcriptional expression profiles were determined. In the larval stages, Bdfbp1 mRNA had significantly higher expression in the late third instar larvae compared with first, second, and early third instar larvae. In the pupal stages, the highest expression of Bdfbp1 mRNA was found in the newly pupated pupae and then decreased with age. In the fat body of female adults, Bdfbp1 was highly expressed in newly emerged samples and decreased rapidly over the following three days. In the fat body of male adults, Bdfbp1 was highly expressed in newly eclosed samples. RNAi treatment decreased the expression level of Bdfbp1 without statistical difference. However, RNAi treatment significantly decreased the rate of eclosion. These results suggest that Bdfbp1 may function as a storage protein and be associated with adult eclosion.

A CpGCluster-Teaching-Learning-Based Optimization for Prediction of CpG Islands in the Human Genome.

Many CpG island detection methods have been proposed based on sliding window and clustering technology, but the accuracy of these methods is proportional to the time required. Therefore, an accurate and rapid method for identifying CpG islands remains an important challenge in the complete human genome. We propose a hybrid method CpGTLBO to detect the CpG islands in the human genome. The method uses the clustering approach and the teaching-learning-based optimization (TLBO) algorithm. The clustering approach is used to detect CpG island candidates, and it can effectively reduce the huge volume of unnecessary DNA fragments. TLBO was used to accurately predict CpG islands among promising CpG island candidates. A comparison based on six contig data sets and a whole human genome analysis showed that the identifying stability of CpGTLBO outperformed eight existing methods in terms of sensitivity (SN), specificity (SP), accuracy (ACC), performance coefficient (PC), and correlation coefficient (CC) and processing time. Results indicated that ClusterTLBO can effectively overcome the drawbacks and maintain the advantages in both the CpGcluster and TLBO.

Incidence of Major Depressive Disorder: Variation by Age and Sex in Low-Income Individuals: A Population-Based 10-Year Follow-Up Study.

Major depressive disorder (MDD), the most prevalent mental disorder is a global public health issue. The aim of this study was to assess the association between low income and major depressive disorder (MDD) by age and sex. The National Health Insurance Research Database (NHIRD) of Taiwan was used to retrieve data. A total of 1,743,948 participants were eligible for the study. Low-income individuals were identified from 2001 and 2003 (specifically, Group Insurance Applicants, ie, category"51" or "52") and followed from 2004 to 2010. MDD was identified using the ICD-9-CM 296.2 and 296.3 codes. Among non-low-income individuals, the MDD incidence rates increased with age in both males and females, that is, 0.35, 0.93, 0.97, 1.40 per 10,000 person-months for males and 0.41, 1.60, 1.89, 1.95 per 10,000 person-months for females aged 0 to 17, 18 to 44, 45 to 64, and ≥65 years, respectively. Low-income females (18-44 years) and males (45-64 years) had the highest incidence of MDD, which was 3.90 and 3.04, respectively, per 10,000 person-months. Among low and non-low-income individuals, the MDD incidence rates were higher in the females than males in all age groups. Males aged 45 to 64 and 0 to 17 years had highest hazard ratios (HR) of 2.789 (95% confidence interval [CI], 1.937-4.014) and 2.446 (95% CI, 1.603-3.732), respectively. The highest HRs for females were 2.663 (95% CI, 1.878-3.775) and 2.219 (CI, 1.821-2.705) in the 0 to 17 and 18- to 44-year age groups. Low income was not found to serve as a risk factor for the development of MDD in males and females aged ≥65 years. Among the non-low-income males and females, the incidence rates of MDD were found to increase with age. Low income was found to serve as a significant risk factor for MDD only in individuals under age 65.

A Hybrid Approach for CpG Island Detection in the Human Genome.

BACKGROUND: CpG islands have been demonstrated to influence local chromatin structures and simplify the regulation of gene activity. However, the accurate and rapid determination of CpG islands for whole DNA sequences remains experimentally and computationally challenging. METHODOLOGY/PRINCIPAL FINDINGS: A novel procedure is proposed to detect CpG islands by combining clustering technology with the sliding-window method (PSO-based). Clustering technology is used to detect the locations of all possible CpG islands and process the data, thus effectively obviating the need for the extensive and unnecessary processing of DNA fragments, and thus improving the efficiency of sliding-window based particle swarm optimization (PSO) search. This proposed approach, named ClusterPSO, provides versatile and highly-sensitive detection of CpG islands in the human genome. In addition, the detection efficiency of ClusterPSO is compared with eight CpG island detection methods in the human genome. Comparison of the detection efficiency for the CpG islands in human genome, including sensitivity, specificity, accuracy, performance coefficient (PC), and correlation coefficient (CC), ClusterPSO revealed superior detection ability among all of the test methods. Moreover, the combination of clustering technology and PSO method can successfully overcome their respective drawbacks while maintaining their advantages. Thus, clustering technology could be hybridized with the optimization algorithm method to optimize CpG island detection. CONCLUSION/SIGNIFICANCE: The prediction accuracy of ClusterPSO was quite high, indicating the combination of CpGcluster and PSO has several advantages over CpGcluster and PSO alone. In addition, ClusterPSO significantly reduced implementation time.

Using LC/MS/MS to determine matrine, oxymatrine, ferulic acid, mangiferin, and glycyrrhizin in the Chinese medicinal preparations Shiau-feng-saan and Dang-guei-nian-tong-tang.

We have developed a simple, rapid, selective, and reproducible method for the quality control of traditional Chinese medicinal preparations. In this study, we used LC/MS/MS to simultaneously identify and quantify five marker compounds - matrine, oxymatrine, ferulic acid, mangiferin, and glycyrrhizin - in preparations of Shiau-feng-saan and Dang-guei-nian-tong-tang. The calibration curves for the five marker compounds were linear over the concentration range 50-2500 ng/mL (R2>0.9971). The matrix effect was minimized and the recoveries of the five marker compounds were >90% at a concentration of 1 microg/mL. Our experimental data reveal that significant differences exist between samples obtained from different sources.