Dependability enhancing mechanisms for integrated clinical environments

In this article, we present a set of lightweight mechanisms to enhance the dependability of a safety-critical real-time distributed system referred to as an integrated clinical environment (ICE). In an ICE, medical devices are interconnected and work together with the help of a supervisory computer system to enhance patient safety during clinical operations. Inevitably, there are strong dependability requirements on the ICE. We introduce a set of mechanisms that essentially make the supervisor component a trusted computing base, which can withstand common hardware failures and malicious attacks. The mechanisms rely on the replication of the supervisor component and employ only one input-exchange phase into the critical path of the operation of the ICE. Our analysis shows that the runtime latency overhead is much lower than that of traditional approaches

Label-free classification of cultured cells through diffraction imaging

Automated classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. We have investigated this possibility experimentally and numerically using a diffraction imaging approach. A fast image analysis software based on the gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images. The results of GLCM analysis and subsequent classification demonstrate the potential for rapid classification among six types of cultured cells. Combined with numerical results we show that the method of diffraction imaging flow cytometry has the capacity as a platform for high-throughput and label-free classification of biological cells

A Novel SALL4/OCT4 Transcriptional Feedback Network for Pluripotency of Embryonic Stem Cells

Background: SALL4 is a member of the SALL gene family that encodes a group of putative developmental transcription factors. Murine Sall4 plays a critical role in maintaining embryonic stem cell (ES cell) pluripotency and self-renewal. We have shown that Sall4 activates Oct4 and is a master regulator in murine ES cells. Other SALL gene members, especially Sall1 and Sall3 are expressed in both murine and human ES cells, and deletions of these two genes in mice lead to perinatal death due to developmental defects. To date, little is known about the molecular mechanisms controlling the regulation of expressions of SALL4 or other SALL gene family members. Methodology/Principal Findings: This report describes a novel SALL4/OCT4 regulator feedback loop in ES cells in balancing the proper expression dosage of SALL4 and OCT4 for the maintenance of ESC stem cell properties. While we have observed that a positive feedback relationship is present between SALL4 and OCT4, the strong self-repression of SALL4 seems to be the “break” for this loop. In addition, we have shown that SALL4 can repress the promoters of other SALL family members, such as SALL1 and SALL3, which competes with the activation of these two genes by OCT4. Conclusions/Significance: Our findings, when taken together, indicate that SALL4 is a master regulator that controls its own expression and the expression of OCT4. SALL4 and OCT4 work antagonistically to balance the expressions of other SALL gene family members. This novel SALL4/OCT4 transcription regulation feedback loop should provide more insight into the mechanism of governing the “stemness” of ES cells

3D Protein structure prediction with genetic tabu search algorithm

Abstract Background Protein structure prediction (PSP) has important applications in different fields, such as drug design, disease prediction, and so on. In protein structure prediction, there are two important issues. The first one is the design of the structure model and the second one is the design of the optimization technology. Because of the complexity of the realistic protein structure, the structure model adopted in this paper is a simplified model, which is called off-lattice AB model. After the structure model is assumed, optimization technology is needed for searching the best conformation of a protein sequence based on the assumed structure model. However, PSP is an NP-hard problem even if the simplest model is assumed. Thus, many algorithms have been developed to solve the global optimization problem. In this paper, a hybrid algorithm, which combines genetic algorithm (GA) and tabu search (TS) algorithm, is developed to complete this task. Results In order to develop an efficient optimization algorithm, several improved strategies are developed for the proposed genetic tabu search algorithm. The combined use of these strategies can improve the efficiency of the algorithm. In these strategies, tabu search introduced into the crossover and mutation operators can improve the local search capability, the adoption of variable population size strategy can maintain the diversity of the population, and the ranking selection strategy can improve the possibility of an individual with low energy value entering into next generation. Experiments are performed with Fibonacci sequences and real protein sequences. Experimental results show that the lowest energy obtained by the proposed GATS algorithm is lower than that obtained by previous methods. Conclusions The hybrid algorithm has the advantages from both genetic algorithm and tabu search algorithm. It makes use of the advantage of multiple search points in genetic algorithm, and can overcome poor hill-climbing capability in the conventional genetic algorithm by using the flexible memory functions of TS. Compared with some previous algorithms, GATS algorithm has better performance in global optimization and can predict 3D protein structure more effectively

Editing independent effects of ADARs on the miRNA/siRNA pathways

Adenosine deaminases acting on RNA (ADARs) are best known for altering the coding sequences of mRNA through RNA editing, as in the GluR-B Q/R site. ADARs have also been shown to affect RNA interference (RNAi) and microRNA processing by deamination of specific adenosines to inosine. Here, we show that ADAR proteins can affect RNA processing independently of their enzymatic activity. We show that ADAR2 can modulate the processing of mir-376a2 independently of catalytic RNA editing activity. In addition, in a Drosophila assay for RNAi deaminase-inactive ADAR1 inhibits RNAi through the siRNA pathway. These results imply that ADAR1 and ADAR2 have biological functions as RNA-binding proteins that extend beyond editing per se and that even genomically encoded ADARs that are catalytically inactive may have such functions

Long-term outcomes of early childhood science education: insight from a cross-national comparative case study on conceptual understanding of science

The purpose of this research was to explore the long term outcomes of either participating or not participating in early childhood science education on Grade 6 students’ conceptual understanding of science. The research is situated in a conceptual framework that evokes Piagetian developmental levels as both potential curriculum constraints and potential models of efficacy. The research design was a multiple case study of Grade 6 children from three schools in China (n=140) who started formal science education in the third grade, and Grade 6 children from three matched schools in Australia (n=105) who started learning science in kindergarten. The students’ understanding was assessed by a science quiz and in-depth interview. The data showed that participating children from the high socio-economic schools in China and Australia had similar understandings of science. Divergence between the medium and low socio-economic schools, however, indicated that the grounding in early childhood science education in Australia may have placed these children at an advantage. Alternative explanations for the divergence including the nature of classroom instruction in the two countries are discussed

Telomere Length Trajectory and Its Determinants in Persons with Coronary Artery Disease: Longitudinal Findings from the Heart and Soul Study

Background: Leukocyte telomere length, an emerging marker of biological age, has been shown to predict cardiovascular morbidity and mortality. However, the natural history of telomere length in patients with coronary artery disease has not been studied. We sought to investigate the longitudinal trajectory of telomere length, and to identify the independent predictors of telomere shortening, in persons with coronary artery disease. Methodology/Principal Findings: In a prospective cohort study of 608 individuals with stable coronary artery disease, we measured leukocyte telomere length at baseline, and again after five years of follow-up. We used multivariable linear and logistic regression models to identify the independent predictors of leukocyte telomere trajectory. Baseline and follow-up telomere lengths were normally distributed. Mean telomere length decreased by 42 base pairs per year (p,0.001). Three distinct telomere trajectories were observed: shortening in 45%, maintenance in 32%, and lengthening in 23 % of participants. The most powerful predictor of telomere shortening was baseline telomere length (OR per SD increase = 7.6; 95 % CI 5.5, 10.6). Other independent predictors of telomere shortening were age (OR per 10 years = 1.6; 95 % CI 1.3, 2.1), male sex (OR = 2.4; 95 % CI 1.3, 4.7), and waist-to-hip ratio (OR per 0.1 increase = 1.4; 95 % CI 1.0, 2.0). Conclusions/Significance: Leukocyte telomere length may increase as well as decrease in persons with coronary arter