An intelligent energy management system for educational buildings

There is a wide variation in the energy consumption between different educational institutions due to the adoption of different management strategies and different levels of occupants’ environmental understanding. The presence of large amounts of information and communication technology (ICT) equipment and heating, ventilation, and air conditioning (HVAC) system causes a major consumption of energy in higher education institution (HEI) buildings. The main objective of this research is to investigate the use of ICT to optimize the energy consumption in HEI buildings and reduce carbon dioxide (CO 2 ) emission. The first phase of the system has been implemented at King Saud University to measure energy consumption through sensors that read energy consumption of electrical appliances and devices every 10 seconds. The analysis of collected data allows us to develop and employ energy saving strategies that lead to a reduction in total energy consumption. Our preliminary results show that up to 17% of energy consumption can be reduced by simply dealing with standby energy loss of labs’ computers. The novelty of this research comes from the use of a functional database approach to deal with high volume of data and query performance and the incorporation of a timetabling system in energy management system

Evaluating the accuracy of a functional SNP annotation system

Many common and chronic diseases are influenced at some level by genetic variation. Research done in population genetics, specifically in the area of single nucleotide polymorphisms (SNPs) is critical to understanding human genetic variation. A key element in assessing role of a given SNP is determining if the variation is likely to result in change in function. The SNP Integration Tool (SNPit) is a comprehensive tool that integrates diverse, existing predictors of SNP functionality, providing the user with information for improved association study analysis. To evaluate the SNPit system, we developed an alternative gold standard to measure accuracy using sensitivity and specificity. The results of our evaluation demonstrated that our alternative gold standard produced encouraging results

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro

Gpr124 is essential for blood-brain barrier integrity in central nervous system disease

Although blood-brain barrier (BBB) compromise is central to the etiology of diverse central nervous system (CNS) disorders, endothelial receptor proteins that control BBB function are poorly defined. The endothelial G-protein-coupled receptor (GPCR) Gpr124 has been reported to be required for normal forebrain angiogenesis and BBB function in mouse embryos, but the role of this receptor in adult animals is unknown. Here Gpr124 conditional knockout (CKO) in the endothelia of adult mice did not affect homeostatic BBB integrity, but resulted in BBB disruption and microvascular hemorrhage in mouse models of both ischemic stroke and glioblastoma, accompanied by reduced cerebrovascular canonical Wnt-β-catenin signaling. Constitutive activation of Wnt-β-catenin signaling fully corrected the BBB disruption and hemorrhage defects of Gpr124-CKO mice, with rescue of the endothelial gene tight junction, pericyte coverage and extracellular-matrix deficits. We thus identify Gpr124 as an endothelial GPCR specifically required for endothelial Wnt signaling and BBB integrity under pathological conditions in adult mice. This finding implicates Gpr124 as a potential therapeutic target for human CNS disorders characterized by BBB disruption

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams