No abstract

No abstract

No abstract

BackgroundAdenosylcobalamin (vitamin B12) is a coenzyme required for the activity of methylmalonyl-CoA mutase. Defects in this enzyme are a cause of methylmalonic acidemia (MMA). Methylmalonic acidemia, cblA type, is an inborn error of vitamin B12 metabolism that occurs due to mutations in the MMAA gene. MMAA encodes the enzyme which is involved in translocation of cobalamin into the mitochondria.MethodsOne family with two MMA-affected children, one unaffected child, and their parents were studied. The two affected children were diagnosed by urine organic acid analysis using gas chromatography-mass spectrometry. MMAA was analyzed by PCR and sequencing of its coding region.ResultsA homozygous deletion in exon 4 of MMAA, c.674delA, was found in both affected children. This deletion causes a nucleotide frame shift resulting in a change from asparagine to methionine at amino acid 225 (p.N225M) and a truncated protein which loses the ArgK conserved domain site. mRNA expression analysis of MMAA confirmed these results.ConclusionWe demonstrate that the deletion in exon 4 of the MMAA gene (c.674 delA) is a pathogenic allele via a nucleotide frame shift resulting in a stop codon and termination of protein synthesis 38 nucleotides (12 amino acids) downstream of the deletion.

Abstract. Future smart-home functionalities enable users to manage their home appliances through a single application by connecting home appliances through an integrated platform and server. In the smart home, a Home Energy Management System (HEMS) is necessary to monitor, control and optimize electrical generation and consumption. On the other hand Demand Response (DR) provides an opportunity for consumers to play a significant role in the operation of the electrical grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. In this paper we propose an autonomous Demand-Side Management (DSM) model to control the residential load of customers equipped with local power storage facilities as an auxiliary source of energy. In our proposed model the power consumption level of local devices, the amount of power being demanded from both local storage facilities and local utility companies are scheduled using a bi-level quadratic optimization approach of a well-defined convex cost function. Therefore we show that this goal can be fulfilled with a bi-level scheduler unit installed inside the smart meters. In addition our proposed model can also achieve the global optimal performance in terms of energy minimization cost at the Nash equilibrium of a formulated non-cooperative game. We also extend our DSM model to a two tiers cloud computing environment in which both customers and utility companies participate on it.