Acyl-CoA dehydrogenase 9 (ACAD9) is an assembly factor for mitochondrial respiratory chain Complex I (CI), and ACAD9 mutations are recognized as a frequent cause of CI deficiency. ACAD9 also retains enzyme ACAD activity for long-chain fatty acids in vitro, but the biological relevance of this function remains controversial partly because of the tissue specificity of ACAD9 expression: high in liver and neurons and minimal in skin fibroblasts. In this study, we hypothesized that this enzymatic ACAD activity is required for full fatty acid oxidation capacity in cells expressing high levels of ACAD9 and that loss of this function is important in determining phenotype in ACAD9-deficient patients. First, we confirmed that HEK293 cells express ACAD9 abundantly. Then, we showed that ACAD9 knockout in HEK293 cells affected long-chain fatty acid oxidation along with Cl, both of which were rescued by wild type ACAD9. Further, we evaluated whether the loss of ACAD9 enzymatic fatty acid oxidation affects clinical severity in patients with ACAD9 mutations. The effects on ACAD activity of 16 ACAD9 mutations identified in 24 patients were evaluated using a prokaryotic expression system. We showed that there was a significant inverse correlation between residual enzyme ACAD activity and phenotypic severity of ACAD9-deficient patients. These results provide evidence that in cells where it is strongly expressed, ACAD9 plays a physiological role in fatty acid oxidation, which contributes to the severity of the phenotype in ACAD9-deficient patients. Accordingly, treatment of ACAD9 patients should aim at counteracting both CI and fatty acid oxidation dysfunctions.

Despite having a relatively low incidence, renal cell carcinoma (RCC) is one of the most lethal urologic cancers. For successful treatment including surgery, early detection is essential. Currently there is no screening method such as biomarker assays for early diagnosis of RCC. Surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF) is a recent technical advance that can be used to identify biomarkers for cancers. In this study, we investigated whether SELDI protein profiling and artificial intelligence analysis of serum could distinguish RCC from healthy persons and other urologic diseases (nonRCC). The SELDI-TOF data was acquired from a total of 36 serum samples with weak cation exchange-2 protein chip arrays and filtered using ProteinChip software. We used a decision tree algorithm c4.5 to classify the three groups of sera. Five proteins were identified with masses of 3900, 4107, 4153, 5352, and 5987 Da. These biomarkers can correctly separate RCC from healthy and nonRCC samples.

Medium-chain acyl-CoA dehydrogenase (MCAD; acyl-CoA:(acceptor) 2,3-oxidoreductase, EC 1.3.99.3) is one of three similar enzymes that catalyze the initial step of fatty acid fl-oxidation. Definition of the primary structure of MCAD and the tissue distribution of its mRNA is of biochemical and clinical importance because of the recent recognition of inherited MCAD deficiency in humans. The MCAD mRNA nucleotide sequence was determined from two overlapping cDNA clones isolated from human liver and placental cDNA libraries, respectively. The MCAD mRNA includes a 1263-base-pair coding region and a 738-base-pair 3'-nontranslated region. A partial amino acid sequence (137 residues) determined on peptides derived from MCAD purified from porcine liver confirmed the identity of the cDNA clone.Comparison of the amino acid sequence predicted from the human MCAD cDNA with the partial protein sequence of the porcine MCAD revealed a high degree (88%) of interspecies sequence identity. RNA blot analysis shows that MCAD mRNA is expressed in a variety of rat (2.2 kilobases) and human (2.4 kilobases) tissues. Blot hybridization of RNA prepared from cultured skin fibroblasts from a patient with MCAD deficiency disclosed that mRNA was present and of similar size to MCAD mRNA derived from control fibroblasts. The isolation and characterization of MCAD cDNA is an important step in the definition of the defect underlying MCAD deficiency and in understanding its metabolic consequences.

Recently, a novel learning algorithm called extreme learning machine (ELM) was proposed for efficiently training single-hidden-layer feedforward neural networks (SLFNs). It was much faster than the traditional gradient-descent-based learning algorithms due to the analytical determination of output weights with the random choice of input weights and hidden layer biases. However, this algorithm often requires a large number of hidden units and thus slowly responds to new observations. Evolutionary extreme learning machine (E-ELM) was proposed to overcome this problem; it used the differential evolution algorithm to select the input weights and hidden layer biases. However, this algorithm required much time for searching optimal parameters with iterative processes and was not suitable for data sets with a large number of input features. In this paper, a new approach for training SLFNs is proposed, in which the input weights and biases of hidden units are determined based on a fast regularized least-squares scheme. Experimental results for many real applications with both small and large number of input features show that our proposed approach can achieve good generalization performance with much more compact networks and extremely high speed for both learning and testing.

Metallohydrolases catalyse some of the most important reactions in biology and are targets for numerous chemotherapeutic agents designed to combat bacterial infectivity, antibiotic resistance, HIV infectivity, tumour growth, angiogenesis and immune disorders. Rational design of inhibitors of these enzymes with chemotherapeutic potential relies on detailed knowledge of the catalytic mechanism. The roles of the catalytic transition ions in these enzymes have long been assumed to include the activation and delivery of a nucleophilic hydroxy moiety. In the present study, catalytic intermediates in the hydrolysis of L-leucyl-L-leucyl-L-leucine by Vibrio proteolyticus aminopeptidase were characterized in spectrokinetic and structural studies. Rapid-freeze-quench EPR studies of reaction products of L-leucyl-L-leucyl-L-leucine and Co(II)-substituted aminopeptidase, and comparison of the EPR data with those from structurally characterized complexes of aminopeptidase with inhibitors, indicated the formation of a catalytically competent post-Michaelis pre-transition state intermediate with a structure analogous to that of the inhibited complex with bestatin. The X-ray crystal structure of an aminopeptidase-L-leucyl-L-leucyl-L-leucine complex was also analogous to that of the bestatin complex. In these structures, no water/hydroxy group was observed bound to the essential metal ion. However, a water/hydroxy group was clearly identified that was bound to the metal-ligating oxygen atom of Glu152. This water/hydroxy group is proposed as a candidate for the active nucleophile in a novel metallohydrolase mechanism that shares features of the catalytic mechanisms of aspartic proteases and of B2 metallo-beta-lactamases. Preliminary studies on site-directed variants are consistent with the proposal. Other features of the structure suggest roles for the dinuclear centre in geometrically and electrophilically activating the substrate.