Biomedical subjects

Kazumi Saito

Publications and source records attributed to Kazumi Saito.

8 recordsLinked to original sources

PubMed2005

Polyamines are essential for the synthesis of 2-ricinoleoyl phosphatidic acid in developing seeds of castor.

The major fatty acid component of castor (Ricinus communis L.) oil is ricinoleic acid (12-hydroxy-cis-9-octadecenoic acid), and unsaturated hydroxy acid accounts for >85% of the total fatty acids in triacylglycerol (TAG). TAG had a higher ricinoleate content at position 2 than at positions 1 and 3. Although lysophosphatidic acid (LPA) acyltransferase (EC 2.3.1.51), which catalyzes acylation of LPA at position 2, was expected to utilize ricinoleoyl-CoA preferentially over other fatty acyl-CoAs, no activity was found for ricinoleoyl-CoA in vitro at concentrations at which other unsaturated acyl-CoAs were incorporated rapidly. However, activity for ricinoleoyl-CoA appeared with addition of polyamines (putrescine, spermidine, and spermine), while polyamines decreased the rates of incorporation of other acyl-CoAs into position 2. The order of effect of polyamines on LPA acyltransferase activity was spermine > spermidine >> putrescine. At concentrations of spermine and spermidine of >0.1 mM, ricinoleoyl-CoA served as an effective substrate for LPA acyltransferase reaction. The concentrations of spermine and spermidine in the developing seeds were estimated at approximately 0.09 and approximately 0.63 mM, respectively. These stimulatory effects for incorporation of ricinoleate were specific to polyamines, but basic amino acids were ineffective as cations. In contrast, in microsomes from safflower seeds that do not contain ricinoleic acid, spermine and spermidine stimulated the LPA acyltransferase reaction for all acyl-CoAs tested, including ricinoleoyl-CoA. Although the fatty acid composition of TAG depends on both acyl-CoA composition in the cell and substrate specificity of acyltransferases, castor bean polyamines are crucial for incorporation of ricinoleate into position 2 of LPA. Polyamines are essential for synthesis of 2-ricinoleoyl phosphatidic acid in developing castor seeds.

Acetyl Coenzyme A↗

PubMed2005

Purification and cDNA cloning of chloroplastic monodehydroascorbate reductase from spinach.

The chloroplastic isoform of monodehydroascorbate (MDA) radical reductase was purified from spinach chloroplasts and leaves. The cDNA of chloroplastic MDA reductase was cloned, and its deduced amino acid sequence, consisting of 497 residues, showed high homology with those of putative organellar MDA reductases deduced from cDNAs of several plants. The amino acid sequence of the amino terminal of the purified enzyme suggested that the chloroplastic enzyme has a transit peptide consisting of 53 residues. A southern blot analysis suggested the occurrence of a gene encoding another isoform homologous to the chloroplastic isoform in spinach. The recombinant enzyme was highly expressed in Eschericia coli using the cDNA, and purified to a homogeneous state with high specific activity. The enzyme properties of the chloroplastic isoform are presented in comparison with those of the cytosolic form.

Amino Acid Sequence↗

PubMed2004

Crystallization and preliminary crystallographic analysis of monodehydroascorbate radical reductase from cucumber.

Monodehydroascorbate (MDA) radical reductase (EC 1.6.5.4) is an FAD enzyme that catalyzes the univalent reduction of MDA radical to ascorbate using NAD(P)H as an electron donor. The recombinant MDA reductase from cucumber was crystallized using polyethylene glycol 6000 as a precipitant. The crystals belong to space group P2(1), with unit-cell parameters a = 60.8, b = 138.6, c = 61.7 A, beta = 114.5 degrees, and contained two molecules per asymmetric unit. The Matthews coefficient (VM) and the solvent content are 2.46 A3 Da(-1) and 50.0%, respectively. Diffraction data were collected to a resolution of 2.4 A at 100 K using Cu Kalpha radiation with a multi-wire area detector and gave a data set with an overall Rsym of 10.0% and a completeness of 92.5%.

Crystallization↗

PubMed2004

Modeling of growing networks with directional attachment and communities.

In this paper, we propose a new network growth model and its learning algorithm to more precisely model such a real-world growing network as the Web. Unlike the conventional models, we have incorporated directional attachment and community structure for this purpose. We show that the proposed model exhibits a degree distribution with a power-law tail, which is an important characteristic of many large-scale real-world networks including the Web. Using real Web data, we experimentally show that predictive ability can be improved by incorporating directional attachment and community structure. Also, using synthetic data, we experimentally show that predictive ability can definitely be improved by incorporating community structure.

Algorithms↗

PubMed2003

Lipid synthesis and acyl-CoA synthetase in developing rice seeds.

Developing rice seeds rapidly accumulated storage lipids between 5 and 12 d after flowering. The contents of palmitic, oleic, and linoleic acids increased throughout seed development, while the alpha-linolenic acid content remained low. The activity of acyl-CoA synthetase varied coincidentally during the period of lipid accumulation, and rice seeds had a sufficient capacity to supply acyl-CoA substrates for TAG synthesis. Acyl-CoA synthetase showed a broad specificity for native FA of rice seeds except for stearic acid, and pi electrons of a delta9-delta11 double bond in the C16-C18 acyl chains were required for its maximal activity.

Cell Membrane↗

PubMed2002

A convenient method for determination of the C20-22 PUFA composition of glycerolipids in blood and breast milk.

A convenient method was developed for preparation of FAME in small amounts from glycerolipids of blood or breast milk. Initially, 0.04-0.06 mL blood or breast milk was spotted onto a small piece of filter paper (1.5 x 1.5 cm) that had been washed with acetone containing 0.05% 2,6-di-tert-butyl-p-cresol (BHT). Each piece, once it had dried, was put in a small test tube, to which 2 mL hexane and 0.2 mL 2 M KOH/methanol were added. After vigorous mixing or sonication for 2 min at room temperature, the solution was neutralized or acidified by the addition of a few drops of acetic acid. To the solution was added 2 mL H2O, and then the hexane layer that separated was concentrated to dryness in vacuo. The FAME obtained were analyzed by GC. The method was applicable to the analysis of a large number of blood and breast milk samples, and the arachidonate/(eicosapentaenoate + docosahexaenoate) ratios could be determined rapidly.

Chromatography, Gas↗

PubMed2002

Extracting regression rules from neural networks.

This paper proposes a new framework and method for extracting regression rules from neural networks trained with multivariate data containing both nominal and numeric variables. Each regression rule is expressed as a pair of a logical formula on the conditional part over nominal variables and a polynomial equation on the action part over numeric variables. The proposed extraction method first generates one such regression rule for each training sample, then utilizes the kappa-means algorithm to generate a much smaller set of rules having more general conditions, where the number of distinct polynomial equations is determined through cross-validation. Finally, this method invokes decision-tree induction to form logical formulae of nominal conditions as conditional parts of final regression rules. Experiments using four data sets show that our method works well in extracting quite accurate and interesting regression rules.

Algorithms↗

PubMedDate not supplied

Cross-entropy embedding of high-dimensional data using the neural gas model.

A cross-entropy approach to mapping high-dimensional data into a low-dimensional space embedding is presented. The method allows to project simultaneously the input data and the codebook vectors, obtained with the Neural Gas (NG) quantizer algorithm, into a low-dimensional output space. The aim of this approach is to preserve the relationship defined by the NG neighborhood function for each pair of input and codebook vectors. A cost function based on the cross-entropy between input and output probabilities is minimized by using a Newton-Raphson method. The new approach is compared with Sammon's non-linear mapping (NLM) and the hierarchical approach of combining a vector quantizer such as the self-organizing feature map (SOM) or NG with the NLM recall algorithm. In comparison with these techniques, our method delivers a clear visualization of both data points and codebooks, and it achieves a better mapping quality in terms of the topology preservation measure q(m).

Algorithms↗