Sphingomyelin Phosphodiesterase 3 Enhances Cytodifferentiation of Periodontal Ligament Cells.

Sphingomyelin phosphodiesterase 3 ( Smpd3), which encodes neutral sphingomyelinase 2 (nSMase2), is a key molecule for skeletal development as well as for the cytodifferentiation of odontoblasts and alveolar bone. However, the effects of nSMase2 on the cytodifferentiation of periodontal ligament (PDL) cells are still unclear. In this study, the authors analyzed the effects of Smpd3 on the cytodifferentiation of human PDL (HPDL) cells. The authors found that Smpd3 increases the mRNA expression of calcification-related genes, such as alkaline phosphatase (ALPase), type I collagen, osteopontin, Osterix (Osx), and runt-related transcription factor (Runx)-2 in HPDL cells. In contrast, GW4869, an inhibitor of nSMase2, clearly decreased the mRNA expression of ALPase, type I collagen, and osteocalcin in HPDL cells, suggesting that Smpd3 enhances HPDL cytodifferentiation. Next, the authors used exome sequencing to evaluate the genetic variants of Smpd3 in a Japanese population with aggressive periodontitis (AgP). Among 44 unrelated subjects, the authors identified a single nucleotide polymorphism (SNP), rs145616324, in Smpd3 as a putative genetic variant for AgP among Japanese people. Moreover, Smpd3 harboring this SNP did not increase the sphingomyelinase activity or mRNA expression of ALPase, type I collagen, osteopontin, Osx, or Runx2, suggesting that this SNP inhibits Smpd3 such that it has no effect on the cytodifferentiation of HPDL cells. These data suggest that Smpd3 plays a crucial role in maintaining the homeostasis of PDL tissue.

Genes associated with the progression of neurofibrillary tangles in Alzheimer's disease.

The spreading of neurofibrillary tangles (NFTs), intraneuronal aggregates of highly phosphorylated microtubule-associated protein tau, across the human brain is correlated with the cognitive severity of Alzheimer's disease (AD). To identify genes relevant to NFT expansion defined by the Braak stage, we conducted whole-genome exon array analysis with an exploratory sample set consisting of 213 human post-mortem brain tissue specimens from the entorinal, temporal and frontal cortices of 71 brain-donor subjects: Braak NFT stages 0 (N=13), I-II (N=20), III-IV (N=19) and V-VI (N=19). We identified eight genes, RELN, PTGS2, MYO5C, TRIL, DCHS2, GRB14, NPAS4 and PHYHD1, associated with the Braak stage. The expression levels of three genes, PHYHD1, MYO5C and GRB14, exhibited reproducible association on real-time quantitative PCR analysis. In another sample set, including control subjects (N=30), and in patients with late-onset AD (N=37), dementia with Lewy bodies (N=17) and Parkinson disease (N=36), the expression levels of two genes, PHYHD1 and MYO5C, were obviously associated with late-onset AD. Protein-protein interaction network analysis with a public database revealed that PHYHD1 interacts with MYO5C via POT1, and PHYHD1 directly interacts with amyloid beta-peptide 42. It is thus likely that functional failure of PHYHD1 and MYO5C could lead to AD development.

Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis.

MOTIVATION: A major issue in computational biology is the reconstruction of pathways from several genomic datasets, such as expression data, protein interaction data and phylogenetic profiles. As a first step toward this goal, it is important to investigate the amount of correlation which exists between these data. RESULTS: These methods are successfully tested on their ability to recognize operons in the Escherichia coli genome, from the comparison of three datasets corresponding to functional relationships between genes in metabolic pathways, geometrical relationships along the chromosome, and co-expression relationships as observed by gene expression data.

Effect of Helicobacter pylori eradication on gastric mucosal phospholipid content and its fatty acid composition.

BACKGROUND AND AIMS: Whether Helicobacter pylori eradication alters gastric mucosal phospholipid contents and their fatty acid composition remains unclear. The aim of the present study was to clarify the effect of H. pylori eradication on gastric mucosal phosphatidylcholine (PC) content and its fatty acid composition. METHODS: Endoscopic biopsy specimens were taken from the antrum and body of each of 19 asymtomatic male volunteers for detection of H. pylori, histopathological assessment of gastritis, phospholipid determination and fatty acid analysis. All the subjects with H. pylori infection were treated with eradication therapy. Endoscopy and tissue sampling were repeated again 1 and 6 months after all treatment. RESULTS: In eight subjects, H. pylori infection was evident and was successfully eradicated. Pretreatment degrees of lymphocytes and plasma cells (inflammation) and polymorphonuclear neutrophils (activity) were greater in H. pylori-positive subjects compared with H. pylori-negative subjects (P<0.001), whereas the degree of inflammation decreased (P<0.001), and neutrophils had completely disappeared at 6 months after eradication. Moreover, the gastric mucosal PC contents at the antrum and body were unchanged within 1 month after cessation of treatment, but increased at 6 months after eradication (P<0.05). At 6 months after cessation of treatment, H. pylori-eradicated subjects had an increase (+30% at antrum, +18% at body) in linoleic acid composition and a decrease (-37%, -43%) in arachidonic acid composition of PC at the antrum and body, respectively. CONCLUSIONS: These findings suggest that H. pylori eradication reduces the production of various eicosanoids, resulting in the normalization of gastric mucosal PC content and its fatty acid composition, which may consequently cause the gastric mucosal hydrophobicity to be normalized.

Helicobacter pylori alters n-6 fatty acid metabolism and prostaglandin E2 synthesis in rat gastric mucosal cells.

BACKGROUND AND AIMS: Little is known about whether Helicobacter pylori infection alters fatty acid metabolism in gastric mucosal cells. By using cultured rat gastric mucosal cells (RGM-1), we investigated the effect of H. pylori broth culture filtrates on this point. Furthermore, our study aimed to find out whether n-6 long chain polyunsaturated fatty acids from linoleic acid are formed in RGM-1 cells. METHODS: Rat gastric mucosal cells were incubated with 10, 20 and 40 microg/mL of linoleic acid or medium alone. Phosphatidylcholine content extracted from whole RGM-1 cells was quantitated by using a densitometer, and its fatty acid composition was analyzed by using gas chromatography. Prostaglandin E2 concentration in the culture medium was measured by using radioimmunoassay. The expression of cyclooxygenase (COX)-1 and COX-2 was examined by using reverse transcription-polymerase chain reaction. In addition, after incubation with [1-14C] linoleic acid, radioactivities of both linoleic acid and arachidonic acid components of the PC fraction were counted. The effects of H. pylori broth culture filtrates on PC content, its fatty acid composition and prostaglandin (PG)E2 synthesis were also assessed. RESULTS: Linoleic acid addition caused an increase in the composition of arachidonic acid, as well as linoleic acid, and also in PGE2 concentration. Cyclo-oxygenase-2 expression was induced in RGM-1 cells by the addition of linoleic acid. In addition, [1-14C] linoleic acid added to the culture medium was converted to [1-14C] arachidonic acid in RGM-1 cells. Helicobacter pylori broth culture filtrates decreased linoleic acid composition and increased arachidonic acid composition. Moreover, after incubation with H. pylori broth culture filtrates, PGE2 concentrations were higher than that of the controls. CONCLUSIONS: These findings suggest the presence of fatty acid elongase and Delta5- and Delta6-desaturases synthesize arachidonic acid from linoleic acid in RGM-1 cells. Thus, H. pylori infection may enhance PGE2 synthesis and accelerate n-6 fatty acid metabolism in gastric mucosal cells, which could make the gastric mucosal barrier more fragile.

Extraction of correlated gene clusters by multiple graph comparison.

This paper presents a new method to extract a set of correlated genes with respect to multiple biological features. Relationships among genes on a specific feature are encoded as a graph structure whose nodes correspond to genes. For example, the genome is a graph representing positional correlations of genes on the chromosome, the pathway is a graph representing functional correlations of gene products, and the expression profile is a graph representing gene expression similarities. When a set of genes are localized in a single graph, such as a gene cluster on the chromosome, an enzyme cluster in the metabolic pathway, or a set of coexpressed genes in the microarray gene expression profile, this may suggest a functional link among those genes. The functional link would become stronger when the clusters are correlated; namely, when a set of corresponding genes form clusters in multiple graphs. The newly introduced heuristic algorithm extracts such correlated gene clusters as isomorphic subgraphs in multiple graphs by using inter-graph links that are defined based on biological relevance. Using the method, we found E.coli correlated gene clusters in which genes are related with respect to the positions in the genome and the metabolic pathway, as well as the 3D structural similarity. We also analyzed protein-protein interaction data by two-hybrid experiments and gene coexpression data by microarrays in S.cerevisiae, and estimated the possibility of utilizing our method for screening the datasets that are likely to contain many false positive relations.

Mining the quantitative trait loci associated with oral glucose tolerance in the OLETF rat.

Although the synergetic effects of multiple marker loci regarding quantitative traits such as blood glucose level have attracted interest, previous conclusions have been based on assumptions that each marker locus behaves independently of the other, leading to approximation. To cope with this problem, this paper focuses on the effects of multiple genetic factors and tries to find significant marker combinations by using conjunctive rules regarding genotypes at multiple marker loci. Application of the proposed method on the OLETF model rat of non-insulin dependent diabetes mellitus (NIDDM) has found significant combinations of marker loci with respect to oral glucose tolerance (OGT).

[Home medical care from our hospital].

From April, 1996 to March, 1999, our hospital provided home medical care on a 24-hour basis for fifty patients with advanced or terminal cancer. Eventually, twenty-four patients died at home and twenty-six in the hospital. Stability of health status, the presence of willing and able caregivers, as well as a greater number of house-calls are suggested factors in facilitating a death at home. However, the patients who died in the hospital were obliged to readmit themselves until the time of death due to caregivers' reasons such as fatigue, emotional stress and/or health problems. In addition to timely availability and accessibility of respite care, psychosocial support for family caregivers by liaison nurses remains an issue to be solved in future.

Tracing Synergetic Behavior of the QTLs Affecting Oral Glucose Tolerance in the OLETF Rat.

The synergetic effects of multiple marker loci regarding quantitative traits such as blood glucose level have attracted interest. In the OLETF model rat of non-insulin dependent diabetes mellitus (NIDDM), our previous study focusing on the effects of multiple genetic factors has found significant marker combinations with respect to oral glucose tolerance (OGT) at 60 minutes after oral administration. Besides the interaction among markers at a particular time point, their correlated behavior in a time series is another interest. Based on the previous results, in this paper, we report the behavior of markers in a time series by using a series of measurements of OGT.

Effect of Helicobacter pylori infection on gastric mucosal phospholipid contents and their fatty acid composition.

To investigate the effect of Helicobacter pylori infection on the 'gastric mucosal barrier', phospholipid contents and the fatty acid composition of endoscopic biopsy specimens of the gastric mucosa were analysed in healthy volunteers with and without H. pylori infection. The gastric corporeal phosphatidylcholine (PC) content of H. pylori-positive healthy volunteers was less than that of H. pylori-negative healthy volunteers (P < 0.05). Moreover, H. pylori-positive healthy volunteers had a decrease in linoleic acid composition (P < 0.0001) and an increase in arachidonic acid composition (P < 0.0001) and in the arachidonic acid/linoleic acid ratio (P < 0.0001) of antral and corporeal PC compared with H. pylori-negative healthy volunteers. These findings suggest that H. pylori infection enhances production of various eicosanoids, resulting in changes in the gastric mucosal phospholipid contents and their fatty acid composition, that may consequently cause the gastric mucosal barrier to be weakened.

Classification of RNA secondary structures using the techniques of cluster analysis.

An RNA molecule has a lot of suboptimal secondary structures. Some of these suboptimal structures are very similar and some are entirely different. In some cases, the free energy of these suboptimal structures does not differ much from that of the optimal structure. In order to characterize this relationship more clearly, we defined a metric among the secondary structures by the unweighted pair group method, using the arithmetic average and extended this metric to the sets of secondary structures. We report two applications of this metric. First, we developed a method for the classification of these suboptimal secondary structures of a given RNA sequence. Results of classification are presented with the secondary structures of cadang-cadang coconut viroid, potato spindle tuber viroid and polio virus as examples. Second, we applied this metric to the classification of the secondary structures derived from a set of mutant RNA sequences. We discuss that the mutation of a given RNA sequence changes not only the optimal secondary structure, but also the population of the cluster of the secondary structures.

Visualization of RNA secondary structures using highly parallel computers.

Results of RNA secondary structure prediction algorithm are usually given as a set of hydrogen bonds between bases. However, we cannot know the precise structure of an RNA molecule by only knowing which bases form hydrogen bonds. One way to understand the structure of an RNA molecule is to visualize it using a planar graph so that we can easily know the geometric relations among the substructures such as stacking regions and loops. To do this, we consider bases to be particles on a plane and introduce a repulsive force and an attractive force among these particles and determine their positions according to these forces. A naive algorithm requires O(N2) time but we can reduce it to O(NlogN) with an approximation algorithm which is often used in the area of N-body simulation. Our program is written in parallel object-oriented language 'Schematic' which is recently developed. Efficiency of our implementation on a parallel computer and results of visualization of secondary structures are presented using cadang-cadang coconut viroid as an example.

RNA secondary structure prediction using highly parallel computers.

An RNA secondary structure prediction method using a highly parallel computer is reported. We focus on finding thermodynamically stable structures of a single-stranded RNA molecule. Our approach is based on a parallel combinatorial method which calculates the free energy of a molecule as the sum of the free energies of all the physically possible hydrogen bonds. Our parallel algorithm finds many highly stable structures all at once, while most of the conventional prediction methods find only the most stable structure. The important idea in our algorithm is search tree pruning, with dynamic load balancing across the processor elements in a parallel computer. Software tools for visualization and classification of secondary structures are also presented using the sequence of cadang-cadang coconut viroid as an example. Our software system runs on CM-5.