Comprehensive DNA microarray expression profiles of tumors in tenascin-C-knockout mice

Tenascin-C (TNC), an extracellular matrix glycoprotein, plays a pivotal role in tumor growth. However, the mechanism whereby TNC affects tumor biology remains unclear. To investigate the exact role of TNC in primary tumor growth, a mouse mammary tumor cell line, GLMT1, was first developed. Subsequently, global gene expression in GLMT1-derived tumors was compared between wild-type (WT) and TNC-knockout (TNKO) mice. Tumors in WT mice were significantly larger than those in TNKO mice. DNA microarray analysis revealed 447 up and 667 downregulated in the tumors inoculated into TNKO mice as compared to tumors in WT mice. Validation by quantitative gene expression analysis showed that Tnc, Cxcl1, Cxcl2, and Cxcr2 were significantly upregulated in WT mice. We hypothesize that TNC stimulates the CXCL1/2-CXCR2 pathway involved in cancer cell proliferation.     

Bioisostere of valtrate,anti-HIV principle by inhibition for nuclear export of Rev

Rational design by the MO calculation disclosed 5,6-dihydrovaltrate (2) as the bioisostere of valtrate (1), the Rev-export inhibitor with anti-HIV activity. The synthesis of 2 was accomplished by ingenious use of asymmetric Diels–Alder reaction and stereoselective epoxidation associated with the adjacent hydroxyl group. Because of similar biological potency to 1, the analog 2 should be recognized as a promising scaffold for new anti-HIV agents with an unprecedented mechanism of action, inhibition for nuclear export of Rev protein, in the conventional remedy.     

Introduction of amino acid residues at the N-terminus of the zeocin-resistance protein increases its expression in Saccharomyces cerevisiae

Nucleotide sequences proximal to the initiation codon of a gene are known to affect the expression efficiency of that gene. We screened 10-bp random sequences upstream of the initiation codon of the zeocin-resistance gene to identify sequences that could enhance its expression in Saccharomyces cerevisiae. Of the isolated sequences, 20 sequences exhibited a common feature, i.e. ATG at the position −9 through −7, which resulted in the incorporation of three amino acids at the N-terminus of the protein. The introduction of these sequences upstream of the initiation codon increased the expression levels of zeocin-resistance protein by 2.2–6.5-fold. One of these sequences increased the expression levels of three out of four human proteins, thereby suggesting that this sequence may also enhance the expression efficiency of mammalian proteins in yeast.     

Epitope analysis of lipid A preparations from Pseudomonas diminuta and Pseudomonas vesicularis

Abstract In vitro antigenic reactivity of lipid A from Pseudomonas diminuta and Pseudomonas vesicularis with homologous and heterologous lipid A antibodies including monoclonal antibodies was studied by inhibition test of enzyme-linked immunosorbent assay (ELISA). The results suggest that both Pseudomonas lipid As have very similar epitopes, including species-specific and cross-reactive epitopes as compared with enterobacterial lipid A.     

Effect of emigration on cannibalism and intraguild predation in aphidophagous ladybirds

Abstract.  1. The incidence and timing of emigration, cannibalism, and intraguild predation of larvae of three aphidophagous ladybirds (Coleoptera: Coccinellidae), Harmonia axyridis Pallas, Coccinella septempunctata brucki Mulsant, and Propylea japonica Mulsant, relative to the presence of prey was determined in the laboratory in single- and mixed-species populations.
2. In single-species populations, 80% of the larvae of C. s. brucki emigrated prior to the extinction of the aphid population and no larvae were lost due to cannibalism; however > 80% of the larvae of the other two species were still present when the aphid became extinct and the losses due to cannibalism for H. axyridis and P. japonica were 25% and 14% respectively. Finally, 28% of the P. japonica larvae completed their development, whereas no larvae of the other two species became adult.
3. In mixed-species populations, mortality of P. japonica attributable to cannibalism or intraguild predation increased greatly to 60%, whereas that of the other two species remained about the same. Consequently, survival of H. axyridis larvae improved and survival of P. japonica worsened; however the survival of C. s. brucki larvae was not affected by the other two species. Early emigration by C. s. brucki larvae may have enabled them to escape intraguild predation by H. axyridis in this system.     

Recursive Random Lasso (RRLasso) for Identifying Anti-Cancer Drug Targets

Uncovering driver genes is crucial for understanding heterogeneity in cancer. L ₁-type regularization approaches have been widely used for uncovering cancer driver genes based on genome-scale data. Although the existing methods have been widely applied in the field of bioinformatics, they possess several drawbacks: subset size limitations, erroneous estimation results, multicollinearity, and heavy time consumption. We introduce a novel statistical strategy, called a Recursive Random Lasso (RRLasso), for high dimensional genomic data analysis and investigation of driver genes. For time-effective analysis, we consider a recursive bootstrap procedure in line with the random lasso. Furthermore, we introduce a parametric statistical test for driver gene selection based on bootstrap regression modeling results. The proposed RRLasso is not only rapid but performs well for high dimensional genomic data analysis. Monte Carlo simulations and analysis of the “Sanger Genomics of Drug Sensitivity in Cancer dataset from the Cancer Genome Project” show that the proposed RRLasso is an effective tool for high dimensional genomic data analysis. The proposed methods provide reliable and biologically relevant results for cancer driver gene selection.     

Differentiation of Langerhans Cells from Interdigitating Cells Using CD1a and S-100 Protein Antibodies

The present study shows that Langerhans cells can be differentiated from Interdigitating cells at the light microscopic level. Superficial lymph nodes and skin taken from necropsies and the lymph nodes of dermatopathic lymphadenopathy (DPL) were used for this experiment. Sections of lymph node and skin were embedded using the acetone, methyl benzoate and xylene (AMeX) method and dendritic cells were immunostained with anti S-100 protein antibody (S-100, and OKT-6 (CD1a) using the restaining method. Langerhans cells in the skin were positive for both CD1a and S-100. Dendritic cells positive for both CD1a and S-100, and dendritic cells positive for S-100, but not for CD1a were observed in superficial lymph nodes. In normal superficial lymph nodes, there were more interdigitating cells than Langerhans cells. The majority of the dendritic cells in the DPL were Langerhans cells. We conclude that the S-100 and CD1a positive cells are Langerhans cells, and the S-100 positive-CD1a negative cells are interdigitating cells.     

Robust Prediction of Anti-Cancer Drug Sensitivity and Sensitivity-Specific Biomarker

The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc.) and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.     

Stereoselective Synthesis of (S,E)-6-Isopropyl-3,9-dimethyl-5,8-decadienyl Acetate,the (S)-Enantiomer of the Yellow Scale Pheromone

The (S)-enantiomer of the sex pheromone of the yellow scale (Aonidiella citrina), (S,E)-6-isopropyl-3,9-dimethyl-5,8-decadienyl acetate, was stereoselectively synthesized from (R)-(+)-citronellic acid.