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Cheng et al. 2511 Figure 4. Significant molecular network of APS LD related genes. Genes or gene products are represented as nodes, and the biological relationship between two nodes is represented as a line. Note that the colored symbols represent gene entries that occur in our data, while the transparent entries are molecules from the Ingenuity knowledge database. Red symbols represent up-regulate genes, green symbols represent down-regulate genes. Solid lines between molecules indicate direct physical relationship between molecules; dotted lines indicate indirect functional relationships. The DEAD box RNA helicase Ddx17 plays important roles in multiple cellular processes, including transcription, pre-mRNA processing/alternative splicing, and miRNA processing, which are commonly dysregulated in cancers (Fuller-Pace and Moore, 2011). Blocking Ddx17 acetylation caused cell cycle arrest and apoptosis, revealing an essential role for Ddx17 acetylation (Mooney et al., 2010). The ability of Ddx17 suggests that transcriptional regulation in cancer were at work not only in the up-regulated genes but also in the down-regulated genes. In addition, the Arl6ip2 gene found to be down-regulated in APS-treated groups has been reported in U937 cells exposed to various NO fluxes (Turpaev et al., 2010). However, with few studies of the gene, its relationship with the activity of APS remains unclear. Future studies are needed to test the exact efficacy of interventions that specifically address the processes suggested by the present gene expression studies. Many of the genes uniquely induced by APS HD or APS LD represented functional families of genes. In the APS HD group, the expressions of Cdc27 and Zc3h10 were induced. In the APS LD group, the expressions of Tubd1 and Fosl2 were modulated. The literature implies that phosphorylation of Cdc27 is involved in TGF-βinduced activation of APC (Zhang et al., 2011), and it is suggested that Cdc27 itself may be a tumor suppressor (Pawar et al., 2010). Zc3h10 inhibits anchorageindependent growth in soft agar, suggesting a tumor suppressor function for this gene (Guardiola-Serrano et al., 2008). The candidate oncogene Tubd1 is associated with breast cancer risk (Kelemen et al., 2009). Fosl2 is a member of the Fos family of AP-1 transcription factors that is often up-regulated in mammary carcinomas. Fosl2
2512 J. Med. Plants Res. over-expression is associated with a more aggressive tumor phenotype and is probably involved in breast cancer progression in vivo (Milde-Langosch et al., 2008). Interestingly, these 4 unique genes again show the ability to regulate cancer development and progression, a function similar to that of the genes previously mentioned. In addition, Hmgcr, a unique gene affected by APS HD which converts HMG-CoA to mevalonate and catalyzes the rate-limiting step in cholesterol biosynthesis (Ohashi et al., 2003), and upstream stimulatory factor Usf2, a unique gene affected by APS LD which regulates the transcription of genes related to immune response, the cell cycle, and cell proliferation (Bussiere et al., 2010) are needed for further exploration on the association between APS and the activities. The IPA results showed that the main functionalities for the networks of APS are antigen presentation, cellular development, cell cycle, RNA damage and repair, protein synthesis, cellular growth and proliferation. While the unique pathways in the network of APS LD include lipid metabolism, molecular transport, small molecule biochemistry, and the pathways for APS HD are cell morphology, cellular function and maintenance, cellmediated immune response. Antigen presentation is the key process for immune response, and it is closely related to RA development (Lebre and Tak, 2009; Wenink et al., 2009; Yanaba et al., 2008). Cell cycle, cellular growth and proliferation, and apoptosis are considered the vital components of various processes including cell turnover, proper development and functioning of the immune system, hormone-dependent atrophy, embryonic development and chemical-induced cell death related to RA pathogenesis (Elmore, 2007; Jiang et al., 2010b; Ryu et al., 2010). APS might demonstrate its pharmacological activity via acting on these pathways. However, the differences between the low dosage and high dosage of APS are still waiting for further validation, though there are evidence demonstrating the correlation between lipid metabolism, cell mediated immune response and RA development (Hansel and Bruckert, 2010; Toms et al., 2010). The results further support the findings in DAVID analysis. Though the data presented provides a more comprehensive picture on how APS mediates biological effects on IELs, there is a limitation in this study. RT-PCR did not be conducted for verification. However the clusters of genes and pathway networks are the main purpose to demonstrate the complicated biological networks induced by APS in the mice, and singe gene verification is hard to meet the requirement. Future pharmacological studies are needed to test the efficacy of APS interventions which specifically address the processes suggested by our microarray analysis. Conclusions 2310079N02Rik, C030015A19Rik, Rnf139, Anapc1, Fbxo3, Cpd, Derl2, Ddx17, Arl6ip2 and the related pathways may be modulated by APS on IELs, and APS might play critical in transcriptional regulations of cancer. ACKNOWLEDGMENTS This research is supported in part by the projects from Ministry of Sciences and Technology of China (No. 2009ZX09502-019), National Science Foundation of China, No. 30825047, 30902000, 81001676 and 81001623, E-institutes of Shanghai Municipal Education Commission No E03008, and Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences No. KL1004. REFERENCES Abruzzo GK, Gill CJ, Flattery AM, Kong L, Leighton C, Smith JG, Pikounis VB, Bartizal K, Rosen H (2000). Efficacy of the echinocandin caspofungin against disseminated aspergillosis and candidiasis in cyclophosphamide-induced immunosuppressed mice. Antimicrob. Agents Chemother., 44: 2310-2318. Bussiere FI, Michel V, Memet S, Ave P, Vivas JR, Huerre M,Touati E (2010). H. pylori-induced promoter hypermethylation downregulates USF1 and USF2 transcription factor gene expression. Cell. Microbiol., 12: 1124-1133. Cha JD, Kim HJ, Cha IH (2011). Genetic alterations in oral squamous cell carcinoma progression detected by combining array-based comparative genomic hybridization and multiplex ligation-dependent probe amplification. Oral. Surg. Oral. Med. Oral. Pathol. Oral. Radiol. Endod., 111: 594-607. Cheroutre H, Lambolez F, Mucida D (2011). The light and dark sides of intestinal intraepithelial lymphocytes. Nat. Rev. Immunol., 11: 445- 456. Cho YS, Iguchi N, Yang J, Handel MA, Hecht NB (2005). Meiotic messenger RNA and noncoding RNA targets of the RNA-binding protein Translin (TSN) in mouse testis. Biol. Reprod., 73: 840-847. Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA (2003). DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol., 4: 3. Elmore S (2007). Apoptosis: A review of programmed cell death. Toxicol. Pathol., 35: 495-516. Fang TH, Lien YY, Cheng MC, Tsai HJ (2006). Resistance of immunesuppressed pigeons to subtypes H5N2 and H6N1 low pathogenic avian influenza virus. Avian. Dis., 50: 269-272. Fleet JC (2007). Using genomics to understand intestinal biology. J. Physiol. Biochem., 63: 83-96. Fong CJ, Burgoon LD, Williams KJ, Forgacs AL, Zacharewski TR (2007). Comparative temporal and dose-dependent morphological and transcriptional uterine effects elicited by tamoxifen and ethynylestradiol in immature, ovariectomized mice. BMC Genomics, 8: 151. Fuller-Pace FV, Moore HC (2011). RNA helicases p68 and p72: multifunctional proteins with important implications for cancer development. Future Oncol., 7: 239-251. Gemmill RM, Bemis LT, Lee JP, Sozen MA, Baron A, Zeng C, Erickson PF, Hooper JE, Drabkin HA (2002). The TRC8 hereditary kidney cancer gene suppresses growth and functions with VHL in a common pathway. Oncogene, 21: 3507-3516. Git A, Dvinge H, Salmon-Divon M, Osborne M, Kutter C, Hadfield J, Bertone P, Caldas C (2010). Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression. RNA, 16: 991-1006.
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Journal of Medicinal Plants Researc
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Editors Prof. Akah Peter Achunike E
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Electronic submission of manuscript
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Fees and Charges: Authors are requi
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Table of Contents: Volume 6 Number
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Figure 1. Chuanxiong Rhizoma (http:
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Table 1. Identification of main pea
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Table 3. Pharmacokinetic parameters
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active component study, many invest
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and 1185 kg ha -1 in the first site
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Table 1. Recommendation for use fer
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Sadanandan AK, Hamza S (1996c). Stu
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and it has been traced to South Ame
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Table 3. Results of phytochemical a
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(a) (b) (c) Figure 1. (a) Normal ce
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emedies in the south of Brazil. J.
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known fatty acids and terpenoids we
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Table 1. Renal function tests of ra
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Al-Radahe et al. 2271 Figure 3.nnnn
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namely disruption of the vascular e
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Zayachkivska OS, Konturek SJ, Drozd
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β-carotene were purchased from Sig
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Figure 1. Effect of ethanol concent
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Table 3. Climatic and soil factors
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content of polysaccharides. Phospha
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Serge et al. 2285 Table 1. Relative
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Percentage inhibition % of inhibiti
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Table 1. Result of phytochemical sc
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Table 3. Result of thin layer chrom
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Table 2. MIC of a compound 1 from c
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Zirihi et al. 2301 Figure 2. Termin
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Figure 5. T. catappa Linn. (Combret
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Figure 8. A. fumigatus: Aspect of c
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Figure 12. Sensitivity of A. fumiga
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Noormi et al. 2311 Table 1. Callus
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Table 2. Contd. NoC=No callus. 4.0
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Figure 2. Contd. at 2.0 mg/L yellow
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Table 1. Biochemical parameters in
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Figure 3. Bcl-xL reactions in inter
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ACKNOWLEDGMENTS The authors would l
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Figure 1. The first page of the boo
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Figure 3. The most widely included
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Figure 4. Lithographic print “St.
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Table 1. List of plants included in
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Table 1. Contd. Nedelcheva 2333 Cin
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Table 1. Contd. Nedelcheva 2335 Rhe
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14 7 1 15 1 35 17 16 Imported plant
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Academy of Science Publishing House
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et al., 1996; van Wyk and Gericke,
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DPPH inhibition (%) DPPH % inhibiti
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% Mortality Concentration (µg/ml)
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information on plants used for the
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Table 1. Levels of independent vari
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Arbutin (mg/g) Co-solvent Figure 1.
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Arbutin (mg/g) Extraction pressure
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Table 3. Arbuitn content of Asian p
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Arbutin (mg/g) Extraction pressure
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Arbutin (mg/g) Extraction temperatu
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Table 1. Chemical composition of es
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Darjazi 2369 Table 2. Statistical a
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Table 3. Correlation matrix (number
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Table 1. Precision test. extraction
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Figure 2. Effect of different alcoh
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Table 6. Results of ANOVA. Nie et a
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Table 2. Plant data and MIC values
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exhibiting the polar extracts of P.
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Table 3. Contd. AcOEt ++ ++ ++ - Me
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Figure 1. Map of Ladakh region of I
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Warghat et al. 2391 Table 3. Summar
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Table 5. Inter-Population genetic i
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Excoffier L, Smouse PE, Quattro JM
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ice residue is an ideal raw materia
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DPPH• scavenging ratio(%) OD valu
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scavenging effect on free radical a
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our new CL system. Fenton reaction
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1 2 Time (s) Figure 2. Kinetic curv
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Wong et al., 2006). It can be seen
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Pan YM, Liang Y, Wang HS, Liang M (
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