Constantly expressed genes are used as internal controls in relative quantification studies. Suitable internal controls for such studies have not yet been defined for Pseudomonas aeruginosa. In this study, the genes ampC, fabD, proC, pbp-2, rpoD and rpoS of P. aeruginosa were compared in terms of expression stability by real-time quantitative RT-PCR. A total of 23 strains with diverse resistance phenotypes were studied. Stability of expression among the housekeeping genes was assessed on the basis of correlation coefficients, with the best-correlated pair accepted as being the most stable one. Eventually, proC and rpoD formed the most stable pair (r ¼ 0·958; P , 0·001). Next, in four ciprofloxacin-selected nfxC-like mutants, levels of oprD, oprM and oprN mRNA were compared with those of their wild-type counterparts. The comparison was made after correcting the raw values by the geometric mean of the internal control genes proC and rpoD. The level of oprN mRNA was significantly up-regulated, while the oprD gene was down-regulated (although this difference was statistically insignificant), in the mutants. This expression pattern was consistent with that of the expected expression profile of nfxC-type mutants; this experiment therefore lends further support to the use of proC and rpoD genes simultaneously as internal controls for such studies.

Agomelatine, a novel antidepressant with established clinical efficacy, acts as an agonist of melatonergic MT1 and MT2 receptors and as an antagonist of 5-HT2C receptors. The present study was undertaken to investigate whether chronic treatment with agomelatine would block unpredictable chronic mild stress (UCMS)-induced cognitive deterioration in mice in passive avoidance (PA), modified elevated plus maze (mEPM), novel object recognition (NOR), and Morris water maze (MWM) tests. Moreover, the effects of stress and agomelatine on brain-derived neurotrophic factor (BDNF) and cyclic adenosine monophosphate (cAMP) response element binding protein (CREB) messenger ribonucleic acid (mRNA) levels in the hippocampus was also determined using quantitative real-time polymerase chain reaction (RT-PCR). Male inbred BALB/c mice were treated with agomelatine (10 mg/kg, i.p.), melatonin (10 mg/kg), or vehicle daily for five weeks. The results of this study revealed that UCMS-exposed animals exhibited memory deterioration in the PA, mEPM, NOR, and MWM tests. The chronic administration of melatonin had a positive effect in the PA and +mEPM tests, whereas agomelatine had a partial effect. Both agomelatine and melatonin blocked stress-induced impairment in visual memory in the NOR test and reversed spatial learning and memory impairment in the stressed group in the MWM test. Quantitative RT-PCR revealed that CREB and BDNF gene expression levels were downregulated in UCMS-exposed mice, and these alterations were reversed by chronic agomelatine or melatonin treatment. Thus, agomelatine plays an important role in blocking stress-induced hippocampal memory deterioration and activates molecular mechanisms of memory storage in response to a learning experience.

Summary. The alterations in gene expression associated with 1,25(OH) 2 D 3 -induced differentiation of HL-60 cells were studied in order to identify potential targets for further investigation of the genetic basis of acute myeloid leukaemia. Atlas human haematology filters, including 406 genes (Clontech), were used to study gene expression in response to 1,25(OH) 2 D 3 (concentration, 5 · 10 )8 mol/l) for 24 and 72 h. Compared with untreated cells, expression differences were found in 43 genes. Downregulated genes at both time-points were: IL2RA, CMYC, NPM, DEK, AF4, FLI1, HTLF, MNDA, BCR, IKAROS, BPI and NFAT4. Upregulated genes at both time-points were IL1B, CD14 and MCL1. CD55, CD58, IRF2, CREB1, ATF4, RAC1, TIAR, KIAA0053, BAT2, BTK, RCK, EV12B and EDN were downregulated at 24 h, while SPI1, MKK3, BTG1 and IL8were upregulated. At 72 h the upregulated genes were IL1RA, IL2RG, CXCR4, SCYA1, SCYA3, SCYA4, SCYA5, SCYA22, ANX2, CD83 and UPAR. cDNA array results were confirmed on randomly selected genes using quantitative real-time polymerase chain reaction for three upregulated (CXCR4, IL1B and CD14) and three downregulated (DEK, AF4 and FLI1) genes. Gene expression analysis after differentiation induction may provide a tool to study the roles of DEK, AF4 and FLI1 in cell proliferation and differentiation. To demonstrate the genes that initiate differentiation, sequential gene expression analysis has to be performed during the first 24 h of the differentiation process.

The molecular mechanism playing a role in the development of prostate cancer (PCA) is not well defined. We decided to determine the changes in gene expression in PCA tissues and to compare them to those in noncancerous samples. Prostate tissue samples were collected by needle biopsy from 21 PCA and 10 benign prostate hyperplasic (BPH) patients. Total RNA was isolated, cDNA was synthesized, and gene expression levels were determined by microarray method. In the progression to PCA, 738 up-regulated and 515 downregulated genes were detected in samples. Analysis using Ingenuity Pathway Analysis (IPA) software revealed that 466 network and 423 functions-pathways eligible genes were up-regulated, and 363 network and 342 functions-pathways eligible genes were down-regulated. Up-regulated networks were identified around IL-1β and insulin-like growth factor-1 (IGF-1) genes. The NFKB gene was centered around two upand down-regulated networks. Up-regulated canonical pathways were assigned and four of them were evaluated in detail: acute phase response, hepatic fibrosis, actin cytoskeleton, and coagulation pathways.Axonal guidance signaling was the most significant down-regulated canonical pathway. Our data provide not only networks between the genes for understanding the biologic properties of PCA but also useful pathway maps for future understanding of disease and the construction of new therapeutic targets.

Functions of the identified genes that were involved in gene networks were cellular development, cell growth and proliferation, cellular movement, cell-cell signaling and interaction, humoral immune response, protein synthesis, cell death and survival, cell population and organization, organismal injury and abnormalities, molecular transport, and small-molecule biochemistry. The data suggest new networks that have important functions as humoral immune response and organismal injury/abnormalities. Future analyses may facilitate proteomic profiling analyses to identify gene-expression patterns related to clinical outcome.

Breast cancer is the most common cancer among women and accounts for 23% of all female types of cancers. It is well recognized that breast cancer represents a heterogeneous group of tumors, and the molecular events involved in the progression to cancer remain undetermined. Moreover, available prognostic and predictive markers are not sufficient for the accurate determination of the risk for many breast cancer patients. Thus, it is necessary to discover new molecular markers for accurate prediction of clinical outcome and individualized therapy. In the present study, we performed omics-based whole-genome trancriptomic and whole proteomic profiling with network and pathway analyses of breast tumors to identify gene expression patterns related to clinical outcome. A total of 20 samples from tumors and 14 normal appearing breast tissues were analyzed using both gene expression microarrays and LC-MS/MS. We identified 585 downregulated and 413 upregulated genes by gene expression microarrays. Among these genes, HPX, POTEE and ApoA1 were the most significant genes correlated with the proteomic profile. Our data revealed that these identified genes are closely related to breast cancer and may be involved in robust detection of disease progression.

Investigation of the relation between MEFV gene mutations and clinical findings of Behçet's disease. Genetic features of 100 patients with Behçet's disease (BD) and 100 healthy controls were analyzed. None of the individuals had a family history of FMF in the patient and control group, and none of the individuals in the control group had a family history of BD. MEFV gene analysis was performed in all the patients with BD and healthy controls; twelve different regions were scanned. In the BD group, mutations were detected in more than one region in 27 patients (27%). Twenty-five patients had heterozygous and two patients had compound heterozygous mutations (M680I-V726A and M694 V-A744S). The most frequent mutation was M694 V with an allelic frequency of 5%. The allelic frequencies of E148Q, M680I (G/C), and V726A were 3, 2, and 2%, respectively. The allelic frequencies of P369S, A744S, and K695R were 1, 1, and 0.5%. MEFV gene analysis revealed mutations in 27 (27%) of the individuals in the control group; the allelic frequency was 14%. The most frequent mutation was E148Q that was detected in 16 individuals. One individual was compound heterozygote (E148Q-M694 V). The allelic frequencies of E148Q, M694 V, V726A, and M680I were 8, 3, 1.5, and 0.5%, respectively. The allelic frequencies of K695R and P369S were 0.5 and 0.5%, respectively. The allelic frequency was similar in the two groups. There was not a significant relation between the mutations in the BD group and clinical findings.

Background:To elucidate molecular signatures of chronic periodontitis (CP) using gingival tissue samples through omics-based whole-genome transcriptomic and whole protein profiling.Methods: Gingival tissues from 18 CP and 25 controls were analyzed using gene expression microarrays to identify gene expression patterns and the proteins isolated from these samples were subjected to comparative proteomic analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data from transcriptomics and proteomics were integrated to reveal common shared genes and proteins. Results:The most upregulated genes in CP compared with controls were found as MZB1, BMS1P20, IGLL1/IGLL5, TNFRSF17, ALDH1A1, KIAA0125, MMP7, PRL, MGC16025, ADAM11, and the most upregulated proteins in CP compared with controls were BPI, ITGAM, CAP37, PCM1, MMP-9, MZB1, UGTT1, PLG, RAB1B, HSP90B1. Functions of the identified genes were involved cell death/survival, DNA replication, recombination/repair, gene expression, organismal development, cell-tocell signaling/interaction, cellular development, cellular growth/proliferation, cellular assembly/organization, cellular function/maintenance, cellular movement, B-cell development, and identified proteins were involved in protein folding, response to stress, single-organism catabolic process, regulation of peptidase activity, and negative regulation of cell death. The integration and validation analysis of the transcriptomics and proteomics data revealed two common shared genes and proteins, MZB1 and ECH1. Conclusion:Integrative data from transcriptomics and proteomics revealed MZB1 as a potent candidate for chronic periodontitis.