However, the mechanisms underlying TNF-α-induced cPLA2 expression in human lung epithelial cells (HPAEpiCs) were not completely understood.Cytosolic phospholipase A2 mRNA and protein expression, promoter activity, and PGE2 secretion in HPAEpiCs. These responses induced by TNF-α were inhibited by pretreatment with the inhibitor of MEK1/2 (PD98059), p38 MAPK (SB202190), JNK1/2 (SP600125), or AP-1 (Tanshinone IIA) and transfection with siRNA of TNFR1, p42, p38, JNK2, c-Jun, c-Fos, or ATF2. We showed that TNF-α markedly stimulated p42/p44 MAPK, p38 MAPK, and JNK1/2 phosphorylation which were attenuated by their respective inhibitors. In addition, TNF-α also stimulated c-Jun and ATF2 phosphorylation which were inhibited by pretreatment with SP600125 and SB202190, respectively, but not PD98059. Furthermore, TNF-α-induced cPLA2 promoter activity was abrogated by transfection with the point-mutated AP-1 cPLA2 construct. Finally, we showed that TNF-α time-dependently induced p300/c-Fos/c-Jun/ATF2 complex formation in HPAEpiCs. On the other hand, TNF-α induced in vivo binding of c-Jun, c-Fos, ATF2, and p300 to the cPLA2 promoter in these cells. In an in vivo study, we found that TNF-α induced leukocyte count in BAL fluid of mice and cPLA2 mRNA levels in lung tissues via MAPKs and AP-1.We demonstrated that TNF-α induced cPLA2 expression was mediated through p38 MAPK- and JNK1/2-dependent p300/c-Fos/c-Jun/ATF2 complex formation in HPAEpiCs.Taken together, these results demonstrated that TNF-α-induced cPLA Although cPLA2 has been shown to mediate inflammatory reactions, the detail mechanisms underlying TNF-α-induced cPLA2 expression and PGE2 synthesis in human lung epithelial cells (HPAEpiCs) were not completely understood.Lung inflammation is a pivotal event in the pathogenesis of chronic obstructive pulmonary disease (COPD) and asthma 2 induction in canine tracheal smooth muscle cells 2 release in human airway smooth muscle cells 2 expression and PGE2 synthesis in HPAEpiCs.Several extracellular stimuli elicit a broad spectrum of biological responses through activation of MAPK cascades leading to phosphorylation of specific target proteins 2 or COX-2 2 expression was also investigated in HPAEpiCs.AP-1 is a heterogeneous collection of dimeric transcription factors comprising Jun, Fos, and ATF subunits. Among AP-1 subunits, c-Jun is the most important transcriptional activator in inflammatory status 2 expression and PGE2 synthesis in HPAEpiCs. These findings suggested that in HPAEpiCs, TNF-α-induced cPLA2 expression associated with PGE2 release was, at least in part, mediated through JNK1/2- and p38 MAPK-dependent p300-AP-1 signaling pathway. These results demonstrated that MAPKs and AP-1 may be the critical components implicated in cPLA2 expression and PGE2 synthesis in TNF-α-challenged HPAEpiCs.In addressing these questions, experiments were performed to investigate the mechanisms underlying TNF-α-induced cPLA2, anti-GAPDH, anti-TNFR1, anti-p42, anti-p38, anti-JNK2, anti-c-Jun, anti-c-Fos, anti-ATF2, and anti-p300 antibodies were from Santa Cruz . Anti-phospho-p42/p44 MAPK, anti-phospho-p38 MAPK, anti-phospho-JNK1/2, anti-phospho-ATF2, and anti-phospho-c-Jun antibodies were from Cell Signaling . Actinomycin D (Act. D), cycloheximide (CHI), SP600125, PD98059, SB202190, AACOCF3, and Tanshinone IIA were from Biomol . AH 6809, SC-19220, and GW627368X were from Cayman . Other chemicals were from Sigma .Recombinant human TNF-α was from R&D System . Anti-cPLAHuman pulmonary alveolar epithelial cells  were purchased from the ScienCell Research Lab.  and grown as previously described g at 4°C for 1 h to yield the whole cell extract, as previously described 2 antibody for 24 h, and then incubated with an anti-mouse horseradish peroxidase antibody for 1 h. The immunoreactive bands were detected by ECL reagents.Growth-arrested HPAEpiCs were incubated with thrombin at 37°C for the indicated time intervals. The cells were washed, scraped, collected, and centrifuged at 45000× 2 and GAPDH mRNAs. The levels of cPLA2 expression were determined by normalizing to GAPDH expression.Total RNA was extracted using TRIzol reagent. mRNA was reverse-transcribed into cDNA and analyzed by real-time RT-PCR. Real-time PCR was performed using SYBR Green PCR reagents  and primers specific for cPLA2-luc plasmid, human cPLA2 promoter, a region spanning −2375 to +75 bp, was cloned into pGL3-basic vector . cPLA2-luc activity was determined as previously described For construction of the cPLA2 was assayed using the PGE2 enzyme immunoassay kit (Cayman) according to the manufacturer's instructions.Cells were cultured in 6-well culture plates. After reaching confluence, cells were treated with TNF-α for the indicated times. After treatment, the medium were collected and stored at −80°C until being assayed. PGEHuman siRNAs of scrambled, TNFR1, p42, p38, JNK2, c-Jun, c-Fos, and ATF2 were from Sigma . Transient transfection of siRNAs (100 nM) was performed using a Lipofectamine™ RNAiMAX reagent according to the manufacturer's instructions.2 promoter, chromatin immunoprecipitation (ChIP) analysis was conducted as previously described 2O and subjected to PCR amplification with the forward primer 5′-GAATTCAACCTGATTTCATTTTCTTCC-3′ and the reverse primer 5′-CTTCAGGCTCCTCAATGCCTCTAGCTTTCAG-3′, which were specifically designed from the cPLA2 promoter region. PCR products were analyzed on ethidium bromide-stained agarose gels (1%).To detect the association of nuclear proteins with human cPLACell lysates containing 1 mg of protein were incubated with 2 µg of an anti-p300 antibody at 4°C for 24 h, and then 10 µl of 50% protein A-agarose beads was added and mixed for 24 h at 4°C. The immunoprecipitates were collected and washed three times with a lysis buffer without Triton X-100. 5X Laemmli buffer was added and subjected to electrophoresis on SDS-PAGE, and then blotted using an anti-c-Fos, anti-c-Jun, anti-ATF2, or anti-p300 antibody.3 (2 mg/kg) for 1 h prior to TNF-α treatment, and sacrificed after 24 h.Male ICR mice aged 6–8 weeks were purchased from the National Laboratory Animal Centre  and handled according to the guidelines of Animal Care Committee of Chang Gung University approved for this study  and National Institutes of Health Guides for the Care and Use of Laboratory Animals. All treatments were performed under pentobarbital sodium anesthesia, and all efforts were made to minimize suffering. ICR mice were anesthetized with intraperieritoneal injection of 200 µl of pentobarbital sodium (5 mg/ml) and placed individually on a board in a near vertical position and the tongues were withdrawn with a lined forceps. TNF-α (0.125 mg/kg body weight) was placed posterior in the throat and aspirated into lungs. Control mice were administrated sterile 0.1% BSA. Mice regained consciousness after 15 min. Mice were i.p. given one dose of PD98059, SB202190, SP600125, Tanshinone IIA, AH 6809, SC-19220, GW627368X, or AACOCFg at 4°C, and cell pellets were washed and re-suspended in PBS. Leukocyte count was determined by a hemocytometer.Mice were injected with TNF-α at a dose of 0.75 mg/kg and sacrificed 24 h later. BAL fluid was performed through a tracheal cannula using 1 ml aliquots of ice-cold PBS medium. BAL fluid was centrifuged at 500× P<0.05 was considered significant.All data were estimated and made using a GraphPad Prism Program . Data were expressed as the mean±S.E.M. and analyzed by one-way ANOVA followed with Tukey's post-hoc test. 2 expression, cells were incubated with TNF-α for the indicated time intervals. As shown in 2 protein expression in a time-dependent manner with a maximal response within 16–24 h. Moreover, TNF-α also enhanced cPLA2 mRNA accumulation in a time-dependent manner with a maximal response within 4–6 h  by the constitutive enzyme COX-1 or by the inducible COX-2. In our previous study, up-regulation of COX-2 has been shown to induce PGE2 synthesis by TNF-α 2 is a good index of AA release that is more sensitive than [3H]AA mobilization 2 synthesis as a parameter of cPLA2 activity. As shown in 2 synthesis. These results suggested that TNF-α induces cPLA2 expression associated with PGE2 generation in HPAEpiCs.To determine the effect of TNF-α on cPLAin 4–6 h . On the se cells . cPLA2 i2 expression required transcription or translation, cells were stimulated with TNF-α (30 ng/ml) in the presence of an inhibitor of transcriptional level, actinomycin D (Act. D) or translational level, cycloheximide (CHI) and cPLA2 protein expression was determined by Western blot. As shown in 2 protein expression and PGE2 release was abolished by either Act. D or CHI in a concentration-dependent manner, while cPLA2 mRNA levels were only attenuated by Act. D. Taken together, these findings demonstrated that the induction of cPLA2 expression by TNF-α depends on de novo protein synthesis in HPAEpiCs. Most of TNF-α actions are elicited through TNFR1 2 expression via TNFR1 in these cells. As shown in 2 expression in HPAEpiCs. Therefore, TNFR1 mainly plays a key role in TNF-α-induced inflammatory responses.To further determine whether TNF-α-induced cPLA2 expression was also mediated via p42/p44 MAPK in HPAEpiCs. As shown in 2 protein and mRNA expression, and promoter activity. To further ensure that TNF-α-induced cPLA2 expression was mediated via p42/p44 MAPK, as shown in 2 protein expression by TNF-α. Finally, we showed that TNF-α stimulated p42/p44 MAPK phosphorylation in a time-dependent manner, which was reduced by PD98059 during the period of observation  reduced TNF-α-induced leukocyte count in BAL fluid of mice . To investigate whether PGE2 could induce leukocyte count in BAL fluid of mice, AH 6809 (an EP1 and EP2 receptor antagonist), SC-19220 (an EP1 receptor antagonist), or GW627368X (an EP4 receptor antagonist) was used. As shown in 2-mediated PGE2 release to cause airway and pulmonary diseases, such as asthma and COPD.TNF-α has been shown to induce ROS generation via NADPH oxidase activation, which in turn initiates the activation of various signaling pathways, including PKCs, PI3K/Akt, and MAPKs or transcription factors, such as NF-κB and AP-1, and ultimately induces expression of cPLA of mice . PGE2, o2 expression by mesenchymal cells in several extra-pulmonary sites may play a key role in generation of PGE2, known as a biologically active lipid mediator implicated in inflammatory responses 22 expression was mediated through the activation of MAPKs and AP-1 was still unknown. In this study, TNF-α induced cPLA2 expression and PGE2 production which were attenuated by pretreatment with the inhibitors of MEK1/2 (PD98059), p38 MAPK (SB202190), JNK1/2 (SP600125), and AP-1 (Tanshinone IIA) or transfection with siRNAs of p42, p38, JNK2, c-Fos, c-Jun, ATF2, and TNFR1. Here, our results suggested that in HPAEpiCs, TNF-α-induced cPLA2 expression associated with PGE2 release was, at least in part, mediated through JNK1/2- and p38 MAPK-dependent p300-AP-1 signaling pathway. These results demonstrated that MAPKs and AP-1 may be the critical components implicated in cPLA2 expression and PGE2 synthesis in TNF-α-challenged HPAEpiCs.Asthma and COPD are pulmonary disorders characterized by various degrees of inflammation and tissue remodeling. Up-regulation of cPLAAccumulating evidence demonstrates that TNF-α may activate downstream protein kinases leading to the expression of inflammatory proteins 2 expression. For example, activation of JNK1/2 and p42/p44 MAPK is required for up-regulation of cPLA2 in response to oncogenic Ras in normal epithelial cells 2 by LPS is mediated through these MAPKs pathways 2 in human airway smooth muscle cells, which is regulated by p38 MAPK and JNK1/2, but not p42/p44 MAPK 2 expression and PGE2 release in HPAEpiCs. These results were consistent with the reports indicating that activation of MAPKs plays a pivotal role in the expression of cPLA2 in various cell types Several extracellular stimuli elicit a broad spectrum of biological responses mediated through activation of MAPKs, including p42/p44 MAPK, p38 MAPK, and JNK1/2. Since TNF-α plays an important role in different cellular responses, the activation of these MAPKs is not necessarily restricted to TNF-α-induced cPLA2 expression via p42/p44 MAPK- and JNK1/2-dependent AP-1 activation in RA synovial fibroblasts (RASFs) 2 expression via MAPKs, AP-1, and NF-κB in human tracheal smooth muscle cells 2 expression and PGE2 release was decreased via AP-1 inhibition. On the other hand, we also demonstrated that TNF-α could enhance c-Jun and c-Fos protein expression, which may promote TNF-α-mediated induction of inflammatory genes. The transcriptional activity of c-Jun is regulated by phosphorylation at Ser63 and Ser73 through JNK1/2 69 and Thr712 expression, which was not mediated through activation of ATF2 and c-Jun in HPAEpiCs. In the future, we will investigate whether p42/p44 MAPK may regulate other transcription factors, such as NF-κB or Elk-1, leading to cPLA2 expression.AP-1 is a dimeric transcription factor comprising proteins from several families whose common denominator is the possession of basic leucine zipper (bZIP) domains that are essential for dimerization and DNA binding. It has been well established that inflammatory responses following exposure to extracellular stimuli are highly dependent on activation of AP-1 which plays an important role in the expression of several target genes 2 gene expression can be regulated by various transcription factors, including Sp1 and c-Jun 2 terminus of core nucleosomal histones in vivo binding of p300, ATF2, c-Fos, and c-Jun to the cPLA2 promoter.In non-small cell lung cancer cells, cPLA2 expression and PGE2 release in HPAEpiCs. Indeed, previous study showed that cigarette smoke extract (CSE) induced cPLA2 expression in airway smooth muscle cells via the NADPH oxidase-dependent p42/p44 MAPK and p38 MAPK/c-Fos and JNK1/2/c-Jun/p300 pathways 2 expression through MAPKs, and then the activated MAPKs regulated the activity of p300 and acetylation of histone H4 and hence led to cPLA2 expression 2 expression via activation of p42/p44 MAPK and JNK1/2, which further stimulated AP-1 activation in rheumatoid arthritis synovial fibroblasts 2. Finally, association of p300, ATF2, c-Jun, and c-Fos led to cPLA2 gene transcription. The mechanisms by which TNF-α induced cPLA2 expression may be an important link in the pathogenesis of lung inflammatory diseases. Therefore, understanding the mechanisms underlying TNF-α-induced cPLA2 expression in HPAEpiCs is important to develop new therapeutic strategies.Based on the observation from literatures and our findings,


However, it is important for the VLPs to retain their structure for them to be fully functional and effective. The medium in which the VLPs are formulated and the temperature at which they are stored are two important factors affecting their stability.HIV-1 Pr55gag VLPs during prolonged storage. Transmission electron microscopy (TEM) was done on VLPs stored at two different concentrations of the media at three different temperatures  over different time periods, and the appearance of the VLPs was compared. VLPs stored in 15% trehalose at −70°C retained their original appearance the most effectively over a period of 12 months. VLPs stored in 5% trehalose, sorbitol or sucrose were not all intact even after 1 month storage at the temperatures tested. In addition, we showed that VLPs stored under these conditions were able to be frozen and re-thawed twice before showing changes in their appearance.We describe the screening of 3 different readily available formulation media  for their ability to stabilise HIV-1 Pr55Although the inclusion of other analytical tools are essential to validate these preliminary findings, storage in 15% trehalose at −70°C for 12 months is most effective in retaining VLP stability. In 2008, an estimated 1.9 million people in sub-Saharan Africa were newly infected with HIV, recombigag) forms non-infectious VLPs that are morphologically similar to HIV-1 particles when expressed in isolation in insect cells[gag DNA inoculation in mice[HIV-1 Gag polyprotein  to maintain the protein in a non-aggregated state without affecting its structure, potency and function at specific temperatures was investigated. Two different concentrations of osmolytes were selected (5% and 15%) to cover the range over which stability of other VLPs has been tested[This research group continually generates HIV-1 VLPs for immunogenicity studies in animals, requiring storage for varying lengths of time: accordingly, and in the interests of reproducibility in our work, in this study we evaluated the stability of HIV-1 Pr55n tested,18. The gag sequence was the same as that used for a South African HIV-1 subtype C vaccine[gag was cloned into pFastBac (Invitrogen) under the polyhedron promoter and expressed as described[The HIV-1 Pr55 vaccine,21 and oescribed.Spodoptera frugiperda-derived Sf9 cell suspension cultures (Invitrogen) by infecting cells with baculovirus encoding gag at a MOI between 2 and 10 PFU/mL. Cells were grown in SF900 serum-free insect cell medium (Gibco) supplemented with 10 μg/ml gentamycin, at 270 rpm and 27°C.Gag VLPs were produced in Sf9 culture supernatant at 72 h post-infection by centrifugation , resuspended in 1 × PBS pH 7.4 and sedimented through a 10–50% Optiprep™ step gradient at 12 000 g (Beckman SW32 Ti rotor) for 3 h at 4°C. The particle band with a density of 1.17 g/ml[g for 1.5 h. Purified VLPs were resuspended in 1 ml 1 × PBS.VLPs were harvested from infected .17 g/ml was syriComposition of purified Gag VLPs was confirmed by anti-p24 western blot analysis (data not shown). Purified VLPs were SDS-PAGE separated and electroblotted onto nitrocellulose  for 1.5 h at 15 V. Membranes were probed with anti-p24 rabbit antiserum , followed by anti-rabbit alkaline phosphatase-conjugated secondary antibody  and developed with Nitroblue tetrazolium chloride/5-bromo-4-chloro-3-indolyl phosphate (Roche).Stock solutions (60%) of sucrose and sorbitol were prepared in sterile, non-pyrogenic water for injection  and filtered through a 0.2 μm filter. Stock solutions (20% and 60%) of trehalose were dissolved in sterile, non-pyrogenic water at 50°C and filtered through a 0.45 μm filter. These were added to VLP aliquots in 1 × PBS resulting in final concentrations of 5% and 15% respectively, and stored at 4°C, –20°C and −70°C.gag polyproteins. This could cause breakdown of the VLP structure, disrupting the highly repetitive surface epitope arrangement thereby altering the extent of the immune response[VLP preparations (between 1 and 2 per storage condition) were thawed and examined by TEM after 1, 3, 6 and 12 months of storage at 4°C, -20°C and −70°C. VLPs were fixed onto carbon-coated copper grids (200 mesh), stained with 2% uranyl acetate and visualized with a LEO 912 microscope. TEM  did not confer stability to VLPs at the three temperatures tested after one month. Indeed, VLPs stored in the low osmolyte concentrations at 4°C were less stable than those stored in PBS alone. While we did not investigate this specifically, 30 years experience of working in the laboratory with purified plant viruses and VLPs indicates that most preparations are more stable in buffers of ionic strength above 0.05 – and the low-osmolyte preparations were lower than this. Accordingly, we surmise that both ionic and cryoprotective agents are necessary for stabilisation. All higher percentage (15%) osmolytes tested retained the original VLP appearance at 4°C for one month, indicating they provided a provisional stabilisation medium.nd freeze-thaw cycle, over 50% of the VLPs lost their uniform spherical shape . Results showed that VLPs can withstand 2 freeze-thaw cycles, after which a change in their appearance occurred  over the period of a year. Sorbitol and sucrose were ineffective in retaining particle stability and conformation, whereas 15% trehalose was highly effective in stabilising the VLPs for at least 1 year at −70°C. In addition, VLPs stored under these conditions could withstand up to 2 freeze-thaw cycles before exhibiting changes in their uniformity.In conclusion, this preliminary investigation into VLP storage and stability enabled us to compare the ability of sucrose, trehalose and sorbitol to stabilise HIV-1 Pr55Our report provides valuable baseline information on exploring the long term-storage stabilisation of potential HIV-1 VLP vaccine candidates. This method is now used to store VLPs made for continued immunogenicity studies in our research group. Other techniques such as asymmetrical flow field flow fractionation (AFFFF-MALS) and electrospray differential mobility analysis (ES-DMA) may provThe authors declared that they have no competing interest.AL produced and purified the VLPs and carried out the TEM. AM and EPR supervised the work, revised the manuscript for important intellectual content, and together with A-LW, conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.


Ovarian cancer, an inflammation-associated cancer, is the fifth leading cause of cancer deaths in women. The malignancy produces a large amount of tumor necrosis factor (TNF) which promotes a proinflammatory tumor microenvironment. In addition, the epidermal growth factor receptor (EGFR) is frequently overexpressed in high-grade ovarian cancer, which likely aggravates cancer progression. Since ovarian cancer progression is closely associated with chemokine networks driven by inflammation or EGFR activation, we investigated the chemokine signatures elicited by EGF and TNF in ovarian cancer cells to determine their individual profiles and if there was in fact some kind of synergy between their actions on the chemokine network.We used a PCR array for the chemokine network to examine the signature of chemokines and their receptors elicited by EGF and TNF in four ovarian cancer cell lines .The chemokine network revealed that ovarian cancer cells commonly expressed high levels of proinflammatory chemokines such as CCL20, CXCL1-3 and CXCL8 in response to EGF or TNF. However, the responsiveness to EGF or TNF displayed a cell line specific pattern. Although OVCAR-3 and SKOV-3 cells were responsive to either EGF or TNF, their TNF responsiveness was dominant. On the other hand, CaOV-3 and TOV-21G cells were responsive to EGF but less to TNF, probably due to the high levels of non-canonical nuclear factor (NF)-κB components such as IKKα and p52 in these cell lines compared to OVCAR-3 and SKOV-3 cells. Among chemokine receptors, only CXCR5 was responsive to EGF or TNF in CaOV-3 cells. Finally, CCL20 and CXCL8 responded synergistically in response to EGF and TNF in OVCAR-3 and SKOV-3 cells.Our results indicate that CCL20, CXCL1-3 and CXCL8 are the primary chemokines induced by EGF or TNF and are elicited in these ovarian cancer cells via NF-κB, Akt and Erk signaling pathways. Of interest, there was a syngergistic response in terms of CCL20 and CXCL8 levels, when OVCAR-3 and SKOV-3 cells were exposed to EGF plus TNF. Targeting these proinflammatory chemokines may be a promising therapeutic strategy for ovarian cancer with abundant TNF and EGFR activation patterns. Inflammation-associated ovarian cancer is the fifth leading cause of cancer deaths among women. Chronic infection and inflammation are considered to be among the most important epigenetic and environmental factors contributing to tumorigenesis and cancer progression-3. OvariThe ErbB/EGFR family of receptors consists of four structurally-related type 1 transmembrane tyrosine kinase receptors: EGFR , ErbB2 , ErbB3 (HER3) and ErbB4 (HER4),13. ActiThese limited reports indicate that ovarian cancer progression is closely associated with chemokine networks driven by inflammation or EGFR activation. Therefore it is important to identify which chemokines are primarily regulated by TNF and EGF to order to devise a therapeutic strategy based on the chemokine signature seen in this malignancy. Thus the present study was designed to assess the characteristics of the chemokine profiles elicited by EGF and TNF, and determine if they induce any synergistic effects with respect to key chemokines in ovarian cancer cell lines. For the purposes of this study, we evaluated four such lines: OVAR-3, SKOV-3, CaOV-3 and TOV-21G.Recombinant human TNF and EGF were obtained from R&D Systems . Antibodies were purchased from the following vendors: ErbB isoform, p65 and β-actin from Santa Cruz Biotechnology  and NF-κB family, IKK isoforms, IκB, Akt, Erk and their phosphorylated forms from Cell Signaling Technology . The PCR array for customized human chemokines, specific PCR primers for CCL2, CCL20, CXCL1-3, CXCL8, CXCL16, CXCR5, β-actin, and SYBR® Green Master Mix came from SABiosciences/Qiagen . Chemiluminescent detection kits were from GE Healthcare . Penicillin G/streptomycin was purchased from Sigma  and Lipofectamine 2000 and all liquid culture media were acquired from Invitrogen . BAY-11-7082, LY294002 and PD98059 were purchased from Cayman Chemical . The Luciferase Reporter Assay System was obtained from Promega .4 cells/ml) were cultured at 37°C in a water-saturated atmosphere of 95% air and 5% CO2 in 24- or 6-well plates with RPMI medium containing 10% fetal bovine serum (FBS) with penicillin (100 U/ml)/streptomycin (100 U/ml). After an overnight culture to allow cellular attachment to the plates, the medium was removed and fresh medium without FBS was added to remove the effects of serum, per se. Where indicated, vehicle , 10 ng/ml EGF, 10 ng/ml TNF, or a combination of EGF and TNF was added, and incubations continued for the indicated time periods.The human ovarian cancer cell lines OVCAR-3, SKOV-3, CaOV-3 and TOV-21G were purchased from the American Type Culture Collection . Human cancer cells  provided by SABiosciences (Qiagen).After isolating total RNA and eliminating genomic DNA, reverse transcription reactions were performed at 42°C for 15 min followed by 94°C for 5 min. According to manufacturers’ instructions, a real-time PCR was performed using a Bio-Rad CFX96  under the following two-step cycling program: 1 cycle at 95°C for 10 min, 40 cycles at 95°C for 15 sec and at 60°C for 1 min. Data analysis was performed based on a Web-Based PCR Array Data Analysis protocol  and 5′-CAC CTG CCA CTC TAG TAC TA-3′ for a sense containing a XhoI site and 5′-CCT TAT GGA GTG CTC CGG TG-3′ for an antisense site containing a HindIII site for the CXCL8 promoter (−322/+10). The PCR reaction was performed for 35 cycles at 94°C for 30 sec, 58°C for 30 sec and 74°C for 1 min with a final extension at 74°C for 10 min. The amplified CCL20 and CXCL8 DNA fragments were digested with XhoI and Hind III and the fragments were purified according to manufacturer‘s instructions . The purified CCL20 and CXCL8 promoter genes were subcloned into the XhoI and HindIII sites of the pGL4.12-basic vector . The constructs of the CCL20 and CXCL8 promoter-luciferase genes were confirmed by DNA sequencing analysis.DNA fragments of the human CCL20 and CXCL8 genes were generated by PCR using genomic DNA isolated from OVCAR-3 cells. Primer sets were designed as follows: 5′-GGA GTT CTG GAA TGT TCC TG -3′ for a sense containing a Human ovarian cancer cells at approximately 50% confluency in 24-well plates were washed once with fresh media without additives and were transiently transfected for 24 h at 37°C using Lipofectamine solution. Transfected cells were treated as outlined in Results and incubated for 6 h. After rinsing cells with ice-cold PBS and adding lysis buffer , cell lysates were used for determination of luciferase activity using a microplate luminometer. Luciferase activity, expressed as relative light units, was normalized to measured protein levels.t-test and one-way analysis of variance (ANOVA) as appropriate. If a statistical significance (P ≤ 0.05) was determined by ANOVA, the data were further analyzed by Tukey’s pairwise comparisons to detect specific differences between treatments.Data were analyzed by the paired Student’s We selected ovarian cancer cell lines OVCAR-3, SKOV-3, CaOV-3 and TOV-21G to determine PCR arrays containing genes that encode human chemokines and chemokine receptors after the addition of EGF or TNF. The present study used the nomenclature of chemokines approved by the IUIS/WHO Subcommittee on Chemokine Nomenclature (2002). The mRNA levels of a panel of 43 chemokines and 19 chemokine receptors were evaluated for each of the 4 cell lines. Based on a Web-Based PCR Array Data Analysis protocol provided by SABiosciences (Qiagen), the absent, low and high expression levels of chemokines were defined as >35, 30–35 and <30 average threshold cycles, respectively.OVCAR-3 cells highly expressed CCL20, CCL28, CXCL1, CXCL2, CXCL3 and CXCL8. Except for CCL28, all were responsive to EGF or TNF  in response to EGF and TNF in OVCAR-3 cells  levels to the addition of EGF plus TNF, TNF alone had a greater effect than EGF alone , but showed a dominant effect of EGF>TNF, when each was added alone  in OVCAR-3 cells, although when added separately, TNF had a dominant effect  and EGF alone had a greater response than TNF alone in CaOV-3 cells Figure B. LY2940 and EGF Although CCL20 was only produced at low levels in TOV-21G cells [even in response to EGF and TNF Figure A], CCL20One of the primary findings in this study is that in these four ovarian cancer cell lines, CCL20, CXCL1-3 and CXCL8 were the major chemokines that responded to EGF or TNF by involving NF-κB, Akt and Erk signaling pathways. Particularly, CCL20 and CXCL8 levels were synergistically elevated in response to a combination of EGF plus TNF.Although the chemokine signature profile was to some degree cell-type specific, the most highly expressed chemokines were as follows: CCL20, CCL28, CXCL1-3, CXCL8 and CXCL16. These experimental findings are supported by clinical data showing that CXCL1 expression levels are greater in ovarian cancer than in normal ovary tissues and are also higher in sera from women with ovarian cancer. CXCL8 hWe found that CCL28 and CXCL16 were either unresponsive or far less responsive to EGF or TNF. Although CCL28 levels remain unchanged in these ovarian cell lines, TNF has been shown to increase CCL28 in cultured canine keratinocytes and in AOn the other hand, CCL20, CXCL1-3 and CXCL8 were highly responsive to EGF or TNF. Because these chemokines contain κB sites on their promoters, NF-κB sActually the relationship between EGFR activation and NF-κB signaling is very controversial in other model systems. For instance, heparin-binding EGF-like growth factor (HB-EGF) inhibited NF-κB activation via PI3K-dependent phosphorylation of Akt in cytokine-stimulated intestinal epithelial cells. In contIn particular, EGF synergistically induced CCL20 and CXCL8 by cooperating with TNF. CXCL8 is well known to be regulated by NF-κB signaling. In addiAlso CCL20 expression is under the direct control of NF-κB in mouse liver and TNF Thus TNF-dominant responsive cells (OVCAR-3 and SKOV-3) produced a greater synergistic effect on CCL20 and CXCL8 mRNA when compared to EGF-dominant responsive cells (CaOV-2 and TOV-21G cells). This may be due to the fact that CCL20 and CXCL8 promoters contain a κB site as a main responsive element. FurtherCompared to chemokines, it was difficult to find cell-type specific patterns for chemokine receptors in these cell lines. OVCAR-3 and SKOV-3 cells had either no, or a very low expression of chemokine receptors. Also those ovarian cancer cells with a high endogenous expression of TNF, expressed higher levels of CXCR4 than cells with a low TNF expression. DespiteInterestingly, CXCR5 was responsive to EGF or TNF in CaOV-3 and TOV-21G cells. Although CXCR5 promotes the growth of tumor cells in the liver, the rolOur results indicate that ovarian cancer cells induce CCL20, CXCL1-3 and CXCL8 as the primary chemokines in response to EGF or TNF. Further, CCL20 and CXCL8 can be significantly elevated by the synergistic actions of EGF plus TNF. Targeting these proinflammatory chemokines may support a promising therapeutic strategy for inflammatory ovarian cancer with abundant TNF and EGFR activation pathways.Authors declare no conflict of interest.Conceived and designed the experiments: DS and EL. Performed the experiments: DS, SK and YD. Analyzed the data: DS and EL. Contributed reagents/materials/analysis tools: DS, EL and SA. Wrote the paper: DS, EL and SA. All the authors have read and approved the final manuscript.


Consequently, indicators of research performance based on the total number of papers do not accurately measure scientific progress. Similarly, those universities with the best reputations in terms of scientific progress differ widely from other universities in terms of the scale of investments made in research and in the higher concentrations of outstanding scientists present, but less so in terms of the total number of papers or citations. This study argues that indicators for the 1% high-citation tail of the citation distribution reveal the contribution of universities to the progress of science and provide quantifiable justification for the large investments in research made by elite research universities. In this tail, which follows a power low, the number of the less frequent and highly cited important breakthroughs can be predicted from the frequencies of papers in the upper part of the tail. This study quantifies the false impression of excellence produced by multinational papers, and by other types of papers that do not contribute to the progress of science. Many of these papers are concentrated in and dominate lists of highly cited papers, especially in lower-ranked universities. The  The comparison of these figures leads to the conclusion that the difference in research performance between these two universities is not best indicated by the ratio of the number of publications or of the other indicators based on the total number of publications, which may have values of 2–3 . It is, of course, difficult to make comparisons regarding research funding and output Considering the highest- and lowest-ranked universities in These examples illustrate that some research indicators may be problematic at both country and university levels. Although the problems can be investigated at both levels, the university level is easier to investigate because universities are research units more homogeneous than countries, where very different institutions coexist. Moreover, it is easy to select a sample of universities that are very different in research activity and similar in size to simplify the analysis of the results.x-index was recently formulated using a statistical procedure which optimized the correlation of the indicator with the number of Nobel Prize achievements x-index only considers the papers that are included in the world’s top 1% of cited papers x-index was effective, it does not address conceptual questions about the papers that are not counted. Besides, it does not provide any indication about the number of papers that are counted with reference to the total number of papers in universities of different research levels. However, this is information is necessary to establish a solid scientific background for evaluations based on the world’s top 1% of cited papers.To evaluate overall research performance, the x-index, or any other research indicator based on highly cited papers: (i) Is the exclusion of 99% of the published papers supported by conceptual or empirical reasons? (ii) Which is the proportion of multinational, reviews, and MCTS papers in highly cited papers? (iii) Is it possible to simplify the x-index formula for universities? The first question is at the basis of research evaluations and it will be addressed from a general point of view. The other two questions are purely technical and they will be addressed studying 18 universities of different research levels.Considering these issues, this study aims to answer three specific questions regarding the The majority of research papers that are published every year receive an ephemeral attention from researchers and no attention from the society, but nevertheless, relevant papers are somehow dependent from apparently irrelevant papers. In principle, this situation resembles a soccer match, where many passes are necessary to strike a goal. The number of passes can be counted, but this number does not determine the winner of the match, which is determined by counting the very low frequency events in which the ball is kicked to the goal. Similarly in research, many papers are necessary to make discoveries, but very few report actual discoveries. Unlike soccer, however, in research, there are discoveries of different levels that cannot be easily counted or added up together. Therefore, valid and reliable indicators are required to estimate the capacity of countries and institutions to drive scientific progress.The Structure of Scientific Revolutions, in this study coining the terms “normal” and “revolutionary” sciences. Kuhn demonstrated that only revolutionary science exerts change on the fundamental structures of science through “paradigm shifts.” As an extension of this central idea, it may be added that, in the short run, important paradigm extensions drive a type of scientific progress that the society appreciates and that must be considered to estimate research performance.Output indicators of scientific research performance were developed many years ago An illustrative example of scientific progress that is based on paradigm extension can be taken from a cancer treatment breakthrough, the use of imatinib mesyalate in the treatment of chronic myelogenous leukemia. The excellent clinical performance of this drug is based on two biological features: a chromosomal translocation that creates a fusion gene, which is vital for the expansion of cancer cells, and the inhibition of the product of this gene by imatinib This example can also be used to answer the question of whether the total number of papers published by countries and institutions should be considered as an accurate means of evaluating their research performance. More than 120,000 papers are published annually on cancer research The discussion of indicators of research performance is more complex than just a numerical comparison as many of the total number of papers are important and necessary to researchers even if these papers do not directly report on scientific progress. In fact, researchers value these papers. However, the larger society, which pays for the research, is interested in tangible evidence of progress, in both technological and basic research, not in the intermediate steps  resource in Thomson Reuters’ ISI Web of Knowledge (http://isiknowledge.com). To retrieve national publications (single-country papers with authors from the involved university), the name of the university was entered in the “Address” search field with the name of the corresponding country using the Boolean operator “SAME” and followed by the names of the remaining 22 countries with the highest number of publications according to the ESI using the Boolean operator “NOT”. To restrict the search to research articles, the option “Article” was selected in the “Document Type” search field. Most searches were restricted to a single year using the “Year Published” search field. The minimum number of citations needed for the publications of a certain year to belong to the percentile ranges 1% and 0.1% are recorded in the percentiles table of the Baselines menu of the ESI. For this study, except in The data-collection methods used in this study were described in a previous paper The data summarized in Except for The conclusion that indicators of research performance for countries and institutions should be based on highly cited papers raises a question about the citation level of these papers. This level is important because it determines the proportion of papers that are included in the evaluation, which involves the first question of this report.As a case study meant to facilitate an examination of this proportion and the associated number of citations of the involved papers, I will use the abovementioned example of the treatment of chronic myelogenous leukemia. I chose to analyze papers published in 2001, as this was the year in which the most-cited paper about the research, which led to the discovery of imatinib These small percentages demonstrate that indicators based on the total number of papers may fail completely to recognize the institutions that make greater contributions to the field of leukemia research.A more general approach to address the question about the citation level that delimits the papers that should be counted for research evaluations is the comparison of two universities with very different levels of research performance. For this purpose, the two universities that I compared above, MIT and Complutense University of Madrid, meet the indicated requirements. Considering that the ratio between research investments is in excess of 10∶1 and taking into account the expected performance of researchers, a reliable indicator of research performance could be as great as 50 times higher for MIT than for Complutense University.To perform the study I chose the field of chemistry because projects of “big science” and papers involving authors from many countries are less frequent in this field than they are in physics or biology. Comparing MIT to Complutense University, the ratios between the total number of papers, 616 versus 422; or citations, 37,701 versus 8,154; or the mean number of citations per paper, 61.1 versus 19.3, varied from 1.5 to 4.6, all figures that are far from the abovementioned value of 50. This finding indicates that indicators calculated from all published papers are unlikely to reveal the actual research performance of universities. A comparison of the frequency distribution of citations  indicateNext, I selected 18 universities of different countries and research levels according to SCImago and CWTS university rankings, including three US universities: MIT, Cornell University, and The University of Utah. All universities included in the study are well-known universities in their respective countries but are not necessarily the highest ranked institutions in each country. The Indian Institute of Technology consists of several autonomous universities; data for the institute as a whole were used for this study.The mean number of citations showed low variability across universities in all cases for both x-index Multinational papers are omitted in the formula of the The obscuring effect of integer counting on research indicators can be estimated by comparing the weight of multinational papers in the bibliometric parameters. The effect was minor when all the papers were considered, given that the ratio between the numbers of multinational and national papers was low. For the 18 universities included in this study the multinational to national ratio for all papers varied from 0.21 for Kyoto and Utah up to 0.86 for ETH, i.e., most or the papers are national. In contrast, for papers in the top 1% of highly cited papers, the corresponding ratio varied from 0.46 for Utah to 3.63 for Paris-Sud 11, i.e., most of the papers were multinational in Paris-Sud 11. The problem with regard to the number of citations is similar, but the differences are even more striking. For papers in the top 1% of highly cited papers, the ratio between citations to multinational and national papers varied form 0.53 for MIT, to 8.02 for Paris-Sud 11. The multinational to national ratio in the top 1% of highly cited papers was dependent on the relative rank of the universities. In lower-ranked universities the weight of multinational papers in each of the two indicators, number of papers and number of citations, was greater than for the higher-ranked universities (compare corresponding ratios in A final observation regarding the top 1% of highly cited papers was that the number of institutions participating in multinational papers was considerably higher than that in national papers. For example, for Sapienza, Paris-Sud 11, and Complutense, the mean numbers of institutions participating in national papers were, 4.9, 3.8, and 1.4, respectively, while the means for multinational papers were 17, 13 and 10, respectively.Review papers were also concentrated in the top 1% of highly cited papers. x-index contains a subtraction term, but this term gave rise to negative index values for countries with less-competitive research systems To correct the problem created by MCTS papers, the formula of the x-index formula. If this term is omitted the correlation coefficient between the x-index and the number of Nobel Prizes decreases a little and the ranking order is not affected. I examined the concentration of MCTS papers among those papers published by universities and concluded that the effects are a minor problem for high- or mid-ranking US universities but are more important to European universities. Although identifying MCTS papers by reading abstracts was not easy, I believe that they account for a higher percentage of the highly cited papers for countries than they do for universities, perhaps due to the large number of hospitals and government agencies which produce clinical trials and statistical studies.As described for multinational and review papers, MCTS papers are concentrated in the top 1% of highly cited papers. However, unlike multinational and review papers, it is difficult if not impossible to identify and count MCTS papers. Among similarly sized institutions MCTS papers fortunately operate as a constant addition term in the x-index can be eliminated. Although this new x-index for universities will overvalue some lower-ranked universities, the problem created by MCTS papers does not have a better solution.In summary, to rank universities the subtraction term in the formula of the To gain a more complete understanding of the information able to be extracted from the number of publications in the top 1% of highly cited papers, three additional parameters are shown in Although h-index is calculated using only the most-cited papers h-index does not correlate with the number of Nobel Prize achievements or with the x-index h-index does not provide the expected differences between countries and institutions in research performance, I examined the h-core papers from the top- and bottom-ranked universities included in the present study. I first eliminated multinational and review papers, but this modification did not appreciably increase the differences between the h-index values for the top and bottom universities. I then examined the percentile positions of the h-core papers with respect to citation distribution, for both a single year, 2005, and for the entire 10-year period covered by the ESI database, 2001–2010. The results were clear, while most h-core papers were in the top 1% of highly cited papers in top-ranked universities, very few were in the top 1% for bottom-ranked universities.Unlike other conventional scientometric indicators, the h-index values were 115 and 42, respectively, for 2005, when considering only national articles. This indicates an unconvincing research performance ratio of 3∶1. The relevant fact that explains why the h-index obscures the differences between these two universities is that while all the MIT h-core papers were in the top 1% of highly cited papers, only three out of the 42 h-core papers of Complutense University were in the top 1%.Returning to the comparison of MIT and Complutense University, their h-index is much more rigorous for prestigious institutions than for institutions with a lower level of research.In sum, according to the citation distribution, the x-index is calculated considering only the papers that are included in the world’s top 1% of cited papers and this amount of papers is very restrictive in comparison to indicators that consider all papers. Surprisingly, a reasonably answer to the posed question is that very few of those in the world’s top 1% of cited papers are really relevant for the progress of science. According with this conclusion the x-index predicts the size of a population of papers that is much smaller than the sample of papers from which it is calculated. Especially, the x-index was formulated to predict the number of Nobel Prize achievements, which are obviously far less than the 1% of the papers. The best explanation for this prediction is that it is possible because the share of highly cited papers follows a power law The first question addressed in this study is about the proportion of all scientific publications that are involved in driving the scientific progress. The Additionally, the finding that more than 99% of the published papers do not most likely report on important breakthroughs but do receive more than 90% of the total number of citations strongly suggest that research performance should be evaluated without considering that lower-cited 99% of published papers. If all papers are considered, the real scientific differences between countries and institutions are blurred.x-index for universities. For this purpose, the size differences between the 18 universities included in the study are not large and the reported counts may be treated as size-independent.The second part of this study aimed to know the number of papers from universities that are in the world’s top percentiles of highly cited papers and the proportion of multinational, reviews, and MCTS papers. A final aim was to investigate the possibility of simplifying the formula of the As a general trend, the rankings of the 18 universities are sound, independently of whether they are based on the counts of papers or citations, either considering the total number of papers or the top 1% of highly cited papers. However, to judge these rankings and to analyze if the ranking parameters accurately reflect the universities’ participation in the progress of science, the variation between the highest and the lowest values of the involved ranking parameter is the most important issue. This variation ranged from 150∶1 for the citation counts of national papers in the top 1% of highly cited papers to 4∶1 for counts of the total number of papers  and 3.To select a ranking parameter it is worth clarifying that counting papers is better than counting citations if the goal is to rank universities on the basis of their research performance. The reason is statistical: the numbers of papers in the top 1% or 0.1% of highly cited paper for different years are entirely equivalent, which allows to use these counts for statistical analyses. This possibility does not apply to citation counting, unless the number of citations is normalized to correct for the time dependence of citations counting.Review, MCTS, and multinational papers are all concentrated in the top 1% of highly cited papers. Review papers may be of several types and may be important for fixing knowledge, but they rarely report on important breakthroughs. However, review papers are not as significant a problem because their effect on the indicators for universities seems to be low and they can easily be omitted from counts by restricting database searches. In contrast, MCTS papers cannot currently be identified using bibliometric procedures and therefore cannot be eliminated. For the evaluation of universities the existence of these papers may be ignored, as described above.Highly cited multinational papers make up a large proportion of the number of papers in the high-citation percentiles of the citation distribution for lower-ranked universities . ConsequThis omission may be controversial because the described effects can potentially be corrected for with fractional counting. In fractional counting, if n countries or institutions participate in producing a paper, each country or institution receives 1/n of the credit z-index Even ignoring these considerations, the crucial point is that the omission of multinational or multi-institutional papers from counts is not a problem when the number of papers remaining in the sample is sufficiently large. In that case, the parameter that best characterizes a country or institution is a size-independent index such as the In the present study, I have addressed the problem of multinational papers, but not that of multi-institutional papers. Differences in the scientific performance of countries are perhaps more important for most evaluations than are differences in the scientific performance of different institutions in the same country. However, the elimination of multi-institutional papers in rankings institutions in the same country deserves further investigation.x index for universities is:N1 and N0.1 are the number of national articles in the top 1% and 0.1% of highly cited papers, respectively. The zu index has the same formula as the z index xu index for that of the x index. The new formula of the zu index eliminating the subtraction term will produce university rankings in which the values of the indicator are 6 units higher than those corresponding to the z index. This increase is of little relevance for the high z values of the higher-ranked universities but is important for the low z values of lower-ranked universities. However, this constant increase does affect rankings and its effect on the indicator is a minor inconvenience considering the current impossibility of bibliometrically eliminating MCTS papers.As a result of these considerations, the formula of the xu and zu indices include the number of national papers in the top 1% and 0.1% most cited papers, but national papers in the top 0.1% of most cited papers are not found among lower-ranked universities (xu and zu indices for these universities have exactly the same mathematical meaning as in higher-ranked universities. However, these indices remain sound indicators for ranking universities of low research performance. In the absence of national articles in the top 1% of highly cited papers, in any of the five successive years that are used to calculate the x index xu and zu indices. The essential issue that this absence reflects is that these universities have a very low level of research achievement and that they have to be evaluated by their “normal” research activity, e.g. counting all papers or those in the top 10% most cited papers.The formulas of the ersities . This fah-core papers in the 1% high-citation tail is not proportional to the value of the h-index. Therefore, using the h-index to rank institutions or countries does not provide a clear picture of the differences in research performance among the to-be-ranked institutions or countries. This consideration is much more important for institutions than for researchers. I have asserted in this study that researchers cannot be evaluated using the same indices as are applied to institutions or countries. Researchers are best evaluated by measuring their capability while evaluations of institutions should measure the achievement of important breakthroughs. Because important breakthroughs are low frequency events, the difference is statistical: the achievements of one versus the achievements of 1,000 or more.I demonstrated, above, that the proportion of Research indicators derived from highly cited papers are field-dependent; the research fields with the highest citation rates have the highest influence in the indicators of multidisciplinary institutions such as universities. This problem is common with any index for institutions and journals, and can be solved by analyzing each paper in its corresponding field of research (as has been done in


Selected cytokines TNF-α, IFNα, or IFNγ reduced the expression of myosin heavy chain (MyHC IIa) when given together. Molecular mechanisms of cytokine activities were controlled by NF-κB and JAK/STAT signaling pathways, as metabolic inhibitors, curcumin and AG490, inhibited some of TNF-α and IFNα/IFNγ effects. Insulin was hardly antagonistic to TNF-α- and IFNα/IFNγ-dependent decrease in MyHC IIa protein expression. Cytokines used individually or together also repressed myogenesis of C2C12 cells. Moreover, TNF-α- and IFNα/IFNγ-dependent effects on C2C12 myotubes were associated with increased activity of Atrogin1 and MuRF1 genes, which code ubiquitin ligases. MyHC IIa gene activity was unaltered by cytokines. Inhibition of NF-κB or JAK/STAT with specific metabolic inhibitors decreased activity of Atrogin1 and MuRF1 but not MyHC IIa gene. Overall, these results suggest cooperation between cytokines in the reduction of MyHC IIa protein expression level via NF-κB/JAK/STAT signaling pathways and activation of Atrogin1 and MuRF1 genes as their molecular targets. Insulin cotreatment or pretreatment does not protect against muscle decay induced by examined proinflammatory cytokines.TNF- Moreover, Guttridge et al.  into an insoluble purple formazan reaction product with minor modifications to protocol described by Jacobson et al. . Briefly2O with ethanol 2% (v/v) for 10 min. Subsequently, they were gently washed with dd.H2O, air dried, and incubated with SDS solution . The absorbances for MTT and CV were measured at 490 and 570 nm, respectively, with ELISA reader type Infinite 200 . Relative percentages (versus nontreated control) of viable or proliferating cells were measured by MTT conversion into purple formazan and quantity of CV bound to cellular DNA, respectively.Cell mitogenicity was determined by crystal violet (CV) assay on identical 96-well flat bottomed multiwell plates. Cells were uniformly seeded and grown in GM for 24 h. Mitogenicity was measured on day 3 of culture. Initially, cells were kept in GM for 24 h, followed by 24 h incubation with the experimental factor(s) dissolved in serum-free 2% BSA/DMEM, and finally recovered in GM for another 24 h. Cells were exposed (or not) to experimental factors during 24 h. Upon completing the experiment, cells were washed with PBS and fixed with two-step bath in ice-cold methanol . Cells were immersed in 0.2%, w/v crystal violet solution in dd.Hμg/mL of aprotinin and 10 μg/mL of sodium orthovanadate were added. To lyse the cell pellets, cells were broken up by repetitive triturating with the syringe with attached needle . Cell suspension was then left on ice (4°C) for 30 min and centrifuged for another 5 min . Next, viscous solution was divided into smaller volumes and transferred to fresh Eppendorf tubes and stored at −80°C until used. For protein quantification in the whole-cell lysates, a protein-dye-binding method of Bradford  were added at 4°C. The samples were subjected to RT-PCR for 50 min at 48°C. After completing the reaction the concentration of newly synthesized cDNA was measured in the NanoDrop 1000  at λ = 230 nm. cDNA was kept frozen at −76°C until further analyses. To perform real time PCR reaction, cDNA was combined with 25 μM of each primer (sense and antisense) and SYBR green . The qRT PCR measurements of individual cDNAs were performed in triplicates using SYBR green dye to measure duplex DNA formation with the LightCycler . The results were analyzed with LightCycler3 Front Screen. 18S rRNA was used as reference gene. The sequences of the primers sets used are shown in the attached Total RNA was extracted from myotubes with the Total RNA Maxi Kit , according to manufacturer's protocol. RNA was frozen at −76°C before the performing the reverse transcription reaction (RT-PCR). Then, 500 Myhc IIa and Atrogin1 60°C ; for MuRF1 58°C ; for 18S rRNA 56°C ; and elongation 72°C .PCR conditions were as follows: denaturation for each cycle 95°C ; annealing both for P values of less than 0.05 were considered statistically significant. Statistical differences from control cells were indicated by asterisks , whereas statistical differences between the treatments and untreated control cells were ticked with different lower case letters (bar charts). Statistical analyses were performed using GraphPad Prism version 5.0 software .Each experiment was repeated at least three times. The data are expressed as the means ± SE. Statistical analyses were performed using one-way analysis of variance (ANOVA) followed by Tukey's, Newman-Keuls'a or Benferroni multiple range test. If necessary, the selection of particular posthoc test  was performed after the same critical difference for the first comparison was tested. Regression analysis was carried out to draw appropriate dose-response or time-course curves. α (10 ng/mL) to the medium stimulated viability (by 88 ± 2.82 to 140% ± 6.84) and mitogenicity (by 30% ± 4.24) of differentiating C2C12 myoblasts . AG490 (5 μM) used individually impaired cell viability at days 3–5 of differentiation , but curcumin (1 μM) did not exert this effect. The effects of TNF-α on cell viability and mitogenicity were abolished by curcumin (NF-κB inhibitor) and AG490 (JAK inhibitor) administration  in 3-day-old C2C12 myotubes, nuclear fractions were isolated and immunoblotted, whereas transcriptional activity was evaluated using TransAM method. Nuclear expression of NF-κB protein increased as early as 15 minutes after TNF-α administration (κB at the same time (α (10 ng/mL), the transcriptional activity of NF-κB was significantly elevated in 30th (by 49% + 8.9) and 60th minute (by 47% ± 7.15) of treatment (P < 0.01 compared to control). Furthermore, also after 24 hours of TNF-α administration both NF-κB expression and its activity were still significantly higher . In contrast to short term treatment (minutes), after 24 hours of TNF-α administration the expression level of IκBα protein was increased in the cytoplasmic fraction (α nor IFNγ affected the activity of NF-κB in C2C12 myotubes in the long term study (P > 0.05 compared to control).To verify the intracellular level of NF-stration . There wame time . As showfraction . Neitherα (10 ng/mL) administration significantly increased TNF-α-dependent NF-κB activity in 15th, 30th but 60th minute  in 3-day old C2C12 myotubes. In contrast, insulin pretreatment neither changed NF-κB activity (P > 0.05) nor expression when administered as pretreatment and cotreatment with IFNα or IFNγ  prior to TNF- or IFNγ .α, IFNγ, 10 ng/mL) sensitized cellular responses to TNF-α administration in 3-day old C2C12 myotubes as evidenced by NF-κB activity . NF-κB activity stimulated by TNF-α and potentiated by IFNα in 3-day-old C2C12 myotubes was additionally substantiated by nuclear NF-κB setting observed in confocal microscopy (Supplementary data 2). Visualization confirmed that these reactions occurred, even though NF-κB expression levels remained unchanged. When insulin was used together with interferons in one-day pretreatment, the effect of insulin on NF-κB protein expression , while insulin + IFNγ by 121% ± 25.19 and 225% ± 20.2 in the 15th and 30th minute of TNF-α treatment (P < 0.001 compared to control).Preincubation with interferons  increased STAT-1α-P-Y701-nuclear protein expression levels and activity in 3-day-old C2C12 myotubes by 39% ± 3.35 and 41% ± 2.78, respectively, (P < 0.01 compared to control). Insulin given together with IFNα did not reduce elevated STAT-1α-P-Y701 activity and nuclear protein expression level .Preincubation with cytokines . Insulin pretreatment  hardly affected the cellular response to TNF-α with respect to STAT-1α-P-Y701 activity as it remained significantly higher than in control conditions during 15 , 30 , and 60  minutes of treatment  followed by TNF-α challenge, STAT-1α-P-Y701 protein expression was similar to the conditions in which TNF-α was given alone . When IFNα was replaced by IFNγ , TNF-α-dependent rise in nuclear protein expression levels of STAT-1α-P-Y701 was halted . Additional preincubation with insulin  neither affected the response to IFNγ nor to IFNα pretreated cells in STAT-1α-P-Y701 expression levels and transcriptional activities  was shown to inhibit the expression of MyHC IIa in C2C12 myotubes (8-day-old), while additional presence of IFNα or IFNγ  amplified TNF-α-dependent drop in MyHC IIa protein expression  or AG490  together with TNF-α and/or IFNα or IFNγ during 48 hours (from 6th to 8th day of differentiation) reversed the nuclear raise in NF-κB protein expression to the control level  were capable to prevent the TNF-α-dependent loss of MyHC IIa expression levels in C2C12 myotubes, when compared with the control level .As MRFs are critical for muscle differentiation and maturation of myotubes, two different transcription factors were chosen for the study, namely, MyoD known as primary muscle regulatory factor and myogenin secondary to MyoD. As presented in to TNF-α . Howeverα protein is activated either by IFNα or IFNγ after binding to respective IFNAR or IFNGR. STAT-1α was previously reported to be bound to TRADD protein [κB-dependent death signal. As STAT-1α protein is modulated by interferons, also NF-κB signaling pathway can be released from inhibition when both TNF-α and IFNα or IFNγ are administered. To verify this assumption STAT-1α protein complexes were isolated by immunoprecipitation, and TRADD protein was immunoblotted after PAGE. As it is shown in α was the highest in untreated myotubes, and it was lowered by TNF-α and further cotreatment with IFNα and IFNγ.In this study, it was assumed that STAT-1 protein –44 and iα together with interferons attenuated the expression of MyHC IIa protein. On this evidence, we queried whether it is associated with lower activity of the respective gene (Myhc IIa). Surprisingly, TNF-α, IFNα, and IFNγ were shown to stimulate the activity of Myhc IIa by 3-, 1.8-, and 2.6-fold, respectively (P < 0.001 versus control). However, the Myhc IIa response to TNF-α was controlled by NF-κB and STAT-1α transcription factors since the blockage of activation by curcumin (NF-κB) or AG490 (STAT-1α) diminished TNF-α-dependent rise in Myhc IIa activity . In contrast to TNF-α, curcumin did not affect the activity of Myhc IIa upon cotreatment with IFNα (P > 0.05 versus TNF-α and IFNα) but it increased Myhc IIa activity when TNF-α was added along with IFNγ (P < 0.01 versus TNF-α and IFNγ). Astonishingly, AG490 co-treatment with IFNα elevated Myhc IIa activity by 2.5-fold (P < 0.001 versus control).TNF-α or IFNα, or both (10 ng/mL) were added to differentiating medium for the last 48 hours of differentiation (days 6–8), Atrogin1 gene activity was stimulated by 1.8- and 1.6-fold at the 8th day of study (P < 0.01 compared to control). TNF-α, but not IFNα, dependent Atrogin1 activation, was inhibited by curcumin . A more pronounced effect was induced by AG490 (5 μM), which almost completely abolished TNF-α and IFNα effects during the last 48 hours of the 8-day incubation time (P < 0.001 compared to control).When TNF-α, IFNα, or IFNγ (10 ng/mL) were added to differentiating medium for the last 48 hours MuRF1 gene activity was stimulated almost 4-fold at the 8th day of study (P < 0.001 compared to control). TNF-α and IFNγ, but not the IFNα-stimulated MuRF1 gene activity in NF-κB-dependent manner, since curcumin (1 μM) was capable to reduce significantly the cellular response . No effect of curcumin was observed with respect to IFNα . AG490 (5 μM) abolished TNF-α-induced effect, but it potentiated the IFNα effect on MuRF1 gene activity by almost 1.6-fold , whereas it had no significant influence on IFNγ-dependent stimulation of MuRF1 gene activity .When TNF-β superfamily  contributes to muscle wasting through SMAD pathway activation [−/ob−) have also reduced lean body mass, apparently other than leptin-dependent signaling pathways must be engaged in muscle cachexia. In this study we showed that TNF-α stimulated DNA synthesis similarly to leptin (P < 0.001 versus control) but it also increased C2C12 muscle cell viability . Thus, both cytokines seem to actively participate in the activation of satellite cells (myoblasts) as was previously reported for leukemia inhibitory factor LIF [α/cachectin, IL-1α, IL-1β, IFNγ, and IL-6 have been implicated in muscle wasting, and their elevated levels were detected in cachectic patients [α, IFNα, and IFNγ during muscle differentiation using C2C12 mouse myoblasts. We also showed their respective effects in fully formed C2C12 myotubes. As TNF-α improved viability and mitogenicity of differentiating C2C12 myoblasts, we suggest that TNF-α might be capable to induce muscle dedifferentiation as demonstrated by Buck and Chojkier [α improved cell respiration through NF-κB-dependent mechanism, as curcumin (1 μM) administered with TNF-α impaired muscle cell viability even stronger than curcumin given alone (P < 0.01). Inhibition of STAT-1α kinase JAK with tyrphostin (AG490) also retarded TNF-α-induced mitogenicity and viability below control level . A similar effect of AG490 on C2C12 myoblast proliferation was observed by Spangenburg and Booth [κB and STAT-1α responded to TNF-α in elevated transcriptional activity, as shown in the 3-day myotubes in short- and long term experiments . These preliminary observations prompted us to study NF-κB and STAT-1α effects in detail. Western blots confirmed transcriptional activation in the 3rd day of myogenesis as it was accompanied by higher nuclear NF-κB and lower cytosolic IκB protein levels after TNF-α , but it could hardly affect IFNα or IFNγ effects (P > 0.05). Insulin however, after initial pretreatment, given in combined treatment with TNF-α, inhibited nuclear translocation of NF-κB  expression and reduced myotube formation (α controls NF-κB activity in muscle cells [κB controls MyoD decay in C2C12 myotubes [κB regulates the expression of a variety of muscle genes and proteins including those involved in control of cell proliferation [κB activity observed after TNF-α administration in this experiment suggests that differentiating myoblasts could be withdrawn from the myogenic program as shown recently in muscle-derived stem cells isolated from transgenic mice [κB activator [α and IFNγ as neither cytokine (10 ng/mL) could affect NF-κB activity (P > 0.05 versus control). However, IFNα and IFNγ used in one-day pretreatment sensitized C2C12 myotubes to TNF-α-induced NF-κB activation on the 3rd day of myogenesis (P < 0.001). Higher NF-κB transcriptional activity upon pretreatment with IFNs was confirmed by higher and earlier nuclear expression of NF-κB  has been detected in the nucleus after TNF-α, IFNα, and IFNγ, whereas insulin pre- and cotreatment could not reduce the effect of IFNs. Thus, it is apparent that TNF-α, IFNα, and IFNγ cooperate in NF-κB activation, and that nonactive STAT-1α seems to inhibit this process. Next, we assumed that STAT-1α might inhibit NF-κB in nonstimulated muscle cells as STAT-1α was previously reported in other cell-types to be assembled with TNF-R1 through TRADD protein partner [α and IFNγ caused reduction in the STAT-1α protein quantity bound to TRADD protein , but it did not change the response of NF-κB or STAT-1α to interferons . Therefore, we assume that similarities between insulin and interferons in TNF-α-dependent NF-κB activation must have different origins. Insulin was capable to reduce NF-κB activation in the presence of IFNα- but not IFNγ . Interestingly, TNF-α raised nuclear STAT-1α-P-Y701 protein levels, while insulin pre- and co-treatment additionally amplified this effect in the 3rd day of myogenic differentiation . These results are in concert with our previous report [γ did not (P > 0.05) but IFNα did increase TNF-α-dependent STAT-1α activation (P < 0.05). Insulin pretreatment did not affect IFNα-induced, TNF-α-dependent activation of STAT-1α (P < 0.05). The latter observation was corroborated by WB results obtained for STAT-1α-P-Y701 protein levels . From a pathophysiological point of view, muscle cachexia is an adaptation mechanism to chronic inflammation and long lasting anorexia . It has pushed through the demands for amino-acids needed to meet the requirements of acute phase protein synthesis. Interestingly, it is clear now that skeletal muscles not only play a pivotal role in mobilization of amino-acids, but they are also the site of extensive production of acute phase proteins [Several signaling pathways have been shown to participate in cancer cachexia , 26. It tivation , whereastivation . Also JAtivation , 15. Rectivation . As leptctor LIF . This efpatients . In thisChojkier . TNF-α ind Booth . Moreoveer TNF-α . Insulinof NF-κB . TNF-α ale cells  and thatmyotubes . NF-κB rferation , myogeneferation . Thus, hnic mice , or by enic mice . Moreovectivator . Actuallof NF-κB . This ob wasting , 40. In  partner –43. Actu05 cells . Raising pathway , was als Figures , althougctively, . Presumantiation . At the s report  as IFNγ  Figures . One shoproteins . Overallα but not IFNα or IFNγ, except when they were administered together with TNF-α  or AG490 (JAK inhibitor) reversed some of the TNF-α-induced effects. Curcumin is a dominant NF-κB inhibitor as it prevents proteasomal degradation of IκB and subsequent NF-κB activation [α, given alone or together with IFNα or IFNγ increased nuclear expression of NF-κB with simultaneous drop in cytosolic expression of IκB , and associated cytosolic IκB expression level remained high (μM) was less potent than curcumin with respect to NF-κB/IκB expression levels  almost totally abrogated the above-mentioned effects of cytokines , which was unexpected as MyoD level was diminished at the same time. Interferons also stimulated MyHC IIa gene expression, but they were apparently weaker . Astonishingly, curcumin (1 μM) was unable to cease the action of either cytokine , although it markedly reduced the effect of TNF-α and IFNγ . AG490 significantly elevated MyHC IIa gene expression either alone or when it was given together with interferons (P < 0.01 versus control), but it abrogated TNF-α- but not IFNα-induced MyHC IIa gene activation. As MyHC IIa protein level decreased upon TNF-α or TNF-α and IFNs administration, two genes Atrogin1 and MuRF1 encoding respective ubiquitin ligases were examined. These genes were previously indicated as crucial for muscle fiber decay [α and IFNγ stimulated (P < 0.001 versus control), whereas IFNα did not affect Atrogin1 gene expression (P > 0.05 versus control). Curcumin protected myotubes from TNF-α-, TNF-α and IFNs-stimulated Atrogin1 gene expression (P > 0.05 versus control). Cytokine-induced Atrogin1 gene activation was considerably diminished by AG490; gene expression even dropped below the control level (P < 0.05 versus control). Surprisingly, AG490 given alone stimulated gene expression (P < 0.01 versus control). MuRF1 gene expression was activated by cytokines in a similar manner  but curcumin and AG490 could repress only TNF-α-induced gene activation . These results are in agreement with the well known effects of transcriptional activity of NF-κB, as both genes are targets in muscle wasting [α. In this study, however, AG490 drastically reduced Atrogin1 gene expression when added with cytokines. AG490 used individually elevated activity of Atrogin1 gene (P < 0.01 versus control). Monitoring of Atrogin1 and MuRF1 genes activity showed dominant effect of TNF-α . We speculate that NF-κB was a major player at the genomic level for TNF-α-induced effects. Where TNF-α was administered together with IFNs, curcumin addition could not repress increased Atrogin1 and MuRF1 genes activity . A similar effect was noted in the case of treatment with AG490. As mentioned above, this JAK/STAT inhibitor normalized Atrogin1 gene activity which was raised by TNF-α and IFNs, but it did not affect MuRF1 gene activity except for the situation when TNF-α was given alone (P < 0.001 versus control).To make the picture of cytokine-dependent muscle differentiation and muscle fiber decay more lucid, additional experiments followed by qRT PCR analysis have been performed. Observations obtained from this study suggest marked differences in the control of muscle differentiation and muscle wasting at genomic and translational levels. er decay , 49. TNF wasting , 50. Mucα, IFNα, IFNγ) to recruit STAT-1α. During this process release of NF-κB allowed both NF-κB and STAT-1α to cooperate at the genomic level. As we showed, some of the cachectic effects were evoked differently for TNF-α, IFNs, and both, as TNF-α-induced activation of Atrogin1 and MuRF1 genes was reduced by NF-κB and STAT-1α inhibitors , while the presence of IFNs deteriorated curcumin effect. Astonishingly, TNF-α was apparently mitogenic and stimulated viability of mononuclear muscle cells, whereas this cytokine efficiently inhibited muscle fiber formation. Moreover, TNF-α indirectly and directly diminished MyHC IIa protein level, even though it stimulated MyHC IIa gene expression. From qRT PCR study it became obvious that proteasome-ubiquitin system activity was activated. Actually, such reaction was previously reported by Tan et al. [Atrogin1 and MuRF1, the activation of MyHC IIa gene by TNF-α could be partially reversed by NF-κB and STAT-1α inhibitors. The effect of NF-κB and STAT-1α inhibitors was diminished upon IFNs cotreatment pointing to the synergy between TNF-α and IFNs in action. Insulin did not prevent combined TNF-α- and IFN-s-dependent muscle decay, even though it is almost ultimate anabolic hormone. Thus, where anyone thought to bring to an end the TNF-α-induced muscle cachexia, either the secretion of this cytokine or IFNs seems to be essential [Our hypothesis addresses competition between cytokines  on cell viability.Supplementary material 1: Dose-response and time-dependent curves showing long term effects of TNF-κB location in 3-day old C2C12 myotubes using confocal microscopy.Supplementary material 2: Immunofluorescent detection of NF-Supplementary material 3: Myotube formation from C2C12 myoblasts.Click here for additional data file.Click here for additional data file.Click here for additional data file.


H9N2 influenza viruses have been circulating worldwide in multiple avian species and have repeatedly infected humans to cause typical disease. The continued avian-to-human interspecies transmission of H9N2 viruses raises concerns about the possibility of viral adaption with increased virulence for humans. To investigate the genetic basis of H9N2 influenza virus host range and pathogenicity in mammals, we generated a mouse-adapted H9N2 virus (SD16-MA) that possessed significantly higher virulence than wide-type virus (SD16). Increased virulence was detectable after 8 sequential lung passages in mice. Five amino acid substitutions were found in the genome of SD16-MA compared with SD16 virus: PB2 , HA (L226Q) and M1 (R210K). Assessments of replication in mice showed that all of the SD16-MA PB2, HA and M1 genome segments increased virus replication; however, only the mouse-adapted PB2 significantly increased virulence. Although the PB2 E627K amino acid substitution enhanced viral polymerase activity and replication, none of the single mutations of mouse adapted PB2 could confer increased virulence on the SD16 backbone. The combination of M147L and E627K significantly enhanced viral replication ability and virulence in mice. Thus, our results show that the combination of PB2 amino acids at position 147 and 627 is critical for the increased pathogenicity of H9N2 influenza virus in mammalian host. H9N2 influenza viruses circulate worldwide and are endemic in multiple terrestrial avian species in Asia To date, some H9N2 viruses have demonstrated increased virulence for mammals. In 2007 to 2009, Bi et al isolated six H9N2 viruses from chickens in northern China that were highly lethal to mice with properties of systemic spread because they replicated well in multiple organs without prior adaptation The pathogenesis of influenza A viruses is a polygenic trait Mice are ideal animal models for investigating pathogenic mechanisms and host range determinants of influenza A viruses All animal research was approved by the Beijing Association for Science and Technology, the approve ID is SYXK (Beijing) 2007–0023, and complied with the guidelines of Beijing laboratory animal welfare and ethical of Beijing Administration Committee of Laboratory Animals.Human embryonic kidney (293T) and Madin-Darby canine kidney (MDCK) cells (Peking Union Cell Center) were maintained in Dulbecco's modified Eagle's medium  supplemented with 10% fetal bovine serum (FBS).The H9N2 virus A/chicken/Shandong/16/05 (SD16) was isolated from diseased chicken in Shandong, China and propagated in 10-day-old embryonated chicken eggs (ECE) at 35°C for 72 h. Virus titers were measured by plaque assay in MDCK cells and were expressed as plaque forming units (pfu). All experiments with live viruses and transfectants generated by reverse genetics were carried out in a biosafety level 3 conditions with investigators wearing appropriate protective equipment and compling with general biosafety standard for microbiological and biomedical laboratories of Ministry of Health of the People's Republic of China (WS 233–2002).Groups of five to seven week-old BALB/c mice  were lightly anesthetized with Zoletil 50  and inoculated intranasally with 50 μl of allantoic fluid containing SD16 virus. At 3 days post-inoculation (dpi), mice were euthanized and their lungs were harvested and homogenized, and 50 μl of supernatant from the centrifuged homogenate was used as inoculum for the next passage. After 8 passages, the infected mice died within 6 dpi. Then the virus in the lung homogenate was cloned twice by plaque purification in MDCK cells, and the cloned virus was passaged once in the allantoic cavities of 10-day-old ECE at 35°C for 72 h to prepare a virus stock. The experimental protocol was evaluated and approved by the Animal Pathogenic Microbiology Laboratory Bio-safety Committee, College of Veterinary Medicine, China Agricultural University.Viral RNAs were extracted from the allantoic fluid of ECE infected with plaque-purified mouse-adapted SD16 (SD16-MA) virus and the eight viral genes were amplified by Reverse transcription-PCR (RT-PCR). The amplified cDNAs were inserted into the genomic expression plasmid PHW2000 The eight gene segments of SD16 and SD16-MA were amplified by RT-PCR and cloned in the genomic expression plasmid, PHW2000. Mutations of interest in the PB2 gene were introduced by PCR-based site-directed mutagenesis with primer pairs containing point mutations. All of the constructs were sequenced to confirm the site-directed mutations.2. Six hours post-transfection, the supernatants were replaced with 2 ml of OPTI-MEM containing 2 μg/ml TPCK-trypsin (Sigma–Aldrich). Forty-eight hours post-transfection, the supernatants were harvested and propagated in 10-day-old ECE to produce stock viruses. Virus titers were determined by plaque assay on MDCK cells.SD16, SD16-MA, reassortant viruses between SD16 and SD16-MA, and SD16 PB2 mutants were generated by reverse genetics as described previously 5 pfu of viruses in 50 μl phosphate buffered saline (PBS). Three mice in each group were euthanized at 3 dpi, lungs, hearts, livers, spleens, kidneys and brains were collected for virus titration in MDCK cells. The remaining five mice in each group were monitored for weight loss and mortality for 14 days. Mice that lost more than 25% of their body weight were humanely euthanized.Groups of 5-week-old female BALB/c mice  were anesthetized with Zoletil 50  and inoculated intranasally with 1050), groups of five 5-week-old female mice anesthetized with Zoletil 50 and inoculated intranasally with 50 μl of 10-fold serial dilutions of viruses in PBS. The mice were monitored for 14 days. MLD50 was calculated and expressed in pfu.To determine the fifty percent mouse lethal dose .For cytokine quantification, mouse lungs collected at 3 dpi were stored in single use aliquots at −70°C. Lungs (n = 3) were homogenized individually in 500 μl tissue lysis buffer. Cytokine concentration in lungs were measured using the Bio-Plex Mouse Cytokine 8-Plex panels  with beads specific for mouse IL-1β, IL-2, IL-4, IL-5, IL-10, IFN-γ, TNF-α and GM-CSF. Array analysis was performed by the Bio-Plex Protein Array System .Confluent MDCK or A549 cells were infected with SD16, SD16-MA or rescued viruses at a multiplicity of infection (MOI) of 0.01, overlaid with serum-free DMEM containing 2 μg/ml TPCK-trypsin (Sigma–Aldrich) and incubated at 37°C. Cell supernatants were harvested every 12 hours until 60 hours post infection (hpi) and titrated by plaque assay on MDCK cells.The PB2, PB1, PA and NP gene segments of SD16, SD16-MA and SD16 PB2 mutants were inserted into pCDNA3.1 plasmid. The PB2, PB1, PA and NP plasmids (125 ng each) were transfected to sixty percent confluent 293T cells, together with fire-fly luciferase reporter plasmid pYH-Luci (10 ng) and internal control plasmid expressing renilla luciferase, Renilla (2.5 ng). After 24 hours of transfection, cell lysate was prepared with Dual-Luciferase Reporter Assay System (Promega) and luciferase activity was measured using GloMax 96 microplate luminometer (Promega).P-value less than 0.05 was considered statistically significant.Statistically significant differences between experimental groups were determined using analysis of variance (ANOVA) with the GraphPad Prism software package . A 6 pfu of virus per mouse. Survival of infected animals was monitored and virus titers of lung homogenates were determined after each passage. The mice infected with wild-type SD16 did not show any clinical symptom of disease and virus titer in the lung was 7.3 log10 pfu/ml. However, after 5 to 6 passages, virus titers increased to 8.5 to 8.8 log10 pfu/ml (data not shown). After 8 passages, mice showed a extensive weight loss and died within 6 dpi, indicating that mouse-adapted variants of H9N2 virus had acquired mutations that profoundly affected virulence.Most H9N2 influenza viruses are avirulent for mice P>0.05), the SD16-MA grew faster than SD16, reaching its maximum titers of 7.8 log10 pfu/ml at 24 hpi, versus virus titer of 5.7 log10 pfu/ml at 24 hpi (P<0.05) and reaching peak yield at 48 hpi for SD16 (10 pfu higher than SD16 before 60 hpi (P<0.05), while the peak yield of SD16-MA was similar to SD16 (P>0.05)  . These r50 value showed that SD16-MA was >103.5-fold more virulent than SD16 virus (5 pfu), all mice infected with SD16-MA exhibited clinical signs of disease, including decreased activity, huddling, bunched posture, and ruffled fur. Mice in this group lost 20.8% weight and began to die at 6 dpi ; IL-1β and IL-5 levels in lungs of mice infected with SD16 and SD16-MA were similar (P>0.05); while the levels of IL-10 and IFN-γ in lung homogenates of mice inoculated with SD16-MA were higher than those of SD16 infected mice (P<0.05). In summary, no obvious correlation was found between the production of inflammatory cytokines and chemokines and the viral pathogenicity.Inflammatory cytokines and chemokines have been suggested to be involved in the pathogenesis of animal and human infected with influenza viruses 10 pfu/g, P<0.05) than wild-type SD16 virus (∼5.7 log10 pfu/g)  . Both viTo identify the molecular markers responsible for the virulence of mouse-adapted variant in BALB/c mice, the genomes of the wild-type and mouse-adapted virus were sequenced. Sequence analysis identified five mutations among 3 genes that were involved in adaptation of SD16 strain to mice; specifically PB2 , HA (L226Q), and M (R210K) . The PB2P<0.05) was ∼achieved by PB2 E627K mutation that was similar for all mutant combinations that contained this mutation, PB2 E627K/M147L, PB2 E627K/V250G and PB2 E627K/M147L/V250G.To evaluate whether the observed mutations in the PB2 protein of mouse-adapted H9N2 variant affect polymerase activity, we measured the activity of reconstituted RNP complexes in 293T cells by a luciferase minigenome assay. SD16-MA carrying PB2 M147L, V250G, and E627K had polymerase activities that was ∼630% relative to wild-type SD16 virus (100%) . To assiin vitro, six single or double gene substituted viruses and six PB2 mutants were generated using the SD16 backbone. The inherent growth characteristics of these rescued viruses in MDCK and A549 cells were studied. Although the SD16-MA virus replicated faster in MDCK cells than SD16, none of the SD16 viruses containing SD16-MA genome segments grew to higher titers than the SD16 parental strain in MDCK cells. Whereas many reassortants generated lower yields than SD16, those reassortants containing SD16-MA PB2 and/or M genes replicated to the highest yields that were better than other single or double gene reassorted viruses (P<0.05), with the maximum titers ranging from 7.80–7.95 log10 pfu/ml (P<0.05), reaching maximum titers of more than 7.7 log10 pfu/ml at 48 hpi  and SD16:MA PB2-M (MLD50  = 103.6 pfu) were less virulent than SD16:MA PB2 (MLD50  = 103.5 pfu), indicating negative gene interaction effects for the combinations. These results indicated that mutations in PB2 alone were responsible for the greatest increases in replication and lethality of H9N2 virus in mice.To determine the role of each SD16-MA mutational gene in the virulence phenotype, six reassortant viruses  were gen50 and viral replication in lungs of these viruses in BALB/c mice were evaluated. Single amino acid substitution PB2 M147L or V250G did not increase the pathogenicity of SD16 in mice with MLD50 >106.5 pfu, while PB2 E627K slightly increased pathogenicity with MLD50 reduced more than 10-fold compared to wild-type virus (50  = 103.8 pfu ) to SD16:MA PB2 (MLD50  = 103.5 pfu)  , indicat16 virus  and 2. TViral adaptation is considered to be one of the major mechanisms for generating pandemic influenza viruses in vitro, but only the mouse-adapted PB2 gene significantly increased viral virulence. Thus all of the 3 mutant genes were demonstrated to possess increased replicative functions in mice indicating the functional basis for their selection on mouse adaptation. The PB2 gene has multiple functions, such as binding host capped mRNAs and initiating viral mRNA synthesis, making it an important pathogenic determinant et al adapted a wildtype duck H9N2 virus in quail and chickens through serial lung passages. The adapted viruses were readily infect mice and resulted in a quick selection of PB2 E627K mutation In the study, viruses containing SD16-MA PB2, HA or M gene all grew better in lungs of mice than SD16, whereas mutations in PB2 and M1 protein demonstrated increased viral replication ability Most of the previous studies found major contributions of single amino acid mutations to viral adaptation and virulence, such as PB2 E158G et al reported that PA N383D contributed to the difference in the polymerase activities of two H5N1 viruses, but could not increase viral virulence, which may be affected by high level of polymerase accumulation in the nucleus of influenza virus-infected cells. Here, PB2 E627K increased the polymerase activity and replication of virus, but did not significantly increase morbidity, as did the combination of V250G and E627K. Combining mutations at 147 and 627 in PB2 could confer increasing polymerase activity and virulence to the adapted virus. These results suggested that high polymerase activity was a prerequisite for the high virulence.Increased polymerase activity was considered to play a role in the adaptation of influenza viruses, because it corresponded to the optimal growth in mammalian cells, replicative fitness and virulence in mice in vivo and in vitro, but were not lethal for mice. These results suggested that high virus load was a prerequisite for the high virulence of virus in mice, but not sufficient. Other factors, such as polymerase activity and regulation of the proinflammatory response, also contribute to virulence of influenza viruses Viral replication is thought to be an important and characteristic prerequisite for virulence. Some highly pathogenic H5N1 avian influenza viruses and wild-type H9N2 viruses that were lethal to mice without adaptation all replicated well in lungs, and even replicated systemically In summary, using a highly lethal mouse-adapted H9N2 virus, we demonstrated mutations in PB2 protein were critical for the adaptation and virulence of H9N2 virus in mice. Although the E627K mutation on its own enhanced replication and polymerase activity, it did not significantly increase pathogenicity of virus in mice. The combination of M147L and E627K in PB2 was critical for the high virulence of mouse-adapted H9N2 virus.