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E, Guadagni F, Garaci E: Vaccination with a synthetic nonapeptide expressed in human tumors prevents colorectal cancer liver metastases in syngeneic rats. Int J Cancer 2004, 20:70–75.CrossRef 18. Tarro G: Tumor liberated protein from lung cancer and perspectives for immunotherapy. J Cell Physiol 2009, 221:26–30.PubMedCrossRef 19. Nicolini A, Carpi A, Tarro G: Biomolecular markers of breast cancer. Front Biosci 2006, 1:1818–1843.CrossRef 20. Garaci E, Sinibaldi P, Rasi G: A new tumour associated antigen of non-small cell lung cancer: tumour liberated proteins PLX3397 purchase (TLP)–a possible new tumor marker. Anticancer Res 1996,16(4B):2253–2255.PubMed 21. Bordignon V, Sinagra JL, Trento E, Pietravalle M, Capitanio B, Cordiali Fei P: Antigen specific cytokine responsein pediatric patients with atopic dermatitis. Pediatr Allergy Immunol 2005, 16:113–120.PubMedCrossRef 22. Albers AE, Strauss L, Liao T, Hoffmann TK,

Kaufmann AM: T cell-tumor interaction directs the development of immunotherapies in head and neck cancer. Clin Dev Immunol 2010, 2010:236378.PubMedCrossRef 23. Hodi FS: Cytotoxic T-lymphocyte-associated antigen-4. P005091 order Clin Cancer Res 2007, 15:5238–5242.CrossRef 24. Li Pira G, Ivaldi F, Moretti P, Manca F: High throughput T epitope mapping and vaccine development. J Biomed Biotechnol 2010, 2010:325720.PubMedCrossRef 25. Corbière V, Chapiro J, Stroobant V, Ma W, Lurquin C, Lethé B, van Baren N, Van den Eynde BJ, Boon T, Coulie PG: Antigen spreading contributes to MAGE vaccination-induced regression of melanoma metastases. Cancer Res 2011, 15:1253–1262.CrossRef 26. Sims S, Willberg C, Klenerman P: MHC-peptide tetramers for the analysis of antigen-specific T cells. Expert Rev Vaccines 2010, 9:765–774.PubMedCrossRef

RG7420 concentration 27. Bocharov G, Quiel J, Luzyanina T, Alon H, Chiglintsev E, Chereshnev V, Meier-Schellersheim M, Paul WE, Grossman Z: Feedback regulation of proliferation vs. differentiation rates explains the dependence of CD4 T-cell expansion on precursor number. Proc Natl Acad Sci USA 2011, 22:3318–3323.CrossRef 28. Lalvani A, Pareek M: Interferon gamma release assays: principles and practice. Enferm Infecc Microbiol Clin 2010, 28:245–252.PubMedCrossRef 29. selleck chemicals llc Andersen MH, Schrama D, Thor Straten P, Becker JC: Cytotoxic T cells. J Invest Dermatol 2006,126(1):32–41.PubMedCrossRef 30. Kurts C, Robinson BW, Knolle PA: Cross-priming in health and disease. Nat Rev Immunol 2010, 10:403–414.PubMedCrossRef 31. Voskoboinik I, Smyth MJ, Trapani JA: Perforin-mediated target-cell death and immune homeostasis.

IAH may play significant role in ischemic bowel complications [35]. Colonic necrosis [36] but also ischemic small bowel [37] can sometimes complicate to course of severe pancreatitis, but the role of IAH in these complications has not been studied. ACS probably plays SHP099 mouse a major role in early mortality caused by multiple organ failure in acute pancreatitis. Our own observation supports this: Pancreatitis patients with ACS had severe multi organ failure early during the course of the disease and early surgical decompression was associated with reduced mortality and none of the patients treated with decompression died during the first week [10]. In most cases adequate and

timely conservative management including ascites drainage [30] is successful, but if ACS develops despite these interventions, surgical decompression Momelotinib in vitro should be done without a delay. Midline laparostomy that allows inspection of bowel viability is recommended in order to diagnose possible ischemic lesions. In acute pancreatitis surgical decompression usually leads

to find more open abdomen of several weeks duration [10]. Vacuum assisted closure with mesh mediated fascial traction is a superior temporary abdominal closure method with low frequency of giant hernias [38, 39]. Nutrition There are no indications for fasting in pancreatitis. Although pancreatitis patient may have nausea and vomiting early during the course, these symptoms usually resolve rapidly. In patients with mild acute pancreatitis oral feeding can be started as soon as patient tolerates GPX6 food; early oral feeding has been associated with faster recovery and shorter hospital stay [40]. In pancreatitis enteral feeding is superior to parenteral feeding. Enteral nutrition prevents bacterial overgrowth in the intestine and reduces bacterial translocation [41]. In pancreatitis enteral nutrition reduces significantly systemic infections, organ dysfunction and mortality [13, 42]. Critically ill patients are typically at risk of malnutrition [43] and therefore nutrition of

patients with acute pancreatitis should be initiated as soon as possible. Initiation of enteral feeding seems to be critical in pancreatitis; if delayed for more than 48 hours, the benefits from enteral feeding are lost [44, 45]. The route of enteral feeding can be either gastric or post pyloric. Gastric feeding succeeds in most of the patients, and therefore feeding can be initiated by using a nasogastric tube [46]. Delayed gastric emptying may cause problems, and therefore gastric residual volume should be monitored every six hours. It is recommended that tube feeding is started with low infusion rate (10 ml/h) and increased by 10 ml/h until every six hours providing that gastric residual volume is below 250 ml [43]. This should be continued until target volume of enteral nutrition is achieved. If gastric emptying is problem prokinetics may help but better option is to place nasojejunal feeding tube, which usually resolves the problem.

9 at a mean of 2.88 months after addition of lercanidipine/enalapril, although the difference from baseline was not statistically significant (p = 0.321). Fig. 3 Therapeutic profile before (baseline) and after adding lercanidipine/enalapril 10/20 mg fixed-dose combination. ACEI angiotensin-converting enzyme inhibitor, ARAII angiotensin II receptor antagonist, CCB calcium channel blocker, FDC fixed-dose combination, RI renin inhibitor 3.4 Tolerability Treatment with lercanidipine/enalapril was well tolerated. Treatment-emergent adverse effects occurred in only one patient (0.3 %), who developed a persistent dry cough after the initiation of lercanidipine/enalapril treatment. This cough was considered to be possibly

related to treatment with enalapril. None of the patients developed edema. 4 Discussion This observational registry study showed that treatment with a lercanidipine/enalapril FDC was associated with significant reductions in SBP FG4592 and DBP and a significant increase in the proportion of patients achieving BP control compared with baseline. The reduction in BP observed in our study was as expected with combinations of two or more antihypertensive drugs. A meta-analysis Elafibranor supplier by Law et al. [11] found that the use of two antihypertensive drugs at half-standard doses produced reductions in SBP and DBP of 13.3 and 7.3 mmHg, respectively;

corresponding values for three drugs at half-standard doses were 19.9 and 10.7 mmHg, respectively11. Our results are also in agreement with the well known efficacy of an FDC of a CCB with a modulator of the RAS [20], even if we consider the relatively old population evaluated, and the extended period of treatment between diagnosis and inclusion in this study. In this context, the rate of Atorvastatin BP control was also impressive, being observed in 51 % of patients with BP <140/90 mmHg after a mean of 2.88 months of treatment with the fixed-dose regimen. In randomized, controlled phase III trials of lercanidipine/enalapril FDC, reductions in SBP and DBP of

7.7–9.8 and 7.1–9.2 mmHg, respectively, were observed after 12 weeks of treatment [21]. The reductions in SBP and DBP observed in our study were greater than this (18.08 and 10.10 mmHg, respectively). In these two studies, the proportion of patients with normalized SBP and DBP was 22–24 % [21]. It should be noted that these studies included only patients who had not achieved BP control with either MK-4827 clinical trial lercanidipine or enalapril as monotherapy, and this could have contributed to the smaller reductions in BP and lower BP control rates compared with our study. Furthermore, one of these studies used a lower dose of enalapril (10 mg) than in our study and produced smaller reductions in SBP and DBP than seen with lercanidipine/enalapril 10/20 mg in the second study. It should also be noted that the patients included in our registry had been receiving antihypertensive regimens prescribed by general practitioners rather than specialists.

(b) Logistic regression multivariate analysis of the gene expression values was performed to evaluate the AUC of each gene and of different multi-gene combinations. Significance of associations AZD6738 between gene expressions was determined using a logrank test.

The best set of coefficient values that maximize the separation between the positive and negative groups were determined. Later, the log ratio calculation was determined in order to reduce the impact of possible noise (c). Thresholds were then set to evaluate sensitivity, specificity and the stability of the prediction. Two individual genes were combined to form a gene pair (d). Then the single pair of genes was https://www.selleckchem.com/products/mcc950-sodium-salt.html coupled to form 2-pair and then 3-pair gene combinations. Logistic regression values were calculated for each gene pair, and we showed that in each case when genes were combined, the area under the curve (AUC ROC) increase.d Of the 234 probe sets, we found that the three selected most frequently and in the best combinations mapped

to genes LDLRAP1 (low density lipoprotein receptor adaptor protein 1), PHF20 (PHD finger protein 20) and LUC7L3 (cisplatin resistant-associated overexpressed protein, also known as CROP), with AUCs of 0·92, 0·97 and 0·96, respectively (Figure 2). The standard errors were relatively very small, at 0·013, 0·007 and 0·008, respectively. The cluster Anlotinib diagram in Figure 2 CYTH4 is based on a combination of these three primary genes with 3 secondary suppressor genes and shows that, to a large extent, the NPC samples stand apart from the controls, which are dispersed throughout the group of samples with other diseases. Figure 2 ROCs of probes that contribute to differentiation of nasopharyngeal carcinoma from other conditions. Combination of 6 genes with three genes appearing most frequently in all top-performing combinations

LDLRAP1, PHF20 and LUC7L3. The additional three secondary genes have little NPC discrimination (ROC AUC: 0.51 – 0.77) but help suppress confounding factors. ROC AUC for each gene is listed in table. Dendrogram for the six-gene combination showing control samples dispersed throughout the “other” sample group with a separate cluster consisting mainly of NPC samples on the right. Heat map and clustering are based on results of 2-fold cross validation iterated 1000 times. This combination of three primary genes (LDLRAP1, PHF20, LUC7L3), together with their associated suppressor genes (EZH1, IFI35, UQCRH), was subjected to 2-fold cross-validation with 1000 iterations. The average ROC AUC was 0.98 (95% C.I. 0.98 – 0.99). An equivalent analysis using randomized NPC status achieved an average ROC AUC of 0.50 (95% C.I. 0.37 – 0.62). There was no overlap between these two distributions. These 6 genes were run on qPCR for a subset of 26 controls and 44 NPC cases for which sufficient mRNA was available.

The catalytic core was defined buy VX-680 by a set of structurally conserved elements, including elements P3 to P8. A G-C pair within P7, i.e. G391-C277 of https://www.selleckchem.com/products/Trichostatin-A.html intron-F was assumed to be G-binding positions [14]. Extended P5 and P9 stems were displayed in the putative structure of intron-F from PV1. Nine intron-Fs from nine strains (PV2, 3, 28, 33, 34 and 41 and TH9, 31 and 35) of P. verrucosa

were predicted to be the same structures as the putative structure of intron-F derived from PV1 drawn in Figure 4[A], alternatively, shown in Additional file 3. These nucleotide variations among intron-F were observed mainly in the loop and at four positions where one nucleotide of P5a, two of P5.1a and one of P5.2 stem were positioned. The base pairs GU and CG within P6 were

formed in the core region of intron-F [12]. The nucleotides A71, A72, U73 were located in segments J3/4 of PV1 intron-F [15–18]. These predictions of secondary structure revealed that all intron-Fs were IC1 group 1 introns. Figure 4 A-C. – Diagrams for predicted secondary structure of P. verrucosa. [A]: intron-F from rDNA of PV1, [B]: intron-G from PV1 and [C]: intron-G from PV3. Capital letters indicate intron sequences and lowercase letters indicate flanking exon sequences. Arrows point to the 5′ and 3′ splice sites. The guanosin cofactor-binding sites are marked with *. The structure of intron-G (L1921) from PV1 was drawn just as was done for intron-Fs (Figure 4[B]). A G-C pair within P7, i.e. G390-C360, was assumed to be the G-binding positions. The GU-CG pair of P6 and the AAU in J3/4 was the same as in the intron-F core region of PV1. This putative selleck inhibitor intron-G exhibited expanded regions of P1 and P5. The three intron-Gs of PV1, PV33 and PV34 were found to be similar among the three strains. Different features were found in PV3 as shown the in Figure 4[C] wherein the sequence of PV3 differed in P1 region among four trains; namely, short stems in P1b and P1c and small bulge loops of L1 and L1a (Additional file 4). Moreover, PV3 added P2.0 and P8c, although the other intron-Gs did not. Prediction structures in the remaining two introns of PV33 and PV34 are not shown. Nevertheless, all subgroups

of intron-G were also identified as IC1, based on comparison of tertiary structures across segments P3-7 of the four strains. In conclusion, we have identified that the ten intron-Fs and four intron-Gs of P. verrucosa belong to IC1 group 1 introns. Characterization of intron-H Loss of P5abcd domain in derived S788 introns was correlated with inability to self-splice in vitro in a previous report [19]. Accordingly, we have not confirmed insertion positions of intron-H by RT-PCR. However, we examined PV-28 strain as the representative strain of intron-H by analyzing the sequence alignment of the core region of subgroup IE from other organisms in the database. Moreover, we predicted the secondary structure of this intron-H as shown in Figure 5.

By statistical analysis, two clusters of strains were obtained. OI-122 encoded genes ent/espL2, nleB and nleE were most characteristic for Cluster 1, followed by OI-71 encoded genes nleH1-2, nleA and nleF. EHEC-plasmid encoded genes katP, etpD, ehxA, espP,

saa and subA showed only medium to low influence on the Selleck GS-1101 formation of clusters. Cluster 1 was formed by all EHEC (n = 44) and by eight of twenty-one EPEC strains investigated, whereas Cluster 2 gathered all LEE-negative STEC (n = 111), apathogenic E. coli (n = 30) and the remaining thirteen EPEC strains [17]. These findings indicate that some EPEC strains share non-LEE encoded virulence properties with O157:H7 and other EHEC strains. Such EPEC strains could be derivatives of EHEC which have lost their stx-genes but could also serve as a reservoir for the generation of new EHEC strains by uptake of stx-phages [16, 20, 25, 26]. To classify strains of the EPEC group according to their relationship to EHEC we have investigated 308 typical and atypical EPEC strains for the presence of nle-genes of O-islands OI-57, OI-71 and OI-122, as well as prophage and EHEC-plasmid-associated genes. OI-122 encoded genes were found to be NSC 683864 significantly associated with atypical EPEC strains that showed close similarities to EHEC regarding their serotypes and other virulence traits. In typical EPEC, the presence of O-island 122 was significantly

associated with strains which are frequently the cause of outbreaks and severe disease in humans. Results Cluster analysis of EHEC, EPEC, STEC and apathogenic Roscovitine clinical trial E. coli strains E. coli pathogroups were established as described in the Methods section. The frequencies and associations between virulence genes and E. coli pathogroups are presented in Table 1. The linkage of genes according to their respective PAI or the EHEC-plasmid was 94.7% (230/243) for OI-122, 41.8% (142/340) for OI-71, 46.2% (80/173) for OI-57 and 1.8% (4/220) for the EHEC-plasmid. As not all PAIs were found to be genetically conserved we decided to perform the cluster analysis on single genes. The results

from the cluster analysis using thirteen virulence genes that were taken as cluster variables are presented IMP dehydrogenase in Table 2. The 445 strains belonging to 151 different serotypes divided into two clusters. Cluster 1 encompassed all 64 EHEC strains, as well as 46 (63%) of the typical and 129 (54.9%) of the atypical EPEC strains. The remaining 133 EPEC strains, as well as all STEC (n = 52) and apathogenic E. coli (n = 21) were grouped into Cluster 2. The distribution of PAIs and the EHEC-plasmid according to E. coli pathogroups is presented in Figure 1. Table 1 Frequency and associations between virulence genes and E. coli pathogroups Genetic element Virulence gene EHEC (n = 64) n, % (95%-CI)a typical EPEC (n = 73) n, % (95%-CI)a atypical EPEC (n = 235) n, % (95%-CI)a STEC (n = 52) n, % (95%-CI)a E. coli (n = 21) n, % (95%-CI)a pMAR2 [12] bfpA 0, 0 (0;5.6) 68b , 93.2 c (84.7;97.7) 0, 0 (0;1.6) 0, 0 (0;6.

1999; Rehmany et al. 2005; Allen et al. 2004). Amino acid signature motifs (RXLR-dEER) were identified in the first oomycete avirulence genes discovered (Birch et al. 2006; Tyler et al.

2006) which were demonstrated to be translocation signals to move these associated proteins into plant cells (Whisson et al. 2007). The complete genome sequences are now available for three Phytophthora species (Haas et al. 2009; Tyler et al. 2006), for Pythium ultimum (Lévesque et al. 2010) and Hyaloperonospora arabidopsidis (Baxter et al. 2010). The RXLR effectors are very Anlotinib common in Phytophthora and Hyaloperonospora but are absent in Pythium ultimum. Many more genome sequences will become available and we are now reaching a new level of understanding of how species differ from each other. Oomycetes as pathogens Oomycetes pathogens are found on all crops and in many aquatic or terrestrial plants as well as in many animals. All the different impacts of oomycetes as plant or animal pathogens cannot be covered here but a few significant examples deserve to be discussed. The re-emergence of a disease The most famous, or maybe infamous, MLN2238 nmr oomycete is Phytophthora infestans, the species that caused the Irish potato famine in the 1800’s. Until the 1980’s, only a single clonal lineage of the A1 mating type was present outside Mexico or the Andes (Goodwin et al. 1994),

the centre of origin being still GS-4997 debated (Grunwald and Flier 2005; Gomez-Alpizar et al. 2007), eltoprazine and after that the A2 mating type was introduced to both Europe and North America. This caused P. infestans to re-emerge as a very serious threat to potato cultivation by increasing its aggressiveness towards the host, reducing fungicide efficacy, facilitating its survival in soil or debris and broadening its host range to include tomato (Fry et al. 1992; Fry and Goodwin 1997; Gavino et al. 2000; Lee et al. 1999). Because of the significant impact

of this migration, P. infestans has become a model system for population genetics and the basis of international collaborations for population tracking (Cooke and Lees 2004; Goodwin et al. 1992; Forbes et al. 1998; Fry et al. 1992). Forestry Fifty years ago, the number of known species of oomycetes having an impact on forestry was quite low. Phytophthora cinnamomi and P. cambivora were the most notable disease agents (Brasier 2000). More recently the impact of oomycetes on forestry has increased dramatically with wider ranges of known diseases and more importantly the emergence of agents that were not previously known. Prior to 2000, only 20% of Phytophthora species were known to have an impact in forestry whereas 60% of the species described since that time are associated with forestry or natural environments (Brasier 2009). This exponential growth post 2000 is mainly due to new species of Phytophthora being described that are associated with forestry (Fig.

5-fold above or below the average of the spots. (DOC 44 KB) Additional file 3:: HTF-Microbi.Array probe list. Sequences (5’ - > 3’) for both discriminating (DS) and common probe (CP) are reported, check details as well as major thermodynamic parameters [melting temperature

(Tm), length (bp), number of degenerated bases (Deg)]. (DOC 64 KB) Additional file 4:: HTF-Microbi.Array raw fluorescence data obtained from the analysis of faecal stools from 19 atopic children (A) and 12 healthy controls (C). (XLSX 207 KB) Additional file 5:: Layout of the HTF-Microbi.Array and complete ZipCode sequences. (PDF 19 KB) Additional file 6:: Box plots of the HTF-Microbi.Array fluorescence signals from atopics and controls. P values Ferrostatin-1 mouse corresponding to the difference in fluorescence response between the two groups are indicated for each probe. (PDF 82 KB) References 1. Romagnani S: Regulatory T cells: which role in the pathogenesis and treatment of allergic disorders? Allergy 2006, 61:3–14.PubMedCrossRef 2. Ngoc PL, Gold DR, Tzianabos AO,

Weiss ST, Celedón JC: Cytokines, allergy, and asthma. Curr Opin Allergy Clin Immunol 2005, 5:161–166.PubMedCrossRef 3. Penders J, Stobberingh EE, van den Brandt PA, Thijs C: The role of the intestinal microbiota in the development of atopic disorders. Allergy 2007, 62:1223–1236.PubMedCrossRef 4. Ehlers S, Kaufmann SH, Participants of the 99(th) Dahlem Conference: Infection, BAY 11-7082 clinical trial inflammation, and chronic diseases: consequences of a modern lifestyle. Trends Immunol 2010, 31:184–190.PubMedCrossRef 5. Rautava S, Ruuskanen O, Ouwehand A, Salminen S, Isolauri E: The hygiene hypothesis of atopic disease–an extended version. J Pediatr Gastroenterol Nutr 2004, 38:378–388.PubMedCrossRef 6. De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, Collini S, Pieraccini G, Lionetti P: Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A 2010, 107:14691–14696.PubMedCrossRef Sclareol 7. Kau AL, Ahern PP, Griffin NW, Goodman AL, Gordon JI: Human nutrition, the gut microbiome and the immune

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155:2907–2918.CrossRef 54. Yin X, Wheatcroft R, Chambers JR, Liu B, Zhu J, Gyles CL: Contributions SCH772984 mouse of O-island 48 to adherence of Enterohemmorrhagic Escherichia coli O157:H7 to epithelial cells in vitro and in ligated pig ileal loops. Appl Environ Microbiol 2009, 75:5779–5786.PubMedCentralPubMedCrossRef 55. Dziva F, Mahajan A, Cameron R, Currie C, McKendrick , Wallis TS, Smith DGE, Stevens MP: EspP, a TypeV-secreted serine protease of enterohaemorrhagic Escherichia coli O157:H7, influences intestinal colonization of calves and adherence to bovine primary intestinal epithelial cells. FEMS Microbiol Lett 2007, 271:258–264.PubMedCrossRef 56. McAllister TA, Bae HD, Jones GA, Cheng KJ: Microbial attachment and feed digestion in the rumen. J Anim Sci 1994, 72:3004–3018.PubMed Competing interests The authors ABT-263 research buy declare no competing financial interests. Authors’ contributions ITK was the project leader and designed, coordinated, conducted experiments, analyzed results, interpreted

data and drafted the manuscript. TBS assisted in design of experiments, VFA analysis, interpreted results and contributed to the final draft of the manuscript. JDL conducted iTRAQ proteomics, verified data generated

and contributed to the final draft of the manuscript. All authors read and approved the final manuscript.”
“Background Dimethyl sulfoxide Haemophilus influenzae is a γ-Proteobacterium from within the order the Pasteurellacae. It is an obligate human commensal of the nasopharynx and in most cases it remains as a commensal but some BIRB 796 strains can transit from the nasopharynx to other parts of the body and in doing so cause numerous types of disease [1]. There are strain-specific factors that enable pathogenic strains to transit to, and then survive within, different parts of the body, where the stresses of multiple environmental conditions require a breadth of adaptive abilities that permit survival and growth [2]. There are a number of physical parameters that are known to vary between parts of the human host, including: oxygen tension, carbon/energy/nitrogen source, pH and the presence of reactive oxygen and reactive nitrogen species. Defence against these can be directly encoded through detoxification genetic pathways, but also through broader mechanisms for environmental adaptation. In addition to specific pathways that respond to and deal with each of the damaging physical or chemical stressors present within the various environments the bacteria may encounter, many bacteria have a capacity to switch their lifestyle such that these stresses no longer cause damage to their cell.

5) in the other in the same serotype of dengue virus. (XLSX 12 KB) Additional file 5: Figure S1: Condon context patterns of DENV 1, 2, 3 and 4. (DOCX 115 KB) Additional file 6: List of positively and negatively selected sites in dengue virus genes. (XLSX 213 KB)

References 1. Kyle JL, Harris E: Global spread and persistence of dengue. Annu Rev Microbiol 2008, 62:71–92.PubMedCrossRef 2. Gubler DJ: Cities spawn epidemic dengue viruses. Nat Med 2004, Selleck HDAC inhibitor 10:129–130.PubMedCrossRef 3. Ramanathan MP, Kuo YC, Selling BH, Li Q, Sardesai NY, Kim JJ, Weiner DB: Development of a novel DNA SynCon tetravalent dengue vaccine that elicits immune responses against four serotypes. Vaccine 2009, 27:6444–6453.PubMedCrossRef 4. Guzman MG, Halstead SB, Artsob H, Buchy P, Farrar J, Gubler DJ, Hunsperger E, Kroeger A, Margolis HS, Martínez E, Nathan MB, Pelegrino JL, Simmons C, Yoksan S, Peeling RW: Dengue: a continuing global STAT inhibitor threat. Nat Rev Microbiol 2010,8(Suppl 12):7–16.CrossRef 5. Gubler DJ, Trent DW: Emergence of epidemic dengue/dengue hemorrhagic fever as a public health problem in the Americas. Infect Agents Dis 1993, 2:383–393.PubMed

6. Holmes EC, Burch SS: The causes and consequences of genetic variation in dengue virus. Trends Microbiol 2000, 8:74–77.PubMedCrossRef 7. Holmes EC, Twiddy SS: The origin, emergence and evolutionary genetics of dengue virus. Infect Genet Evol 2003, 3:19–28.PubMedCrossRef 8. McBride WJ, Bielefeldt-Ohmann H: Dengue viral infections; pathogenesis and epidemiology. Microbes Infect 2000, 2:1041–1050.PubMedCrossRef 9. Lewis JA, Chang GJ, Lanciotti RS, Kinney RM, Mayer LW, Trent DW: Phylogenetic relationships of dengue-2 viruses. Virology 1993, 197:216–224.PubMedCrossRef 10. Rico-Hesse R, Harrison LM, Nisalak

A, Vaughn DW, Kalayanarooj S, Green S, Rothman AL, Ennis FA: Molecular evolution of dengue type 2 virus in Thailand. Am J Trop Med Hyg 1998, 58:96–101.PubMed 11. Leitmeyer KC, Vaughn DW, Watts DM, Salas R, Villalobos I, De C, Ramos C, Rico-Hesse R: Dengue virus structural differences that correlate with pathogenesis. J Virol 1999, 73:4738–4747.PubMed 12. Diamond MS, Edgil D, Roberts TG, Lu B, Harris E: Infection of human cells by dengue virus is modulated by different cell types and viral strains. J Virol 2000, Urocanase 74:7814–7823.PubMedCrossRef 13. Zanotto PM, Gould EA, Gao GF, Harvey PH, Holmes EC: Population dynamics of flaviviruses revealed by molecular phylogenies. Proc Natl Acad Sci U S A 1996, 93:548–553.PubMedCrossRef 14. Twiddy SS, Farrar JJ, Vinh Chau N, Wills B, Gould EA, Gritsun T, Lloyd G, Holmes EC: Phylogenetic relationships and differential selection pressures among genotypes of dengue-2 virus. Virology 2002, 298:63–72.PubMedCrossRef 15. Twiddy SS, Woelk CH, Holmes EC: Phylogenetic evidence for adaptive evolution of dengue viruses in Q-VD-Oph chemical structure nature. J Gen Virol 2002, 83:1679–1689.PubMed 16.