In fact, in the majority of cases, the region outlined by the radiologist as malignant

appears spatially inhomogeneous, with areas of vascular proliferation and areas of necrosis. The presence of necrotic tissue inside the lesion, in particularly in high-grade Ilomastat price gliomas and large metastases, surely affects data, decreasing the average values of blood volume, flow and permeability. It can be supposed that, for these reasons, some parameters such as CBV and CBF did not appear to be significant for identifying the lesion, contrary to the results of other authors [7–9]. The complexity of the microvascular environment of tumor is clearly shown by the blood volume maps Temsirolimus manufacturer (see Fig. 1, 2): for some patients, the outlined ROIs are very large, with areas up to 500.0 mm2, as demonstrated by the histogram in Fig. 3. Nevertheless, this variability allowed

us to identify among the perfusion maps those having the highest PFT�� cell line prognostic power. Using the ROC curves, it was possible to establish the predictive value of each parameter that resulted statistically significant: PS, Pat Rsq and T peak . Both Pat Rsq and PS were confirmed to be equally reliable metrics for discriminating between malignant and normal tissues, with AUCs of 0.82 and 0.81 respectively, and pz value of 0.02. Instead, T peak was not found to be significant, with an AUC of 0.68 and pz value of 0.11. The strong relation between PS and Pat Rsq has also been confirmed by the Spearman correlation coefficient (Table 6) and the scatter plot in Fig. 5. The perfusion studies, both with CT and or MRI, considered by recent studies, can be used for preoperative grading of the gliomas, in particularly for the differential diagnosis of low and high-grade selleck screening library astrocitomas because these technique can provide complementary information about tumor hemodynamics, not available with conventional CT or MR. The potential role of these techniques in follow-up analysis, lies in the differential

diagnosis between radiation necrosis and recurrence in patients who have undergone radiotherapy and in the evaluation of the response to the anti-angiogenetic therapy, and its ability to detect the biological effects to treatment by depicting early microvascularization modifications, related to a reduction in microvessel density, before tumor dimension modifications [21–24]. Conclusion Tumors are characterized by higher values of all the perfusion parameters. Using statistical analyses both the PS and Pat Rsq resulted significant for discriminating between malignant and normal tissue, with comparable prognostic power. Additional studies, including a greater quantity of data, to differentiate between the patients with high and low grade tumors, or those with radionecrosis and recurrence are warranted.

PubMedCrossRef 24. Ranjard L, Lejon DP, Mougel C, Schehrer L, Merdinoglu D, Chaussod R: Sampling strategy in molecular microbial ecology: influence of soil sample size on DNA fingerprinting analysis of fungal and bacterial communities. Environ Microbiol 2003, 5:1111–1120.PubMedCrossRef 25. Braid MD, Daniels LM, Kitts CL: Removal of PCR inhibitors from soil DNA by chemical flocculation. J Microbiol Meth 2003, 52:389–393.CrossRef 26. Yankson KK, Steck TR: Strategy for extracting DNA from clay soil and detecting a specific target sequence via selective enrichment

and real-time (quantitative) PCR amplification. Appl Environ Microbiol 2009, 75:6017–6021.PubMedCrossRef 27. Cai P, Huang Q, Zhang X, Chen H: Adsorption of DNA on clay minerals and various colloidal particles from an Alfisol. Soil Biol Biochem 2006, 38:471–476.CrossRef 28. De la Varga H, Águeda B, Martínez-Peña F, Parladé Tariquidar ic50 J, Pera J: Quantification of extraradical soil mycelium and ectomycorrhizas ofBoletus edulisin a Scots click here pine forest with variable sporocarp productivity. Mycorrhiza 2011,  : . 29. Bridge P, Spooner BM: Soil fungi: diversity and detection. Plant Soil 2001, 232:47–154.CrossRef 30. Nilsson RH, Kristiansson E, Ryberg M, Hallenberg N, Larsson KH: Intraspecific ITS variability in the kingdom fungi as expressed in the international sequence

databases and Its implications for molecular species identification. Evol Bioinform 2008, 4:193–201. 31. Iotti M, Amicucci A, Bonito G, Bonuso E, Stocchi V, Zambonelli A: Selection of a set of specific primers for the SYN-117 chemical structure identification ofTuber rufum: a truffle species PtdIns(3,4)P2 with high genetic variability. FEMS Microbiol Lett 2007, 277:223–231.PubMedCrossRef 32. Mello A, Murat C, Vizzini A, Gavazza V, Bonfante P: Tuber magnatumPico, a species of limited geographical distribution: its genetic diversity

inside and outside a truffle ground. Environ Microbiol 2005, 7:55–65.PubMedCrossRef 33. Murat C, Díez J, Luis P, Delaruelle C, Dupré C, Chevalier G, Bonfante P, Martin F: Polymorphism at the ribosomal DNA ITS and its relation to postglacial re-colonization routes of the Perigord truffleTuber melanosporum. New Phytol 2004, 164:401–411.CrossRef 34. Wedén C, Danell E, Camacho FJ, Backlund A: The population of the hypogeous fungus Tuber aestivum syn. T. uncinatum on the island of Gotland. Mycorrhiza 2004, 14:19–23.PubMedCrossRef 35. Bonuso E, Zambonelli A, Bergemann S, Iotti M, Garbelotto M: Multilocus phylogenetic and coalescent analyses identify two cryptic species in the Italian bianchetto truffle,Tuber borchiiVittad. Conserv Genet 2010, 11:1453–1466.CrossRef 36. Frignani F: Analisi floristico-vegetazionale delle tartufaie sperimentali situate in Toscana ed Emilia Romagna.    ,  : . [http://​www.​agrsci.​unibo.​it/​magnatum/​home.​htm >Risultati > Analisi floristiche - vegetazionali > Emilia Romagna e Toscana] 37. Ciaschetti G: Analisi floristico-vegetazionale delle tartufaie sperimentali situate in Abruzzo ed in Molise.

The results are the means ± standard deviation of four sets of experiments. Figure 3 Overepression of A. fumigatus AfCrzA increased the mRNA accumulation of several genes. Fold increase in mRNA levels after the growth of the wild type and alcA::crzA

mutant strain in MM+2% glycerol+2% ethanol for 6 hours at 37°C of (A) AfpmcB (Afu3g10690), (B) AfzfpA (Afu8g05010), (C) A. fumigatus Phospholipase D (Afu2g16520), (D) AfctfA (Afu4g03960), (E) Af BAR adaptor protein (Afu3g14230), (F) AfrcnA (Afu2g13060), (G) AfrfeF (Afu4g10200), (H) Af AAA ATPase (Afu4g04800), and (I) Afscf1 (Afu1g17370). The relative quantitation of all the genes and tubulin gene expression was determined by a standard curve (i.e., CT -values plotted against logarithm of the DNA copy number). The results are the means YH25448 ± standard deviation Eltanexor of four sets of experiments. The values represent the number of times the genes are expressed compared to the corresponding

wild type control strain (represented absolutely as 1.00). A. fumigatus AfRcnA belongs to a class of endogenous calcineurin regulators, calcipressins, a family of calcineurin-binding proteins, conserved from yeast to mammals [34, 35]. A phylogenetic analysis was performed to determine the relationship of AfRcnA to calcipressin homologues in several different organisms (Additional file 3, Figure S1). The see more mechanism how this protein family functions still remains controversial. There are reports showing that calcipressins can both stimulate and inhibit the calcineurin pathway 34 35 36. Induction of S. cerevisiae RCN1-lacZ in response to calcium was completely blocked

by addition of FK506 or by deletion of the genes encoding Tcn1p or calcineurin [33]. The S. cerevisiae RCN1 is also induced by calcium, repressed by calcium+FK506 and in the crz1 background [30]. Another member of this family, Cbp1, was identified in Cryptococcus neoformans, and is required for mating but not for growth at 37°C [37]. We have observed that AfrcnA mRNA accumulation upon calcium stress is dependent on both calcineurin and AfCrzA (Figure 1A). These results suggest that both S. cerevisiae and A. fumigatus RCAN homologues may Oxymatrine be downstream targets of the calcineurin-dependent transcription factor. This fits a model where increased A. fumigatus AfRcnA regulation in response to calcineurin signaling is possibly a negative-feedback mechanism modulating calcineurin acitivity. We constructed an A. nidulans alcA::AncrzA also by replacing the endogenous AncrzA promoter region homologously with the A. nidulans alcA promoter. We investigate the genetic interactions between ΔAncnaA and ΔAncrzA mutations and a double mutant ΔAncnaA ΔAncrzA displays the same growth behavior than the ΔAncnaA mutant indicating as expected that AncnaA is epistatic to AncrzA (data not shown).

On the other hand, it should be noted that improperly-performed paraffin embedding damages DNA and can favor methods that are more robust to variation in the amount and quality of the starting material (this would arguably disfavor TheraScreen because it requires eight PCR reactions whereas the other methods HDAC cancer require only one equivalent reaction). It has been suggested that the issue of limited material for testing can be largely circumvented by using whole genome amplification techniques [39, 40], although the potentially biasing impact of the genome amplification techniques on low frequency somatic mutation genotyping is still not fully addressed.

However, we suppose that our tests of kit performance on frozen tissue samples provide useful insights into their general utility and will be valuable for orchestrating genotyping efforts across molecular pathology laboratories. Conclusions The performance of five methods (Direct sequencing, Pyrosequencing, High resolution melting analysis, the TheraScreen DxS kit, C188-9 mouse and the K-ras StripAssay) for Selleck PARP inhibitor detecting mutations in the KRAS gene was compared using DNA extracted from 131 frozen NSCLC samples. The TheraScreen DxS kit was found to be the most effective, followed by the StripAssay kit. However, because of the heterogeneity of typical cancer tissue samples and the differences in the two methods’ mechanisms

of action, there are still unsatisfactory numbers of discrepancies between these two ‘best’ methods, which failed to agree on 8 of the 131 specimens examined in this work. Nevertheless, our findings

should facilitate the rational selection of methods for detecting mutations at the KRAS locus using heterogeneous clinical samples obtained from biopsies of cancer patients. Acknowledgements This research was supported by grants from the Ministry of Industry and Trade not (MPO TIP FR-TI1/525), and the Ministry of Health of the Czech Republic (NT 13569 and NS 9959) and Internal Grant Agency of Palacky University (IGA UP VG911100371/32). Infrastructural part of this project (Institute of Molecular and Translational Medicine) was supported by the Operational Program “Research and Development for Innovations” (project CZ.1.05/2.1.00/01.0030). References 1. Jancik S, Drabek J, Radzioch D, Hajduch M: Clinical relevance of KRAS in human cancers. J Biomed Biotechnol 2010., 2010: 150960. 1–13, Epub 2010 Jun 7 2. Lorigan P, Califano R, Faivre-Finn C, Howell A, Thatcher N: Lung cancer after treatment for breast cancer. Lancet Oncol 2010, 11:1184–1192.PubMedCrossRef 3. Matesich SM, Shapiro CL: Second cancers after breast cancer treatment. Semin Oncol 2003, 30:740–748.PubMedCrossRef 4. Vasudevan KM, Garraway LA: AKT signaling in physiology and disease. Curr Top Microbiol Immunol 2010, 347:105–133.PubMedCrossRef 5.

Materials and Methods: RCAS1 and CD68 antigens immunoreactivity was determined in 50 tissue samples of salivary gland adenocarcinomas and in 50 tissue samples of their stroma and 30 tissue samples of healthy control (palatine tonsils) by immunohistochemistry method in the Department of Pathology. Results: RCAS1 immunoreactivity was identified in both adenocarcinoma and healthy stromal samples. Significantly higher RCAS1 immunoreactivity was shown in the cancer samples than in stromal samples. RCAS1 immunoreactivity in stromal samples was significantly higher in patients with the presence of lymph node metastases in comparison to patients without metastases. We also observed Vactosertib significantly higher number of CD68

positive cells (macrophages) in adenocarcinoma samples and in stromal samples than in the control group. Moreover, the number of CD68 positive cells in adenocarcinoma and stroma were higher in patients with lymph node metastases in comparison to patients without metastases. Additionally, in our study macrophages

were identified to possess the immunoreactivity of RCAS1, RCAS1 expressing macrophages were observed in the mucous. Conclusion: In the present study we have demonstrated that RCAS1 expression Cell Cycle inhibitor by the tumor cells, tumor microenvironment and tumor associated macrophages participate in creating the immunosuppressive microenvironment in salivary adenocarcinomas. O71 Tumor Microenvironment Rapamycin in vitro Induced Drug and Radio Resistance in Invasive Breast Cancer Cells Sumanta Goswami 1,2 1 Anatomy and Structural Biology, Albert Einstein College of Medicine of Yeshiva University, Bronx, NY, USA, 2 Department of Biology, Yeshiva University, New York, NY, USA Metastasis, drug and radio resistance continue to cause significant morbidity and patient mortality. This is in spite of recent introduction of a number of different chemotherapy agents and newer radiotherapy protocols. Using unique animal models and cell separation techniques coupled with sensitive assays we have recently discovered that the invasive breast cancer cells are hypoproliferative and antiapoptotic. Since the invasive cells have shut

down their cell cycle and have become dormant they continue to resist cytotoxic drugs and ionizing radiation. We have used cells isolated from the primary tumor, invasive cells, circulating tumor cells and lung metastasis to identify the underlying molecular mechanism for drug and radio resistance. We used a combination of cytotoxic and cytostatic drugs along with molecular pathway directed drugs to target the invasive, drug and radio resistant breast cancer cells. https://www.selleckchem.com/products/oicr-9429.html Secondly using both classical gene expression studies as well as by the identification of different invasion and resistance specific splice variants we have identified a genetic signature which will predict potentially invasive, chemo and radio resistant cancers.

This gene set while limited may provide a useful initial guide to researchers

to probe a strains genetic origin. We propose that using the gene-set as a guide; researchers may be able to design primers for their desired “”niche”" and determine the organism’s ability to survive the niche. Undoubtedly this barcode will have to be continuously monitored and further validated as more genomes are sequenced to uphold its accuracy. Additionally there is always the potential for dairy organisms to be introduced to the gut environment through 4EGI-1 cell line functional food which may lead to them evolving to survive in this environment, for this reason also, we must constantly monitor and update the barcode. Methods Genome Sequences Eleven LAB genomes were selected for analysis. Five from a gut environment; Lb. gasseri ATCC 33323 [NCBI:CP000413] [5], Lb. acidophilus NCFM [NCBI:CP000033] [2]Lb. johnsonii NCC533 [NCBI:AE017198] [5], Lb. salivarius subsp.salivarius PI3K Inhibitor Library datasheet UCC118 [NCBI:CP000233] [40] and Lb. reuteri F25 [NCBI:CP000705]

[41] three from a dairy environment; Lb. helveticus DPC4571 [NCBI:CP000517] [1], Lb. delbrueckii subsp.bulgaricus ATCC 11842 [NCBI:CR954253] [36] and S. thermophilus LMG 18311 [NCBI:CP000023] [13] and three multi-niche organisms (i.e. can survive in both a gut or dairy environment); Lb. brevis Daporinad ic50 ATCC367 [NCBI:CP000416], Lb. plantarum WCFS1 [NCBI:AL935263] [37], Lb. sakei subsp.sakei 23 K [NCBI:CR936503] [39] (see tables 1 and 3 Flucloronide for genome features and niche of the genomes). These genomes were chosen based on a number of criteria; their phylogenetic proximity to Lb. acidophilus NCFM and Lb. helveticus DPC4571, their availability in the public database and their proven ability to survive a dairy or gut niche. Table 3 Source of isolation and environmental niche of the selected LAB Species Isolated From Environmental Niche Lb. helveticus DPC4571 Cheese Dairy Lb. acidophilus NCFM

Infant faeces Gut Lb. johnsonii NCC533 Human faeces Gut Lb. sakei 23 K Meat Multi-niche Lb. salivarius UCC118 Terminal ileum of human Gut Lb. delbrueckii subsp. bulgaricus ATCC11842 Yoghurt Dairy Lb. plantarum WCFS1 Human saliva Multi-niche S. thermophilus LMG18311 Yoghurt Dairy Lb. reuteri F275 JCM 1112 Adult Intestine Gut Lb. brevis ATCC3567 Silage Multi-niche Lb. gasseri ATCC 33323 Human Gut Gut Determination of the gene set (“”Barcode”") The initial selections were based on an unbiased “”all against all”" comparison of the Lb. acidophilus NCFM and Lb. helveticus DPC4571 genomes. A manual comparison of the two genomes was undertaken producing a gene list containing potential “”gut”" genes (those present in NCFM only) and “”dairy”" genes (those present in DPC4571 only). The differences in the DPC4571 and Lb.

Limits of sensitivity of LSplex Next we wished to determine check details the minimum amount of target DNA efficiently supporting the optimized LSplex Go6983 mw amplification protocol. Agarose gel electrophoresis was unable to detect the LSplex amplification

products from templates containing less than 10 ng of DNA (105–106 genomic equivalents) from several bacterial species (not shown). However, after fluorescent labeling of the amplification products followed by microarray hybridization strong signals were readily detected. In fact, LSplex amplification (with 800 primer pairs) of 10 ng and also of 1 ng of DNA template resulted in a find more hybridization pattern mostly identical to the one obtained with 2 μg of genomic DNA, while 10 ng of the same genomic DNA were below the limit of sensitivity of the microarray for pathogen detection (Fig. 3). The hybridization pattern obtained with 100 ng genomic DNA showed 22 mismatches compared to 2 μg. In contrast, LSplex on 1 ng template displayed a hybridization profile comparable to the one obtained with 2 μg of non amplified DNA, although the amplification of certain probes was diminished. For instance, lipase (lip) delta-aminolevulinic acid dehydratase (hemB) and Pantone-Valentine

leukocidin F subunit (lukF) were poorly amplified and fell below detection threshold. Most of the LSplex products amplified from 0.1 ng or 0.01 ng (not shown) template were below the limit of detection of the microarray analysis, making species identification impossible. Thus application of LSplex increases the microarray detection of target templates by a factor of 102 to 103 with >95% fidelity. Figure 3 Enhancement of sensitivity of pathogen DNA detection by microarray by LSplex amplification. Hybridization profile of non-amplified genomic S. aureus DNA (2 μg, 100 ng, 10 ng and 1 ng) and indirectly labelled LSplex amplification product of the same DNA starting from 10 ng, 1 ng and 0.1 ng template (columns). Adenosine triphosphate Each row represents individual S. aureus-specific capture probes as well as positive (16S-derived probes) and negative controls. Fluorescent signals were quantified and classified as positive (black boxes) hybridization or absence of hybridization (white boxes). Specificity of LSplex on several DNA templates In the next step we evaluated if the PCR amplification employing 800 primer pairs results in the generation of nonspecific amplification products cross-hybridizing with non-target species.

Approved standard, NCCLS document M2-A8 8 Edition NCCLS, Wayne, Pa 2003. 19. Ward LR, de Sa JD, Rowe B: A phage-typing scheme for Salmonella enteritidis. Epidemiol Infect 1987,99(2):291–294.CrossRefPubMed 20. Anderson ES, Ward LR, Saxe MJ, de Sa JD: Bacteriophage-typing designations of Salmonella typhimurium. J Hyg (Lond) 1977,78(2):297–300.CrossRef 21. Ribot EM, Fair MA, #Akt inhibitor randurls[1|1|,|CHEM1|]# Gautom R, Cameron DN, Hunter SB, Swaminathan B, Barrett TJ: Standardization of pulsed-field gel electrophoresis

protocols for the subtyping of Escherichia coli O157:H7, Salmonella, and Shigella for PulseNet. Foodborne Pathog Dis 2006,3(1):59–67.CrossRefPubMed 22. Lindstedt BA, Vardund T, Aas L, Kapperud G: Multiple-locus variable-number tandem-repeats analysis of Salmonella enterica subsp. enterica serovar Typhimurium using PCR multiplexing and multicolor capillary electrophoresis. J

Microbiol Methods 2004,59(2):163–172.CrossRefPubMed Authors’ contributions ND and MC conceived of and participated in INK 128 manufacturer the design of the study. ND drafted the manuscript. ND, JOC, GMD and GD carried out the serotyping, AST, PFGE and VNTR. MC helped to draft the manuscript. All authors read and approved the final manuscript.”
“Background Salmonella enterica serovar Enteritidis (SE) is one of the leading etiologic agents of non-typhoid fever [1]. The disease usually manifests as a self-limiting enteritis, although systemic spread of the infections accompanied by mortalities occurs in young and immunocompromised human patients [2]. Epidemiological studies suggest that poultry flocks may serve as a major reservoir for SE organisms implicated in human clinical cases [3]. Salmonella enterica silently colonizes the intestinal and reproductive tracts of chickens, which can provide a mechanism for SE-contamination of chicken meat, shell-eggs, and hatchery eggs if proper from processing and handling are not observed [4]. Recent investigations have shown that SE utilizes its type three secretion systems (T3SS) encoded by Salmonella pathogenicity island-1 and -2 (SPI-1

and SPI-2), respectively, to promote intestinal and reproductive tract colonization [5–7]. The T3SS of Salmonellae functions as a needle-like apparatus that injects an array of effector proteins into host cells. The T3SS-1 effectors act in concert to modulate host cell cytoskeleton rearrangement, thereby facilitating bacterial entry into host epithelial cells [8]. The T3SS-2 effectors promote bacterial survival or replication within host phagocytes [9]. The T3SS effectors also shape the type of pathological changes associated with Salmonella infection via modulating host cytokine and chemokine expressions [10]. It has been commonly accepted that the outcomes of microbial infections, including salmonellosis, are largely determined by the type and magnitude of host systemic and local immune responses.

Learning any VRT752271 price genetic information is something https://www.selleckchem.com/products/lazertinib-yh25448-gns-1480.html you should share. It doesn’t affect only you. People need to overcome their spontaneous reaction of hiding something that is bad and share it. This

might make a difference in other people’s lives. They might have the opportunity to get tested, follow up even have a treatment. It is a moral obligation (Participant 03). A second important factor that was acknowledged by most participants was that this is an area in which knowledge and scientific understanding is constantly developing. This needs to be taken into account when making choices about the results that should be returned. The problem with genetics is that we think we know something today and then in a year’s time it is proven

wrong or insufficient. We can’t pretend we know everything because we don’t (Participant 02). Because everything changes so quickly we might have to consider keeping findings and returning them on a later time if we are not sure what they mean now (Participant 05). Third, there was a consensus among all experts that when using clinical sequencing, especially NGS, it is the interpretation of the results that is important, not the test itself. Anyone could buy the equipment for NGS but there are only a few who could interpret results. And there is the whole importance. Because we will get so many results, we will have a look and using specific PX-478 in vitro software we will throw 1998 or 1999 out of 2000. The remaining ones we will see. We will have to think about them and consider the family as well (Participant 08).

Fourth, clinicians in particular also until suggested that genetic conditions differ in another important way: most genetic conditions are not actionable. For some conditions the only “action” that could be taken would be the option of prenatal or preimplantation diagnosis, if available, as no preventive measures were available. The problem is that for most genetic conditions there is nothing you can do! Only be informed, follow-up and help other make reproductive choices if you can (Participant 04). A patient with a hereditary genetic condition comes very close to his doctor. It’s not like having a respiratory condition that he could take two sprays [respiratory drug] and get well. Here you have many issues, social, psychological, moral (Participant 10). Fifth, returning genetic information to patients differs from returning other health-related information because learning genetic information has the potential to change someone’s life, especially if it is unexpected and serious. Many participants suggested that when conveying “bad news”, the support of a clinical psychologist would be vital. Especially if what you are going to tell them is really bad you need there a psychologist. They will know better how to help them (Participant 05). We had a psychologist at some point as a member of our group when disclosing such information. And that made a great difference.

Biochem Biophysic Res Comm 1993,190(1):302–307.CrossRef 13. Ito T, Higuchi T, Hirobe M, Hiramatsu K, GSK3235025 supplier Yokota T: Identification of a novel sugar, 4-amino-4,6-dideoxy-2-O-methylmannose in the lipopolysaccharide of Vibrio cholerae O1 serotype Ogawa. Carbohydrate Res 1994,256(1):113–128.CrossRef 14. Faruque SM, Nair GB, Mekalanos JJ: Genetics of stress adaptation and virulence in toxigenic Vibrio cholerae. DNA Cell Biol 2004,23(11):723–741.PubMedCrossRef Selleckchem mTOR inhibitor 15. Comstock LE, Johnson JA, Michalski JM, Morris JG Jr, Kaper JB: Cloning and sequence of a region encoding a surface polysaccharide of Vibrio cholerae O139 and characterization of the insertion site in the chromosome of Vibrio cholerae O1.

Mole Microbiol 1996,19(4):815–826.CrossRef 16. Bhaskaran K, Gorrill RH: A study of antigenic variation in Vibrio cholerae. J Gen Microbiol 1957,16(3):721–729.PubMedCrossRef

HMPL-504 nmr 17. Sack RB, Miller CE: Progressive changes of Vibrio serotypes in germ-free mice infected with Vibrio cholerae. J Bacteriol 1969,99(3):688–695.PubMed 18. Sheehy TW, Sprinz H, Augerson WS, Formal SB: Laboratory Vibrio cholerae infection in the United States. Jama 1966,197(5):321–326.PubMedCrossRef 19. Ito T, Hiramatsu K, Ohshita Y, Yokota T: Mutations in the rfbT gene are responsible for the Ogawa to inaba serotype conversion in Vibrio cholerae O1. Microbiol Immunol 1993,37(4):281–288.PubMed 20. Koelle K, Pascual M, Yunus M: Serotype cycles in cholera dynamics. Proc Rapamycin in vitro 2006,273(1603):2879–2886. 21. Ogg JE, Ogg BJ, Shrestha MB, Poudayl L: Antigenic changes in Vibrio cholerae biotype eltor serotype Ogawa after bacteriophage infection. Infect Immunity 1979,24(3):974–978. 22. Stroeher UH, Karageorgos LE, Morona R, Manning PA: Serotype conversion in Vibrio cholerae O1. Proc Nat Acad Sci USA 1992,89(7):2566–2570.PubMedCrossRef 23. Ito T, Ohshita Y, Hiramatsu K, Yokota T: Identification

and nucleotide sequence determination of the gene responsible for Ogawa serotype specificity of V. cholerae 01. FEBS letters 1991,286(1–2):159–162.PubMedCrossRef 24. Rijpkema SG, Durrani Z, Ramamurthy T, Nair GB: Assessing clonality of Vibrio cholerae Inaba isolates by characterization of nonsense mutations in wbeT. J Med Microbiol 2004,53(Pt 11):1105–1107.PubMedCrossRef 25. Felsenfeld O: A review of recent trends in cholera research and control. With an annex on the isolation and identification of cholera vibrios. Bull World Health Org 1966,34(2):161–195.PubMed 26. Longini IM Jr, Yunus M, Zaman K, Siddique AK, Sack RB, Nizam A: Epidemic and endemic cholera trends over a 33-year period in Bangladesh. J Infect Dis 2002,186(2):246–251.PubMedCrossRef 27. Wei CY: Cholera prevention and control – China, 1961–2011. J Prev Med Inf 2012,28(7):497–504. 28. Mukerjee S, Roy UK, Rudra BC: Studies on typing of cholera vibrios by bacteriophage. V. Geographical distribution of phage-types of vibrio cholerae. Annals Biochem Exp Med 1963, 23:523–530. 29.