This indicates that the internal interface between the two GaAsBi

This indicates that the internal interface between the two GaAsBi regions of different Bi contents is highly perturbed and prevents the free flow of photo-excited carriers. At RT, the PL emission peaks are

dominated by band-to-band transitions, and hence, the PL peak energies can be tentatively correlated to the Bi composition of the material. From the AZD6244 relationship between band gap energy and Bi composition established by Usman et al. [28] the PL peaks of S100 at 1,108 and 980 nm correspond to a Bi content of approximately 5.1% and approximately 2.6%, respectively. Similarly, the main peak of S25 at 1,057 nm corresponds to a Bi content of approximately 4.2%. This indicates that the maximum Bi content of S100 is higher than S25, despite nominally identical flux ratios were used Fosbretabulin mw during growth. This discrepancy is believed to be due to an inherent error in the temperature calibration that resulted in S100 being grown approximately 15°C lower than S25 and not a result of the thinner overall layer thickness. Despite the difference in the absolute peak position, the RT-PL spectra of both samples exhibit a similar envelope comprising (1) a high-wavelength tail and (2) a lower wavelength shoulder. This asymmetric emission indicates that both

spectra are formed from the superposition of at least three individual PL peaks. It is therefore possible that the shape of the PL spectra corresponds to structural or compositional features that are present in both samples, whereas the distinct lower energy peak in S100 corresponds to a feature not present in S25. Structural and compositional TEM Protein kinase N1 In order to find an explanation of the PL spectra, TEM studies were carried out by diverse techniques. Low-magnification CTEM images acquired using different diffraction conditions sensitive to defects (not shown in this paper) revealed defect-free epilayers in the electron-transparent area of sample S25 and some isolated dislocations in sample S100. Thus, the RT-PL

intensity of both samples is nominally identical despite the presence of threading dislocations in S100; however, their presence at the internal-interface may explain the splitting of the PL peaks in S100. The physical origin of the each of the PL peaks requires further analysis. HAADF-STEM images were used to study the distribution of bismuth in the GaAsBi layers. see more Interpretation of this kind of image (also called Z-contrast images) is relatively straightforward, since the contrast is roughly proportional to the square of the atomic number at constant sample thickness [29, 30]. Hence, for the case of a ternary alloy where bismuth is the only variable element, brighter contrast should in principle be associated with higher Bi content. Z-contrast images (Figure 2a,b) showed uniform GaAs1−x Bi x layer widths in both samples, corresponding to the nominal ones.

CrossRef 18 Shepherd JE: Multiscale Modeling of the Deformation

CrossRef 18. Shepherd JE: Multiscale Modeling of the Deformation of Semi-Crystalline Polymers. Atlanta: Georgia Institute of Technology; 2006. 19. Hoover WG: Canonical dynamics: equilibrium phase-space distributions.

Phys Rev A 1985,31(3):1695–1697.CrossRef 20. Perpete E, Laso M: Multiscale Modelling of Polymer Properties, Volume 22 (Computer Aided Chemical Engineering). New York: Elsevier; 2006. 21. Takeuchi H, Roe RJ: Molecular-dynamics simulation of local chain motion in bulk amorphous polymers.1. Dynamics above the glass transition. J Chem Phys 1991,94(11):7446–7457.CrossRef 22. Valentini P, Gerberich WW, Dumitrica T: Phase-transition plasticity response in uniaxially compressed silicon nanospheres. Phys Rev Lett 2007,99(17):175701.CrossRef 23. Gurtin ME: An Introduction to Continuum Mechanics. San Diego: Academic; 2003. 24. Zhou MA: Selleckchem Ilomastat A new look at the Belnacasan manufacturer atomic level virial stress: on continuum molecular system equivalence. Proc R Soc London Ser A 2003,459(2037):2347–2392.CrossRef 25. Parashar A, Mertiny P: Multiscale model to investigate the effect of graphene on the fracture characteristics of graphene/polymer nanocomposite. Nanoscale Res Lett 2012, 7:595.CrossRef 26. Gerberich WW, Mook WM, Perrey CR, Carter CB, Baskes MI, Mukherjee R, Gidwani A, Heberlein J, McMurry PH, Girshick SL: Superhard silicon

AZD6738 cell line nanospheres. J Mech Phys Solids 2003,51(6):979–992.CrossRef 27. Cuenot S, Fretigny C, Demoustier-Champagne S, Nysten B: Surface tension effect on the mechanical properties of nanomaterials measured by atomic force microscopy. Phys Rev B 2004,69(16):165410.CrossRef 28. Sharma P, Ganti S, Bhate N: Effect of surfaces on the size-dependent elastic state of nano-inhomogeneities. Appl Phys Lett 2003,82(4):535–537.CrossRef 29. Momeni K, Odegard GM, Yassar RS: Finite size effect on the piezoelectric properties of ZnO nanobelts: a molecular dynamics approach. Acta Mater 2012,60(13–14):5117–5124.CrossRef 30. Hadden CM, Jensen BD, Bandyopadhyay A, Odegard GM, Koo A, Liang R: Molecular modeling of EPON-862/graphite composites: interfacial characteristics for multiple crosslink densities.

Compos Sci Technol 2013, 76:92–99.CrossRef 31. Odegard GM, Clancy TC, Gates TS: Modeling of the mechanical selleck chemical properties of nanoparticle/polymer composites. Polymer 2005,46(2):553–562.CrossRef 32. Mansfield KF, Theodorou DN: Atomistic simulation of a glassy polymer graphite interface. Macromolecules 1991,24(15):4295–4309.CrossRef 33. Li CY, Browning AR, Christensen S, Strachan A: Atomistic simulations on multilayer graphene reinforced epoxy composites. Compos Part A-Appl S 2012,43(8):1293–1300.CrossRef 34. Kogut L, Etsion I: Elastic–plastic contact analysis of a sphere and a rigid flat. J Appl Mech-T ASME 2002,69(5):657–662.CrossRef Competing interests The authors declare that they have no competing interests. Authors’ contributions JZ and SN constructed the coarse-grained polymer model and carried out the simulation. JZ, GO, and JH drafted the manuscript.

In vivo, athymic

mice were administered thrombopoietin (T

In vivo, athymic

mice were administered thrombopoietin (TPO) to expand their megakaryocyte populations prior to intracardiac PC-3 luciferase tagged (PC-3luc) cell inoculation. TPO significantly increased MKs in the bone marrow and reduced numbers of luciferase positive prostate tumors in the long bones. These data show a novel role for megakaryocytes as potential gate-keepers in the bone marrow microenvironment of the prostate skeletal metastatic lesion. O172 Culture of Human Laryngeal Carcinoma Cell Line Hep-2 in NSC23766 Presence of Fibronectin Increases MMP-9 Expression with the Involvement of Multiple Signaling Pathways Triparna Sen1, Anindita Dutta1, Gargi Maity1, Amitava Chatterjee www.selleckchem.com/products/pnd-1186-vs-4718.html 1 1 Department of Sotrastaurin Receptor Biology and Tumor Metastasis, Chittaranjan National Cancer Institute, Kolkata, India The microenvironment is being increasingly recognized as critical component in tumor progression and invasion. During cell migration, there is a continuous interaction between cell surface receptors

and ECM proteins. In the present communication we studied the effect of Fibronectin-integrin interaction in human laryngeal carcinoma cell line, Hep-2 and the downstream effectors. The study indicates that culture of Hep-2 cells in SFCM in presence of FN enhances MMP-9 expression. FN induces the activity and expression of MMP-9 by binding to its receptor a5b1 in Hep-2 cells. This induction medroxyprogesterone occurs through the possible involvement of multiple signaling pathways. We propose that there is a “cross-talk” between

the signaling pathways. The silencing of FAK with FAK siRNA and its subsequent effect on FN-induced MMP-9 expression has confirmed the involvement of FAK as an important modulator in the pathway. When FN binds to its receptor, it causes the phosphorylation of FAK, which in turn causes activation and nuclear translocation of PI-3 K and subsequent activation of ERK finally leading to MMP-9 transactivation and stimulation. PI-3 K on the other hand, upon integrin ligand interaction, could also independently activate ILK. These signaling pathways work in concert with each other and disruption of one could affect the function of another. The signals from the signaling pathways finally leads to the increased DNA binding activity of important transacting factor on MMP-9 promoter and thus transcription of MMP-9 in turned on. Our study provides scopes for future clinical interventions by targeting these signaling pathways in FN-induced MMP-9 upregulation and invasion of laryngeal cancer cells.

0) to a final concentration of 1 mg/ml 100 μl of the hyaluronic

0) to a final concentration of 1 mg/ml. 100 μl of the hyaluronic acid solution was incubated with 400 μl of the filter-sterilized supernatants of the wild types and mutants for 30 min at 37°C. One ml of a solution containing 2% NaOH and 2.5% cetramide (cetyltrimethylammonium bromide, Sigma) was added to the Fedratinib in vivo reaction mixture. The turbidity of the insoluble

complex formed between cetramide and hyaluronic acid was measured at 400 nm [37]. The reduction in turbidity, reflecting the decrease in hyaluronic acid because of the activity of hyaluronidase, was calculated by comparing the turbidities of samples containing the supernatant of each culture with controls containing BHI alone. The enzyme assays for all the enzymes were performed three times

from three different cultures of each strains. Cytotoxicity of C. perfringens supernatants for macrophages Macrophages were obtained from C57BL/6 male mice, 4–6 weeks old, which had ad libitum access to food and water. The maintenance, handling and sacrifice of mice were according to procedures approved by the NCTR Institutional Animal Care and Use Committee. Resident mouse peritoneal macrophages were harvested by peritoneal lavage, using 4 ml of supplemented DMEM medium, containing 5% heat-inactivated fetal bovine serum, 100 μg/ml streptomycin sulfate, 100 units/ml penicillin G, 110 mg/L sodium pyruvate, and 2 mM glutamine. Red blood cells were removed by hypotonic lysis. The peritoneal exudate cells MAPK Inhibitor Library concentration were washed once with DMEM, plated and incubated at 37°C in a humidified atmosphere of 5% CO2[33]. Floating cells were removed and the macrophages were incubated in DMEM, containing 10% C1GALT1 BHI or filter-sterilized supernatants of

overnight cultures of wild types and mutants, for 18 h at 37°C in a CO2 incubator. A CytoTox 96® Non-Radioactive Cytotoxicity Assay Kit (Promega) was used to measure the toxicity of the mutants and wild type cultures for macrophages. The cytotoxicity of each absorbance unit of the cells of different strains was calculated by the amount of lactate dehydrogenase (LDH) released from the macrophages. The differences in cytotoxicity due to the mutants and wild types were assessed using Student’s t-test. Morphological examination Colony morphology of the strains was compared after overnight growth on BHI plates. For cellular morphology, log phase grown cells were Gram stained and examined under the light microscope. DNA sequencing Several regulatory and toxin genes and enzymes from wild types and mutants were Akt assay amplified and sequenced as previously described [29]. Results Transcriptional analysis by DNA microarray Using the genome sequences of C. perfringens strain 13 and strain ATCC 13124, microarray probes were designed for genome-wide transcriptional analysis of two fluoroquinolone-resistant C. perfringens strains, NCTRR and 13124R, and their wild types. Microarray analysis showed that a variety of genes were upregulated (≥ 1.

1996; Kornyeyev et al 2010); however,

the level of photo

1996; Kornyeyev et al. 2010); however,

the level of photoinhibition is inversely proportional to the level of photoprotection and to the ability to repair photodamaged PSII elements. Many studies show that both the photoprotection and the repair ability increase with longtime exposure to high excitation pressure, mostly at HL intensities (Tyystjärvi et al. 1992; Niinemets and Kull 2001). Together with a very low ETR and non-photochemical quenching (of Chl fluorescence), similar to that in sun plants, selleck kinase inhibitor we could expect severe photoinhibitory damage in shade plants exposed to HL treatment. However, low differences in photoinhibitory effects (q I) between sun and shade leaves did not correspond with high differences in excitation pressure. One possible explanation is that the values of the excitation find more pressure may have been estimated inaccurately and 1-qP values are really not the true estimates of the PSII redox poise. Rosenqvist (2001) has discussed the possible “inaccuracy” of the calculated values of photochemical quenching, qP, as it probably inaccurately estimates the fraction of oxidized QA due to “connectivity among PSII units” (Joliot and Joliot 1964; Paillotin 1976; Joliot and Joliot 2003). The concept of connectivity among PSII units

is included in many models; however, there is still a lack of reliable data for the correct values of probability parameter p in different plant species. Kramer et al. (2004), based on the data published by Lazar (1999), have reported that the p value in higher Thymidine kinase plants is usually higher than 0.6 (supported by Joliot and Joliot 2003, who obtained p = 0.7); in such a case, the qL would

reflect fully the redox state of QA. On the other hand, the data published by Kroon (1994) show p values between 0.25 and 0.45. Further, GSK458 molecular weight Strasser and Stirbet (2001), using direct measurements of fast ChlF kinetics, found a value of p 2G around 0.25, using both ChlF curves in the presence and the absence of DCMU; it represents a p value of ~0.5 (Stirbet 2013). Although the connectivity is estimated from the initial part of chlorophyll fluorescence curve, it does not mean that it is valid only for the initial phase. According to the theory of PSII connectivity, the migration possibilities for excitons that are inferred from the sigmoidal shape of fluorescence induction also influence the efficiency of utilization of absorbed light for trapping electrons in the RC and hence, it has an effect on the entire fluorescence kinetics (Lavergne and Trissl 1995). Recently, Tsimilli-Michael and Strasser (2013) documented that the p 2G can be correctly calculated even if only some of the RCs are inactive as well as in the case when the true F m (all RCs closed) is not reached experimentally.

4,501 SNPs consistent with transfer from Eagan (i e they were in

4,501 SNPs consistent with transfer from Eagan (i.e. they were in the same genome location as the Eagan SNPs identified above) were found in the Rd+EaganstrR transformants. We identified 202 SNPs that were common to all respective sequence reads, were not linked closely to other SNPs and were found in both Rd+EaganstrR and Rd+Eagan transformants obtained in control experiments using non-strR Eagan DNA as donor. We conclude that these SNPs were consistent with, and most likely explained by, errors within the reported Rd genome sequence published in 1995. Another possibility,

not mutually exclusive with sequencing errors, could be sequence drift in our laboratory strain (RM118) when compared to the sequenced isolate (Rd KW20). This level of error is similar to the several hundred SNPs reported upon re-sequencing of strain Rd by other investigators

GW786034 in vitro SHP099 chemical structure [17] and comparable with the 243 discrepancies found between the Ro-3306 original 1997 E. coli strain MG1655 genome sequence [19] and the 2006 re-sequencing [20] of the same strain. Figure 4 Frequency of Eaganstr R and Eagan SNPs in the Rd+Eaganstr R and Rd+Eagan transformants. Panel A; Location and frequency of EaganstrR specific SNPs plotted as estimated number of strains (y-axis) against location in RdKW20 genome sequence (x-axis) using SNPSeeker. MAQ was used to identify SNPs in the pooled sequences from 200 transformants. The location of the strR point mutation is indicated. Panel B; A magnified view of one region marked on Panel A showing a putative secondary transformation event. The extent of the chromosomal region involved with this predicted transformation event (13 kbp) is marked. Panel C; A magnified view of the primary transformation event from Panel A with the location of the strR point mutation marked. Panel D; The location and frequency of Eagan-specific SNPs in the genome of pooled Rd+Eagan transformants (200); Eagan unmarked (wild-type) genomic DNA was used as the donor. In the Rd+EaganstrR transformants, a large peak in SNP density centred on the site of the point mutation in rpoB conferring strR (Figure  4). Moving outwards from this central SNP peak,

the Eagan-specific SNPs decrease at a relatively constant rate such Flavopiridol (Alvocidib) that within 10 kbp of the strR mutation the frequency of strains containing Eagan-specific SNPs decreases at approximately 1 strain/100 bp. Across the 200 transformants, the region of the genome involved in recombination events centred on the strR locus would appear to span an arc of the genome over 80 kbp in size (Figure  4). Given that the strR locus can be at any location in the recombined block of DNA, this indicates a maximum size for the recombined block of at least 40 kbp. In addition to the intense peak centred on the strR conferring SNP, secondary small peaks of SNPs can be observed at other locations in the genome. These secondary peaks contain Eagan strain-specific SNPs at a frequency of approximately 0.

BMC Microbiol 2009, 9:50 PubMedCrossRef 34 Tindall BJ, Rosselló-

BMC Microbiol 2009, 9:50.PubMedCrossRef 34. Tindall BJ, Rosselló-Móra R, Busse HJ, Ludwig W, Kämpfer P: Notes on the characterization of prokaryote

strains for taxonomic purposes. Int J Syst Evol Microbiol 2010,60(Pt 1):249–66.PubMedCrossRef 35. Rosselló-Mora R, Amann R: The species concept for prokaryotes. FEMS Microbiol Rev 2001, 25:39–67.PubMedCrossRef 36. Chain PSG, Carniel E, Larimer FW, Lamerdin J, Stoutland PO, Regala WM, Georgescu AM, Vergez LM, Land ML, Motin VL, Brubaker RR, Fowler J, Hinnebusch J, Marceau M, Medigue C, Simonet M, Chenal-Francisque V, Souza B, Dacheux D, Elliott JM, Derbise A, Hauser LJ, Garcia E: Insights into the evolution of Yersinia pestis through whole-genome comparison with Yersinia pseudotuberculosis. MK5108 clinical trial Proc Natl Acad Sci USA 2004,101(38):13826–31.PubMedCrossRef 37. Kersey P, Bower L, Morris L, Horne A, Petryszak R,

Kanz C, Kanapin A, Das U, Michoud K, Phan I, Gattiker A, Kulikova T, Faruque N, Duggan K, Mclaren P, Reimholz B, Duret L, Penel S, Reuter I, Apweiler R: Integrted and Genome Reviews: integrated views of complete genomes and proteomes. Nucleic Acids Res 2005, (33 Database):D297–302. 38. Tatusov RL, Koonin EV, Lipman DJ: A genomic perspective on protein families. Science 1997,278(5338):631–637.PubMedCrossRef 39. Tatusov RL, Galperin MY, Natale DA, Koonin EV: The COG Sotrastaurin database: a tool for genome-scale analysis of protein functions and

evolution. Nucleic Acids Res 2000, 28:33–36.PubMedCrossRef 40. Tatusov RL, Natale DA, Garkavtsev IV, Tatusova TA, Shankavaram UT, Rao BS, Kiryutin B, Galperin MY, Fedorova ND, Koonin EV: The COG database: new developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res 2001, 29:22–28.PubMedCrossRef 41. Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B, Koonin EV, Krylov DM, Mazumder R, Mekhedov SL, Nikolskaya AN, Rao BS, Smirnov S, Sverdlov AV, Vasudevan S, Wolf YI, Yin JJ, Natale DA: The COG database: an updated version includes eukaryotes. BMC selleck chemical Bioinformatics 2003, 4:41.PubMedCrossRef 42. Fulton DL, Li YY, Laird MR, Horsman BG, Roche FM, Brinkman FS: Improving the Selleck Bortezomib specificity of high-throughput ortholog prediction. BMC Bioinformatics 2006, 7:270.PubMedCrossRef 43. Chiu JC, Lee EK, Egan MG, Sarkar IN, Coruzzi GM, DeSalle R: OrthologID: automation of genome-scale ortholog identification within a parsimony framework. Bioinformatics 2006,22(6):699–707.PubMedCrossRef 44. Zmasek CM, Eddy SR: RIO: analyzing proteomes by automated phylogenomics using resampled inference of orthologs. BMC Bioinformatics 2002, 3:14.PubMedCrossRef 45. Storm CEV, Sonnhammer ELL: Automated ortholog inference from phylogenetic trees and calculation of orthology reliability. Bioinformatics 2002, 18:92–99.PubMedCrossRef 46.

Therefore, the impact of COLD on performance measures may be more

Therefore, the impact of COLD on performance measures may be more evident at higher temperatures. Most studies have addressed rise in core temperature with a dehydrated population

during hot and/or humid conditions over a longer period of time [6, 7]. Future research may address the effects of a cold water trial in a 90–120 minute exercise session on rise in core temperature. Even though there was not a significant improvement for subjects when drinking COLD water prior to performance tests, overall performance measures may not be sensitive enough to measure the small changes that COLD water may have. Moreover, if the same study was done with dehydrated subjects or in a hot/humid environment, there may have been a greater performance benefit exhibited. The repeated measures analysis of variance showed no significant interactions (p=0.286), indicating that subjects click here did not perform eFT-508 cost significantly different over time in one condition than in the other. There was also no significant effect of group (p=0.619). There was, however, a significant effect of time (p<0.001). There were two limitations to this

study. Environmental conditions of temperature and humidity were controlled throughout the study at a constant value. Secondly, the total duration of the study was less than 90 minutes. COLD water may provide the most benefits in stressful environmental conditions (higher temperatures and humidity levels and/or longer duration of exercise) [1], but the current study did not test these independent variables. Conclusion This study found that drinking COLD water during a traditional exercise 3-mercaptopyruvate sulfurtransferase program in a moderate climate can have a significant impact on the body’s ability to maintain core temperature. The benefits for reducing the rise in core temperature did not translate to significant improvements in power, aerobic endurance,

and muscular endurance-based exercises. Secondary to the significant impact of the COLD water on the body’s ability to maintain core temperature, it is still recommended that both, athletes and physically fit individuals, consume COLD beverages during exercise. Delaying a rise in core temp may have positive impact on exercises not investigated in this study, but it’s unlikely to have negative effects. It is recommended that SAHA HDAC mw further work be done to further investigate the impact of COLD water consumption on strength and power performance in an extreme environment, with dehydrated subjects, or specific exercise bouts of longer duration. Acknowledgements We would like to thank the participants that participated in this study as well as our fellow colleagues, at Athletes’ Performance who assisted with data collection. This study was funded by Thermos L.L.C., (Schaumburg, IL, USA).

So, improvement of existing methods or development of new methods

So, improvement of existing methods or development of new methods is needed for the analysis of gene expression microarray data. Many gene expression signatures have been identified in recent years for accurate classification of tumor

subtypes [16–19]. It has been indicated that rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, a relatively few attempts have been aware of the importance of prior information in cancer classification [20–22]. Lung cancer is one of the leading causes of cancer death worldwide [23–26], can be classified broadly into small cell lung Selonsertib purchase cancer (SCLC) and non-small cell lung cancer (NSCLC), and adenocarcinoma

is the most common form of lung cancer. Because in China the cigarette smoking rate continues to be at a high level [27], a peak in lung cancer incidence is still expected [28]. Therefore, only lung cancer gene expression microarray dataset was selected in the present study. In summary, together with the application of support vector machine as the discriminant approach and PAM as the feature gene selection method, we Tucidinostat mw propose one method that incorporates prior knowledge into cancer classification based on gene expression data. Our goal is to improve classification accuracy

based on the publicly available lung cancer microarray dataset [29]. Methods Microarray dataset In the present study, we analyzed Cyclin-dependent kinase 3 the well-known and publicly available microarray dataset, malignant pleural mesothelioma and lung adenocarcinoma gene expression database http://​www.​chestsurg.​org/​publications/​2002-microarray.​aspx[29]. This Affymetrix Human GeneAtlas U95Av2 microarray dataset contains 12 533 genes’ expression profiles of 31 malignant pleural mesothelioma (MPM) and 150 lung adenocarcinomas (ADCA, published in a previous study [30]), aims to test expression ratio-based analysis to TEW-7197 in vivo differentiating between MPM and lung cancer. In this dataset, a training set consisted of 16 ADCA and 16 MPM samples. Microarray data preprocessing The absolute values of the raw data were used, then they were normalized by natural logarithm transformation. This preprocessing procedure was performed by using R statistical software version 2.80 (R foundation for Statistical Computer, Vienna, Austria). Gene selection via PAM Prediction analysis for microarrays (PAM, also known as Nearest Shrunken Centroids) is a clustering technique used for classification, it uses gene expression data to calculate the shrunken centroid for each class and then predicts which class an unknown sample would fall into based on the nearest shrunken centroid.

Genes Dev 2006, 20:1776–1789 PubMedCrossRef

Genes Dev 2006, 20:1776–1789.PubMedCrossRef CX-6258 mouse 13. El-Samad H, Kurata H, Doyle JC, Gross CA, Khammash M: Surviving heat shock: control strategies for robustness and performance. Proc Natl Acad Sci USA 2005, 102:2736–2741.PubMedCrossRef 14. Long SR:

Genes and signals in the rhizobium -legume symbiosis. Plant Physiol 2001, 125:69–72.PubMedCrossRef 15. Oke V, Long SR: Bacteroid formation in the Rhizobium -legume symbiosis. Curr Opin Microbiol 1999, 2:641–646.PubMedCrossRef 16. Spaink HP: Root nodulation and infection factors produced by rhizobial bacteria. Annu Rev Microbiol 2000, 54:257–288.PubMedCrossRef 17. Zahran HH: Rhizobium -legume symbiosis and nitrogen fixation under severe conditions and in an arid climate. Microbiol Mol Biol Rev 1999, 63:968–989.PubMed 18. Green HA, Donohue TJ: Activity of Rhodobacter sphaeroides RpoHII, a second member of the heat shock sigma factor family. J buy SYN-117 Bacteriol 2006, 188:5712–5721.PubMedCrossRef 19. Kaneko T, Nakamura Y, Sato S, Asamizu E, Kato T, Sasamoto S, Watanabe A, Idesawa K, Ishikawa A, Kawashima K, et al.: Complete genome structure of the

nitrogen-fixing symbiotic bacterium Mesorhizobium loti . DNA Res 2000, 7:331–338.PubMedCrossRef 20. Narberhaus F, Krummenacher P, find protocol Fischer HM, Hennecke H: Three disparately regulated genes for sigma 32-like transcription factors in Bradyrhizobium japonicum . Mol Microbiol 1997, 24:93–9104.PubMedCrossRef 21. Galibert F, Finan TM, Long SR, Pühler A, Abola P, Ampe F, Barloy-Hubler F, Barnett MJ, Becker A, Boistard P, et al.: The composite genome of the legume symbiont Sinorhizobium meliloti . Science 2001, 293:668–672.PubMedCrossRef 22. Bittner AN, Oke V: Multiple groESL operons are not key targets

of RpoH1 and RpoH2 in Sinorhizobium meliloti . J Bacteriol 2006, 188:3507–3515.PubMedCrossRef ADP ribosylation factor 23. Oke V, Rushing BG, Fisher EJ, Moghadam-Tabrizi M, Long SR: Identification of the heat-shock sigma factor RpoH and a second RpoH-like protein in Sinorhizobium meliloti . Microbiology 2001, 147:2399–2408.PubMed 24. Ono Y, Mitsui H, Sato T, Minamisawa K: Two RpoH homologs responsible for the expression of heat shock protein genes in Sinorhizobium meliloti . Mol Gen Genet 2001, 264:902–912.PubMedCrossRef 25. Mitsui H, Sato T, Sato Y, Ito N, Minamisawa K: Sinorhizobium meliloti RpoH1 is required for effective nitrogen-fixing symbiosis with alfalfa. Mol Genet Genomics 2004, 271:416–425.PubMedCrossRef 26. Glenn AR, Reeve WG, Tiwari RP, Dilworth MJ: Acid tolerance in root nodule bacteria. Novartis Found Symp 1999, 221:112–126.PubMed 27. Graham PH: Stress tolerance in Rhizobium and Bradyrhizobium , and nodulation under adverse soil conditions. Can J Microbiol 1992, 38:475–484.CrossRef 28. Hungria M, Vargas MAT: Environmental factors affecting N2 fixation in grain legumes in the tropics, with an emphasis on Brazil. Field Crops Research 2000, 65:151–164.CrossRef 29.