“
“Symbiosis, a range of intimate relationships Plants, animals, and diverse microbes engage in a wide range of interactions that can be characterized as symbiotic, that is, the living together of unlike NVP-AUY922 organisms [1–5]. The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium

[6] has been developing an extensive set of Gene Ontology (GO) [7] terms that describe processes and structures underlying symbiotic interactions between organisms, ranging from mutualists through parasites [8]. This mini-review focuses on the nutrient acquisition selleckchem strategies of a range of symbiotic organisms. Here “”nutrient”" is defined as any chemical substance required for metabolism or development. GO terms that describe gene products related to nutrient exchange during symbiosis are discussed along with examples of symbioses involving bacteria, protozoans, fungi, animals, oomycetes, algae, and plants. The Gene Ontology The GO is a controlled vocabulary consisting of GO terms that describe gene product attributes in any organism [9]. GO terms are arranged as directed acyclic graphs (DAGs) within three ontologies, “”GO: 0005575 cellular

component”", “”GO: 0008150 biological process”", and “”GO: 0003674 molecular function”". DAGs differ from hierarchies in that each term (child) may be related to more than one less specific term (parent). Three specific relationships among parent and child terms within a DAG are currently recognized by the GO: “”is_a”", “”part_of”", and “”regulates”". For example, “”GO: 0052010 catabolism by symbiont of host cell wall I BET 762 cellulose”" Methocarbamol is a type of “”GO: 0052009 disassembly by symbiont of host cell wall”", and thus these terms would be

connected by the “”is_a”" relationship (for more information on term-term relationships and ontology structure, see [9]). The concept of symbiosis in the Gene Ontology In the GO, the concept of symbiosis is represented by the term “”GO: 0044403 symbiosis, encompassing mutualism through parasitism”", which is defined as: “”An interaction between two organisms living together in more or less intimate association. The term host is usually used for the larger (macro) of the two members of a symbiosis. The smaller (micro) member is called the symbiont organism”" [10]. The various forms of symbiosis include parasitism, in which the association is disadvantageous or destructive to the host organism; mutualism, in which the association is advantageous to both; and commensalism, in which the symbiont benefits while the host is not affected [8]. However, mutualism, parasitism, and commensalism are not discrete categories of interactions but rather a continuum. In fact, the nature of a symbiotic interaction may vary due to developmental changes in the host or symbiont, changes in the biotic or abiotic environment, or variation in host genotype [11]. Correspondingly, the exchange of nutrients between symbiotic partners may be context dependent and may be bidirectional or heavily unidirectional.

The transmission characteristics of the PMF-based MRLPG were measured using the experimental setup as shown in Figure 3. The measurement setup consists of a broadband light source, linear translation SB431542 stages, and an optical spectrum analyzer. Both ends of the PMF-MRLPG were clamped by two linear translation stages. A distance between two translation stage was 30 cm. Strain was applied by GSK2126458 cost moving the translation stage outwards. Figure 3 Experimental setup for measurement of the transmission characteristics of the PMF-based MRLPG. Figure 4a shows

the transmission spectra of the fabricated PMF-based MRLPG with variations in strain. The birefringence of the PMF generated two resonant peaks in the transmission spectrum of the PMF-based MRLPG when strain was applied. Since the mode coupling between core and cladding modes based on the photoelastic effect is enhanced by increasing strain, the extinction ratio of the PMF-based MRLPG is obviously raised by strain. Two resonant wavelengths of the PMF-based MRLPG corresponding to two orthogonal polarization states were measured to be 1,395 and 1,471 nm. In Figure 4b, the variations of extinction ratios of two resonant peaks at wavelengths of 1,395 and 1,471 nm were measured to be https://www.selleckchem.com/products/SRT1720.html −10.16 and −14.13 dB, respectively, when the applied strain was 840 μϵ. However, two resonant wavelengths were almost not changed by the applied

stain because the photoelastic effect was simultaneously induced in the core and the cladding regions. When strain is applied to the PMF-based MRLPG, the variations of the effective refractive indices in the core and the cladding regions are almost identical, which induces the same amount of two self-coupling strengths in the core and the cladding modes [4]. It means that the proposed PMF-based MRLPGs can provide a simple sensing

scheme for measurement of strain filipin by monitoring the transmission power variation with respect to the external strain change. Figure 4 Transmission spectra (a) and variation of extinction ratios of two resonant peaks (b) of PMF-based MRLPG. Conclusion We proposed and experimentally demonstrated a fabrication method for the PMF-based MRLPG using the double coating and the wet etching processes, which has the great potential for mass production. The transmission characteristics of the PMF-based MRLPG with variations in strain were measured. Two resonant peaks of the PMF-based MRLPG were observed in the transmission spectrum of the PMF-based MRLPG because of the birefringence of the PMF. The extinction ratios of two resonant peaks of the PMF-based MRLPG were enhanced by increasing the applied strain without variation in their resonant wavelengths because of the photoelastic effect. The variation of the extinction ratios of two resonant peaks at wavelengths of 1,395 and 1,471 nm were measured to be −10.16 and −14.

Our results suggest further that YgjD depletion has two (possibly linked) effects: first, depletion triggers (p)ppGpp synthesis. Second, it leads to termination of cell division. To gain insights in which phase of the cell cycle YgjD-depleted cells are arrested we visualized the DNA-content of individual

cells with DNA-staining and subsequent fluorescence microscopy (Additional File 17 – Figure S8). After YgjD depletion in (p)ppGpp+ cells (TB80), DNA was localized at midcell and filled large areas of the cell (Additional File 17 – Figure S8 b), possibly indicating that cells were unable to carry out additional cell divisions due to “”nucleoid occlusion”" [31]. This mechanism prevents premature cell division before chromosomes

this website have been distributed to opposite cell halves. However, termination of cell division also manifests in a (p)ppGpp0 strain (Additional File 17 – Figure S8 c): depleted cells were elongated, TPX-0005 cell line and only a small fraction of the cell volume was filled with DNA. Thus, in the (p)ppGpp0 background, nucleoid occlusion alone cannot be responsible for termination of cell division. The elongated phenotype of YgjD depleted (p)ppGpp0 cells resembles filamentous cells blocked in cell division. However, since abrogating cell division is not inhibiting DNA replication or DNA segregation [32] it appears unlikely that YgjD directly affects cell division. Conclusions Our results show that single cell experiments coupled with statistical analysis can uncover phenotypic transitions that come about when an essential gene is depleted. We captured phenotypic changes with high temporal resolution across several cell generations. Cell tracking techniques allowed us to build

lineages of cells, and to analyze correlations between phenotypic traits at the level of sister cells emerging from the same division. This information can be used to describe growth transitions on the cellular level. We found that YgjD depletion has two, possibly linked, effects: a decrease in cell size that is accompanied by accumulation of (p)ppGpp, and the arrest of cell division. The involvement of (p)ppGpp in the alteration of cell size homeostasis under YgjD depletion conditions might explain the discrepancies between two studies ([3] and [17]) that click here observed Dapagliflozin opposite effects on cell size upon YgjD depletion. Katz et al. [17] used a relA + spoT + strain that is very similar to the ppGpp+ strain TB80 used here, and – consistent with our findings – observed shorter cells upon YgjD depletion. In contrast the MC4100 derivative that was used by Handford and colleagues [3] carries a relA1 allele. This allele is known to cause reduced cellular (p)ppGpp levels under certain growth conditions [26, 33]. Thus, their finding of elongated cells upon YgjD depletion might be similar to what we observed with the ppGpp0 strain TB84.

Children are addressed in Chapters 16 (diagnosis) and 17 (treatment), and elderly patients are addressed separately in Chapter 20. Renal replacement therapy is covered in Chapters 18 (dialysis) and 19 (renal transplantation), but the discussion is centered on problems encountered when non-dialysis CKD patients are switched to renal replacement therapy. These Guidelines are focused on non-dialysis CKD

patients and exclude, in principle, dialysis and renal transplant patients. 4. Evidence levels and recommendation grades Evidence was classified into six levels based on the study design, and was arranged roughly from the most reliable study type (Level 1) to the least reliable (Level Selleckchem Entospletinib 6). These levels do not necessarily represent rigorous scientific standards; they

are APR-246 concentration intended for use as a convenient reference for quickly assessing the significance of various clinical data during the physician’s decision-making process. Evidence levels Level 1: Systematic review/meta-analysis. Level 2: At least one randomized controlled trial (RCT). Level 3: A non-randomized controlled trial. Level 4: An analytical epidemiologic study (cohort study or case–control study) or a single-arm intervention study (no controls). Level 5: A descriptive study (case report or case series). Level 6: Opinion of an expert committee or https://www.selleckchem.com/products/byl719.html an individual expert, which is not based on patient data. However, for a systematic review/meta-analysis, the evidence level was decided based on the designs of the underlying studies. If the underlying study designs were mixed, the lowest level underlying study was why used to determine the overall evidence level. For example, a meta-analysis of cohort studies would be Level 4, but the same Level 4 would also be assigned to a meta-analysis including both RCTs and cohort studies. In addition, a decision based on committee consensus was that all sub-analyses and post hoc analyses of RCTs should be categorized at evidence Level 4. Accordingly, it was decided that the evidence level of

findings representing the primary endpoints of an RCT would be Level 2, but the evidence level of findings determined via a sub-analysis or post hoc analysis of that RCT would be Level 4. When a statement related to a certain treatment was presented, consideration was given to the level of the evidence serving as the basis of that statement, and a recommendation grade was assigned as outlined below: Recommendation grades Grade A: Strongly recommended because the scientific basis is strong. Grade B: Recommended because there is some scientific basis. Grade C1: Recommended despite having only a weak scientific basis. Grade C2: Not recommended because there is only a weak scientific basis. Grade D: Not recommended because scientific evidence shows the treatment to be ineffective or harmful.

pestis specific virulence plasmids pPCP1 and pMT1. The plasmid pCD1 was not used as it is shared by other Selleck Bortezomib pathogenic Yersinia species. A chromosomal sequence of unknown function that had been identified using comparative genome hybridization [17] was selected as Y. pestis specific chromosomal target. find more Spores of B. thuringiensis were used as internal

control, not only for DNA amplification but also for successful DNA extraction. This member of the B. cereus group is closely related to B. anthracis and forms similar spores, while it contains species-specific plasmids. The B. thuringiensis plasmid gene encoding insecticidal crystal proteins (cry genes) was used as the signature sequence for the detection of DNA released from this organism’s spores. Sequence analysis tools, bioinformatics software Sequences retrieved from NCBI/EMBL were organized and aligned using the software package Kodon (Applied Maths, Ghent, Belgium). Comprehensive sequence alignments were made by performing BLAST searches from the selected targets to make sure all available sequence homologues were included in the alignments. Oligonucleotides for multiplex qPCR assays and for conventional PCR assays were designed using the software package Visual Oligonucleotide Modeling Platform version 6 (DNA software Inc. Ann Arbor, USA). The design strategy for multiplex qPCR assays was as follows. First, a hydrolysis

probe and primer Sotrastaurin manufacturer set were designed for the B. thuringiensis internal control. Then, for each selected signature sequence a hydrolysis probe was designed, followed by the design of the corresponding primer set. A different strategy was chosen for the B. anthracis assay, because its chromosomal target sspE has homologues in other Bacillus, notably the internal control B. thuringiensis. To make sure that detection of B. anthracis sspE was highly selective, the exact positions of probe and primers were guided based on visual inspection of the alignment. Probe and primers were located in regions with mismatches Selleck Vorinostat between Bacillus species (notably between B. thuringiensis and B. anthracis),

and the primers were designed such that mismatch positions were located at their highly discriminating 3′-ends. Oligonucleotides that were calculated by the design software were first checked against the consensus alignment to exclude designs not covering all sequence variants, and were then evaluated using the simulation module of Visual OMP. All oligonucleotides designed were validated in silico by using BLAST searches in general and microbial genomes databases (NCBI/EMBL). Sequencing Sequences were obtained from the cry1 gene from B. thuringiensis strain ATCC 29730 and from the sspE gene from all B. anthracis strains in our culture collection, B. thuringiensis ATCC 29730 and B. cereus strains WSBC 10583, 10619, 10766, 10483, 10572, 10705, 10770 and 10865 (Additional file 1 Table S1).

B. Selleckchem TPCA-1 fragilis and B. thetaiotaomicron are usually commensal components of the normal intestinal microbiota. However, B. fragilis cells adhered to epithelial cells in biopsy samples from IBD patients [36, 37]. In addition, release of these organisms into other body sites can result in serious complications and they are associated with Temozolomide cell line a range of extraintestinal infections [5]. Growth of B. fragilis in bile, blood and oxygen has previously been shown to enhance properties associated with increased virulence [6, 27, 38]. Bile is secreted into the small intestine as a normal part of fat digestion/metabolism. Previous studies on the exposure of B. fragilis to physiological

concentrations of bile reported the increase of outer membrane vesicle formation and fimbria-like appendages, and increased expression of genes encoding antibiotic resistance-associated RND-type efflux pumps [38]. The same study showed that the bile salt-treated bacterial cells had increased resistance to a range of antimicrobial agents and as well as increased co-aggregation, biofilm formation, and adhesion to intestinal epithelial cells [38]. Bile is normally associated with small intestinal secretions. In the current study, B. fragilis and B. thetaiotaomicron were grown in the presence of physiological levels of bile (0.15% bile

salts approximates to a concentration of 3.7 mM), reflecting concentrations found in the distal Vadimezan ileum (2 mM). These conditions did not alter the expression level of C10 protease genes in either organism. This suggests that in the large intestine, where the bile concentrations PJ34 HCl are considerably lower (0.09 to 0.9 mM), the production of these proteases is not likely

to be responsive to residual levels of bile transiting from the small intestine. The oxyR gene encodes a redox-sensitive transcriptional regulator of the oxidative stress response in B. fragilis[39]. It has been shown previously that B. fragilis oxyR mutants are attenuated in an intra-abdominal abscess infection model [27]. Thus the ability of B. fragilis to survive in oxygenated environments such as blood is thought to be linked with pathogenesis. Two of the B. fragilis C10 proteases (bfp1 and bfp4) displayed increased expression levels when exposed to oxygen. The expression levels of the other protease genes (bfp2 and bfp3) remained unchanged. Interestingly, genes encoding superoxide dismutase and an oxidoreductase can be found directly upstream of bfp4. These two genes encode proteins involved in the processing of reactive oxygen species and are also likely to be up-regulated in the presence of atmospheric oxygen. Three of the C10 protease genes in B. thetaiotaomicron were up-regulated significantly in the presence of oxygen, while btpA was down-regulated.

In the latest years an increasing number of genomes have been sequenced paving the path for genomics-based approaches. For P. gingivalis genome sequences of the virulent strain W83 and the less-virulent strain ATCC33277 have become available [28, 29]. Comparative genomic hybridization (CGH) analysis using microarrays of these well-described bacterial strains could yield new insights in the virulence mechanisms of P. gingivalis. A recent study reported on the CGH analysis of several P. gingivalis strains to describe the genetic buy PF-6463922 variety among them [30]. In this study we analyzed the genetic contents of representative strains of each of the seven capsular serotypes (Table 1): W83 (K1), HG184

(K2), ATCC53977 (K3), ATCC49417 (K4), HG1690 (K5), HG1691 (K6), 34-4 (K7). We also included the non-encapsulated strain FDC381 (K-) in the CGH analysis to compare with each of the encapsulated strains. Strain FDC381 does however express a non-CPS anionic extracellular polysaccharide as do the other strains [31]. The strains were classified into three virulence levels as determined by using a subcutaneous mouse infection model [18, 32]. Although not an optimal measure for the ability to cause periodontitis, this classification has long been used [33] and proven useful in studying virulence determinants [34–37]. Table 1 P. gingivalis strains used in this study Strain Capsular serotype Origin Virulencec W83a K1 Clinical

specimen High HG184 K2 Periodontitis

patient Medium HG1025 K3 Periodontitis patient with diabetes Wortmannin mellitus High ATCC49417 K4 Advanced adult periodontitis patient High HG1690 K5 37-year-old male periodontitis patient High HG1691 K6 28-year-old female periodontitis patient Medium 34-4 K7 Severe periodontitis patient Low FDC381b else K- Adult periodontitis patient Low a A kind gift of H. N. Shah (NCTC, London, UK) b A kind gift of S. S. Socransky (The Forsyth selleck Institute, Boston, MA, USA) c As determined in a subcutaneous mouse infection model [18, 32] Triplicate hybridization experiments and three types of analysis, 1) aberrant gene calling, 2) breakpoint analysis and 3) absent gene calling, have been performed for optimal use of the new genetic information. The careful design of the experiment and the thorough analysis of the data lead to a high resolution data set, yielding more detailed information on the genetic differences between strains than has been shown before. In this study we initiate the description of a core-gene set of P. gingivalis allowing a more focused search for potential important virulence factors. Results and discussion Microarray performance and data interpretation The P. gingivalis version 1 microarray from the PFGRC used in this study has been used in several studies before [30, 38] and consists of 1907 probes and 500 negative control probes (Arabidopsis thaliana) printed in four replicates.

Biofuels 2007, 108:205–235.CrossRef 6. Lynd LR, van Zyl

WH, McBride JE, Laser M: Consolidated bioprocessing of cellulosic biomass: an update. Current Opinion in Biotechnology 2005,16(5):577–583.PubMedCrossRef 7. Dror TW, Morag E, Rolider A, Bayer EA, Lamed R, Shoham Y: Regulation of the cellulosomal celS ( cel48A ) gene of Clostridium thermocellum is growth rate dependent. J Bacteriol 2003,185(10):3042–3048.PubMedCrossRef 8. C646 ic50 Dror TW, Rolider A, Bayer EA, Lamed R, Shoham Y: Regulation of expression of scaffoldin-related genes in Clostridium thermocellum . J Bacteriol 2003,185(17):5109–5116.PubMedCrossRef 9. Dror TW, Rolider A, Bayer EA, Lamed R, Shoham Y: Regulation of major cellulosomal endoglucanases of Clostridium thermocellum differs from that of a prominent cellulosomal xylanase. J Bacteriol 2005,187(7):2261–2266.PubMedCrossRef

10. Mishra S, Beguin P, Aubert JP: Transcription of Clostridium thermocellum endoglucanase genes celF and celD. J Bacteriol 1991,173(1):80–85.PubMed 11. Stevenson DM, Weimer PJ: Expression of 17 genes in Clostridium www.selleckchem.com/products/ferrostatin-1-fer-1.html thermocellum ATCC 27405 during fermentation of cellulose or cellobiose in continuous culture. Appl Environ Microbiol 2005,71(8):4672–4678.PubMedCrossRef 12. Zhang YH, Lynd LR: Regulation of cellulase synthesis in batch and continuous cultures of Clostridium thermocellum . J Bacteriol 2005,187(1):99–106.PubMedCrossRef 13. Carere CR, Kalia V, Sparling R, Cicek N, Levin DB: Pyruvate catabolism and hydrogen synthesis pathway genes of Clostridium thermocellum ATCC 27405. Indian Journal of Microbiology 2008,48(2):252–266.CrossRef 14. Rydzak T, Levin DB, Cicek N, Sparling R: Growth phase-dependant enzyme profile of pyruvate catabolism and end-product formation in Clostridium thermocellum ATCC 27405. J Biotechnol 2009,140(3–4):169–175.PubMedCrossRef 15. Brown SD, Raman B, McKeown CK, Kale SP, He Z, Mielenz JR: Construction and evaluation of a Clostridium thermocellum ATCC GBA3 27405 whole-genome oligonucleotide microarray. Appl Biochem Biotechnol

2007,137–140(1–12):663–674.PubMedCrossRef 16. Raman B, Pan C, Hurst GB, Rodriguez M Jr, McKeown CK, Lankford PK, Samatova NF, Mielenz JR: Impact of pretreated ARRY-162 nmr Switchgrass and biomass carbohydrates on Clostridium thermocellum ATCC 27405 cellulosome composition: a quantitative proteomic analysis. PLoS One 2009,4(4):e5271.PubMedCrossRef 17. Chhabra SR, He Q, Huang KH, Gaucher SP, Alm EJ, He Z, Hadi MZ, Hazen TC, Wall JD, Zhou J, Arkin AP, Singh AK: Global analysis of heat shock response in Desulfovibrio vulgaris Hildenborough. J Bacteriol 2006,188(5):1817–1828.PubMedCrossRef 18. Saeed AI, Bhagabati NK, Braisted JC, Liang W, Sharov V, Howe EA, Li J, Thiagarajan M, White JA, Quackenbush J: TM4 microarray software suite. Methods Enzymol 2006, 411:134–193.PubMedCrossRef 19. Sparling R, Islam R, Cicek N, Carere C, Chow H, Levin DB: Formate synthesis by Clostridium thermocellum during anaerobic fermentation.

a.   P. pentosaceus (16)                   8 8               n.a.   W. cibaria (15)                           15         n.a. aMICs determined by a VetMIC test. The click here antibiotic dilution ranges were: 0.03-16 mg/L (ampicillin, clindamycin, penicillin and linezolid), 0.25-128 mg/L (vancomycin and

ciprofloxacin), 0.5-256 mg/L (gentamicin, streptomycin and neomycin), 2-1024 mg/L (kanamycin), 0.016-8 mg/L (erythromycin), 0.12-64 (tetracycline, chloramphenicol, rifampicin and trimethoprim). MICs which exceeded the upper or lower limit of the tested range are listed in the next dilution series. MICs higher than the EFSA breakpoints are indicated in bold. bLAB with MICs higher than the EFSA breakpoints are considered as resistant strains [15]. n.r., not required; n.a., not available. Detection of antibiotic resistance genes The non-enterococcal strains showing antibiotic resistances in the VetMIC assays (17 strains)

were further submitted to PCR in order to identify the presence of the respective antibiotic resistance genes. The tested strains were the following: Lb. selleck carnosus B43 (ampicillin resistant), P. pentosaceus TPP3 and SMF120 (tetracycline resistant), P. pentosaceus LPP32, LPM83 and B5 (clindamycin resistant), P. pentosaceus LPV57 and W. cibaria P50, P61, P64, P73, SDM381, SDM389, SMA14 and BCS50 (kanamycin resistant), and P. pentosaceus MAPK inhibitor LPM78 and W. cibaria SMA25 (kanamycin, erythromycin and clindamycin resistant). Acquired antibiotic resistances likely due to added genes were only found in strains within the genera Pediococcus (12.5%) and Weissella (6.7%). The genes involved in the horizontal transfer of resistance

to tetracycline [tet(K), tet(L) and tet(M)], kanamycin [aac(6´ )-Ie-aph(2´ ´ )-Ia] and erythromycin [erm(A), erm(B) and erm(C)] were not detected. However, P. pentosaceus LPM78 and W. cibaria SMA25 harboured the erythromycin resistance gene mef(A/E). The obtained amplicons were sequenced and found to have 99% homology with the macrolide-efflux protein (mefE) gene described for Streptococcus pneumoniae and other Streptococcus spp. Arachidonate 15-lipoxygenase Moreover, P. pentosaceus LPM78 and LPM83 harboured the lnu(A) gene encoding the lincosamide O-nucleotidyltransferase that inactivates lincomycin and clindamycin. Sequencing of both amplicons showed 97% and 93% homology with lincosamide nucleotidyltransferase [lnu(A)] gene described for Staphylococcus haemolyticus and S. aureus, respectively. Nevertheless, lnu(B) was not detected in any of the tested strains. With regard to E. faecium BNM58, which was phenotypically resistant to erythromycin, none of the respective genes [erm(A), erm(B), erm(C) and mef(A/E)] were detected.

References 1. Kanaoka M, Liu C, Nomura K, Ando M, Takino H, Fukuda Y, Mimura H, Yamauchi K, Mori Y: Figuring and smoothing capabilities of elastic emission machining for low-thermal-expansion glass optics. J Vac Sc Technol B (Microelectronics and Nanometer Structures) 2007, 25:2110–2113.CrossRef 2. Axel S, Georg B, Thomas H, BAY 1895344 Wilfried F, Andreas N, Bernd R, Frieder B: Precision optical asphere fabrication by plasma jet chemical etching (PJCE) and ion beam figuring. Int Society Opt Eng 2001, 4451:242–248. 3. Marc T, Paul D, Greg F, Mike DM: Recent advances in sub-aperture approaches to finishing and metrology. Int Society Opt Eng 2006, 6149:614903–1-19. 4. Kazuto Y, Erastin order Hidekazu M, Kouji I,

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M, Takashi K, Daisuke Y, Weimin L, Yoshihiro U, Selleckchem MLN0128 Hirokatsu Y, Satoshi M, Yoshinori N, Kenji T, Haruhiko O, Makina Y, Tetsuya I, Hitoshi O, Kazuto Y: Fabrication of a 400-mm-long mirror for focusing X-ray free-electron lasers to sub-100 nm. In Proceedings of SPIE – The International Society for Optical Engineering. 7077 edition. San Diego; 2008:70770R-1–70770R-8. 8. Takahiro S, Yoshinori T, Hidekazu M: Development of surface profile measurement method for ellipsoidal X-ray mirrors using phase retrieval. In Proceedings of SPIE – The International Society for Optical Engineering. 8501 edition. San Diego; 2012:850103–1-850103–8. 9. Anirban G, Barron RM, Ram B: An experimental and numerical study of water jet cleaning process. J Mater Process Technol 2011, 211:610–618.CrossRef Progesterone 10. Hitoshi SOYAMA, Yoshiaki YAMAUCHI, Yasunori ADACHI, Kazunori

SATO, Takenori SHINDO, Risaburo OBA: High-speed observations of the cavitation cloud around a high-speed submerged water jet. JSME Int J B-Fluid T 1995, 38:245–251.CrossRef 11. Goodarz A: On the k-ϵ model of turbulence. Int J Eng Sci 1985, 23:849–856.CrossRef 12. Kazuto Y, Kazuya Y, Hidekazu M, Yasuhisa S, Akira S, Katsuyoshi E, Alexei S, Makina Y, Kenji T, Tetsuya I, Yuzo M: Two-dimensional submicron focusing of hard X-rays by two elliptical mirrors fabricated by plasma chemical vaporization machining and elastic emission machining. Jpn J Appl Phys 1 2003, 42:7129–7134.CrossRef Competing interests Both authors declare that they have no competing interests. Authors’ contributions YT performed simulations and experiments. HM supervised the research work and helped amend the manuscript.