Yu Q, Yu C, Wang J, Guo F, Gao S, Jiao S, Li H, Zhang X, Wang X,

Yu Q, Yu C, Wang J, Guo F, Gao S, Jiao S, Li H, Zhang X, Wang X, Gao H, Yang H, Zhao L: Gas sensing properties of self-assembled ZnO nanotube bundles. RSC Adv 2013, 3:16619–16625.CrossRef Competing interests The authors declare that they have no competing interests. Authors’ contributions YCL designed the experiments and drafted the manuscript. TYL carried out the sample preparations

and the material analyses. Both authors read and approved the final manuscript.”
“Background Silicon-based technology is the prime enabler for high-density integrated microelectronic circuits, optoelectronics, and photovoltaic devices with ubiquitous applications ranging from mobile devices to high-end computing and communications. As Si complementary metal-oxide-semiconductor (CMOS) circuits are

relentlessly scaled down to 16 nm or smaller dimensions, knowledge about fundamental nanoscopic #PD0332991 molecular weight randurls[1|1|,|CHEM1|]# processes in Si is becoming crucial for developing a good understanding on the limitations of nanofabrication and the development of future evolutionary directions for the technology as a whole. Many processing reactions including epitaxial growth, doping, oxidation, selleck and silicidation are affected by the native defects in Si such as vacancies, self-interstitials, and their complexes. It is believed that Si interstitials play an important role in these processes, mostly detrimental, for instance causing such effects as undesirable transient-enhanced diffusion of dopants

in p/n junctions [1, 2], metal spiking at silicide/Si interfaces [3], interfacial traps along the gate oxide/Si interface [4], and stacking faults/dislocations in the epitaxial layer [1, 5, 6]. In this paper, we report a unique effect, hitherto unreported, that is attributable to Si interstitials present within oxide layers previously generated by the selective oxidation of polycrystalline-SiGe (poly-SiGe) nanopillars leaving behind Ge quantum dots (QDs) or nanocrystallites when the preferential oxidation of Si is complete. In this novel phenomenon, these Ge QDs or nanocrystallites appear to be very sensitive to the presence of Si interstitials, almost acting as detectors for these interstitial species. The mechanism appears to be complex and long range in comparison to the typical diffusion lengths of Si interstitials within oxide layers. Methods Three different Dipeptidyl peptidase cases were considered for our experimental study. All cases consisted of heterostructures as shown in Figures 1,2,3,4. These samples were prepared using a CMOS-compatible approach by the deposition of poly-Si0.85Ge0.15 layers over buffer layers of Si3N4 or SiO2 on Si substrates using low-pressure chemical vapor deposition. In general, a multilayer deposition of Si3N4/SiO2/Si0.85Ge0.15/SiO2 was carried out sequentially on top of a Si substrate. The topmost, thin SiO2 layer is deposited as a hard mask for subsequent plasma etching for producing SiGe nanopillars.

Ecotoxicol Environ Saf 2007, 67:75–81 PubMedCrossRef 12 Morgante

Ecotoxicol Environ Saf 2007, 67:75–81.PubMedCrossRef 12. Morgante V, López-López A, Flores C,

González M, González B, Vásquez M, Rosselló-Mora R, Seeger M: Bioaugmentation with Pseudomonas sp. strain MHP41 promotes simazine attenuation and bacterial community changes in Peptide 17 chemical structure agricultural soils. FEMS Microbiol Ecol 2010, 71:114–126. Erratum in FEMS Microbiol Ecol 2010, 72:152PubMedCrossRef 13. Hernández M, Jia Z, Conrad R, Seeger M: Simazine application inhibits nitrification and changes the ammonia-oxidizing bacterial communities in a fertilized agricultural soil. FEMS Microbiol Ecol 2011, 78:511–519.PubMedCrossRef 14. Niklinska M, Chodak M, Laskowski R: Characterization of the forest humus microbial community in a heavy metal polluted area. Soil Biol Biochem 2005, 37:2185–2194.CrossRef 15. Dell’Amico E, Mazzocchi XAV-939 price M, Cavalca L, Allievi L, Andreoni V: Assessment of

bacterial community structure in a long-term copper-polluted ex-vineyard soil. Microbiol Res 2008, 163:671–683.PubMedCrossRef 16. Li Z, Xu J, Tang C, Wu J, Muhammad A, Wang H: Application of 16S rRNA PCR amplification and DGGE fingerprinting for detection of shift microbial community diversity in Cu-, Zn-, and Cd-contaminated paddy soil. Chemosphere 2006, 62:1374–1380.PubMedCrossRef 17. Magnani D, Solioz M: How bacteria handle cooper. In Molecular microbiology of heavy metals. Volasertib solubility dmso Edited by: Nies DH, Silver S. Springer-Verlag, Berlin Heidelberg; 2007:259–285.CrossRef 18. Wei G, Fan L, Zhu W, Fu Y, Yu J, Tang M: Isolation and characterization of the heavy metal resistant bacteria CCNWRS33–2 isolated from root nodule of Lespedeza cuneata in gold mine tailings in China. J Hazard Mater 2009, 162:50–56.PubMedCrossRef 19. Dupont CL, Grass G, Rensing C: Copper toxicity and the origin of Protein tyrosine phosphatase bacterial resistance-new insights and applications. Metallomics 2011, 3:1109–1118.PubMedCrossRef 20. Tetaz TJ, Luke RK: Plasmid-controlled resistance to copper in Escherichia coli. J Bacteriol 1983, 154:1263–1268.PubMed 21. Mellano MA, Cooksey DA: Nucleotide sequence and organization of copper

resistance genes from Pseudomonas syringae pv. tomato. J Bacteriol 1988, 170:2879–2883.PubMed 22. Voloudakis AE, Reignier TM, Cooksey DA: Regulation of resistance to copper in Xanthomonas axonopodis pv. vesicatoria. Appl Environ Microbiol 2005, 71:782–789.PubMedCrossRef 23. Teitzel GM, Geddie A, de Long SK, Kirisits MJ, Whiteley M, Parsek MR: Survival and growth in the presence of elevated copper: transcriptional profiling of copper-stressed Pseudomonas aeruginosa . J Bacteriol 2006, 188:7242–7256.PubMedCrossRef 24. Monchy S, Benotmane MA, Janssen P, Vallaeys T, Taghavi S, van der Lelie D, Mergeay M: Plasmids pMOL28 and pMOL30 of Cupriavidus metallidurans are specialized in the maximal viable response to heavy metals. J Bacteriol 2007, 189:7417–7425.PubMedCrossRef 25. Nies D: Microbial heavy-metal resistance.

In general, one will only find those SNPs that exist among the ge

In general, one will only find those SNPs that exist among the genomic samples used in the comparisons and novel SNPs will remain undiscovered [21]. This discovery bias can strongly affect taxonomic interpretation of results [22, 23].

Although discovery bias is often less consequential for genotyping efforts, the effects of our choice of strains for SNP discovery are clearly apparent in our phylogenetic tree. The discovery strains are distinguished by their positions at terminal branches in the phylogeny. There is greater diversity observed in B. abortus simply because two strains were part of the Sapanisertib nmr discovery panel. Furthermore, although isolates on a branch will be grouped by the SNPs they share (or do not share), additional structure exists in the “true” phylogeny that is not apparent in the

genotype tree. Branch lengths are also highly affected by the SNP discovery process. Species that are basal within this phylogeny, such as B. ceti B. pinnipedialis B. ovis, and B. neotomae have short branch lengths merely because these genomes were not part of SNP discovery. It must also be noted that B. suis biovar 5 is part of this basal group. SNPs that should group it with the rest of the B. suis clade were not present in our MIP assay, which is not surprising since this branch is extremely short, even with whole genome analysis [JTF unpubl. data, [24]. We did not observe differentiation of these and the other Brucella species, nor PD173074 did we expect it because genomes from these groups were not a part of SNP discovery. Whole genome resequencing at the Broad Institute of MIT/Harvard recently generated genomes for over 100 additional Brucella strains and these genomes should provide a broad basis for future genotyping efforts, with canonical SNPs developed for each of the important isolates and clades. Future genotyping

efforts should include SNPs from all of the recognized species and biovars. Comparative work using some of these genomes has already been fruitful, demonstrating the emergence of Branched chain aminotransferase the marine Brucella from within the terrestrial Brucella and showing a methodology for whole genome analysis [24]. A trade-off exists in current genotyping efforts between throughput and genomic sampling. Does one aim for a maximum amount of potentially informative loci through approaches such as whole genome sequencing but having to sacrifice the number of isolates that can be evaluated? Or does one aim for more complete sampling of large numbers of isolates but with a limited set of loci using RG7112 molecular weight individual SNP assays such as CUMA? Of course the ultimate answer depends on your research interest or clinical application as well as the amount of resources at hand. MIP assays provide phylogenetic resolution for an intermediate number of samples and intermediate number of SNPs.

Molecular microbiology 2003,50(3):729–738 PubMedCrossRef 15 Patt

Molecular microbiology 2003,50(3):729–738.PubMedCrossRef 15. Patton SIS3 clinical trial TG, Yang SJ, Bayles KW: The role of proton motive force in expression of the Staphylococcus aureus cid and lrg operons. Molecular microbiology 2006,59(5):1395–1404.PubMedCrossRef 16. Kong KF, Vuong C, Otto M: Staphylococcus quorum

sensing in biofilm formation and infection. Int J Med Microbiol 2006,296(2–3):133–139.PubMedCrossRef 17. Boles BR, Horswill AR: Agr-mediated dispersal of Staphylococcus aureus biofilms. PLoS pathogens 2008,4(4):e1000052..PubMedCrossRef 18. Toledo-Arana A, Merino N, Vergara-Irigaray M, Debarbouille M, Penades JR, Lasa I: Staphylococcus aureus develops an alternative, ica-independent biofilm in the absence of the arlRS two-component system. Journal of bacteriology 2005,187(15):5318–5329.PubMedCrossRef 19. Wang J, Zhu T, Lou Q, Wu Y, Han C, Qu D: Biological functions of arlS gene of two-component signal transduction system in Staphylococcus epidermids. Chinese Journal of Microbiology and Immunology selleck kinase inhibitor 2007,27(10):.. 20. Brunskill EW, Bayles KW: Identification of LytSR-regulated genes from Staphylococcus aureus. Journal of bacteriology 1996,178(19):5810–5812.PubMed 21. Lim Y, Jana M, Luong TT, Lee CY: Control of selleck products glucose-and NaCl-induced biofilm formation by rbf in Staphylococcus aureus.

Journal of bacteriology 2004,186(3):722–729.PubMedCrossRef 22. Howell A, Dubrac S, Andersen KK, Noone D, Fert J, Msadek T, Devine K: Genes controlled by the essential YycG/YycF two-component system of Bacillus subtilis revealed through a novel hybrid regulator approach. Molecular microbiology Progesterone 2003,49(6):1639–1655.PubMedCrossRef 23. Fabret C, Hoch JA: A two-component signal transduction system essential for growth of Bacillus subtilis: implications for anti-infective therapy. Journal of bacteriology 1998,180(23):6375–6383.PubMed 24. Dubrac S, Boneca IG, Poupel O, Msadek T: New insights into the WalK/WalR (YycG/YycF) essential signal transduction pathway reveal a major role in controlling cell wall metabolism and biofilm formation

in Staphylococcus aureus. Journal of bacteriology 2007,189(22):8257–8269.PubMedCrossRef 25. Qin Z, Zhong Y, Zhang J, He Y, Wu Y, Jiang J, Chen J, Luo X, Qu D: Bioinformatics analysis of two-component regulatory systems in Staphylococcus epidermidis. CHINESE SCIENCE BULLETIN 2004,49(12):1267–1271.CrossRef 26. Rice KC, Firek BA, Nelson JB, Yang SJ, Patton TG, Bayles KW: The Staphylococcus aureus cidAB operon: evaluation of its role in regulation of murein hydrolase activity and penicillin tolerance. Journal of bacteriology 2003,185(8):2635–2643.PubMedCrossRef 27. Yang SJ, Dunman PM, Projan SJ, Bayles KW: Characterization of the Staphylococcus aureus CidR regulon: elucidation of a novel role for acetoin metabolism in cell death and lysis. Molecular microbiology 2006,60(2):458–468.PubMedCrossRef 28.

Lüders (unpublished work) to also include miRNA for further

Lüders (unpublished work) to also include miRNA for further analyses. Approximately

60 mg frozen tissue was homogenized in TriReagent (Ambion) using Mixer Mill MM301 (Retch) for 2 × 2 min at 30 Hz. After phase-separation with chloroform, the aqueous eFT-508 molecular weight phase (containing RNA) was mixed with 1.5 volumes 100% ethanol and transferred to an RNeasy Mini spin column (Qiagen). Further processing was performed following the manufacturer’s protocol. A DNase INCB28060 concentration treatment was included in the procedure. RNA was eluted in 60 μl RNase-free water and stored at -80°C. The concentration of each RNA sample was obtained from A260 measurements using the

NanoDrop 2000 (Thermo Fischer Scientific Inc.). The RNA integrity number (RIN) was tested by using the Agilent 2100 Bioanalyzer (Agilent Technologies). cDNA synthesis Complementary DNAs (cDNAs) were produced from 1 μg RNA of each sample using the High Capacity RNA-to-cDNA Master Mix (Applied Biosystems) according to the manufacturer’s instructions. The following thermal cycler conditions were used: 5 min at 25°C, 30 min at 42°C and 5 min at 85°C. Three random RNA samples were GSK2245840 additionally run in the absence of reverse transcriptase enzyme to assess the degree of contaminating genomic DNA. Real-time PCR with genomic DNA specific assay revealed that RNA was free of genomic DNA (data not shown). TLDA design and preparation TaqMan Endogenous Control Assays (Applied Biosystems) are 384-well microfluidic cards containing 16 preoptimized human TaqMan Gene Expression Assays commonly used as endogenous controls and genes that exhibit minimal differential expression across different

tissues (Table 1). Methane monooxygenase The assay was performed in triplicates. 50 μl cDNA (1 μg mRNA) was used as a template. Matched samples from 4 patients where loaded on each card. NTC (no template control) was added in one loading port. PCR amplification was performed using the ABI Prism 7900 HT Real Time PCR System (Perkin-Elmer Applied Biosystems, Foster City, California, USA). Thermal cycling conditions were used as follows: 2 min at 50°C, 10 min at 94.5°C, 30 sec at 97°C, and 1 min at 59.7°C for 40 cycles. Table 1 Candidate reference genes included in the TaqMan Endogenous Control Assay.

Different types of fimbriae were reported to be associated with S

Different types of fimbriae were reported to be associated with STEC diarrhea in animals of different age groups [15–18]. The Yersinia high-pathogenicity island (HPI) carrying fyuA (find more encoding the pesticin receptor) and irp (encoding the siderophore yersiniabactin) is also present in certain non-O157 STEC lineages and was previously reported only in stx 2e carrying human isolates [19]. Domestic ruminants, especially cattle, are the major

reservoirs of STEC. Other animals like sheep, goats have been confirmed as important natural reservoirs in some countries [2, 20–22]. Swine also play an important role as a carrier of this pathogen. STEC strains that produce Stx2e can cause edema disease in pigs [23] and can also been isolated from human stools at low frequency. STEC carried by healthy pigs may pose a potential risk to humans [24–27]. Relatively little is known about the prevalence and characteristics of STEC in pigs

in China. In this GDC 0032 mw study, we isolated and characterized STEC from different pig slaughter houses and pig farms from 3 geographical regions, Beijing city, Chongqing city and Guizhou province in China. Results Prevalence of STEC in swine samples Out of 1003 swine samples collected in this study, 25.42% (255/1003) were stx-positive by PCR. A total of 93 STEC isolates was obtained from 62 samples, giving a culture positive rate of 24.31% (62/255) of all stx-positive Epacadostat in vivo samples. Different stx-positive rates in small intestine contents (10.83%), colon contents (47.24%) and feces (19.33%) samples were Y-27632 2HCl observed. The colon contents samples gave the highest stx-positive rate (P < 0.05) and also the highest culture positive rate (18.09%) (P < 0.05) (Table 1). Table 1 Prevalence of STEC in swine samples Sample location (city/province)

No. of samples Type of samples (N, %) stx positive samples (N, %) Samples with STEC isolates (N, %) STEC isolates (N, %) Beijing 523 SC (248, 24.73) SC (30, 8.55) SC (3, 0.85) SC (7, 1.99) CC (275, 27.42) CC (139, 42.64) CC (36, 11.04) CC (57, 17.48) Chongqing 326 F (326, 32.50) F (63, 19.33) F (17, 5.21) F (23, 7.06) Guizhou 154 SC (103, 10.27) SC (8, 2.28) SC (4, 1.14) SC (4, 1.14) CC (51, 5.08) CC (15, 4.60) CC (2, 0.61) CC (2, 0.61) Total 1003 SC (351, 35.00) SC (38, 10.83) SC (7, 1.99) SC (11, 3.13) CC (326, 32.50) CC (154, 47.24) CC (38, 11.66) CC (59, 18.09)     F (326, 32.50) F (63, 19.33) F (17, 5.21) F (23, 7.06) Sample codes: F, fecal samples; CC, colon contents samples; SC, small intestine contents samples. The number (N) and rate (%) are showed in the parentheses. Only a single isolate was recovered from 44 stx-positive samples each. But 2 isolates per sample were recovered from 15 samples, 3 isolates per sample from 3 samples, 4 isolates per sample from 2 samples and 5 isolates per sample from 1 sample. Serogroups and serotypes The 93 STEC isolates were typed into 19 serotypes, comprising 12 O serogroups and 15 H types.

Extracts derived from MC4100 (wild type) revealed mainly the proc

Extracts derived from MC4100 (wild type) revealed mainly the processed form of the catalytic subunit of all three enzymes (Figure 3A), which is indicative of successful insertion of the [NiFe]-cofactor [5]. In contrast, a mutant unable to synthesize the HypF protein C59 wnt mouse (DHP-F2) is unable to generate the diatomic CN- ligands and consequently fails to insert the cofactor. Extracts from a hypF mutant therefore only showed the AZD1480 purchase unprocessed form of each catalytic subunit (Figure 3A), which indicates that

the large subunit lacks a cofactor [5]. Extracts derived from CP416 (entC) and CP422 (fecA-E) both showed levels of processed large subunits for Hyd-1, Hyd-2 and Hyd-3 similar to those seen for the wild-type MC4100 (Figure 3A). Densitometric analysis of the levels of these processed polypeptides in the autoradiogram shown in Figure 3A, however, revealed that in extracts of CP416 and CP422 Hyd-1 large subunit levels were only 20% and 50%, respectively, of that observed in the wild type, while in extracts of CP416 the level of Hyd-3 large subunit HycE was almost 3-fold increased compared with the level in the wild type (Figure Momelotinib mouse Amino acid 3B). Extracts derived

from the fecA-E entC double null mutant CP415 showed the similar increased level of Hyd-3 large subunit and decreased level of Hyd-1 large subunit as was observed with CP416; however, the difference was that Hyd-2 levels were decreased by approximately 40% compared with the wild type. These results suggest that under mild iron-limiting conditions, intracellular iron is preferentially used for hydrogen-evolving

function. The feoB mutant PM06 showed strongly reduced levels of processed Hyd-1 large subunit and barely detectable levels of Hyd-2 processed large subunit; the amount of processed Hyd-3 large subunit was approximately 50% that of the wild-type. Cell-free extracts of CP411 (entC feoB::Tn5) and CP413 (entC fecA-E feoB::Tn5), on the other hand, essentially completely lacked either the unprocessed or processed forms of the large subunits of Hyd-1 or Hyd-2, which correlates with the lack of Hyd-1 and Hyd-2 enzyme activity observed in Figure 2. Both the processed and unprocessed forms of the Hyd-3 large subunit HycE were observed in extracts from both strains but at significantly reduced levels, which is in accord with the observed FHL activity measured in the strains (see Table 4).

g , $$ f = \left( {{\frac{{{\raise0 7ex\hbox{${\Updelta {}^34\tex

g., $$ f = \left( {{\frac{{{\raise0.7ex\hbox{${\Updelta {}^34\textO_2 }$} \!\mathord{\left/ {\vphantom {{\Updelta {}^34\textO_2 } {\left[ Selleck GSK1904529A {{}^34\textO_2 } \right]}}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${\left[ {{}^34\textO_2

} \right]}$}}}}{{{\raise0.7ex\hbox{${\Updelta {}^32\textO_2 }$} \!\mathord{\left/ {\vphantom {{\Updelta {}^32\textO_2 } {\left[ {{}^32\textO_2 } \right]}}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${\left[ {{}^32\textO_2 } \right]}$}}}}}} \right) \times 1000 $$ (9)The key advantage of this technique is that discrimination

values can be derived in a matter of minutes (the time for a reaction) rather than days (the time for subsequent gas extraction and processing). This technique is in its infancy, but has been used already to study CO2 discrimination in Rubisco carboxylase reactions and O2 discrimination in mitochondrial terminal oxidases (McNevin et al. 2006; McNevin see more et al. 2007; Armstrong et al. 2008). Substrate water exchange in PSII Isotopic exchange of water-derived oxygen ligands of the oxygen-evolving complex (OEC) into O2 has been of long standing interest with PSII, because it contains information of how, when, and where substrate-water is bound to the OEC and in what manner it is oxidized to molecular O2—e.g. via: (1) a sequence of oxidation steps involving partial water oxidation mafosfamide intermediates; or (2) a concerted reaction mechanism during the S3 → S0 transition. A MIMS approach

to this question was first employed by Radmer and Selleck Rabusertib Ollinger (Radmer and Ollinger 1980a). They attempted to determine the rate of appearance of 18O in the O2 products of water splitting by PSII samples suspended in 18O-enriched water. The experiment is analogous to stop-flow experiments and requires rapid injection/mixing of isotopically labeled water into the suspension of photosynthetic samples followed by a series of light flashes to photogenerate O2. This first MIMS experiment indicates that water exchanges rapidly and by inference conceded that there are no non-exchangeable stable water oxidation products (e.g., bound peroxides) up to the S3 state of the OEC. This work and others that followed (Radmer and Ollinger 1980a, 1986; Bader et al. 1993) were limited by mixing/stabilization times of >30 s, and it wasn’t until more rapid mixing techniques were developed that also strongly reduced the O2 background rise from the injection of the labeled water that more specific information about water binding could be learned (Messinger et al. 1995).

Laparoscopy seems to have an advantage above laparotomy in terms

Laparoscopy seems to have an advantage above laparotomy in terms of adhesion formation to the abdominal wall and to the operative site [98, 99]. Laparoscopic adhesiolysis for small bowel obstruction has a number of potential advantages: (1) less postoperative pain, (2) quicker

return of intestinal function, (3) shorter hospital stay, (4) reduced recovery time, allowing an earlier return to full activity, (5) fewer wound complications, and (6) decreased postoperative adhesion formation [100]. However No randomized controlled trial comparing open to laparoscopic adhesiolysis exists up to date, and both the precise indications and specific outcomes of laparoscopic adhesiolysis for adhesive SBO remain poorly understood. The only RCT on laparoscopic adhesiolysis assessed the incidence of chronic abdominal pain after selleck randomization to laparoscopic adhesiolysis or no treatment during diagnostic laparoscopy and it failed to demonstrate any significant differences in terms of pain or discomfort [101]. Although data from retrospective

clinical controlled trials suggest that laparoscopy seems feasible and better in terms of hospital stay and mortality reduction, high quality randomised controlled trials RepSox purchase assessing all clinically relevant outcomes including overall mortality, morbidity, hospital stay and conversion DNA-PK inhibitor are lacking [102]. Although the adhesiolysis hospitalization rate has remained constant in USA since 1988, inpatient expenditures have decreased by nearly 10% because of a 15% decrease in the average length of stay (from 11.2 days in 1988 to 9.7 days in 1994) [103]. From this large population Hospital Discharge reports Survey, is derived that laparoscopic less invasive surgical techniques for adhesiolysis, increased over the last years, have contributed to the decreased time required in the hospital for both the surgical procedure itself and the recovery time. However the increased use of laparoscopy during this study period Gemcitabine cell line did not appear to be associated with a concomitant reduction in the adhesiolysis hospitalization rate therefore a common denominator may exist

between surgical trauma and immune response to foreign bodies. When deciding between an open or laparoscopic approach, the first consideration is that the surgeon be trained and capable of performing advanced laparoscopy. With regards to patient selection, patients with an acute small bowel obstruction and peritonitis or free air requiring an emergent operation are best managed with a laparotomy. Patients without peritonitis who do not resolve with nonoperative management should be considered for laparoscopic adhesiolysis. In these cases, it is important to consider the bowel diameter, degree of abdominal distention, and location of the obstruction (ie, proximal or distal). Suter et al [104] found that a bowel diameter exceeding 4 cm was associated with an increased rate of conversion: 55% versus 32% (p = 0.02).

2 2 3 CPE2192 CPF_2457 (atpL) ATP synthase C chain 3 6 2 3 Fatty

2 2.3 CPE2192 CPF_2457 (atpL) ATP synthase C chain 3.6 2.3 Fatty acid and phospholipid metabolism CPE1068 CPF_1324 (fabH) 3-oxoacyl-(acyl-carrier-protein) synthase III 2.2 4.7 CPE1069 CPF_1325 (fabD) malonyl CoA-acyl carrier protein transacylase 1.1 3.6 CPE1071 CPF_1327 (fabF) 3-oxoacyl-(acyl-carrier-protein) synthase II 1.3 3.8 CPE1072 CPF_1328 (accB) acetyl-CoA carboxylase, biotin carboxyl

carrier 0.9 4.0 CPE1073 CPF_1329 (fabZ) beta-hydroxyacyl-(acyl-carrier-protein) dehydratase FabZ 1.0 4.5 CPE1074 CPF_1330 (accC) acetyl-CoA carboxylase, biotin carboxylase 1.7 4.9 CPE1075 CPF_1331 (accD) acetyl-CoA carboxylase, carboxyl transferase, beta subunit 3.4 5.0 CPE1076 CPF_1332 (accA) acetyl-CoA carboxylase, carboxyl transferase, learn more check details alpha subunit 1.9 4.6 Protein synthesis CPE1697 CPF_1951 (frr) ribosome recycling factor 1.1 2.0 CPE2441 CPF_2720

ribosomal protein L7AE family 1.1 2.6 CPE2660 CPF_2997 (rpmH) ribosomal protein L34 1.4 2.0 Purine, pyrimidine, nucleotides, and nucleosides CPE1050 CPF_1305 (mtnH) 5-methylthioadenosine/S-adenosylhomocysteine nuclosidase 3.2 2.6 CPE2162 CPF_2418 (cpdC) 2`,3`-cyclic-nucleotide 2`-phosphodiesterase 3.4 1.6 Transport and binding proteins CPE0977 CPF_1235 potassium transporter 7.1 2.9 Unknown functions CPE2601 CPF_2928 conserved hypothetical protein 6.7 58.0 All of the data are the means of three different experiments. Table 3 Microarray analysis of the genes that were downregulated in both gatifloxacin-resistant strains, 13124 R and NCTR R Gene ID (name) Function/Similarity Microarray (mt/wt)       NCTR ATCC 13124 Biosynthesis of cofactors, prosthetic

groups, and carriers CPE1085 CPF_1341 (ispH) 4-hydroxy-3-methylbut-2-enyl diphosphate reductase −2.4 −2.2 Energy metabolism CPE0292 CPF_0288 NVP-AUY922 concentration carbohydrate kinase family protein −3.1 −2.5 CPE1185 CPF_1389 (pfk) 6-phosphofructokinase −1.7 −2.7 CPE0585 CPF_0565 (fruB) fructose-1-phosphate kinase −5.2 −2.3 CPE0692 CPF_0684 transaldolase −2.8 −2.3 CPE0725 CPF_0721 (nanI) * exo-alpha-sialidase −3.5 1.5 CPE0894 CPF_0887 (eutP) ethanolamine utilization protein, EutP −1.9 −2.0 CPE2348 CPF_2657 (ptb) phosphate butyryltransferase −2.3 −1.6 Purine, pyrimidine, nucleotides, and nucleosides CPE1398 CPF_1652 (deoD) purine nucleoside phosphorylase −1.7 −3.4 Regulatory functions CPE0586 CPF_0566 (fruR) transcriptional regulator, DeoR family −3.6 −2.6 CPE0631 PAK6 CPF_0612 probable PBP5 synthesis regulator protein −2 −2.5 CPE1077 CPF_1333 transcriptional regulator, PadR family −3.1 −3.2 CPE2510 CPF_2833 transcriptional regulator, PadR family −2.6 −2.7 CPE1305 CPF_1512 probable transcriptional regulator −2 −1.6 Transport and binding proteins CPE0600 CPF_0581 amino acid ABC transporter −4.8 −3.4 CPE1534 CPF_1785 PTS system, sucrose-specific IIBC component −3.1 −14.3 CPE2345 CPF_2654 putative maltose/maltodextrin ABC transporter −2.0 −1.8 Unknown functions CPE2509 CPF_2832 degV family protein −3.6 −3.3 CPE1171 CPF_1374 mutator mutT protein homolog −6.4 −2.