Furthermore, it is interesting to note that the LSPR location of simulation data fits quite Veliparib well with the experimental results (788 nm in experiment, 792 nm in simulation). Due to the strong SPRs in the pulse AC-grown Au nanoarray,

it is believed that the uniform Au nanoarray can generate large enhancement of electric field and local density of states, which makes the Au nanoarray a good candidate for nanoantennas. Thus, we use the FDTD and Green function methods to do our further theoretical investigation. Figure 3 shows the field distribution of the Au nanoarray with L = 150 nm, where the incident light is a plane wave at the wavelength of 792 nm with an incident angle of 40°. The field intensity enhancements are drawn at the logarithmic scale. The large field enhancement at every tip of the Au nanoarray is clearly seen, and this field enhancement can cause the increment of LDOS. However, the electric field tends to concentrate at some certain nanowire in the nonuniform Au nanoarray, and this asymmetric field distribution decreases the whole extinction intensity and displays nonuniform field enhancement which may affect

the stability and repeatability of the Au nanoarray in the application of nanoantennas (see Additional file 1: Figure S3). Furthermore, with the help of the Green function, the LDOS is given as [44]: where Im stands for the imaginary part and tr denotes the trace of the Green tensor matrix in brackets. Figure Selleckchem FK506 3 Field distribution and LDOS enhancement. (a) The field distribution of Au nanoarray (L = 150 nm, d = 34 nm, a = 110 nm) at the plane wave wavelength of 792 nm with an incident angle of 40°. (b) The x-position dependence of LDOS enhancement at the wavelength of 792 nm. As shown from the sketch of the simulation model in the inset, the zero point is at 10 nm above the center Au

nanowire. The enhancement of LDOS Lonafarnib in vivo at the center and the edge is 66.7 and 81.2, respectively. (c) The z-position dependence of LDOS enhancement. From the Maxwell equations, one can get By setting a dipole source the Green function can be calculated by the electric field at the position of the dipole as . Also, the matrix form of can be written as: After choosing three of different directions, all the elements of the Green matrix can be obtained so as to get the LDOS. The LDOS is calculated by the finite element method with the help of the COMSOL software (version 4.2a). As shown in Figure 3b, one can see that the LDOS enhancement at 792 nm is much larger at the edge which is in accord with the field distribution in Figure 3a, and the maximum enhancement is 81.2 times (define the LDOS enhancement as the ratio of LDOS around the nanoarray to LDOS in vacuum).

Moreover the EPS-induced increased expression of the human defensin HBD-2 in vaginal cells was also verified, identifying a possible connection with C. albicans growth inhibition [24]. Results Strain identification and H2O2 production A Lactobacillus strain isolated from human vaginal secretion was Acalabrutinib in vitro allotted to crispatus subspecies by 16S ribosomal DNA sequencing [25] and it was named L. crispatus L1. In

particular, PCR products were pooled, purified and sequenced. In addition, the ability of 72 Lactobacillus strains to produce H2O2 was evaluated. The percentage of strains classified as strong, medium, weak and negative H2O2 producers was 23, 34, 38 and 5%, respectively. L. crispatus L1 was found to be the best of the isolates in the

laboratory collection. In vitro digestion Results from shake flask experiments simulating the passage through the gastrointestinal tract showed a good resistance of L. crispatus L1 to the in vitro digestion process. The bacterial dose significantly influenced results, as shown in Figure 1a clearly indicating that 1.8⋅109 cells∙ml−1 corresponds to the minimal required initial concentration of cells necessary to survive gastric juices. Incubation in simulated pancreatic juices (Figure 1b) with different Oxgall concentrations (10 mg and 25 mg) did not affect viability, whereas a slight increase of the cell number within 4 h was observed. Moreover, 5-Fluoracil treated cells reached a final biomass yield comparable with that of the control cells (data not shown). Figure 1 Simulation of human digestion in shake flasks. (a) Survival of L. crispatus L1 to gastric juices (pH 2.0, pepsine 3 g∙l−1). Response of different doses of bacteria, high (1.8 · 109 cells∙ml−1)

and low (6.0 · 108 cells∙ml−1), to the treatment. (b) Survival of L. crispatus L1 to pancreatic juices (pH 4.0, Phenylethanolamine N-methyltransferase pancreatine 2 g∙l−1, Oxgall in different concentrations). Effect of two different concentrations of bile salts on the viability of 1.0 · 109 cells∙ml−1.The asterisks indicate a statistically significant difference between samples with P < 0.01. Shakeflask experiments A semidefined medium containing soy peptone (10 g∙l−1) and yeast extract (2.5 g∙l−1) was used to investigate the amount of biomass and lactic acid produced using different carbon sources (Table 1). The final titer of biomass produced in shake flasks was very similar in all the media analysed. The production of lactic acid was quite high ranging between 7.5 and 13.1 g∙l−1 (Table 1) and resulting in relevant Yp/s ranging between 0.68 and 0.89 g∙g−1. The Yp/s on dextrins could not be calculated due to the presence of high molecular weight carbohydrates (glucose residues >7) that were not degraded and metabolized as evidenced by High Performance Anion Exchange Chromatography with Pulsed Amperometric Detection (HPAEC-PAD) analyses. Table 1 Growth of L.

The target protein was found to be enriched in the 100 mM imidazole Tanespimycin molecular weight eluent. All samples were analyzed by 12% SDS-PAGE. The p16INK4a fusion protein was further verified by Western blotting using a specific anti-p16INK4a antibody (Figure 4b). Figure 4 Purification, verification, and transduction of exogenous p16INK4a fusion protein. a. Successful

expression and purification of the p16INK4a fusion protein was confirmed by 12% SDS-PAGE analysis. The bacterial sample before IPTG induction showed almost no protein expression (lane 1). After IPTG induction and centrifugation, p16INK4a fusion protein was abundant in the clear supernatant (lane 3) (indicated by the arrow) and absent from the bacterial precipitate (lane 2). The supernatant was loaded onto a Ni2+-affinity chromatography column, which binds the His-p16INK4a fusion protein. Nonspecifically bound proteins were removed with washing buffer; the flow-through liquid can be seen in lane 4. Elution buffer with different concentrations of imidazole was used to elute the p16INK4a fusion protein: 20 mM (lane 5), 50 mM nt (lane 6), 100 mM (lane 7) and 200 mM (lane were. The fractions were assessed by SDS-PAGE and the sample corresponding to the 100 mM imidazole eluent (lane 7) was found to contain p16INK4a fusion protein of high purity (arrow). b. The purified protein was Dabrafenib research buy verified by Western-blot

analysis using the specific p16INK4a antibody. c. Immunocytochemical assay to assess transduction efficiency. All nuclei of A549 cells stained with Hoechst fluorescent and the exogenous p16INK4a protein was detected in about 50% of cells, as shown by the FITC signal. As shown in the figure, the transduction efficiency

was about 50%. Purified p16INK4a fusion protein was transduced into A549 cells and transduction efficiency was examined by fluorescence immunocytochemistry. As shown in Figure 4c, all A549 cell nuclei were positive for Hoechst fluorescence and about 50% were positive for FITC, indicating that these cells had been successfully transduced with p16INK4a. Growth suppression of A549 cells following p16INK4a induction To evaluate the effect of p16INK4a on cell growth, the growth curves of A549 cells transduced with the protein were compared with those of control cells (A549 cells incubated with Lipofectamine 2000). Cells transduced with p16INK4a the day before the ADAM7 start of the experiment were counted at 12-h intervals. Figure 5a shows that, 36 h after cell subculture, p16INK4a began to induce growth retardation. At 72 h, p16INK4a had significantly suppressed proliferation compared with the control (Figure 5a, b). Furthermore, cell cycle changes, as analyzed by flow cytometry (Figure 5c), showed that the presence of exogenous p16INK4a resulted in a marked retardation of the G1→S transition of A549 cells 48 h after transduction. Figure 5 Cell growth inhibition and cell cycle redistribution effects of p16INK4a in A549 cells.

J Exp

Med 1997, 185:1759–1768.PubMedCrossRef 20. Seo JH, Lim JW, Kim H, Kim KH: Helicobacter pylori in a Korean isolate activates mitogen-activated protein kinases, AP-1, and NF-kappaB and induces chemokine expression in gastric epithelial AGS cells. Lab Invest 2004, 84:49–62.PubMedCrossRef 21. Kunkel SL, Standiford T, Kasahara K, Strieter RM: Interleukin-8 (IL-8): the major neutrophil chemotactic factor in the lung. Exp Lung Res 1991, 17:17–23.PubMedCrossRef 22. Matsushima K, Baldwin ET, Mukaida N: Interleukin-8 and MCAF: novel leukocyte recruitment and activating cytokines. Chem Immunol 1992, 51:236–265.PubMedCrossRef 23. Papoff P, Fiorucci RXDX-106 P, Ottaviano C, Bucci G: Interleukin-8: a potent neutrophil chemotactic factor. Arch Dis Child Fetal Neonatal Ed 1995, 73:F54.PubMedCrossRef 24. Roebuck KA: Regulation of interleukin-8 gene expression. J Interferon Cytokine Res 1999, 19:429–438.PubMedCrossRef 25. Sharma SA,

Tummuru MK, Miller GG, Blaser MJ: Interleukin-8 response of gastric epithelial cell lines to Helicobacter pylori stimulation in vitro. Infect Immun 1995, 63:1681–1687.PubMed 26. Straubinger RK, Greiter A, McDonough SP, Gerold A, Scanziani E, Soldati S, et al.: Quantitative evaluation of inflammatory and immune responses in the early stages of chronic Helicobacter pylori infection. Infect Immun 2003, 71:2693–2703.PubMedCrossRef 27. Sun J, Aoki K, Zheng JX, Su BZ, Ouyang XH, Misumi J: Effect of NaCl and Helicobacter pylori vacuolating cytotoxin on cytokine Epothilone B (EPO906, Patupilone) expression and viability.

World J Gastroenterol 2006, 12:2174–2180.PubMed 28. Tummuru MK, Sharma SA, Blaser MJ: Helicobacter pylori picB, Talazoparib order a homologue of the Bordetella pertussis toxin secretion protein, is required for induction of IL-8 in gastric epithelial cells. Mol Microbiol 1995, 18:867–876.PubMedCrossRef 29. Wunder C, Churin Y, Winau F, Warnecke D, Vieth M, Lindner B, et al.: Cholesterol glucosylation promotes immune evasion by Helicobacter pylori. Nat Med 2006, 12:1030–1038.PubMedCrossRef 30. Gebert B, Fischer W, Haas R: The Helicobacter pylori vacuolating cytotoxin: from cellular vacuolation to immunosuppressive activities. Rev Physiol Biochem Pharmacol 2004, 152:205–220.PubMedCrossRef 31. Kao JY, Rathinavelu S, Eaton KA, Bai L, Zavros Y, Takami M, et al.: Helicobacter pylori-secreted factors inhibit dendritic cell IL-12 secretion: a mechanism of ineffective host defense. Am J Physiol Gastrointest Liver Physiol 2006, 291:G73-G81.PubMedCrossRef 32. Sewald X, Gebert-Vogl B, Prassl S, Barwig I, Weiss E, Fabbri M, et al.: Integrin subunit CD18 Is the T-lymphocyte receptor for the Helicobacter pylori vacuolating cytotoxin. Cell Host Microbe 2008, 3:20–29.PubMedCrossRef 33. Shimoyama T, Fukuda S, Liu Q, Nakaji S, Munakata A, Sugawara K: Ecabet sodium inhibits the ability of Helicobacter pylori to induce neutrophil production of reactive oxygen species and interleukin-8. J Gastroenterol 2001, 36:153–157.PubMedCrossRef 34.

Br J Cancer 2006, 95:1626–1631.PubMedCrossRef 9. Brédart A, Dolbeault S, Savignoni A, Besancenet C, This P, Giami A, Michaels S, Flahault C, Falcou MC, Asselain B, Copel L: Prevalence

and associated factors of sexual problems after early-stage breast cancer treatment: results Selleck GSK1120212 of a French exploratory survey. Psychooncology 2011, 8:841–850. 10. Emilee G, Ussher JM, Perz J: Sexuality after breast cancer: a review. Maturitas 2010, 66:397–407.PubMedCrossRef 11. Avis NE, Crawford S, Manuel J: Quality of life among younger women with breast cancer. J Clin Oncol 2005, 23:3322–3330.PubMedCrossRef 12. Jun EY, Kim S, Chang SB, Oh K, Kang HS, Kang SS: The effect of a sexual life reframing program on marital intimacy, body image, and sexual function among breast cancer survivors. Cancer Nurs 2011, 34:142–149.PubMedCrossRef 13. Mousavi SM, Montazeri A, Mohagheghi MA, Jarrahi AM, Harirchi I, Najafi M, Ebrahimi M: Breast cancer in Iran: an epidemiological review. Breast J 2007, 13:383–391.PubMedCrossRef 14. Vahdaninia M, Montazeri A, Goshtasebi A: Help-seeking behaviours for female sexual dysfunction: a cross sectional study from Iran. BMC Women’s Health 2009, 9:3.PubMedCrossRef 15. Rosen R, Brown C, Heiman BGJ398 mouse J: The Female Sexual Function Index (FSFI): a multidimensional self report instrument for the assessment of female sexual function. J Sex Marital Therapy 2000, 26:191–208.CrossRef

16. Mohammadi Kh, Heydari M, Faghihzadeh S: The Female Sexual Function Index (FSFI): validation of the Iranian version. Payesh 2008, 7:269–278. [abstract in English] 17. Knobf MT: The influence of endocrine effects of adjuvant therapy on quality of life outcomes in younger breast cancer survivors. Uroporphyrinogen III synthase Oncologist 2006, 11:96–110.PubMedCrossRef 18. Cella D, Fallowfield LJ: Recognition and management of treatment-related side effects for breast cancer patients receiving adjuvant endocrine therapy. Breast Cancer Res Treat 2008, 107:167–180.PubMedCrossRef 19. Karabulut N, Erci B: Sexual desire and satisfaction in sexual life affecting factors in breast cancer survivors

after mastectomy. J Psychosoc Oncol 2009, 27:332–343.PubMedCrossRef 20. Alder J, Zanetti R, Wight E, Urech C, Fink N, Bitzer J: Sexual dysfunction after premenopausal stage I and II breast cancer: do androgens play a role? J Sex Med 2008, 5:1898–1906.PubMedCrossRef 21. Sadovsky R, Basson R, Krychman M, Morales AM, Schover L, Wang R, Incrocci L: Cancer and sexual problems. J Sex Med 2010, 7:349–373.PubMedCrossRef 22. Den Oudsten BL, Van Heck GL, Van der Steeg AF, Roukema JA, De Vries J: Clinical factors are not the best predictors of quality of sexual life and sexual functioning in women with early stage breast cancer. Psychooncology 2010, 19:646–656.PubMed 23. Yang EJ, Kim SW, Heo CY, Lim JY: Longitudinal changes in sexual problems related to cancer treatment in Korean breast cancer survivors: a prospective cohort study.

0251). Table 3 Relationships among tumor depth, histological type, and lymph node metastases Tumor depth Histologic type pN(+) Hazard ratio 95% confidence interval p-value m-sm1 (n = 204) Differentiated 1/72 (1.4%) 1.000       Mixed differentiated 1/31 (3.2%) 2.367 0.092-61.123 0.5527   Mixed undifferentiated 3/22 (13.6%) 11.211 1.351-233.786 0.0251*   Undifferentiated 3/79 (3.8%) 2.803 0.350-57.357 0.3449 sm2 (n = 123) Differentiated 11/41 (26.8%)

1.000       Mixed Selleckchem PF-2341066 differentiated 8/25 (32.0%) 1.283 0.423-3.808 0.6539   Mixed undifferentiated 8/14 (57.1%) 3.636 1.042-13.478 0.0430*   Undifferentiated 10/43 (23.3%) 0.826 0.303-2.230 0.7054 * p < 0.05 Of 123 patients with pT1b2 tumors (sm2 group), 37 had nodal metastases. There was a significant association between depth of tumor invasion and nodal metastases in pT1b tumors. The incidence Ivacaftor manufacturer of nodal metastases was higher in the mixed undifferentiated type group than in the differentiated

type group (p = 0.0430). The pathological characteristics of patients in the pT1a-pT1b1 (m-sm1) group with nodal metastases are shown in Table 4. All four node-positive patients with pT1a tumors had ulceration (Figure 1). The smallest tumor size was 10 mm in diameter. One patient had non-perigastric nodal metastases along the common hepatic artery. Table 4 Pathological characteristics of pT1a and pT1b1 tumors with lymph node metastases Case Tumor depth * Macro type Ulceration Tumor size, mm Histologic type L† V† Number of positive node Follow-up time, months Status 1 m 0-IIc Yes 10 sig, tub2 0 0 1 97 Alive 2 m 0-IIc Yes 42 sig, tub2, muc 0 0 1 7 Alive 3 m 0-IIc Yes 60 sig 0 0 1 82 Alive 4 m 0-IIc Yes 100 sig, por, tub1 1 0 1 25 Alive 5 sm1 0-IIc No 25 tub1 0 0 1 76 Alive 6 sm1 0-IIc Yes 25 tub2, por 2 0 4 37 Alive 7 sm1 0-IIc Yes 31 sig 1 1 11 58 Deceased (bone metastasis) 8 sm1 0-IIc Yes 32 por, sig 1 0 1 20 Alive RAS p21 protein activator 1 * According to the third English edition of the Japanese

Classification of Gastric Carcinoma [4]. † According to the seventh edition of the International Union Against Cancer TNM guidelines [3]. muc = mucinous adenocarcinoma; por = poorly differentiated adenocarcinoma; sig = signet-ring cell carcinoma; tub1 = well differentiated adenocarcinoma; tub2 = moderately differentiated adenocarcinoma. Figure 1 Endoscopic, macroscopic and pathological images of mucosal tumors with lymph node metastases. Four of 161 patients with mucosal tumors had nodal metastases. All of these patients had signet-ring cell carcinomas with ulceration. The smallest tumor was 10 mm in diameter (Case 1). One patient had non-perigastric nodal metastases along the common hepatic artery (Case 2). Only 4 of 45 patients with nodal metastases were diagnosed preoperatively (sensitivity 8.9%, specificity 96.1%). Nine patients had recurrence of cancer, and died.

Thus, it is necessary to analyze the entire set of produced proteins [8]. Proteome analysis of M. loti in mid-growth phase has been reported [9], but it has not been performed for the symbiotic phase. Proteome analyses of other rhizobia, such as B. japonicum[10–14], and S. meliloti[15–20], have been previously reported. They employed 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE)-based analysis combined with matrix-assisted laser desorption and ionization time-of-flight mass spectrometry

(MALDI-MS), but time-consuming steps, such as gel spot isolation and individual measurement, are necessary in this method. In addition, previous 2D-PAGE-based analyses have only identified up to 500 proteins [13]. Another report employed liquid chromatography-tandem Atezolizumab mass spectrometry (LC-MS/MS)-based technology combined with prefractionation, such as multidimensional chromatography VX-809 research buy [21] or gel-based separation [22], but these prefractionation steps decreased throughput. Furthermore, all of them included a complicated isolation step of the bacteroid (a symbiotic form of rhizobia) from the nodule, and the step required a large amount of biological samples, such as 1–5 g nodules collected from approximately 40 plants [23]. Detection of small amount of proteins present in complex biological samples remains difficult

and requires a combination of prefractionation steps. To solve the problems, we used a nanoLC-MS/MS system equipped AZD9291 chemical structure with a long monolithic silica capillary column (200 cm long, 0.1 mm ID). Monolithic silica materials offer high separation efficiency in long column formats because of their high permeability [24], and they have been successfully applied to separate tryptic fragments in highly complex samples with a shallow gradient.

As this high-resolution system does not require any additional prefractionation prior to the separation and detection step by LC-MS/MS, this approach can simplify the workflow of shotgun proteomics and minimize the sample amount, as well as total analysis time [25]. Using this system, we have successfully performed proteome analysis of Candida albicans[26] and Clostridium cellulovorans[27]. Here, we report the first comparative proteome analysis of M. loti under the free-living and symbiotic conditions by using our system. Our data should accelerate functional and comprehensive studies focused on molecular mechanisms of L. japonicus – M. loti symbiosis. Results and discussion Identification of proteins extracted from free-living and symbiotic M. loti The tryptic digests were injected to a LC-MS/MS system equipped with a long monolithic silica capillary column; 1,658 proteins were successfully identified by efficient separation (Additional file 1).

Cancer Res 2006, 66:9617–9624.PubMedCrossRef 34. Winter MC, Holen I, Coleman RE: Exploring the anti-tumour

activity of bisphosphonates in early breast cancer. Cancer Treat Rev 2008, 34:453–475.PubMedCrossRef Competing interests The authors declare that they have no competing interests. Authors’ contributions BK carried out cytotoxicity experiments, and participated in PLX4032 purchase the drafted manuscript, BK participated in the design of the study, UV performed statistical analysis, UM carried out molecular genetic studies, BC carried out cytotoxicity experiments, HA carried out apoptosis experiments, AK carried out apoptosis experiments, and molecular genetic studies, SU participated in design of the study, RU conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.”
“Background Estrogen stimulation plays an important role in human breast cancer cell growth and development. It was reported HDAC inhibitor that estrogen could affect breast cancer risk through stimulating cellular

proliferation and promoting tumor progression[1]. It might be important to obtain a better understanding of enzymatic mechanism in breast cancer tissues. Enzymatic mechanism involves in the formation of estrogen including two main pathways. One is the sulfatase pathway which involves conversion of inactive estrone sulfate into active estrone[2]. Sulfotransferase (SULT) sulfonates estrone to inactive estrone sulfate (E1-S), whereas steroid sulfatase (STS) hydrolyzes estrone sulfate to estrone. Another is the aromatase pathway which converts androstenedione into estrone and aromatase inhibitor has been successfully used in breast cancer standard treatment[3]. However, it was reported that aromatase manner was five hundred times lower than sulfatase one pointed by quantitative enzymatic evaluation [4]. Besides, early study showed that the conversion of estrogen to the inactive estrogen sulfate was very essential, as serum level of unconjugated estrone

(E1) or estradiol (E2) had 10-fold lower than the level of E1-S. In addition, tissue concentration of E2 in breast cancer was 10 times higher than the level in plasma. The accumulation of E2 in breast cancer was mainly caused by the over expressed STS and the decreasing of SULT Tideglusib expression [5]. There are three families of SULTs. They are SULT1 family which is the major “”phenol”" SULT, sulfating a wide range of substrates including eight subfamilies, SULT2 family and SULT4 family. SULT1A1 gene locates in chromosome 16p11.2 – p12.1. Previous study reported that exon 7 of the SULT1A1 gene contained a G to A transition at codon 213 and showed that relevant polymorphism significantly reduced its enzymatic activity [6]. For the above reasons, genetic studies of SULT polymorphisms may improve our understanding of the mechanism of SULT and enable us to screen for individuals at high risk for different cancers.

Available nutrients (%) Treatment pH OM (%) N P K Ca NP0K 6.73a 3.40ghi 0.044hij 0.0015kl 0.020fgh 0.032i NPTCPK 6.63ab 3.63defghi 0.049efgh 0.0021ghij 0.025cde 0.038h NPSSPK 6.50abc

3.48efghi 0.046fghi 0.0025defg 0.022efg 0.033hi NPTCPK+Pt BIHB 728 6.26abcd 3.90bcde 0.052def 0.0019ijkl 0.025cde 0.069bc NPTCPK+Pt BIHB 736 6.23bcd 3.42fghi 0.057bcd 0.0026defg 0.024def 0.057fg NPTCPK+Pt BIHB 745 5.93d 4.17ab 0.065a 0.0038a 0.033ab 0.085a NPTCPK+Pt BIHB 747 6.02cd 4.13abc 0.062ab 0.0027cdef 0.030abc 0.081a NPTCPK+Pt BIHB 749 6.12cd 3.57efghi 0.042ijk 0.0024efgh 0.029bc 0.074b NPTCPK+Pt BIHB 750 6.24bcd 3.55efghi 0.039jkl TGF-beta inhibitor 0.0019ijkl 0.019fgh 0.080a NPTCPK+Pt BIHB 757 5.93d 3.79bcdefg 0.059bc 0.0024efgh 0.026cde 0.070bc NPTCPK+Pt BIHB 759 6.20bcd Protease Inhibitor Library 4.00abcd 0.040jk 0.0022fghi 0.022efgh 0.072b NPTCPK+Pt BIHB 763 6.18bcd 3.82bcdefg 0.039kl 0.0028cde 0.018gh 0.058ef NPTCPK+Pt BIHB 769 6.30abcd 3.29i 0.046ghi 0.0026cdef 0.027cde 0.059e NPTCPK+Pp BIHB 730 6.23bcd 3.55efghi 0.050efg 0.0020hijkl 0.027cde 0.052g NPTCPK+Pp BIHB 752 6.17bcd 3.89bcde 0.037kl 0.0020hijk 0.018gh 0.057fg NPTCPK+Pp BIHB 808 6.21bcd 3.43fghi 0.049fgh 0.0017ijkl 0.022efg 0.061de NPTCPK+Pf BIHB 740 6.25bcd 3.85bcdef 0.055cde 0.0021ghij 0.027cde 0.072b NPTCPK+Psp BIHB

751 6.33abcd 3.43fghi 0.034l 0.0016jkl 0.017h 0.053fg NPTCPK+Psp BIHB 756 6.13bcd 4.32a BTK inhibitor 0.060abc 0.0033b 0.035a 0.072b NPTCPK+Psp BIHB 804 6.18bcd 3.74cdefgh 0.049efgh 0.0015l 0.028bcd 0.069bc NPTCPK+Psp BIHB 811 6.19bcd 4.06abc 0.051efg 0.0031bc 0.022efg 0.062de NPTCPK+Psp BIHB 813 6.17bcd 3.36hi 0.049fgh 0.0030bcd 0.025cde 0.065cd Values are the mean of 8 replicates. N and K applied as ammonium sulfate @ 240 kg N/ha, and muriate of potash @ 80 kg K/ha to all the treatments, respectively. TCP = tricalcium phosphate (120 kg P/ha). SSP = single super phosphate (120 kg P/ha). Values with common letters in each column do not differ statistically according to Duncan’s Multiple Range Test

at p ≤ 0.01. Pt = P. trivialis, Pp = P. poae, Pf = P. fluorescens, and Psp = Pseudomonas sp. The soil N content was significantly higher in five PSB treatments than NP0K, NPTCPK and NPSSPK and statistically at par among NP0K, NPTCPK and NPSSPK. The soil P content was significantly higher in three PSB treatments over NP0K, NPTCPK and NPSSPK. The highest available P content was obtained with NPTCPK+Pt BIHB745 among PSB treatments and with NPSSPK among uninoculated treatments. The soil K content was significantly higher in nine PSB treatments than other PSB treatments, NP0K, NPTCPK and NPSSPK. The highest available K was recorded for NPTCPK+Psp BIHB 756. The available Ca was significantly higher in three PSB treatments than other PSB treatments, NP0K, NPTCPK and NPSSPK.

In studies where no genotyping method was used, it was assumed that each isolate represented a strain. Results and discussion Comparative performance

of the five molecular methods The percentage of correctly identified strains obtained using the five identification methods, and the number of misidentified non-targeted species greatly depended upon the method used (Tables 1 and 2). The percentage of misidentified strains ranged from 16.8% to 67.4% (Table 2). The m-PCR method of Kabeya et al. [15] had the worst performance, and produced unreliable results for all three of its targeted species (Tables 1 Akt inhibitor and 2). Although all strains of A. cryaerophilus and A. skirrowii were correctly identified, a further eight and six non-targeted species, respectively, were mistakenly identified as one of these two species (Table 1). Furthermore, only 4.8% of the A. butzleri strains were correctly identified, with six non-targeted species being confused with this species (Tables 1 and 2). Globally, the Kabeya et XAV-939 cost al. m-PCR method correctly identified just 32.6% (31/95) of the studied strains. Although this method

was also designed to differentiate subgroups 1A and 1B of A. cryaerophilus, not all strains of these subgroups were correctly identified (Table 2). This correlates with the in silico observations of Douidah et al. [9] who reported that the primer used [15] were not specific enough to provide correct identification of A. cryaerophilus at the subgroup level. Further to this, Debruyne et al.[21] have suggested, that based on results of AFLP and hsp60 analyses, the subgroup nomenclatures 1A and 1B should be abandoned. The second least reliable method analysed was the m-PCR technique described by Houf et al.[14]. This correctly

identified 55.8% (53/95) of the strains (Table 2), including all those belonging Ixazomib price to its targeted species (A. butzleri, A. cryaerophilus, and A. skirrowii; Table 1). This method was 100% reliable for the identification of A. butzleri, and there was no confusion with other species. However, nine of the fourteen non-targeted species generated the typical amplicon of A. cryaerophilus; two that of A. skirrowii; and two simultaneously generated both amplicons (Tables 1 and 2). Only A. cibarius produced no amplification when using this method (Table 2). These results agree with previous studies that showed the existence of misidentifications when using this method [1, 5–7]. A similar number of correctly identified strains (83.2%) were obtained when using the other three evaluated methods (Pentimalli et al.[16]; the combined method of Douidah et al. [9] and De Smet et al.[17]; and Figueras et al.[18]). However, the number of misidentified non-targeted species differed depending upon the method used (Tables 1 and 2). Most misidentification occurred when using the method of Pentimalli et al.[16]. In this case, four non-targeted species were confused with A. butzleri, one with A.