T cells generated by DC transfected with GPC-3 mRNA are functional in vitro GPC-3 mRNA transfected DC but not mock transfected DC induced

proliferation of autologous T cells (Figure 2a), indicating that T cells reacting to GPC-3 epitopes are represented in the peripheral T cell repertoire. ELISPOT assay for interferon-gamma production found that DC expressing GPC-3 generated significantly more T cells producing interferon-gamma than mock transfected DC (53 ± 15 versus 4 ± 3 spots per well, respectively; p < 0.01) (Figure 2b). P505-15 These data demonstrate that monocyte-derived DC transfected with GPC-3 mRNA and matured with LPS were able to process and present GPC-3 derived epitopes, resulting in the proliferation of autologous T cells, which were functional as assessed by interferon-gamma production. Figure 2 T cells generated by DC transfected with GPC-3 mRNA are functional in vitro. PBMC were depleted of HLA class II positive cells and co-cultured with autologous, γ-irradiated, LPS matured DC in serum-free X-Vivo medium supplemented on days 1, 3 and 7 of culture with IL-2 (20 U/ml) and IL-7 (10 ng/ml). After 7 days, T cells were re-stimulated with the same DC for a further 5 days. a. T cell proliferation (1 × 105/well) was measured by

3H-thymidine incorporation, T cells this website were cultured alone, with DC (1 × 104/well) transfected with 20 μg GPC-3 mRNA, or mock transfected DC. b. ELISPOT assay for interferon-γ production was performed on T cells (1 × 105/well) stimulated by DC transfected with 20 μg GPC-3 mRNA or mock transfected DC. Assessment of binding affinity of GPC-3 peptides to HLA-A2 Among the 6 GPC-3

peptides tested, peptides 1, 2, 4 and 5 (GPC-3 229-237, 522-530, 186-194 and 222-230, respectively) showed significant binding affinities, whereas peptides 3 and 6 (GPC-3 299-307 and 169-177, respectively) did not show significant binding under the conditions used in these experiments (Figure 3). However, none of the GPC-3 peptides exhibited very strong binding to HLA-A2, as all demonstrated weaker binding than the “”immunodominant”" AFP peptide (GVALQTMKQ). Figure 3 Binding affinity of GPC-3 peptides MYO10 to HLA-A2. T2 cells were plated into 96-well U-bottomed plates at 1 × 105 cells per well in 200 μL X-Vivo (Biowhittaker) and cultured overnight at 18°C to increase cell surface HLA-A2 expression. a. 3 hours after MEK162 in vivo pulsing with increasing concentration of GPC-3 peptides, positive control (AFP) peptide or negative control (random) peptide plus 5 nM β2 microglobulin and incubation at 37°C, T2 cells were stained with a FITC-conjugated HLA-A2 specific antibody and examined by flow cytometry; b. T2 cells were stained with a FITC-conjugated HLA-A2 specific antibody and examined by flow cytometry at time points after the cells had been incubated for 3 hours at 37°C with 100 μM peptide, 5 nM β2 microglobulin and 5 μg/ml Brefeldin A. The data shown are representative of three independent experiments.

Therefore, the drug was released incompletely from the NPs in 48 h. Thus, PTX-MPEG-PLA NPs are promising in the expansion of dosing range of chemotherapeutic drugs and rendering patients safe cancer therapy. Additionally, it was interesting to note that the cell viability in PTX-MPEG-PLA NPs was higher than that in PTX-PLA NPs at a series of increasing concentrations (2.5, 10, 20, and 40 μg/mL). This result can most likely be attributed to the drug release rate of the PTX-MPEG-PLA NPs being higher than that of the PTX-PLA NPs. Figure 7 In vitro cell viability assays GSK1120212 for growth inhibition effect after 48

h ( n  = 6). Conclusions In our previous study, a simple but successful method was developed to obtain PTX-MPEG-PLA NPs with appropriate formulation characteristics including small particle size, narrow particle size distribution,

high zeta potential, satisfactory drug encapsulation efficiency, and appreciable drug-loaded content. The PTX-MPEG-PLA NPs presented a faster drug release rate but minor burst release as well as a higher cell cytotoxicity Capmatinib in vivo compared to the PTX-loaded PLA NPs. A further study on the in vivo pharmacokinetics and antitumor effects of PTX-MPEG-PLA NPs is currently in progress. Acknowledgements This work was funded by the National Natural Science Foundation of China (grant nos. 81000660 and 31271071) and Xiamen Science and Technology Project (XMU-MP-1 3502Z20123001 and 3502Z20114007). References 1. Peer D, Karp JM, Hong S, Farokhzad OC, Margalit R, Langer R: Nanocarriers as an emerging platform for cancer therapy. Nat Nanotechnol 2007, 2:751–760.CrossRef 2. Petros RA, DeSimone JM: Strategies in the design of nanoparticles for therapeutic applications. Nat Rev Drug Discovery 2010, 9:615–627.CrossRef 3. Adair JH, Parette MP, Altinoglu EI, Kester M: Nanoparticulate 4-Aminobutyrate aminotransferase alternatives for drug delivery. ACS Nano 2010, 4:4967–4970.CrossRef 4. Kievit FM, Zhang M: Cancer nanotheranostics: improving imaging and therapy by targeted delivery

across biological barriers. Adv Mater 2011, 23:H217–247.CrossRef 5. Elsabahy M, Wooley KL: Design of polymeric nanoparticles for biomedical delivery applications. Chem Soc Rev 2012, 41:2545–2561.CrossRef 6. Davis ME, Chen ZG, Shin DM: Nanoparticle therapeutics: an emerging treatment modality for cancer. Nat Rev Drug Discovery 2008, 7:771–782.CrossRef 7. Mai Y, Eisenberg A: Self-assembly of block copolymers. Chem Soc Rev 2012, 41:5969–5985.CrossRef 8. Schacher FH, Rupar PA, Manners I: Functional block copolymers: nanostructured materials with emerging applications. Angew Chem Int Ed 2012, 51:7898–7921.CrossRef 9. Nie Z, Petukhova A, Kumacheva E: Properties and emerging applications of self-assembled structures made from inorganic nanoparticles. Nat Nanotechnol 2010, 5:15–25.CrossRef 10. Kwon GS, Kataoka K: Block copolymer micelles as long-circulating drug vehicles. Adv Drug Delivery Rev 2012, 64:237–245.CrossRef 11. Rowinsky EK, Donehower RC: Paclitaxel (taxol).

PCR analysis of a 236 bp oriT fragment demonstrated an extinction of pEXKm5 plasmid backbone in both the mutant and GDC-0941 concentration complement strains. The pEXKm5 plasmid was removed from the SDO mutant and the complement strains by sucrose selection. Absence of a 236 bp oriT amplicon indicated the removal of pEXKm5 plasmid from the chromosome of the B. pseudomallei SDO mutant and the complement strains. B. pseudomallei SDO exhibits GDH activity under salt stress B. pseudomallei is known to up-regulate SDO in high salt condition [11]. The structural model of B. pseudomallei SDO indicates a catalytic triad and

cofactor binding domain, similar to the structure of B. megaterium glucose Mizoribine cell line 1-dehydrogenase. This is highly specific to beta-D-glucose and is capable of using either NAD+ or NADP+ as a cofactor [20]. We hypothesized that the glucose dehydrogenase activity of B. pseudomallei SDO might be similar to B. megaterium. www.selleckchem.com/products/Trichostatin-A.html We determined the GDH activity of B. pseudomallei SDO

in wild type and SDO mutant strains grown in LB broth containing 0–300 mM NaCl. The results showed that B. pseudomallei wild type exhibited strong GDH activity under high salinity at 300 mM NaCl, whereas the activity of B. pseudomallei was comparable in salt-free and 150 mM NaCl (Table 1). This correlated with previous finding that suggested B. pseudomallei SDO transcription was enhanced by salt stress [11]. Table 1 Effect of NaCl treatment on GDH activity by B. pseudomallei K96243, SDO mutant, and complement strains

NaCl GDH activity mU/mg (mM) K96243 SDO mutant SDO complement 0 0.049 ± 0.006 0.045 ± 0.003 0.042 ± 0.005 150 0.066 ± 0.012 0.050 ± 0.027 0.056 ± 0.017 300 0.996 ± 0.109 0.067 ± 0.026 0.952 ± 0.060 Data represent mean ± standard error (SE) of three experiments made in triplicate. It was also evident that the GDH activity of SDO mutant was impaired under high salt concentration condition containing 300 mM NaCl (Table 1), which was 15-fold lower than the wild type Montelukast Sodium (p-value ≤ 0.0001). The SDO complement strain was able to recover SDO mutant GDH activity (Table 1). The data suggested that high salt concentration is associated with induction of SDO-dependent GDH activity in B. pseudomallei. SDO plays a role in host interaction of B. pseudomallei The ability of B. pseudomallei to invade and survive in host cells is an important process that contributes to the pathogenesis of melioidosis. Invasion of B. pseudomallei has been reported as being induced by exogenous salt [11], and previous study indicated that high salt concentration increases the expression of SDO [11]. We thus investigated whether SDO affects the invasion of B. pseudomallei into A549 human lung respiratory epithelial cells. We found that invasion efficiency into A549 cells was significantly reduced in the B. pseudomallei SDO mutant, compared to the wild type (p-value ≤ 0.05) (Figure 2). The invasion efficiency of the B.

Free PHB granules, i.e. PHB granules that were not in contact PX-478 mw to the nucleoid GSK3326595 region were not observed. Apparently, constitutive over-expression of phaM resulted in formation of an increased number of small and nucleoid-attached PHB granules. If PhaM is responsible

for the formation of small granules and for the close contact to the nucleoid region, deletion of phaM should have a phenotype. In fact, R. eutropha ∆phaM cells accumulated only very few (0–2) PHB granules that were significantly larger in diameter than those of the phaM over-expressing mutant or of the wild type (Figure 5). Since the diameters of PHB granules of the ∆phaM strain were considerably larger even at early time points a precise analysis whether or not the granules were attached to the nucleoid region was difficult. In most ∆phaM cells the PHB granules were still located close to the nucleoid; however, VX-809 manufacturer at least in some cells a detachment of PHB granules from the nucleoid region could not be excluded for the wild type or for the phaM over-expressing strain. A clear decision whether the absence of PhaM resulted in detachment from the nucleoid can, however, not be made. Since

R. eutropha expresses at least one other protein with DNA-binding and PHB-binding property (PhaR) [30, 31] it might be that PhaR also contributes to association of PHB with DNA. In summary, our data on mutants with altered expression of PhaM clearly show that number, diameter and subcellular localization of PHB granules depends on the presence and concentration of PhaM. Time course of formation and localization of PHB granules in R. eutropha over-expressing PhaP5 PhaP5 had previously been identified as a phasin in R. eutropha by its in vivo interaction with PhaP2 and other phasins [22]. Remarkably, PhaP5 also interacted

with PhaM. To investigate the influence of PhaP5 on 5-Fluoracil PHB granule formation the phaP5 gene was cloned in a broad host range plasmid (pBBR1MCS-2) under control of the strong and constitutive phaC1 promotor (PphaC), transferred to R. eutropha H16 and HF39 via conjugation and investigated for PHB granules formation and localization under PHB permissive conditions (Figure 6). In case of strain HF39 a eypf-phaP5 fusion was cloned and used to confirm localization of PhaP5 on the PHB granules by fluorescence microscopy. Controls showed that free eYfp is a soluble protein in R. eutropha (Figure 7). Figure 7 Fluorescence microscopical (FM) investigation of R. eutropha H16 (pBBR1MCS-2-P phaC – eyfp -c1) with over-expression of eYfp (a); R. eutropha H16 (pBBR1MCS-2-P phaC – phaP5 ) with over-expression of PhaP5 (b), and R. eutropha H16 (pBBR1MCS-2-P phaC -eyfp- phaP5 ) with over-expression of eYfp-PhaP5 fusion (c) at various stages of PHB formation.

[17, 18]. According to this, the incidence of these infections is rising because of an increase in the number of immunocompromised patients, diabetes, cancer, alcoholism, vascular insufficiencies click here and organ transplants. Almost half of these infections are idiopathic, because we are not able to identify any underlying lesion at the site of the NSTI [7]. The best examples of such cases are scrotal

or penile NF. Causative organisms are numerous and often may be polymicrobial (Table 3) [18, 19]. There is no age or sex predilection for infection [18]. Because of the Lazertinib accompanying systemic illness and profound tissue inflammation, these patients are usually critically Rigosertib concentration ill and have prolonged ICU stay. They need critical care therapy and complex surgical management, and can be treated in a specialized facility such as a burn center or a burn unit [7]. Laboratory based scoring systems as LRINEC score test (The Laboratory Risk Indicator for Necrotizing Fasciitis) [20] (Table 3.) or APACHE II score test (The Acute Physiology and Chronic Health Evaluation) may help in the early diagnosis of NF [21]. Both scoring tests are not NSTI specific, but are accurate predictors of mortality rates

in most NF cases. Pathophysiology and microbiological findings According to the updated consensus for NSTIs (1,2), microbial invasion of skin and

subcutaneous tissue occurs either through external trauma and surgical wounds, or directly through bacterial invasion from a perforated viscus. Table 4 present potential antibiotic therapeutic regimens however for certain pathogenic organisms and predisposing factors. Microorganisms appearing in the skin and subcutaneous tissue spaces produce various endo- and exotoxins that cause prolonged vasoconstriction in the dermal capillary network. When these toxins are released into the systemic circulation, they produce the SIRS, which can progress into septic shock, MODS and finally, death [1, 2, 14]. The central pathohistological point in the pathogenesis of NSTIs is the thrombosis of perforating vessels of the skin and subcutis [17]. As the spread and extent of infection do not correspond with overlying skin changes, an inexperienced surgeon might not clearly determine the seriousness and extent of infection that takes place under the skin surfaces and in the subcutaneous space. In case of fulminating NF, MODS will develop within the first 24 hours of infection. In this case the disease will very often become fatal if not promptly recognized and treated with extensive surgical debridement, appropriate a combination of the antibiotics, and intensive care resuscitation [21].

OTUs of Streptosporangiaceae and Frankiaceae were present only during flowering stage (4% relative abundance) while that of Geodermatophilaceae were also present during branching in addition to the flowering stage with relative abundance of 10 and 6%. Kineosporaceae and Actisymmetaceae SBI-0206965 in vitro resembling OTUs were present only during maturation stage with 7 and 23% relative abundance, respectively. Streptomycetaceae group was confined to the post-harvest stage (20% relative abundance). Nakamurellaceae was detected

during branching and maturation stages with 25 and 12% relative abundance, respectively while Pseudonocardiaceae only during flowering stage (12.5% relative abundance) (Figure 4). However, Thermomonosporaceae in addition to post-harvest stage (20%), was also detected during maturation stage (18% abundance) along with Corynebacteriaceae (5%). Except Nakamurellaceae, most of the OTUs of such exclusive groups of the non-Bt and Bt crop were affiliated with the reference strains that mostly originated from the soil / rhizospheric soil of the plants (Table S3 and S4). In the present study, Micrococaceae and Nocardioidaceae were found to be the dominant group Ferrostatin-1 nmr in cultivated soils. These taxa have been selectively enriched by the increased organic input to the soil [47, 48], and also frequently detected in the manure and organic compost treated soils [49, 50]. OTUs belonging to the exclusive groups in non-Bt and Bt planted soils

as discussed above, are probably due to the specific nature of root exudates whose quantity and quality are likely to change via Cry1Ac gene based modification [3]. Rengel et al. [51] suggested that the resulting variations in the root exudates could be caused by the transformation of the plants. However, these exclusive actinomycetes groups were restricted Rucaparib in vitro to only a few growth stages of non-Bt and Bt crop. Also, the relative abundance of these OTUs for both the crops did not exceed the dominant taxa (Arthrobacter and Nocardia) as found for both the crops. Our findings corroborate with the result of Weinert et al. [52] wherein the genetic modification effect is more prominent only at the maturation stage compared

to others in transgenic potato. Thus, it could be inferred that the genetic modification of brinjal using Cry1Ac gene, will have little impact on distribution of the dominant microbial groups (Micrococaceae and Nocardiodaceae). Under the control of constructive promoter, the transgene Cry1Ac was expressed in all parts of the transgenic brinjal plant, throughout the entire cropping period [21]. However, the transgene was detected only during the flowering stage in the rhizospheric soils of Bt brinjal (data not shown). Sims and Holden [53] reported 50% decrease in the insecticidal activity of the Cry1Ab protein during 1.6 days, and 90% decrease within 15 days. Various studies suggested rapid degradation of Cry MK-1775 concentration proteins but the reports are mostly contradictory [5].

Thus, nucleotide changes at position 274, Rigosertib ic50 Leucine (L) was changed to Valine (V). At position 340, Asparagine (N) was changed to Aspartic acid (D) while at position 391, Aspartic acid (D) was changed to Asparagine (N) and at position 436, Serine (S) was changed to Alanine

(A) (Table 5). The SIFT software was used to predict the effect of these changes with 41 homologous sequences fetched from the UniProt-SwissProt 56.6 database. Using SIFT, it predicts the possibility of the effect caused by the substitution change by using the scoring method. The score is the normalized probability that the amino acid change is tolerated. The reliability of this score is supported by the value, which measures the diversity of the sequences in the alignment. Generally, the substitution site of the score less than 0.05 is predicted as a deleterious site with the support of median conservation values between 2.75 and 3.25 considered as a reliable prediction. Our results showed that all substitution changes were tolerated to the alteration of the protein function with all prediction scores > 0.05 and supported by the median conservation value of 3.08 Transmembrane Transporters inhibitor (Table 5). Table 4 The genetic divergence of assemblages A and B Assemblage Nucleotide divergence (%) Ks Ka A 0.96 0.0019 -a B 6.76 0.039 0.001 Ks; divergence at synonymous

positions, Ka; divergence at nonsynonymous positions;ano nonsynonymous change Table 5 Score and median conservation values from the prediction Histone demethylase of the effect of amino acid substitutions Positions Substitution Changes Score Median conservation 274 Leu to Val 0.34 3.08 340 Asn to Asp 0.11 3.08 391

Asp to Asn 0.1 3.08 436 Ser to Ala 1.0 3.08 Since the low genetic variation level of assemblage A does not reach the usual value observed in sexual populations, almost identical nucleotide sequences do not warrant further analysis. Thus, the sequence data of assemblage A were not included in the downstream analysis. Estimate of geographic differentiation Phylogenetic https://www.selleckchem.com/products/gs-9973.html analysis has shown that both assemblage A and B isolates have been dispersed throughout all studied geographical locations and appeared to be weakly supported for geographical sub-structuring. To determine if the traits from this inference were correct, the level of genetic distinction between each geographic population was estimated. The Wright’s test measures the level of genetic distinction between populations, representing with fixation index (F ST) value from 0 to 1. A value of zero indicates no divergence and implies that two populations are freely spread whereas the positive deviation from zero indicates the extent of genetic differences. A value of one would imply that two populations are completely separate. The estimated values showed little difference between each pair of the three regions and no significant differences were exhibited (Table 6).

The sensitivity of the estimated plasmid loss parameter σ DS of the DS model for the estimates of the intrinsic growth rate and the maximum density K

was determined for ten-fold smaller and ten-fold larger values of and K. The third and final step was estimation of the conjugation coefficient from experiments 2a-b. We estimated either two separate conjugation coefficients γ D and γ T for the donor and for the transconjugant, or a single conjugation coefficient for both (γ = γ D  = γ T ). Long term behaviour For the long term behaviour of the system, we simulated the outcomes of the population dynamics for a situation in which the populations are regularly diluted 10 000 times and transplanted to new medium. This was done for either 24 h selleck kinase inhibitor intervals or 48 h intervals. The initial concentration of the first round was T 0  = 105 and R 0  = 102. We used the parameter estimates from the mixed culture experiment 2 only, because the simulation also concerned a mix of R and T. The results of the simulations were compared to those of the long term experiment (experiment

3). We simulated five scenarios: no fitness costs (basic model), a lower growth rate of T, a lower maximum density of T, plasmid loss with constant rate (the CS SB-715992 mw model), and plasmid loss with density-dependent rate (the DS model). For the two scenarios with a lower growth rate or a lower maximum density of T, we used values that were 0.80, 0.90, and 0.95 times the value of the recipient R. These values are within the confidence intervals of the estimated Entinostat manufacturer parameters values (Table 2). For the PAK6 CS model and DS model, we used 80%, 90% and 95% of the upper limits of the estimate of the plasmid loss parameters (Table 2). Table 2 Estimates of the intrinsic growth rate ( ψ ), maximum density ( K ), lag-phase ( λ ) and initial concentration ( N 0 ) from experiment 2a and 2b (with mixed populations of R and T ) Parameter Value   95% confidence interval ψ 1.86 h-1 (1.49 – 2.33) K 9.33 108 cfu/ml (7.79 108 – 11.2 108) λ 1.17 h (0.70 – 1.64) N 0 2.51 106 cfu/ml (1.75 106 – 3.60 106) Results

Parameter estimates In Table 1 the estimates of the best model based on the AICc and the full model are given (for all other fits see Additional file 4, Table A1-A3). No differences in growth rate ψ, maximum density K or length of lag phase λ were found between the donor D, recipient R and the transconjugant T in experiment 1, where single populations were grown. Also from mixed populations in experiment 2, no difference was found between the overall growth rate of the donor D and the combined populations of recipient R and transconjugant T (see Additional file 4, Table A4). The estimated values of the growth parameters from experiments 2a-b (Table 2) were used in the simulations of the long term experiment.

An incarcerated hernia may be defined as a hernia in which the contents have become irreducible due to a narrow opening in the abdominal wall

or adhesions within the cavity. Intestinal obstruction can complicate an incarcerated hernia. In contrast, a strangulated hernia is one in which the blood supply to the contents of the hernia (eg omentum, bowel) s becomes compromised [2]. Strangulated click here hernias remain a significant challenge, as they are sometimes difficult to diagnose purely by physical examination yet require urgent surgical intervention. Early surgical intervention of a strangulated hernia with obstruction is crucial as delayed diagnosis can lead to bowel resection with longer MK-8931 solubility dmso recovery and its attendant complications. Strangulated hernias can have serious deleterious effects such as, bowel obstruction, bacterial translocation, and intestinal wall necrosis (potentially resulting in bowel perforation). It poses a significant risk to emergency hernia repair, as there is an increased incidence of surgical field contamination, leading to high rates of post-operative infection and probably recurrence. Bacteria inherently colonize all surgical wounds, but only a fraction

of these contaminates ultimately lead to infection. In most patients infection does not occur because innate host defences are able to eliminate microbes at the surgical site. However, there is some evidence that the implantation of foreign materials, such as prosthetic www.selleckchem.com/products/Vorinostat-saha.html mesh, may lead to a decreased threshold for infection [3]. While many factors can influence surgical wound healing and post-operative infection, bacterial burden is the most significant risk factor. Wounds are classified according to the likelihood and degree of wound contamination at the time of operation. Classifications include: clean wounds, clean-contaminated wounds, contaminated wounds, and dirty or infected wounds [4]. The pathogens involved in an infection depend on the type of surgery. In an aseptic surgical procedure, Staphylococcus

aureus is a common source of infection, either from the patient’s own skin flora or surrounding environment. Surgeons can minimize the risk of infection and associated complications by routinely employing site-specific spectrum antibiotic prophylaxis. Resminostat In clean-contaminated, contaminated, and dirty surgical procedures, the polymicrobial aerobic and anaerobic flora closely resemble the normal endogenous microflora of the gastrointestinal (GI) tract and are the most frequently observed pathogens. The contaminating pathogens in GI surgery include gram-negative bacilli (e.g., Escherichia coli) and gram-positive microbes, such as enterococci and anaerobic organisms. A classification scheme has been demonstrated in multiple studies to predict the relative probability that a given wound will become infected [5, 6].

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T, Flohr Selleck Go6983 T, Blocker H, Bottger EC: Detection and identification of mycobacteria by amplification of rRNA. J Clin Microbiol 1990,28(8):1751–1759.PubMedCentralPubMed 10. Zolg JW, Philippi-Schulz S: The superoxide dismutase gene, a target for detection and identification of mycobacteria by PCR. J Clin Microbiol 1994,32(11):2801–2812.PubMedCentralPubMed 11. Pryor M, Springthorpe S, Riffard S, Brooks T, Huo Y, Davis G, Sattar SA: Investigation of opportunistic pathogens in municipal drinking water under different supply and treatment regimes. Water Sci Technol 2004,50(1):83–90.PubMed 12. Niva M, Hernesmaa A, Haahtela K, Salkinoja-Salonen M, Sivonen K, Haukka K: Actinobacteria communities of borel forest soil and lake water are rich in mycobacteria. Boreal Environ Res 2006,11(1):45–53. 13. Leys NM, Ryngaert A, Bastiaens L, Wattiau P, Top EM, Verstraete W, ABT-737 molecular weight Springael D: Occurrence

and community composition of fast-growing Mycobacterium in soils contaminated with polycyclic aromatic hydrocarbons. MNK inhibitor FEMS Microbiol Ecol 2005,51(3):375–388.PubMedCrossRef 14. Uyttebroek M, Vermeir S, Wattiau P, Ryngaert A, Springael D: Characterization of cultures enriched from acidic Polycyclic Aromatic Hydrocarbon-contaminated soil for growth on pyrene at low pH. Appl Environ Microbiol 2007,73(10):3159–3164.PubMedCentralPubMedCrossRef 15. Uyttebroek M, Breugelmans P, Janssen M, Wattiau P, Joffe B, Karlson U, Arachidonate 15-lipoxygenase Ortega-Calvo JJ, Bastiaens L, Ryngaert A, Hausner M, et al.: Mycobacterium

community and polycyclic aromatic hydrocarbons (PAHs) among different size fractions of a long-term PAH-contaminated soil. Environ Microbiol 2006,8(5):836–847.PubMedCrossRef 16. Uyttebroek M, Spoden A, Ortega-Calvo JJ, Wouters K, Wattiau P, Bastiaens L, Springael D: Differential responses of Eubacterial , Mycobacterium , and Sphingomonas communities in Polycyclic Aromatic Hydrocarbon (PAH)-contaminated soil to artificially induced changes in PAH profile. J Environ Qual 2007,36(1):1403–1411.PubMedCrossRef 17. Radomski N, Lucas FS, Moilleron R, Cambau E, Haenn S, Moulin L: Development of a real-time qPCR method for detection and enumeration of Mycobacterium spp. in surface water. Appl Environ Microbiol 2010,76(11):7348–7351.PubMedCentralPubMedCrossRef 18. Fukushima M, Kakinuma K, Hayashi H, Nagai H, Ito K, Kawaguchi R: Detection and identification of Mycobacterium species isolates by DNA microarray. J Clin Microbiol 2003,41(6):2605–2615.PubMedCentralPubMedCrossRef 19.