Nat Biotechnol 1983, 1:784–790 CrossRef 41 Miller JH: Experiment

Nat Biotechnol 1983, 1:784–790.CrossRef 41. Miller JH: Experiments in Molecular Genetics. Cold Spring Habor. New York: Cold Spring Habor Laboratory Press; 1972. ed. 42. Tsai JW, Alley MR: Proteolysis

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alignment with hierarchical clustering. Nucleic Acids Res 1988,16(22):10881–10890.PubMedCrossRef RG7420 chemical structure 48. Letunic I, Doerks T, Bork P: SMART 7: recent updates to the protein domain annotation resource. Nucleic Acids Res 2012,40(Database issue):D302-D305.PubMedCrossRef Competing interests The authors declare that they have no competing interests. Authors’ contribution CK, RFL and SLG planned the experiments; CK, RFL and GMA conducted the experiments; CK and RFL analyzed as well as interpreted the data. CK, RFL and SLG prepared the manuscript. All authors read and approved the final Rolziracetam manuscript.”
“Background Oral infections, such

as caries and periodontal disease, are among the most common instances of bacterial pathogenesis in humans. Current models of oral disease development center around the microbial communities found in dental plaque biofilms. Development of the dental plaque biofilm involves competition and cooperation among hundreds of different organisms. Early colonizing organisms, dominated by streptococci such as S. gordonii[1], bind to a variety of host derived molecules coating oral surfaces known as the acquired pellicle. Secondary colonizing species then adhere to those bound to the pellicle. Fusobacterium nucleatum can bind these early colonizing organisms and later additions to the biofilm [2]. In addition, F. nucleatum is aerotolerant and metabolic activity can reduce the concentration of oxygen to levels that can be tolerated by more pathogenic organisms such as P. gingivalis[3]. P. gingivalis can bind to both F. nucleatum and S. gordonii[4, 5], and these organisms are metabolically compatible when associated [3, 6]. While destruction of periodontal tissue is generally associated with later colonizers like P.

: Heterogeneity of enteroaggregative Escherichia coli virulence d

: Heterogeneity of enteroaggregative Escherichia coli virulence demonstrated in volunteers. J Infect Dis 1995, 171:465–468.PubMedCrossRef 7. Baudry B, Savarino SJ, Vial P, Kaper JB, Levine MM: A sensitive

MK-8669 concentration and specific DNA probe to identify enteroaggregative Escherichia coli, a recently discovered diarrheal pathogen. J Infect Dis 1990, 161:1249–1251.PubMedCrossRef 8. Harrington SM, Dudley EG, Nataro JP: Pathogenesis of enteroaggregative Escherichia coli infection. FEMS Microbiol Lett 2006, 254:12–18.PubMedCrossRef 9. Pereira AL, Ferraz LR, Silva RS, Giugliano LG: Enteroaggregative Escherichia coli virulence markers: positive association with distinct clinical characteristics and segregation into 3 enteropathogenic E. coli serogroups. J Infect Dis 2007, 195:366–374.PubMedCrossRef 10. Nataro JP, Steiner

T, Guerrant RL: Enteroaggregative Escherichia coli. Emerg Infect Dis 1998, 4:251–261.PubMedCrossRef 11. Knutton S, Shaw R, Phillips AD, Smith HR, Willshaw GA, Watson P, et al.: Phenotypic and genetic analysis of diarrhea-associated Escherichia coli isolated from children in the United Kingdom. J Pediatr Gastroenterol Nutr 2001, 33:32–40.PubMedCrossRef 12. Weintraub A: Enteroaggregative Escherichia coli: epidemiology, virulence and detection. Journal of Medical Microbiology 2007, 56:4–8.PubMedCrossRef 13. Sheikh J, Hicks S, Dall’Agnol M, Phillips AD, Nataro JP: Roles for Fis and YafK in biofilm formation by enteroaggregative Escherichia

coli. Mol Microbiol 2001, 41:983–997.PubMedCrossRef buy AZD9291 14. Dudley EG, Abe C, Ghigo JM, Latour-Lambert P, Hormazabal JC, Nataro JP: An IncI1 plasmid contributes to the adherence of the atypical enteroaggregative Escherichia coli strain C1096 to cultured cells and abiotic surfaces. Infect Immun 2006, 74:2102–2114.PubMedCrossRef 15. Yoshida T, Kim SR, Komano T: Twelve pil genes are required for biogenesis of the R64 thin pilus. Journal of Bacteriology 1999, 181:2038–2043.PubMed GNA12 16. Mattick JS: Type IV pili and twitching motility. Annu Rev Microbiol 2002, 56:289–314.PubMedCrossRef 17. Sowa BA, Moore D, Ippen-Ihler K: Physiology of F-pilin synthesis and utilization. J Bacteriol 1983, 153:962–968.PubMed 18. Schroder G, Lanka E: The mating pair formation system of conjugative plasmids-A versatile secretion machinery for transfer of proteins and DNA. Plasmid 2005, 54:1–25.PubMedCrossRef 19. Ou JT, Anderson TF: Effect of Zn2+ on bacterial conjugation: inhibition of mating pair formation. J Bacteriol 1972, 111:177–185.PubMed 20. Ghigo JM: Natural conjugative plasmids induce bacterial biofilm development. Nature 2001, 412:442–445.PubMedCrossRef 21. May T, Okabe S: Escherichia coli harboring a natural IncF conjugative F plasmid develops complex mature biofilms by stimulating synthesis of colanic acid and Curli. J Bacteriol 2008, 190:7479–7490.PubMedCrossRef 22.

Nanotechnology 2013,

24:335601 CrossRef 29 Harmand J-C,

Nanotechnology 2013,

24:335601.CrossRef 29. Harmand J-C, Glas F, Patriarche G: Growth kinetics of a single InP 1−x As x nanowire. Phys Rev B 2010, 81:235436.CrossRef 30. Colombo C, Spirkoska D, Frimmer M, Abstreiter G, Fontcuberta i Morral A: Ga-assisted catalyst-free growth mechanism of GaAs nanowires by molecular beam epitaxy. Phys Rev B 2008, 77:155326.CrossRef 31. Werner F, Limbach F, Carsten M, Denker C, Malindretos J, Rizzi A: Electrical conductivity of InN nanowires and the influence of the native indium oxide formed at their surface. Nano Lett 2009, 9:1567.CrossRef 32. Glas F, Harmand J-C, Patriarche AUY-922 G: Why does wurtzite form in nanowires of III-V zinc blende semiconductors? Phys Rev Lett 2007, 99:146101.CrossRef 33. Dick KA, Caroff P, Bolinsson J, Messing ME, Johansson J, Deppert K, Wallenberg LR, Samuelson L: Control of III–V nanowire crystal structure by growth parameter tuning. Semicond Sci Technol 2010, 25:024009.CrossRef 34. Johansson J, Dick KA, Caroff P, Messing ME, Bolinsson J, Deppert K, Samuelson L: Diameter Dependence of the wurtzite-zinc blende transition in InAs nanowires. J Phys Chem C 2010, 114:3837.CrossRef 35. Yamashita T, Akiyama T, Nakamura K, Ito T: Theoretical investigation on the structural stability of GaAs nanowires with two different types of facets. Phys

E 2010, 42:2727.CrossRef 36. Akiyama T, Sano K, Nakamura K, Ito T: An empirical potential approach to wurtzite–zinc-blende polytypism Diflunisal in group III–V semiconductor nanowires. J J Appl Phys 2006, 45:L275.CrossRef Selleckchem EPZ6438 37. Krogstrup P, Popovitz-Biro R, Johnson E, Hannibal Madsen M, Nygård J, Shtrikman H: Structural phase control in self-catalyzed growth of GaAs nanowires on silicon (111). Nano Lett 2010, 10:4475.CrossRef 38. Krogstrup P,

Curiotto S, Johnson E, Aagesen M, Nygård J, Chatain D: Impact of the liquid phase shape on the structure of III-V nanowires. Phys Rev Lett 2011, 106:125505.CrossRef Competing interests The authors declare that they have no competing interests. Authors’ contributions QZ and EA carried out expitaxial synthesis, participated in SEM studies and drafted the manuscript. AS carried out the TEM measurements and analysis. MKR, TDV and AZ carried out SEM measurements. BJR and OK participated in the substrate preparation. VF and FA conceived of the study, and participated in its design and coordination and provided financial support. All authors read and approved the final manuscript.”
“Background Primary liver cancer is one of the top malignancies around the world with respect to morbidity and mortality [1]. Liver cancer cases reported in China account for 43.7% of people affected by this disease in the world. Still in China, liver cancer is the second most fatal malignancy, accounting for 20.37 deaths per 100,000 individuals [2]. Moreover, liver cancer incidence has steadily increased in recent years and constitutes a serious threat to health in China.

To this end, we examined consecutive chest radiographs of elderly

To this end, we examined consecutive chest radiographs of elderly AA and CA women and found that the racial difference in vertebral fracture prevalence was considerably smaller (only 1.3-fold higher in CA women) and not

statistically significant. We then investigated whether this unexpected observation could be explained by differences in medical conditions which lead to osteoporosis and vertebral fractures. Our results suggest that this is not the case. The two races were similar in age, which is a known strong predictor of vertebral fractures. When medical Ceritinib in vitro conditions that may be associated with fractures (Table 1) were added as covariates to regression analyses with vertebral fractures as outcome, and race and age as fixed predictors, the point estimates (coefficients) for race did not change. None of the medical conditions examined had a significant effect in the regression Sunitinib in vitro models or significant interaction with

race. Cancer was present in a higher proportion of CA women. However, that should result in a greater, rather than smaller, difference in the vertebral fracture prevalence between CA and AA women, assuming that some of the fractures are due to malignant causes or to osteoporosis resulting from treatment for malignancy. below The AA group had higher

prevalence of ESRD, but the racial differences in the vertebral fracture prevalence were similar in patients without ESRD and in the whole study sample. We also observed higher prevalence of smoking in the AA subjects. Interestingly, we found greater (albeit not statistically significant) racial difference in the vertebral fracture prevalence among smokers than non-smokers (Fig. 2b). It is possible that this was due to a difference in body weight (lower weight in CA as compared to AA smokers) which was not available in our study. We found grater racial difference in vertebral fracture prevalence (again not statistically significant) in women with history of glucocorticoid use (Fig. 2c). However, we did not have an accurate estimate of the glucocorticoid dose, which makes any conclusion regarding the racial differences in its effect unreliable. We also entertained the possibility that our observation may be due to heterogeneity of our study sample, which included both patients who received their primary care at our institution and those who were referred for tertiary care. We found similar racial differences in vertebral fracture prevalence among patients who were and those who were not receiving primary care at the University of Chicago (Fig. 2d).

It needs 20 months average until PD However, high risk

It needs 20 months average until PD. However, high risk SB203580 research buy group are difficult to control in this manner Fig. 7 A case of Bor-maintenance

therapy. Elderly patient (81 year old female: IgGλ + BJPλ, stage IIIb) living far from hospital, can visit only once monthly. After 14 months therapy, she achieved CR when switched from VGPR to maintenance therapy Recently, lenalidomide maintenance therapy improved median progression-free survival (41 vs. 23 months with placebo; hazard ratio, 0.50; P < 0.001) [30]. Therapy for relapsed or refractory multiple myeloma (RRMM) Progressive disease is defined as follows: (1) Above 25 % elevation of M-protein, (2) hypercalcemia: corrected serum calcium >11.5 mg/dL, (3) the absolute increase of free light chain (FLC) must be >10 mg/dL, (4) definite development of new

bone lesions or soft tissue plasmacytomas, (5) decrease in hemoglobin of >2 g/dL, (6) rise in serum creatinine by 2 mg/dL or more, (7) increase of BM myeloma cell above 10 %. Analysis of second primary malignancies (SPM) Another important issue in MM is risk of developing SPMs due to living longer from diagnosis. Population studies show MM patients have increased risk of specific SPMs following initial diagnosis, notably acute myeloid leukemia (AML). Some MM therapeutic agents are particularly associated with elevated risk of SPMs. Melphalan is associated with increased risk of secondary acute leukemia. There were imbalances in SPM incidence, including myeloid and lymphoid leukemias, Akt assay with post-transplant lenalidomide maintenance therapy and with MP-lenalidomide. Persistent significant OS benefit with VMP versus MP; 13.3-months increase in median, and MPT versus MP increase 6.6 months [9]. Secondary malignancies and lenalidomide: by summarizing the data to-date, the incidence of all/invasive SPM is significantly increased in Lenalidomide arms, driven by hematologic SPM (P < 0.001). B-ALL, Hodgkin lymphoma is reported in post high-dose melphalan and ASCT setting. Sensitivity analysis Endonuclease (including SPM as an event) demonstrates negligible PFS differences.

The overall benefit–risk profile of lenalidomide in NDMM remains positive [31, 32]. Risk Factors for Secondary Malignancies Treatment with lenalidomide may be treatment duration >24 months, male, age >55 years, ISS stage III, previous DCEP (role of concomittant or previous exposure to alkylators?) induction by univariate and multivariate analysis in IFM 2005. In Japanese SPM Report by JRCMC, retrospective analysis for 325 MM patients from 1998 to 2010 (13 years) showed t-MDS/AML developed 17 (5.2 %) patients. Median time to onset: 52 months in t-AML and months in t-MDS. All the patients with t-AML died in a short time, suspected to be treated with Melphalan, and no patients had been given Lenalidomide. We have to select chemo regimen taking into account the risk of t-MDS/AML [33].

The variance of the random intercept, D(1,1), represented the deg

The random effects consisted of patient-specific intercepts and slopes as well as a residual variance. The variance of the random intercept, D(1,1), represented the degree of variability of patients’ cognitive impairment at baseline, while the variance of the random slope, D(2,2), indicated whether response to management over time was similar (small) or variable (large) between patients. The covariance (correlation) between the patient-specific intercept and slope indicated Venetoclax manufacturer whether the evolution of patients’ cognitive impairment over time was related to their

condition at baseline. Higher order (quadratic and cubic) models were considered at both the fixed- and random-effects level and Akaike’s information criteria (AIC) indicated that the linear model was acceptable (Table 3) [30]. Fig. 2 LOESS line plots of cognitive outcomes

over time by randomly selected Dabrafenib clinical trial patients and diagnosis groups: a patient-level evolution of MMSE, b average evolution of MMSE by diagnosis group, c patient-level evolution of MoCA, and d average evolution of MoCA by diagnosis group. AD Alzheimer’s disease, MMSE Mini-Mental State Examination, MoCA Montreal Cognitive Assessment, svCVD small vessel cerebrovascular disease Table 3 Univariable and multivariable analyses of cognitive outcomes based on MMSE and MoCA Models   MMSE MoCA Estimate (SD) p value Estimate (SD) p value Base model  Intercept  

20.33 (0.45) <0.0001 19.83 (0.51) <0.0001  Pure AD   2.36 (1.03) 0.0226 1.85 (1.12) 0.0999  FDur (months)   −0.04 (0.01) 0.0101 −0.04 (0.02) 0.0168  PureAD × FDur   −0.03 (0.03) 0.2160 −0.02 (0.03) 0.5409  D11   24.60 (3.07) <0.0001 21.53 (3.52) <0.0001  D12   0.12 (0.07) 0.0977 −0.02 (0.10) 0.8532  D22   0.01 (0.00) <0.0001 0.01 (0.00) 0.0042  Residual variance   5.74 (0.33) <0.0001 5.52 (0.45) <0.0001 Univariable models  Age   −0.08 (0.05) 0.1227 −0.08 (0.06) 0.1318  Female   −2.51 (0.80) 0.0018 −1.99 (0.85) 0.0206  Chinese   −1.13 (0.99) 0.2505 0.19 (1.05) 0.8597  Years of education   0.39 (0.08) <.0001 0.21 (0.10) 0.0294  Diabetes mellitus   −0.67 (0.91) 0.4606 −0.62 (1.02) 0.5426  Hypertension   −0.09 (0.83) 0.9153 0.03 (0.90) 0.9720  Hyperlipidemia selleck kinase inhibitor   0.63 (0.83) 0.4460 0.99 (0.92) 0.2847  Medicationsa Donepezil 0.06 (0.47) 0.9018 −0.27 (0.66) 0.6877   Galantamine 0.08 (0.67) 0.9096 0.93 (0.98) 0.3415   Memantine −1.58 (0.71) 0.0266 −0.88 (1.20) 0.4624   Rivastigmine – – –   Duration of treatment   0.01 (0.01) 0.4651 −0.01 (0.02) 0.5022 Baseline MoCA|MMSE   0.68 (0.05) <0.0001 0.84 (0.06) <0.0001 Baseline GDS   0.08 (0.18) 0.6693 0.03 (0.21) 0.886 Multivariable models  Intercept   18.04 (0.63) <0.0001 18.33 (0.84) <0.0001  Pure AD   1.48 (1.04) 0.1561 1.64 (1.11) 0.1396  FDur (months)   −0.04 (0.01) 0.0069 −0.04 (0.02) 0.0189  Pure AD × FDur   −0.03 (0.03) 0.2461 −0.02 (0.03) 0.

For QWs, ζ = 2 4048 In our case, the diameter of the

For QWs, ζ = 2.4048. In our case, the diameter of the Protease Inhibitor Library manufacturer nanocone is a function of its height d(z); therefore, it is a graded band gap semiconductor. The shape of this quantum structure allows us to obtain graded band gap in elementary semiconductors. The physical properties of a semiconductor strongly depend on the solid angle of the nanocone. So if the angle is about 60°, then the nanocone is a quantum dot – 0D system; if the angle tends

to be at 180°, then the nanocone degenerates to a quantum well – 2D system; and if the angle tends to 0°, then the nanocone degenerates to the wire – 1D system. The most interesting case is when the angle is between 60° and 0°, then band gap of a semiconductor gradually increases towards the top of the nanocone, leading to a graded band gap structure. The possibility of wide applications of graded band gap structure in optoelectronics devices was shown in [12]. For example, a photodetector possessing both properties can be of bolometric type with an ‘open window’ on top of the cones or with a selective spectral sensitivity depending on light propagation direction and a light source with gradual change of the emitted wavelength depending on z-coordinate. FGFR inhibitor Understanding of the mechanism of nanocones formation in semiconductors

by laser radiation is a very important task for physics and nanotechnology. Recently, we have shown a possibility to form nanocones by Nd:YAG laser radiation on the surface of elementary semiconductors such as Si [8], Ge [7], and CdZnTe [13], and SiGe [9] solid solutions. The phenomena of ‘blue shift’ of the PL spectra and ‘red shift’ of the phonon LO line in the Raman spectra are explained by exciton

and phonon quantum confinement effect Vildagliptin in nanocones [7]. The asymmetry of the PL band in the spectrum of Si nanocones is explained by the formation of 1D-graded band gap structure [8]. A two-stage mechanism of nanocones formation has been proposed for SiGe solid solution [9]. The first stage of nanocones formation is the generation and redistribution of point defects (impurity atoms and intrinsic defects – vacancies and interstitials) in temperature gradient field, the so-called thermogradient effect (TGE) [15]. As a result of TGE, a new phase on the irradiated surface is formed, for example, Ge phase on the surface of SiGe solid solution [9], which was confirmed by appearance of new LO line in back-scattering Raman spectra. The second stage is characterized by mechanical plastic deformation of the strained top layer leading to arise of the nanocones due to selective laser absorption of the top layer. This stage is more or less similar to Stranski-Krastanov (S-K) growth mode of quantum dots.

However, they measured creatine kinase and myoglobin 24 h and 48

However, they measured creatine kinase and myoglobin 24 h and 48 h after exercise, which might explain the disparate findings. In marathon runners, post-race

creatine kinase was significantly elevated among faster compared to slower runners and the elevations of creatine kinase drawn 24 hours after a marathon were inversely related to the finishing times [26]. Skenderi et al. described 39 runners in the Spartathlon, a 246 km ultra-marathon, which the athletes completed within 33.3 (±0.5) h [6]. The finishing time was not correlated to the post race creatine kinase concentration, as has been found in the present study. Duration of amino acid supplementation Our athletes ingested the amino acids as a pre-race load of 12 g and then 4 g at each aid station during the 100 km ultra-marathon. The total amount was 52.5 g amino acids and Fulvestrant in vitro the time of supplementation was between 12 and 13 hours. This time period might be too short to show an effect of the amino acid supplementation on performance. An amino acid supplementation period of two weeks [27], four weeks [28] or even eight weeks [29] showed beneficial effects on performance. The supplementation of amino acids for a shorter period may nonetheless have positive effects on serum variables or muscle soreness. Shimomura et al. demonstrated that the

ingestion of 5 g of branched-chain amino acids 15 minutes prior to seven sets of 20 squats per set reduced the delayed onset of muscle soreness and muscle Selleckchem Compound Library fatigue for several days after exercise [18]. The duration of supplementation might also have been too short to show an effect on creatine kinase. Consuming 12 g of branched-chain amino acids during seven days reduced the increase of creatine kinase and lactate dehydrogenase after performance [30]. Ohtani et al. showed a decrease in post exercise creatine kinase serum concentrations compared

to pre-exercise when athletes ingested, three times per day, 2.2 g of a mixture of amino acids during one month [28]. However, there is data that shows that the ingestion of amino acids during performance has an effect on variables of skeletal muscle damage. In a recent study in untrained through male cyclist, the ingestion of branched-chain amino acids reduced the increase in creatine kinase serum concentration after performance [31]. The disparate findings might be explained by the fact that those researchers investigated untrained subjects during cycling where as we investigated well-trained and experienced ultra-runners. Two recent studies showed an enhanced performance when both protein and carbohydrates were ingested during endurance performances. In two studies of cyclists, the combined intake of carbohydrate and protein during exercise enhanced performance [16, 17]. In the first study of Saunders et al., the subjects were given a carbohydrate and protein beverage with 7.3% carbohydrate and protein plus 1.

5-5′-AGCTTGGGGACTTTCCGA-3′ DNA probe (Bio-Protech, Taipei, Taiwan

5-5′-AGCTTGGGGACTTTCCGA-3′ DNA probe (Bio-Protech, Taipei, Taiwan) as fluorescence. Nuclear protein extracts from RAW 264.7 cells were prepared following the method of Chen et al. [23]. The DNA binding reaction with nuclear protein was performed at

room temperature in a volume of 20 μl, which contained the binding LY2606368 molecular weight buffer (10 mM Tris–HCl, pH 7.5, 50 mM NaCl, 1 mM dithiothreitol (DTT)), 1 μg of poly(dI-dC), 50 nM cy5.5-labeled probe, 0.5 % Tween 20, and 15 μg of nuclear extracts. After incubation for 30 min, the samples were electrophoresized on native 5 % acrylamide gels prepared in a 0.5× TBE buffer (AMRESCO, Solon, OH, USA). Supershift assays using anti-p65 and anti-p50 antibody were also conducted to confirm the specificity of NF-κB DNA-binding activity. “Cold” represents a nuclear extract preincubated with an excess of unlabeled oligonucleotide. The gel was subsequently imaged with a LI-COR Odyssey Infrared Imaging System (LI COR Biosciences, Lincoln, VX-770 research buy NE, USA) in 700-nm channels with a 169 μm resolution. The density

of fluorescence in each band was measured in triplicate using LI-COR imaging software. Immunofluorescent staining Effects of kinsenoside on the nuclear translocation of p65 were examined by immunofluorescence, as described previously [24]. Briefly, 5 × 104 RAW 264.7 cells were seeded onto a 24-well plate preseeded with coverslips. After overnight incubation to allow for cell attachment, the cells were preincubated with kinsenoside (10, 25, and 50 μM) for 2 h before stimulation for 1 h with RANKL (50 ng/ml). After incubation, cells were washed twice Thymidine kinase with 1× PBS, fixed for 15 min at room temperature with 4 % paraformaldehyde in 1× PBS (pH 7.4), and then washed extensively with 1× PBS. Cells were then permeabilized in 1× PBS containing 0.1 % Triton X-100. After blocking with 0.1 % BSA-PBS, cells were incubated at 4 °C overnight with anti-p65 antibody (Cell Signaling, Danvers,

MA, USA) diluted 1:200 in PBS. Cells were then labeled for 1 h at room temperature with an Alexa Fluor 488 phallotoxin (Molecular Probes, Inc., Eugene, OR, USA) diluted 1:500 in PBS. Cells were then washed in PBS as before, counterstained for 3 min at room temperature with 4′-6-diamidino-2-phenylindole (DAPI) (Santa Cruz Biotechnology, Inc., CA, USA), and mounted for confocal microscopy (Leica TCS SP2, Buffalo Grove, IL, USA). Luciferase assay To examine NF-κB activation, RAW 264.7 cells (5 × 104 in 1 ml of fresh medium) were seeded in a 24-well plate before transfection. The NF-κB luciferase reporter plasmids and pRL-TK used in this study were obtained from Promega (Madison, WI, USA). The DNA/jetPEI®-Macrophage mixture was then added to the cells. The cells were incubated in a humid atmosphere of 5 % CO2 at 37 °C for 6 h. After 6 h, the transfected cells were treated with kinsenoside for 120 min and then stimulated with RANKL (50 ng/ml) for 24 h.

24 Gotovac S, Yang C-M, Hattori Y, Takahashi K, Kanoh H, Kaneko

24. Gotovac S, Yang C-M, Hattori Y, Takahashi K, Kanoh H, Kaneko K: Adsorption of polyaromatic hydrocarbons on single wall carbon nanotubes of different functionalities RO4929097 purchase and diameters. J Colloid Interface Sci 2007, 314:18–24. 25. Long RQ, Yang RT: Carbon nanotubes as superior sorbent for dioxin removal. J Am Chem Soc 2001, 123:2058–2059. 26. Lu C, Chung Y-L, Chang K-F: Adsorption thermodynamic

and kinetic studies of trihalomethanes on multiwalled carbon nanotubes. J Hazard Mater 2006, 138:304–310. 27. Peng X, Li Y, Luan Z, Di Z, Wang H, Tian B, Jia Z: Adsorption of 1,2-dichlorobenzene from water to carbon nanotubes. Chem Phys Lett 2003, 376:154–158. 28. Upadhyayula VK, Deng S, Mitchell MC, Smith GB: Application of carbon nanotube technology for removal of contaminants in drinking water: a review. Sci Total Environ 2009, 408:1–13. 29. Yang K, Zhu L, Xing B: Adsorption of polycyclic aromatic hydrocarbons by carbon nanomaterials. Environ Sci Technol 2006, 40:1855–1861. 30. Zhang S, Shao T, Kose HS, Karanfil T: Adsorption of aromatic compounds by carbonaceous adsorbents: a comparative study on granular activated carbon, activated carbon fiber, and carbon nanotubes. Environ Sci Technol 2010, 44:6377–6383. 31. Zhang S, Shao T, Kose HS,

Karanfil T: Adsorption kinetics of aromatic compounds on carbon nanotubes and activated carbons. Environ Toxicol Chem 2012, 31:79–85. 32. Savage N, Diallo MS: Nanomaterials and water purification: opportunities and challenges. J Nanopart Res 2005, 7:331–342. 33. Di Z-C, Ding J, Peng X-J, Li Y-H, Luan Z-K, Liang J: Chromium adsorption selleck compound by aligned carbon nanotubes supported ceria nanoparticles. Chemosphere 2006, 62:861–865. 34. Li Y-H, Di Z, Ding J, Wu D, Luan Z, Zhu Y: Adsorption thermodynamic, kinetic and desorption studies

of Pb 2+ on carbon nanotubes. Water Res 2005, 39:605–609. 35. Rao GP, Lu C, Su F: Sorption of divalent metal ions from aqueous solution by carbon nanotubes: a review. Sep Purif Technol 2007, 58:224–231. 36. Peng X, Luan Z, Ding J, Di Z, Li Y, Tian B: Ceria nanoparticles supported on carbon nanotubes for the removal of arsenate from water. Mater Lett 2005, 59:399–403. 37. Yan X, Shi B, Lu J, Feng C, Wang D, Tang H: Adsorption PRKACG and desorption of atrazine on carbon nanotubes. J Colloid Interface Sci 2008, 321:30–38. 38. Akasaka T, Watari F: Capture of bacteria by flexible carbon nanotubes. Acta Biomater 2009, 5:607–612. 39. Deng J, Yu L, Liu C, Yu K, Shi X, Yeung LWY, Lam PKS, Wu RSS, Zhou B: Hexabromocyclododecane-induced developmental toxicity and apoptosis in zebrafish embryos. Aquat Toxicol 2009, 93:29–36. 40. Upadhyayula VK, Deng S, Smith GB, Mitchell MC: Adsorption of Bacillus subtilis on single-walled carbon nanotube aggregates, activated carbon and NanoCeram™. Water Res 2009, 43:148–156. 41. Brady‒Estévez AS, Kang S, Elimelech M: A single‒walled‒carbon‒nanotube filter for removal of viral and bacterial pathogens. Small 2008, 4:481–484. 42.