We thus argue that all ReRAM that exhibit a filamentary type of mechanism could possess stochastic switching characteristics, though our study only exploits TiO2-based devices. Considering the further ReRAM development, this impact of defect distribution should be carefully considered in device engineering as it could significantly affect the fabrication reproducibility

and the accurate control of the devices’ states, necessitating A-1210477 concentration fault-tolerant design paradigms. It is possible to suppress the defects’ broad distribution in TiO2-based pristine devices via annealing [15], Trichostatin A although this extra processing step is not always preferable. Acknowledgements This work was supported by EPSRC EP/K017829/1 and the National Nature Science Foundation (61171017). References 1. Strukov DB, Snider GS, Stewart DR, Williams RS: The missing memristor found. Nature 2008, 453:80–83.CrossRef 2. Yang YC, Pan F, Liu Q, Liu M, Zeng F: Fully room-temperature-fabricated nonvolatile resistive memory for ultrafast and high-density memory application. Nano Lett Alvocidib cost 2009, 9:1636–1643.CrossRef 3. Waser R, Dittmann R, Staikov G, Szot K: Redox‒based resistive switching memories–nanoionic mechanisms, prospects, and challenges. Adv Mater 2009, 21:2632–2663.CrossRef 4. Yang Y, Gao P, Gaba S, Chang T, Pan X, Lu W: Observation of conducting

filament growth in nanoscale resistive memories. Nat Commun 2012, 3:732.CrossRef 5. Yang JJ, Pickett MD, Li X, Ohlberg DA, Stewart DR, Williams

RS: Memristive switching mechanism for metal/oxide/metal nanodevices. Nat Nanotechnol 2008, 3:429–433.CrossRef 6. Salaoru I, Khiat A, Li Q, Berdan R, Papavassiliou C, Prodromakis T: Origin of the OFF state variability in ReRAM cells. J Phys D Appl Phys 2014, 47:145102.CrossRef 7. Ielmini D, Nardi F, Cagli C: Physical models of size-dependent nanofilament formation and rupture in NiO resistive switching memories. Nanotechnology 2011, 22:254022.CrossRef 8. Long S, Lian X, Ye T, Cagli C, Perniola L, Miranda E, Liu M, Sune J: Cycle-to-cycle intrinsic RESET statistics in HfO 2 -based unipolar RRAM devices. Electron Device Lett IEEE 2013, selleck screening library 34:623–625.CrossRef 9. Long S, Lian X, Cagli C, Perniola L, Miranda E, Liu M, Sune J: A model for the set statistics of RRAM inspired in the percolation model of oxide breakdown. Electron Device Lett IEEE 2013, 34:999–1001.CrossRef 10. Chen Y, Chen B, Gao B, Chen L, Lian G, Liu L, Wang Y, Liu X, Kang J: Understanding the intermediate initial state in TiO 2 -δ/La 2/3 Sr 1/3 MnO 3 stack-based bipolar resistive switching devices. Appl Phys Lett 2011, 99:072113–072113–072113.CrossRef 11. Shibuya K, Dittmann R, Mi S, Waser R: Impact of defect distribution on resistive switching characteristics of Sr 2 TiO 4 thin films. Adv Mater 2010, 22:411–414.CrossRef 12.

It is possible that expression of these genes was repressed

when leptospires encountered the low-iron milieu in serum. Similar findings were observed in Yersinia pseudotuberculosis grown in plasma, resulting in down-regulation of several enzymes of the TCA cycle [79]. The transition of Leptospira to serum resulted in up-regulation of pyrD (LIC13433), predicted to encode a dihydroorotate dehydrogenase which catalyzes the fourth step in the de novo pyrimidine nucleotide biosynthetic pathway [80], possibly due to limited availability of pyrimidine in serum. This finding is consistent with previous reports Ruxolitinib showing that the scarcity of nucleotide precursors is the key limitation of bacterial growth in blood [81]. Therefore, de novo nucleotide SB203580 concentration biosynthesis may be required for growth of leptospires in serum. However, enzymes involved in de novo biosynthesis of purine nucleotides were not induced in our study. Notably, down-regulation of one of the purine

salvage enzymes (LIC13399, predicted to encode a purine-nucleoside phosphorylase) was observed. It has been suggested that transcription of genes in purine and pyrimidine biosynthetic pathways is independently regulated [80, 81]. In addition, it is possible that differential expression of genes involved in purine biosynthesis was transient and may not show steady-state expression ratios. Therefore, these genes were not detected as differentially expressed. Selleckchem SN-38 In addition, coaE (LIC13085) encoding dephospho-CoA kinase, which catalyzes the final step in coenzyme A biosynthesis [82], was up-regulated in response to serum, consistent with the use of coenzyme A

as a key cofactor during serum exposure. The kdpFABC operon is typically induced under conditions of severe K+ limitation or osmotic upshift and repressed during growth in media of high external K+ concentration [83]. The putative kdpA (LIC10990) encoding the A chain of potassium-transporting ATPase was down-regulated in response to serum. However, as the level of potassium in EMJH (2.2 mM) is lower than in serum (~5.2 mM) this result is not surprising. Two leptospiral genes predicted to encode fatty acid desaturases (LIC13053 [desA] and LIC20052) were up-regulated in the presence Cetuximab research buy of serum. The unsaturated bonds introduced into fatty acids by these enzymes have been reported to be essential for membrane lipid homeostasis to maintain the fluidity of biological membranes, especially in response to downward temperature shift [84, 85]. The ability of Leptospira to modulate its membrane lipid using fatty acid desaturases may thus be important for survival in response to environmental stresses encountered in serum. Bacterial genes of related functions, including enzymes of metabolic pathways, are frequently but not always co-transcribed as a single transcriptional unit.

01) (Figure 3). Of all strains classified as buy Cobimetinib strong biofilm

producers, MRSA and MSSA associated with MLST CC8 produced the most biomass under all tested glucose concentrations (Figure 4a and 4b). Strains defined as strong biofilm formers and associated with MLST CC5, CC25 and CC30 approached approximately the same level of biomass at the following glucose concentrations, BIBF 1120 in vivo i.e. CC5 at 0.25%, CC 25 at 0.5% and CC30 at 0.5% glucose, respectively. Figure 2 Quantification of strong biofilm formation in MSSA and MRSA. Quantification of strains of the specified group defined as strong biofilm former at different glucose concentrations. Black bars represent MRSA, dark grey bars represent MSSA with MRSA associated

MLST CCs and light grey bars represent MSSA with MSSA associated MLST CCs. Asterisks denote statistically significant difference, (*) P < 0.05 and (**) P < 0.01. Figure 3 Biomass quantification of MSSA and MRSA. Absorbance (A 590) of the crystal violet stained biofilm matrix for strong biofilm formers (with A 590 above the threshold value of 0.374, represented by the horizontal dashed line) at different glucose concentrations. Boxplots at the left show MRSA, in the middle MSSA with MRSA associated MLST CCs and Pritelivir research buy at the right MSSA with MSSA associated MLST CCs. The lower and higher boundary of the box indicates the 25th and 75th percentile, respectively. The line within the box marks the median. Whiskers above and below the box indicate the 90th and 10th percentiles. Open circles indicate the 95th and 5th percentiles. Asterisks denote statistically significant difference, (*) P < 0.05 and (**) P < 0.01. Figure 4 Biomass formation related to the genetic background of S. aureus. Absorbance (A 590) of the crystal violet stained biofilm matrix of strong biofilm forming S. aureus strains in relation to different associated MLST CCs (a) and of strong biofilm forming strains associated with MLST CC1, CC5, CC8, CC22, CC30 and CC45 (b). R in Megestrol Acetate the legend represents MRSA and S represents MSSA. Quantification of strains of the specified genetic background defined as strong biofilm former

at different glucose concentrations, (c) and (d). Asterisks denote statistically significant difference, (b) and (d), and statistical significant difference of individual CCs versus all other associated MLST CCs, (a) and (c), except #, (*) P < 0.05 and (**) P < 0.01. The main contributors to the higher prevalence of MRSA and MSSA with MRSA associated MLST CCs to produce strong biofilms at 0.1% glucose were MLST CC8 isolates, approximately 60% (26 of 41), (Figure 4c), especially with a tendency towards MRSA (Figure 4d). Additionally, blood stream isolates of MSSA associated with MLST CC8 and MLST CC7 were included in the study, to address the question whether the isolation site is an (additional) predisposing factor for strong biofilm formation.

CrossRef 16. Horcas I, Fernandez R, Gomez-Rodriguez JM, Colchero J, Gomez-Herrero J, Baro AM: WSxM: A software for scanning probe microscopy and a tool for nanotechnology. Rev Sci Instrum 2007, 78:013705.CrossRef 17. Murarka SP: Silicides for VLSI Applications. New York: Academic; 1983. 18. Samsonov GV, Dvorina LA, Rud’ BM: Silicides. Moscow: Metallurgia; 1979. [in Russian] 19. Colgan EG, Gambino JP, Hong QZ: Formation and AZD6244 stability of silicides on polycrystalline silicon. Mater Sci Eng 1996,

R16:43–96. 20. Chang YJ, Erskine JL: Diffusion layers and the Schottky-barrier height in nickel–silicon interfaces. Phys Rev B 1983,28(10):5766–5773.CrossRef 21. Sze SM: Physics of Semiconductor Devices. New York: Wiley; 1981. 22. Grunthaner PJ, Grunthaner FJ, Scott DM, Nicolet MA, Mayer JW: Oxygen impurity effects at metal/silicide interfaces: formation of silicon oxide and suboxides in the Ni/Si system. J Vac Sci Technol 1981,19(3):641–648.CrossRef 23. Chang YJ, Erskine JL: Diffusion layers of Ni on Si(100). Phys Rev B 1982,26(8):4766–4769.CrossRef 24. Mataré HF: Defect Electronics in Semiconductors. New York: Wiley; 1971. 25.

Shannon JM: Control of Schottky barrier height using highly doped surface layers. Solid State find more Electron 1976, 19:537.CrossRef 26. Shannon JM: Increasing the effective height of a Schottky barrier using low-energy ion implantation. Appl Phys Lett 1974, 25:75.CrossRef 27. Guliants EA, Ji C, Song YJ, Anderson WA: A 0.5-μm-thick polycrystalline silicon Schottky diode with rectification ratio of 106. Appl Phys Lett 2002,80(8):1474.CrossRef 28. Wong M: Metal-induced laterally crystallized polycrystalline silicon: technology, material and devices. Proc SPIE 2000, 4079:28–42.CrossRef 29. Miyasaka M, Makihira K, Asano T, Pécz B, Stoemenos J: Structural properties of nickel-metal-induced laterally crystallized silicon films. Solid State EPZ015938 solubility dmso Phenomena 2003, 93:213–218.CrossRef

30. Hwang JD, Lee KS: A high rectification ratio nanocrystalline p-n junction diode prepared by metal-induced lateral crystallization for solar cell applications. J Electrochem Soc 2008,155(4):H259-H262.CrossRef Competing interests The authors declare that they have no competing interests. Authors’ contributions KVC participated in the design of the study, carried out the Vitamin B12 experiments, performed data analysis, and participated in the discussions and interpretation of the results. VAC participated in the design of the study and took part in the discussions and interpretation of the results; he also supervised the research performed by young scientists and students. VPK participated in the design of the study and took part in the discussions and interpretation of the results. VYR performed the TEM studies and took part in the discussions and interpretation of the results. MSS investigated the photo-emf spectra; he carried out the experiments, performed data analysis, and took part in the discussions and interpretation of the results.

TP conceived of the study, participated in the design and coordination, and aided in drafting the manuscript. NS conceived of the study,

participated in its design and click here coordination, performed the bioinformatics and participated in drafting the manuscript. All authors read and approved the final manuscript.”
“Background Unsaturated fatty acids, particularly α-linolenic acid (LNA; cis-9, cis-12, cis-15-18:3) and linoleic acid (LA; cis-9, cis-12-18:2), are abundant in grass and other VX-809 in vivo ruminant feedstuffs, yet are present at low concentrations in meat and milk. Furthermore, tissue lipids of ruminants have been known for a long time to be more saturated than those of non-ruminants [1]. As the consumption of saturated acids in dairy products and ruminant meats is often associated with an increased incidence of coronary heart disease in man [2], the transformation of unsaturated fatty acids to saturated fatty acids, or biohydrogenation, in ruminants presents a major human health issue. The biohydrogenation Verteporfin process has long been known to occur in the rumen as the result of microbial metabolic activity [3, 4]. Thus, if ruminal biohydrogenation of unsaturated fatty acids can be controlled, it may be possible to improve the

healthiness of ruminant meats and milk by increasing their unsaturated fatty acids composition in general and the n-3 fatty acids in particular [5]. One of the unsaturated fatty acids that appears Fossariinae most desirable is conjugated linoleic acid (CLA; cis-9, trans-11-18:2) because of its anticarcinogenic and other health-promoting properties [6, 7]. Major advances have been made in achieving the desired changes in fatty acid content of meat and milk experimentally, via dietary manipulation in ruminants, generally by adding oils containing

unsaturated fatty acids to the diet [5, 8–10]. The inclusion of fish oil in particular seems to alter biohydrogenating activity in the rumen [11]. Butyrivibrio fibrisolvens was identified many years ago to undertake biohydrogenation of fatty acids [12] and to form CLA as intermediate in the process [13]. Kim et al. [14] noted that LA inhibited growth of B. fibrisolvens A38, an effect that depended both on the concentration of LA and the growth status of the bacteria. Growing bacteria were more tolerant of LA. In a study of CLA production in different strains of B. fibrisolvens, Fukuda et al. [15] found that the most tolerant strain had the highest linoleate isomerase (forming CLA from LA) specific activity. Different members of the Butyrivibrio/Pseudobutyrivibrio phylogenetic grouping, all of which biohydrogenate PUFA, had different sensitivities to growth inhibition by LA, the most sensitive possessing the butyrate kinase rather than the acyl transferase mechanism of butyrate production [16]. For reasons that were unclear, lactate exacerbated the toxicity of LA to Clostridium proteoclasticum [17], now renamed Butyrivibrio proteoclasticus [18].

During the oxidation process, the Ce2O3 and CeO2 GSK923295 datasheet increases as the electricity increases. It should be highlighted that the existence of Ce2O3 and CeO2 in TNTs-Ce which indicated that the reduction see more process contribute not only the reduced state of Ce but also the oxidation state. The tendency of Ti/O is not clear. Table 1 Ratio of Ce in various photoelectrodes calculated from XPS analysis   Ce Ce 2 O 3 CeO 2 Ti/Ce Ti/O TNTs         0.43 TNTs-Ce 71.6 6.70 21.6 3.57 0.19 TNTs-0.00001

C 57.3 13.3 29.4 3.78 0.30 TNTs-0.00025 C 33.7 33.6 32.6 3.89 0.28 TNTs-0.005 C 28.4 36.7 34.9 5.34 0.31 TNTs-0.01 C 16.1 42.0 41.9 5.56 0.23 Values in at.%. The photocurrent spectra vs. wavelength are showed in Figure 3A. The TNTs-Ce indicates stronger photocurrent response in visible light region and weaker photocurrent response in UV light region compared to the TNTs without deposition. After anode oxidation, Ce-Ce2O3-CeO2 modification photoelectrodes showed stronger photocurrent response in visible. In UV light region, the photocurrents responses of the photoelectrodes are reinforced as oxidation electricity increases with CeO2 increasing except TNTs-0.00001 C. The reason could be as followed: the Ce4+ is an efficient

electron acceptor during the photocurrent production. But the deposition of Ce and its oxide affect the surface morphology of TNTs (Figure 2B) which

reduced the absorption Nutlin-3a cell line of light. In visible light region as the oxidation in depth with Ce2O3 is increasing, firstly, the photocurrent 5-Fluoracil responses of the TNTs-0.00001 C, TNTs-0.00025 C, and TNTs-0.005 C are gradually increased; then, the photocurrent response of TNTs-0.01 C is slightly decreased by Ce2O3 transfer to CeO2. Figure 3 Photocurrent analysis results. (A) Photocurrent responses vs. wavelength plots. (B) Photocurrent responses vs. photon energy plots. (C) Low photon energy part of Figure 3B (from 2.0 to 3.0 eV). The relationship between photocurrent I ph and bandgap energy E g of the oxide films on alloys can be written in the form [15]: (1) where I 0, hv, E g, A, and n are fully discussed in [15] and n = 2 for the indirect transition of semiconductors. Figure 3B shows the photocurrent responses vs. photon energy plots for TNTs with various Ce deposits. Based on linear fitting, the characteristic E g of various photoelectrodes can be derived respectively. E g of the TNTs-Ce is reduced to 2.92 eV. After anodic oxidation, all the samples are located in the E g between 3.0 to 3.1 eV, which are smaller than E g of TNTs (3.15 eV) as a result of simple substance Ce existence. Figure 3C shows the details of low electron energy part of Figure 3B. The various Ce-deposited TNTs indicated E g of 2.1 ± 0.1 eV which is close to the E g = 2.4 eV of Ce2O3. And these differences may be caused by the deposition of the simple substance Ce.

Receptor methylesterase activity has also been ascribed to CheD in T.maritima[32].

Similar to the situation in E.coli[26, 106], receptor deamidase and methylesterase activities have been detected in Hbt.salinarum CheB [25]. It is not clear whether both CheB and CheD deamidate and/or demethylate receptors in the latter organism [25]. Thus the function of the CheD protein in Hbt.salinarum remains to be elucidated. We identified interactions between CheD and CheC2, CheC3, CheB, as well as CheF1, CheF2 and OE2401F. Hence CheD is a hub in the Hbt.salinarum Che protein interaction network. The high conservation of CheD among chemotactic bacteria and archaea [3] and the severe phenotype of a CheD deletion (almost complete loss LY411575 manufacturer of tactic capabilities; our unpublished results) support the hypothesis that this protein has a central role in the taxis signaling network. Of the interactions detected here, only CheC-CheD has been described before [29, 66]. In B.subtilis an interaction of CheD with the MCPs was identified through Y2H analysis [113]. This interaction was not detected in the present study. This might be due to different functions of CheD in the two organisms. However, it seems more likely that the affinity of a putatively dynamic CheD-Htr interaction was simply LDN-193189 manufacturer not high enough for detection

by our bait fishing methods. A CheD-dependent adaptation system in Hbt. salinarum? The interactors CheC and CheD in B.subtilis form a feedback loop from CheY-P to the transducers and thereby constitute one of the three adaptation systems of this organism (the other two being the methylation/demethylation system of CheR and CheB, and the CheV system) [48]. CheC binding to CheD decreases the latter’s receptor deamidase activity [30]. Additionally and more important for adaptation, CheD regulates the activity of CheA [113]. CheY-P stabilizes the CheC-CheD complex,

which in turn reduces CheA stimulation and thus closes the feedback circuit. Indeed, the CheY-P binding ability of CheC seems to be more important for B.subtilis chemotaxis than its enzymatic activity [30]. Tideglusib In contrast to B.subtilis, a direct regulation of CheA activity by CheD seems questionable in Hbt.salinarum since receptor deamidase or methylesterase activity in Hbt.salinarum have till now only been demonstrated for CheB and not for CheD [25]. Additionally, in Hbt.salinarum a CheY-dependent or CheY-P-dependent regulation of transducer demethylation was experimentally demonstrated by Perazzona and Spudich [114], which implies the presence of a slightly different adaptational mechanism. A predictive computational model of transducer methylation [47] strongly supports the ISRIB order possibility that in Hbt.salinarum CheY and not CheY-P is indeed the feedback regulator. Based on these findings we used the detected interactions to propose an alternative feedback mechanism from the response regulator to the Htrs that might contribute to adaptation.

e., a simple sum of its components’ risks), or if they act as effect modifiers for each other [synergistic (i.e., greater than the simple sum), or antagonistic (i.e., less than the simple sum)]. In particular, the following questions have been rarely asked: whether there is a meaningful interaction selleck screening library between job control and social support at work on common mental disorders; and whether the interaction will differ by the level of job demands. For instance, recent meta-analyses

about psychosocial work characteristics and common mental disorders are mute to the above questions (Bonde 2008; Netterstrøm et al. 2008; Stansfeld and Candy 2006). These questions are important for accurate risk assessments (Rothman 1986; Thompson 1991) of the

psychosocial work characteristics for common mental disorders, for instance, the combined risk of the psychosocial work characteristics could be substantially underestimated JQ-EZ-05 price under the additive Lenvatinib cost assumption. In addition, they are essential in terms of targeting of intervention (Thompson 1991), for instance, the benefit of an intervention (i.e., eliminating a risk factor) could be greater in those who are subject to multi-risk factors under the synergistic assumption. Furthermore, they would be informative in understanding complex mechanisms of the psychosocial work characteristics to common mental disorders as well as evaluating contemporary job stress models. Job stress Non-specific serine/threonine protein kinase models and the interaction between job control and social support at work Some contemporary work stress models such as the demand-resource (DR) models (de Jonge and Dormann 2003; Demerouti et al. 2001) and demand-control-support (DCS) model (Johnson and Hall 1988; Karasek et al. 1982) include job control and social support at work as their key concepts. Nonetheless, none of them propose a specific hypothesis on the relationship between job control and social support at work with

regard to health outcomes. Although job control and social support at work are each regarded as the component of resources in the DR models to meet job demands, no due attention is given to the nature of the interaction (i.e., additive vs. non-additive) between the resources on health outcomes. The DCS model was developed by incorporating social support at work into the demand-control (DC) model (Karasek 1979). However, the focus of the model is the interaction between social support at work and job strain (as one variable consisted of job control and job demands, usually dichotomized for analysis into high and low strain) on health outcomes. As a result, the interaction effects between job control and social support at work and between job demands and social support at work on health outcome become the out-of-focus areas in the model.

glabrum, P. spinulosum

and P. subericola sp. nov. were very similar to each other. All species were predominantly monoverticillate, with vesiculate conidiophores and 6–12 ampulliform phialides. The main microscopical difference was the conidia ornamentation, ISRIB order which was smooth to slightly rugose in P. glabrum and P. subericola sp. nov., and distinctly rugose in P. spinulosum. Moreover, the conidia of P. subericola tended to be more rugose than in P. glabrum and the conidiophores of this species occasionally were branched, a character not observed in P. glabrum and P. spinulosum. Extrolites analysis The majority of the strains assigned to P. glabrum, P. spinulosum and P. subericola produced a pattern of extrolites typical for each species (see Table 2). The P. glabrum isolates

had a typical extrolites profile containing asterric acid, Selleck BAY 1895344 bisdechlorogeodin, sulochrin or citromycetin, while isolates of P. spinulosum produce asperfuran, palitantin and frequentin. Asperfuran, deoxybrevianamide E and unidentified compounds which were tentatively named AMF were found in the P. subericola. These AMF compounds are indols with an extended chromophore similar to penitremone. Two cork isolates which phylogenetically clearly belong to P. glabrum (CBS 126333 and 127701) were chemically weak and show no detectable extrolite production. Table 2 Extrolite profile of the cork isolates and type or CSF-1R inhibitor authentic isolates belonging to Glabra series on CYA, YES and OA after 7 days of incubation Species Fludarabine chemical structure Isolates Extrolites P. glabrum CBS 213.28 Asterric acid,

bisdechlorogeodin, questin, sulochrin CBS 328.48 = FRR 1915 Asterric acid, bisdechlorogeodin, citromycetin, PI-3, PI-4 ATCC 42228 = IBT 13946 Asterric acid, bisdechlorogeodin, sulochrin CBS 127703 Asterric acid, bisdechlorogeodin, PI-4, sulochrin CBS 127700 Asterric acid, bisdechlorogeodin, PI-4, sulochrin CBS 126336 Asterric acid, citromycetin, bisdechlorogeodin, PI-4, questin, questinol,sulochrin CBS 127702 Asterric acid, citromycetin, bisdechlorogeodin, PI-4, questin, questinol, sulochrin CBS 127704 Asterric acid, bisdechlorogeodin, PI-4, questinol, sulochrin CBS 126333 No metabolites expressed CBS 127701 No metabolites expressed P. palmense CBS 336.79 = IBT 4912 4 chromophore types in common with P. subericola, and 4 chromophore types only found in this species ATCC 38669 = IBT 16227 4 chromophore types in common with P. subericola, and 4 chromophore types only found in this species P. spinulosum NRRL 1750 Asperfuran DAOM 215366 = IBT 22621 Asperfuran, palitantin, frequentin DAOM 227655 = IBT 22622 Asperfuran, palitantin CBS 127698 2 chromophore types found in this isolate and CBS 127699 CBS 127699 2 chromophore types found in this isolate and CBS 127698 P.

3A and 3C). The expression was maintained in mouse tumor cells for at least 48-72 h (Fig. 3B and 3D). The same result was observed by immunohistochemical staining with 14F7 antibody on in vitro monolayer cultured cells (Fig. 2E and 2F). Figure 3 Detection of NeuGc-GM3 in cell membrane fraction by slot blot assay in B16 (A and B) and F3II (C and D) cells. A and C, tumor cells were preincubated

with different concentrations of NeuGc-rich BSM and processed 24 h later. Gemcitabine nmr B and D, tumor cells were preincubated with 250 μg/ml of NeuGc-rich BSM and further processed 24, 48 or 72 h after preincubation. In all cases, densitometric analysis was normalized to the respective control. Means ± SEM of at least 3 determinations

are shown. *p < 0.05, **p < 0.01 (ANOVA contrasted with Dunnet test). Interestingly, incubation of tumor cells with purified NeuGc modulates the in vitro behaviour. Tumor cell adhesion showed a significant increase in both cell lines (Fig 4A); while NeuGc addition impacted differently on proliferation, significantly increasing growth in B16 but not in F3II cells (Fig 4B). Figure 4 A, adhesion assay. B16 or F3II cells were incubated for 1 h in medium with 2% FBS, either with (filled bars) or without (empty bars) 50 μg/ml of purified NeuGc. Data represent mean ± SEM (n = 6). *p < 0.05, **p < 0.01 (t test). B, proliferation assay. SCH 900776 price B16 (black square) or F3II (black diamond) Flucloronide cells were grown for 72 h in medium supplemented with 1, 5 or 10% FBS, either with or without 100 μg/ml of purified NeuGc. Dashed line refers to proliferation in control monolayers without addition of NeuGc. Data represent mean of 6 determinations; in all cases SEM was less than 5%. ***p < 0.001 versus the respective control (ANOVA contrasted with Tukey-Kramer multiple comparisons test). Finally, we evaluated tumorigenicity and lung colonization of BSM-preincubated

tumor cells in syngeneic mice. In both mouse models click here preincubation with NeuGc-rich BSM significantly enhanced the metastatic ability of tumor cells, approximately doubling the number of lung nodules after intravenous cell injection (Table 1). Similar results were obtained after preincubation with purified NeuGc. B16 NeuGc-treated cells showed a 65% increase in lung nodules (Control: 14.5 ± 4.8, NeuGc: 22.3 ± 3.8; p = 0.14, Mann-Whitney U test), while for F3II NeuGc-treated cells the number of lung nodules resulted in a 112% increase (Control: 7.3 ± 1.8, NeuGc: 15.5 ± 2.2; p < 0.05, Mann-Whitney U test). Although all animals challenged in the flank developed subcutaneous tumors, we observed a rapid tumor take with BSM-preincubated B16 cells. Significant differences were obtained for tumor latency and size of melanoma tumors. However, preincubation with BSM did not significantly modify tumor growth rate (Table 2).