Results ELS habitat quality scores Of the 35 experts contacted, 27 (77 %) responded; Compound C mw eighteen of which (51 %) returned completed questionnaires while nine (25 %) declined to participate due to concerns with the use of expert questionnaires to inform ecological models, concerns over their own expertise or a lack of time available. As expected, option EF4 (Nectar flower mix) was given the greatest PHB with a mode score of 3 and a mean of 2.83 (Table 2). On average, each expert allocated six options a PHB score of 0 and an average of 1.5 options a PHB score of 3. Expert confidence in responses

was click here generally high with 13 (72 %) giving confidence scores of 3 or 4 and only two (11 %) experts giving scores of 1. When weighted for expert confidence, mean PHB values for all options fell sharply (mean 0.86); EF4 remained the highest rated (PHB 2.83) followed by options for hedges EB10, EB3, EB8/9 and woodland edges EC4 (mean PHB ≥ 1.75) while options for winter stubbles EF6, EF22 and EG4 remained the lowest rated options (mean PHB ≤ 0.5). Model costs and benefits The three most important options in the 2012 baseline option mix were for hedges and low input grassland GW4869 purchase EB1/2, EK2 and EK3 (Table 2) which collectively account for 50 % of total points. The grassland option area was 216 % greater than the arable option area, most likely because of high uptake

of these options in less productive areas (Hodge and Reader 2010). Total costs of the ELS options considered from a 2012 baseline were estimated at £32.2 M, giving a £1:£4.13 cost:benefit ratio compared with the ELS payments (£133 M) provided. In terms of pollinator habitat quality; the baseline ELS provides 200 M units total HQ benefit, quantitatively equivalent to 1.5 units of HQ per £1 of ELS payment. The most costly options were those that included seed costs (See Table 7 in Appendix). EB1/2, EF6, EK2 and EC2 contributed the greatest proportion of points to the hedge/ditch (48.1 %),

arable (18 %), grassland (18.6 %) and plot/tree (75.5 %) option categories respectively. To assess the costs of providing pollinator habitat oriented ELS compositions, the study utilised expert opinion to weight three redistributions of ELS options by multiplying the PHB values provided by the ELS points conferred to each option. The most beneficial options Ketotifen in each category were EB10 (hedge/ditch option), EF4 (arable option), EK1 (grassland option) and EC1 (tree/plot option). Under Model A the number of units within each of the four option categories was restructured to reflect the benefits to pollinator habitat, increasing the quality of the absolute area currently managed (Table 3). This increased the area managed under ELS by 108.3 % (Table 4) but also produces the greatest total private costs (~£59.1 M) and more than doubles both public costs (£144 M; 108 %) and total HQ benefits (+140 %).

According to a two-tailed t-test, the P-value for this comparison was less than 0.001, indicating that the difference in core proteome size between the three B. anthracis isolates, and randomly chosen sets of three Bacillus isolates, was statistically significant. In fact, none of the 25 randomly-generated sets contained a larger core proteome than the set of B. anthracis isolates.

B. anthracis therefore satisfied our first criterion, since the three B. anthracis isolates had more similar protein content than randomly-chosen sets of three Bacillus isolates. B. anthracis also satisfied the second criterion, which stated that species should be distinct from other isolates of the same genus. OSI-906 Table 3 shows that the B. anthracis isolates contained 168 proteins not found in any other Bacillus isolate, compared to an average of just one unique protein for the 25 randomly-generated sets (P-value < 0.001). None of the 25 randomly-generated sets contained

more unique proteins than the three B. anthracis isolates. Overall, the fact that B. anthracis satisfied both criteria supports its current taxonomic classification. As another example, consider R. leguminosarum. There were selleck inhibitor 3678 proteins in its core proteome, compared to an average of 4063 for randomly selected sets of two Rhizobium isolates. This difference was not statistically significant due to the fact that only four corresponding

random groups could be created. Two of the four random GNE-0877 groups–the first containing Rhizobium etli strain ATCC 51251 and R. leguminosarum strain 3841, and the second containing R. etli strain CIAT 652 and R. leguminosarum strain 3841–had larger core proteome sizes than the two R. leguminosarum isolates. The results for unique proteomes were similar, with the same two random groups having a larger unique proteome size than the two R. leguminosarum isolates. However, this apparent lack of cohesiveness can be attributed to differences in the proteome sizes of the individual isolates: the proteome of R. leguminosarum strain WSM2304 contains just 4320 proteins, compared to 5921 for the next-smallest Rhizobium isolate. As such, it might be expected that two Rhizobium isolates having proteomes much larger than that of R. leguminosarum strain WSM2304 would also have a larger core and/or unique proteome. The apparent lack of cohesiveness of Y. click here pestis can also be readily explained, although the reason is different than that for R. leguminosarum. There were four random groups of seven isolates each, all of which contained a mixture of Y. pestis and Yersinia pseudotuberculosis isolates, that had larger core proteomes than the seven Y. pestis isolates. All of the isolates of both Y. pestis and Y.

Lettat was the recipient of a CIFRE Danisco SAS research fellowship. The authors thank the skilled INRA personnel of the Herbivores Research Unit, especially D. Durand for performing animal surgery, S. Alcouffe, M. Fabre and D. Roux, for the care of animals, L. Genestoux and V. Chomilier for their aid in performing laboratory analysis. We also thank E.A. Galbraith and A.H. Smith (Danisco, Waukesha, WI) and B. Meunier (INRA Clermont Ferrand/Theix) for their help in DGGE analysis, as well as P. Mosoni (UR 454 Microbiologie, INRA Clermont Ferrand/Theix) and P. Horvath (Danisco, SAS France) for providing the QNZ cost 16 S rDNA standards.

References 1. Krause DO, Denman SE, Mackie RI, Morrison M, Rae AL, Attwood GT, McSweeney CS: Opportunities to improve fiber degradation

Idasanutlin in the rumen: microbiology, ecology, and genomics. FEMS Microbiol Rev 2003,27(5):663–693.PubMedCrossRef 2. Khafipour E, Li S, Plaizier JC, Krause DO: Rumen microbiome composition determined using two nutritional models of subacute ruminal acidosis. Appl Environ Microbiol 2009,75(22):7115–7124.PubMedCrossRef 3. Enemark JMD: The monitoring, prevention and treatment of SAHA in vitro sub-acute ruminal acidosis (SARA): A review. Vet J 2008,176(1):32–43.PubMedCrossRef 4. Martin C, Brossard L, Doreau M: Mécanismes d’apparition de l’acidose ruminale latente et conséquences physiopathologiques et zootechniques. INRA Prod Anim 2006, 19:93–108. 5. Kleen JL, Hooijer GA, Rehage J, Noordhuizen JPTM: Subacute ruminal acidosis (SARA): A review. J Vet Med A 2003,50(8):406–414.CrossRef 6. Meschy F, Bravo D, Sauvant D: Analyse quantitative des réponses des vaches laitières à l’apport de substances tampon. INRA Prod Anim 2004, 17:11–18. 7. Packer EL, Clayton EH, Cusack PMV: Rumen fermentation and liveweight Montelukast Sodium gain in beef cattle treated with monensin and grazing lush forage. Aust Vet J 2011,89(9):338–345.PubMed 8. Chaucheyras-Durand F, Walker ND, Bach A: Effects of active dry yeasts on the rumen microbial ecosystem: Past, present and future. Anim Feed Sci Technol 2008,145(1–4):5–26.CrossRef 9. Desnoyers M, Giger-Reverdin S, Bertin G, Duvaux-Ponter

C, Sauvant D: Meta-analysis of the influence of Saccharomyces cerevisiae supplementation on ruminal parameters and milk production of ruminants. J Dairy Sci 2009,92(4):1620–1632.PubMedCrossRef 10. Meissner HH, Henning PH, Horn CH, Leeuw K-J, Hagg FM, Fouché G: Ruminal acidosis: a review with detailed reference to the controlling agent Megasphaera elsdenii NCIMB 41125. S Afr J Anim Sci 2010,40(2):79–100. 11. Nocek JE, Kautz WP, Leedle JAZ, Block E: Direct-fed microbial supplementation on the performance of dairy cattle during the transition period. J Dairy Sci 2003,86(1):331–335.PubMedCrossRef 12. Chiquette J: Evaluation of the protective effect of probiotics fed to dairy cows during a subacute ruminal acidosis challenge. Anim Feed Sci Technol 2009,153(3–4):278–291.CrossRef 13.

cDNA synthesis and cDNA-AFLP analysis were performed for the 10 Avapritinib concentration replicates. First-strand cDNA was synthesised from 2 μg of total RNA using a SuperScript III First Strand Synthesis System (Invitrogen, USA) in accordance with the manufacturer’s instructions. Second-strand cDNA was sythesised by adding the first-strand

cDNA reaction to a reaction mix that contained MG-132 cost 15 μl of 10 × cDNAII buffer, 35 U DNA of Polymerase I (Invitrogen), 3 U of RNase H (Invitrogen), and 1 μl dNTPs (25 mM) in a final volume of 150 μl, and incubating for 2 h at 16°C (). The resulting double-stranded cDNA was purified in accordance with the method of Powell and Gannon [34]. The concentration of the cDNAs was determined using spectrophotometer (Bio-Rad) and their quality was determined by electrophoresis on a 1.2% agarose gel. cDNA- AFLP A 500-ng aliquot of double-stranded cDNA was used for AFLP analysis as described by Bachem et al. [35] with the following modifications. The template for cDNA-AFLP was digested with the restriction enzymes, EcoR I/Mse I and Psu I/Mse I (Invitrogen). The Sequence of the primers and adapters used for the AFLP reactions are given in Additional File 2. AFLP reactions were performed in accordance with Bachem et al. [36]. Selective amplification products

were separated on a 10% polyacrylamide gel and stained with silver nitrate [37]. The gels were dried Bcl-w onto 3 MM Whatman paper. Cloning, sequencing and bioinformatic characterisation To select DE-TDFs, the profiles CHIR98014 nmr of infected and non-infected samples were compared between replicates. TDFs that differed in abundance between the two types of sample, namely infected and non-infected plants, were selected only when the same pattern was observed in all replicates. The cloning of bands of interest was performed as previously described[38]. Briefly, the bands were excised from the gels using a razor blase. Each gel slice was incubated

in 10 μl of distilled water for 10 min at 96°C. Aliquots of the eluent were subjected to PCR using the same conditions as for the selective PCR described before. PCR products were separated on 10% polyacrylamide gel to confirm that the correct polymorphic fragments had been selected [39]. After verification, the recovered products re-amplified using primer pair E-0/M-0 and P-0/M-0 to provide sufficient DNA for cloning. The purified PCR products were cloned into the pGEM-T Easy vector (Promega) and then sequenced. The sequences were compared with those in the non-redundant databases of the National Center for Biotechnology Information (NCBI; http://​www.​ncbi.​nlm.​nih.​gov/​BLAST/​) and The Arabidopsis Information Resource (TAIR; http://​www.​arabidopsis.

The specific surface area and pore volume of the prepared alumina nanofibers were measured using the BET equation and the Horvath-Kawazoe (HK) method (ASAP2020, Micromeritics) after preheating the samples to 150°C for 2 h to eliminate adsorbed water. The pore size distributions were obtained by applying the HK method (micro-pore) to the nitrogen adsorption isotherms at 77 K using the software ASAP 2020. Results and discussion Figure 1 shows the results of the thermogravimetric curve and the derivative weight loss curve of the as-electrospun PVP and AIP/PVP composite nanofibers.

At the AIP/PVP composite nanofiber curve, endothermic and exothermic peaks were observed with a corresponding weight loss of EPZ015938 cell line about 20%, in the region extending to 175°C. These peaks were attributed to the vaporization of physically absorbed water and the removal of any remaining solvent from the composite fibers. In the region extending from 200°C to 300°C, an endothermic and exothermic peak was observed that was associated with a weight loss of 30%. This

observation was in accordance with the previous report by Kang et al. [18, 19] that a weight loss resulted from the decomposition and burning of the PVP polymer fibers. The peaks were observed between 300°C and 400°C, and the weight loss associated with these peaks was 60% and indicated the complete find more combustion of the PVP polymer fibers and the organometallic compound of AIP. In contrast to a study Romidepsin datasheet on sol–gel process without PVP performed by Xu et al. [17], the prominent exothermic peak was observed at 429°C and indicating the complete combustion of

the PVP polymer fibers. Figure 1 Thermogravimetric curve and derivative weight loss curve of the as-electrospun AIP/PVP composite nanofibers. The SEM micrographs of the composite nanofibers show that the as-electrospun Meloxicam fibers as well as those calcined at 800°C and 1,200°C had similar morphologies (Figure 2). As can be readily seen, in addition to their shapes, the continuous morphology of the as-electrospun composite nanofibers was maintained in the calcined nanofibers as well. Cylindrical nanofibers with diameters in the range of 276 to 962 nm could be successfully prepared using AIP as the precursor (Figure 2b). The diameter of these nanofibers decreased after calcinations at 800°C and 1,200°C, and alumina nanofibers with diameters of 114 to 390 nm (Figure 2c) and 102 to 378 nm (Figure 2d) were obtained after the respective heat treatments. In addition, as the calcination temperature increased, the average diameter of the alumina nanofibers decreased continuously, indicating that the organic groups further decrease in diameter for an increase in the calcination temperature beyond 1,200°C. The alumina nanofibers fabricated in this study were thinner and had narrower diameter distributions than those reported by Kang et al. [8]. From the EDX analysis, as-electrospun AIP/PVP nanofibers calcined at 800°C and 1,200°C showed C, O, and Al, and only Al and O, respectively.

Edited by: Ramos J-L. New York: Kluwer Academic/Plenum Publishers; 2004:147–172. 14. Ongena M, Jacques P: Bacillus lipopeptides: versatile weapons for plant disease biocontrol. Trends Microbiol 2008,16(3):115–125.PubMedCrossRef 15. Bender CL, Scholz-Schroeder BK: New insights into the biosynthesis, https://www.selleckchem.com/products/17-AAG(Geldanamycin).html mode of action and regulation of syringomycin, syringopeptin and coronatine. In Pseudomonas Vol2, Virulence and Gene Regulation Volume 2. Edited by: Ramos J-L. New York: Kluwer Academic/Plenum Publishers; 2004:125–158. 16. Gross H, Loper JE: Genomics of secondary metabolite production by Pseudomonas spp. Nat Prod Rep 2009,26(11):1408–1446.PubMedCrossRef 17.

Delcambe L, Peypoux F, Besson F, Guinand M, Michel G: Structure of iturin-like substances. Biochem Soc Trans 1977, 5:1122–1124.PubMed 18.

Arima K, Kakinuma A, Tamura G: Surfactin, a crystalline peptide lipid surfactant produced by Bacillus subtilis : isolation, ACP-196 mouse characterization and its inhibition of fibrin clot formation. Biochem Biophys Res Commun 1968,31(3):488–494.PubMedCrossRef 19. Vanittanakom N, Loeffler W, Koch U, Jung G: Fengycin- a novel antifungal lipopeptide antibiotic produced by Bacillus subtilis F-29–3. J Antibiot 1986,39(7):888–901.PubMedCrossRef 20. Hathout Y, Ho Y-P, Ryzhov V, Demirev SB203580 P, Fenselau C: Kurstakins: a new class of lipopeptides isolated from Bacillus thuringiensis . J Nat Prod 2000,63(11):1492–1496.PubMedCrossRef 21. Roongsawang N, Thaniyavarn J, Thaniyavarn S, Kameyama T, Haruki M, Imanaka T, Morikawa M, Kanaya S: Isolation and characterization of halotolerant Bacillus subtilis BBK-1 which produces three kinds of lipopeptides: bacillomycin L, plipastatin and surfactin. Extremophiles

2002,6(6):499–506.PubMedCrossRef 22. Duitman HE, Hamoen LW, Rembold M, Venema G, Seitz H, Saenger W, Bernhard F, Reinhard R, Schmidt M, Ullrich C, Stein T, Leenders F, Vater J: The mycosubtilin synthetase of Bacillus subtilis ATCC6633: A multifunctional about hybrid between a peptide synthetase, an amino transferase and a fatty acid synthase. Proc Natl Acad Sci USA 1999,96(23):13294–13299.PubMedCrossRef 23. Besson F, Michel G: Biosynthesis of iturin and surfactin by Bacillus subtilis : evidence for amino acid activating enzymes. Biotechnol Lett 1992,14(11):1013–1018.CrossRef 24. Mandal SM, Barbosa AE, Franco OL: Lipopeptides in microbial infection control: scope and reality for industry. Biotechnol Adv 2013. (In press), S0734–9750(13)00006–2. 25. Abee T, Krockel L, Hill C: Bacteriocins: modes of action and potentials in food preservation and control of food poisoning. Int J Food Microbiol 1995,28(2):169–185.PubMedCrossRef 26. Tally FP, De Bruin MF: Development of daptomycin for Gram-positive infections. J Antimicrob Chemother 2000,46(4):523–526.PubMedCrossRef 27. Baindara P, Mandal SM, Chawla N, Singh PK, Pinnaka AK, Korpole S: Characterization of two antimicrobial peptides produced by a halotolerant Bacillus subtilis strain SK.DU.

oryzae[25, 26]. AspGD curators read the published experimental literature to record information including gene names and synonyms, write free-text descriptions of each gene, record phenotypes and assign terms that describe functional information about genes and proteins using the Gene Ontology (GO; http://​www.​geneontology.​org). Go6983 in vitro These annotations are an important resource for the scientific

research community, used both for reference on individual genes of interest as well as for analysis of results from microarray, proteomic experiments, or other screens that produce large lists of genes. The GO is a structured vocabulary for describing the functions associated with genes products [27]. GO terms describe the activity of a gene product (Molecular Function;

MF) within the cell, the biological process (Biological Process; BP) in which a gene product is involved and the location within the cell (Cellular Component; CC) where the gene product is observed [28]. Evidence codes are assigned to GO annotations based on the type of available experimental evidence. At the start of this project most of the terms needed to describe secondary metabolite biosynthetic genes or regulators of secondary metabolism did not yet exist in the GO. Thus, in order to provide an improved ABT-737 datasheet annotation of secondary metabolite biosynthetic genes and their regulatory proteins, we developed new GO terms for secondary metabolite production in collaboration with the GO Consortium, and reannotated the Wortmannin nmr entire set of genes associated with secondary metabolism in AspGD. We then performed a comprehensive analysis of the secondary metabolism biosynthetic genes and their orthologs across the genomes of A. nidulans, A. fumigatus, A. niger and A. oryzae and now provide a set Carbohydrate of

manually annotated secondary metabolite gene clusters. We anticipate that these new, more precise annotations will encourage the rapid and efficient experimental verification of novel secondary metabolite biosynthetic gene clusters in Aspergillus and the identification of the corresponding secondary metabolites. Results Identifying genes for reannotation Many branches of the GO, such as apoptosis and cardiac development [29], have recently been expanded and revised to include new terms that are highly specific to these processes. The secondary metabolism literature has expanded over the last several years, allowing AspGD curators to make annotations to an increasing number of genes with roles in secondary metabolism. During routine curation, it became apparent that hundreds of Aspergillus genes that were candidates for annotation to the GO term ‘secondary metabolic process’ had the potential for more granular annotations, since, in many cases, the specific secondary metabolite produced by a gene product is known.

2000; Gaston 2003). Unfortunately, locally rare taxa are susceptible to the same threats that affect all rare and FRAX597 endangered ecological communities. Although there is current legislation in the United States designed to protect rare plants within large jurisdictions (e.g. CESA 1970; ESA 1973; CEQA 2005), JSH-23 cost most conservation efforts and development decisions happen at local and regional scales (Reid 1998; Brooks et al. 2006; Leppig and White 2006). In addition to the rare taxa identified by global, national, and state or provincial agencies, locally rare taxa are important for the preservation of species

diversity, and therefore require see more effective and recognizable conservation status. Pärtel et al. (2005) conclude that in the case of vascular plants, an analysis of multiple conservation characteristics, including restricted global and local distributions, would provide a powerful and objective tool for conservation planning. They further highlight that “biogeographic reasons” may play an important role in determining local

abundance of a species, and that the area of a species distribution is the most common characteristic associated with conservation need. Furthermore, White (2004) demonstrated that area of occupancy, when used with an optimal methodology, significantly reduces experimental error for the estimation of range size, especially for rare taxa. Thus, analysis of area of occupancy criteria is important for plant conservation efforts. Although Magney (2004) directly applied the Natural Heritage Network Element Ranking System’s (NatureServe

2006) next criteria for the sub-national assessment scale to a county jurisdiction (Ventura, California), there are no specific local rarity ranks or criteria presently in use to systematically categorize taxa at the county level. Furthermore, when the absence of a standardized summary system is coupled with a frequent lack of accurate distribution data, locally rare taxa are not well integrated into conservation planning efforts. Regrettably due to such vagueness, repeatable studies are difficult and germane regulations are often not effectively applied to locally rare taxa (Leppig and White 2006). Nevertheless, several programs have been developed using various methods in attempts to identify and protect locally rare plants (see CNPS 2010). The purpose of this research was to develop and outline a set of criteria for systematically categorizing and assigning conservation ranks to locally rare taxa. The aim was to address the current gap in the available methods for classifying biodiversity at local assessment scales (e.g., counties) in order to catalog locally rare organisms and give them conservation status.

Finally, we calculated the proportion of patients that filled only a single prescription, the proportion that switched to a different bisphosphonate, and the median days of exposure within 1 year after index, and over the entire follow-up

period. Results Descriptive characteristics We identified 451,113 new bisphosphonate users meeting our inclusion criteria. Of these, 84% were female and the mean age was 75.6 years (SD = 6.9). From April 2000 to March 2009 fiscal year groups, we found that the proportion of male users increased over time (from 8.9% to 23.6%), SGC-CBP30 manufacturer etidronate use at index declined over time (from 91.0% to 22.5%), and BMD testing prior to treatment initiation has been stable at 63% since 2000 (Table 1). Table 1 Characteristics of new users of oral bisphosphonatesa: Ontario residents aged 66 or more years, April 1996–March 2009   April 1996–March 2000 April 2000–March 2003 April 2003–March 2006 EPZ5676 solubility dmso April 2006–March 2009 Overall N = 106,456 N = 119,468 N = 119,326 N = 105,863 N = 451,113 Age, mean (SD) 75.1 (6.4) 75.4 (6.7) 76.0 (7.1) 75.6 (7.2) 75.6 (6.9) Males,% Saracatinib research buy 8.9 13.3 19.8 23.6 16.4 Etidronate,% 91.0 89.5 55.3 22.5 65.1 BMD test,%b 58.1 63.6 63.3 63.2 62.1 Fracture history,%c  Thoracic vertebral 0.1 0.2 0.2 0.2 0.2  Hip, humerus, radius/ulna 5.4 5.5 6.2 6.5 5.9

aAlendronate (5, 10, and 70 mg), cyclical etidronate and risedronate (5 and 35 mg). bBMD testing identified within 1 year prior to index date using Ontario Health Insurance Plan (OHIP) billing codes for dual photon absorptiometry (DPA) prior to 1998, and dual-energy X-ray absorptometry (DXA) from 1998 to 2009 (see Appendix 1). cFractures were identified using ICD-9-CM codes before April 2002, and ICD-10-CA codes since April 2002 (see Appendix 1). Persistence with bisphosphonate therapy A summary of persistence with

bisphosphonate therapy over time is provided in Table 2. In our primary analysis that used a 60-day permissible gap, we identified that the proportion of patients that persisted with therapy declined from 63% at 1 year to 12% after 9 years. We also identified that most patients Teicoplanin experienced one or more extended gaps in bisphosphonate therapy. For example, among the 213,029 new users with at least 5 years of follow-up, 25% persisted with therapy for the full 5 years, 61% experienced one (24%) or more (37%) extended gaps in therapy, and 14% discontinued treatment without returning to bisphosphonate therapy. Using a more lenient 120-day permissible gap to define non-persistence, we note that persistence rates increased and fewer users were identified to have experienced extended gaps in drug therapy. For example, persistence at 1 year increased from 63% using a 60-day permissible gap to 77% when using a 120-day permissible gap (Table 2).

Figure 1 Proposed see more 3D cross-point architecture by using Cu pillar. Schematic view of proposed three-dimensional cross-point architecture with copper (Cu) pillar for high-density memory application. It is expected that five layers of cross-point RRAM devices will be connected by using Cu pillar through Al2O3 isolation layer because Cu could be migrated through Al2O3 film under external positive bias on the TE. This is the general theory from conductive bridging resistive selleck inhibitor random access memory (CBRAM) devices. To succeed the 3D memory architecture with Cu pillar in the future, the via-hole with a size of 4 × 4 μm2 was fabricated in an Al/Cu/Al2O3/TiN M-I-M structure in this study. Tight distribution

of the Cu pillars for 100 devices is observed with a low formation voltage of <5 V and high current compliance (CC) of 70 mA. The formation of strong metallic path in Al2O3 layer suggests that Cu pillar could be formed. The Cu pillars have long read pulse endurance of >106 cycles under positive read voltage; however, it has short read endurance under negative read voltages of less than −1.5 V, owing to random read stress-dependent ruptured Cu pillar. On the selleck kinase inhibitor other hand, bipolar resistive switching memory characteristics are observed by reducing the

CC of 500 μA under a small operating voltage of ±1 V. The resistive switching mechanism is formation/dissolution of Cu filament in the Al2O3 film under external bias. The memory device has good data

retention of >103 s with acceptable resistance ratio of >10. Methods Titanium-nitride (TiN) as a bottom electrode (BE) was deposited on 8-in. SiO2 (200 nm)/Si substrates. The thickness of TiN BE was approximately 200 nm. Then, the SiO2 film with a thickness of 150 nm was deposited. The via-holes with a size of 4 × 4 μm2 were patterned by lithography and opened by dry etching. To follow the lift-off process, photo-resist (PR) was coated and opened on the via-hole and top electrode (TE) regions. Then, the Al2O3 switching layer with a thickness of approximately 20 nm was deposited by rf Miconazole sputtering. The Al2O3 target with a purity of 99.9% was used for deposition. During deposition, the argon (Ar) flow rate was 25 sccm. The deposition power and pressure was 80 W and 30 mTorr, respectively. In next step, Cu as a TE was deposited by thermal evaporator. The deposition rate was 0.5 Å/s. The thickness of Cu was approximately 40 nm. After that aluminum (Al) as a capping layer was deposited by using the same thermal evaporator. The Al deposition rate was 1 Å/s. The thickness of Al was approximately 160 nm. Finally, lift-off was performed to get the final resistive switching memory device. The schematic view of our Al/Cu/Al2O3/TiN via-hole device is shown in Figure 2a. Optical microscope image of the via-hole with a size of 4 × 4 μm2 is shown in Figure 2b. Both the TE and BE were also isolated from other devices.