The elevated diversity in the zoo apes cannot be due to sample size, as the sample sizes for the zoo apes are considerably smaller than those for the sanctuary apes. Moreover, rarefaction analysis (Additional file 2: Figure S1) indicates that the elevated diversity in the zoo apes is not an artifact of differences in sequencing depth. Instead,

this extraordinary diversity appears to be an inherent feature of the saliva microbiome of the zoo apes. In fact, the rarefaction analysis suggests that much diversity remains to be documented in the zoo ape saliva microbiomes, so the patterns noted below may change with additional sampling. Table 2 Statistics for the microbiome diversity in zoo apes Species Number of individuals Number of sequences Number of OTUs Unknown (%) Unclassified(%) Number Bucladesine cell line of see more genera Variance between individuals (%) Variance within individuals (%) Bonobo 3 558 247 4.3 5.9 54 2.1 97.8 Chimpanzee 5 2263 700 8.8 4.5 135 1.7 98.3 Gorilla 4 1943 644 5.9 8.8 100 4.2 95.8 Orangutan 5 2174 562 4.9 4.3 93 0.8 99.2 Unknown (%) is the percentage

of sequences that do not match a sequence in the RDP database. Unclassified is the percentage of sequences that match a sequence in the RDP database for which the genus has not been classified. The relative abundance of the predominant genera in zoo apes vs. sanctuary apes is shown in Figure 2B. These 32 genera VX809 accounted for 96.7% of all sequences in sanctuary apes but only 87% in zoo apes. At the phylum level, sanctuary and zoo apes showed comparable relative abundances, except for the presence of the Deinococcus phylum in zoo apes. However differences were seen within phyla,with the most striking differences seen in the Gamma-Proteobacteria; zoo apes were virtually free of Enterobacteriaceae

but instead had a much higher abundance of Neisseria and Kingella. Pasteurellaceae were present PFKL in roughly equal proportions in sanctuary and zoo apes. With one exception (Granulicatella), genera within the phyla Firmicutes and Actinobacteria had consistently higher abundances in zoo than in sanctuary apes. No consistent trend could be observed for the genera within Fusobacteria and Bacteroidetes, however overall those two phyla were more abundant in sanctuary apes (Figure 2B). The average Spearman’s rank correlation coefficient based on the frequency of genera among pairs of individuals was 0.51 (range 0.50-0.57) within each species of zoo ape and 0.51 (range 0.49 – 0.54) between each pair of species of zoo ape. For the zoo apes, the within-species correlations are thus closer to (and in some cases even overlap) the between-species correlations, compared to the correlations for the humans vs. the sanctuary apes. Nevertheless, the ANOSIM analysis indicates that the between-species differences are significantly greater than the within-species differences for the zoo apes (p = 0.0002 based on 10,000 permutations).

Part of the results was presented at the 52nd Interscience Conference on Antimicrobial Agents and Chemotherapy,

ICAAC, held San Francisco, USA, September 2012. References 1. Denning DW, Riniotis K, Dobrashian R, Sambatakou H: Chronic cavitary and fibrosing pulmonary and pleural aspergillosis: case series, proposed nomenclature change, and review. Clin Infect Dis 2003, 37:S265-S280.LY294002 ic50 PubMedCrossRef 2. Shapiro RS, Robbins N, Cowen LE: Regulatory circuitry governing fungal development, drug resistance, and disease. Microbiol Mol Biol Rev 2011, 75:213–267.PubMedCentralPubMedCrossRef 3. Walsh TJ, Anaissie EJ, Denning DW, Herbrecht R, Kontoyiannis DP, Marr KA, Morrison VA, Segal BH, Steinbach WJ, Stevens DA, van Burik J, Wingard JR, Patterson TF: Treatment of Aspergillosis: Clinical Practice Guidelines of the Infectious Diseases Society of America. Clin Infect Dis 2008, 46:327–360.PubMedCrossRef 4. Howard see more SJ, Cerar D, Anderson MJ, Albarrag A, Fisher MC, Pasqualotto AC, Laverdiere M, Arendrup MC, Perlin DS, Denning DW: Frequency and evolution of Azole resistance in Aspergillus LXH254 molecular weight fumigatus associated with treatment failure. Emerg Infect Dis 2009, 15:1068–1076.PubMedCentralPubMedCrossRef 5. Arikan-Akdagli S: Azole resistance in Aspergillus : global status in Europe and Asia. Ann N Y Acad Sci 2012, 1272:9–14.PubMedCrossRef 6. Hof H: Critical annotations to the use of

azole antifungals for plant protection. Antimicrob Agents Chemother 2001, 45:2897–2990.CrossRef 7. Bowyer P, Denning DW: Environmental fungicides and triazole resistance in Aspergillus . Pest Manag Sci 2014, 70:173–178.PubMedCrossRef 8. Snelders E, Camps SM, Karawajczyk A, Schaftenaar G, Kema GH, van der Lee HA, Klaassen

CH, Melchers WJ, Verweij PE: Triazole fungicides can induce cross-resistance tomedical triazoles in Aspergillus fumigatus . PLoS One 2012, 7:e31801.PubMedCentralPubMedCrossRef 9. Snelders E, Veld RA HI’t, Rijs AJ, Kema GH, Melchers WJ, Verweij PE: Possible Environmental Origin of Resistance of Aspergillus fumigatus to Medical Triazoles. Appl Environ Microbiol 2009, 75:4053–4057.PubMedCentralPubMedCrossRef 10. Verweij PE, Snelders E, Kema GH, Mellado E, Melchers WJ: Azole resistance in Aspergillus fumigatus : a side-effect selleckchem of environmental fungicide use? Lancet Infect Dis 2009, 9:789–795.PubMedCrossRef 11. Stensvold CR, Jorgensen LN, Arendrup MC: Azole-Resistant Invasive Aspergillosis: Relationship to Agriculture. Curr Fungal Infect Rep 2012, 6:178–191.CrossRef 12. Meletiadis J, Mavridou E, Melchers WJ, Mouton JW, Verweij PE: Epidemiological cutoff values for azoles and Aspergillus fumigatus based on a novel mathematical approach incorporating cyp51A sequence analysis. Antimicrob Agents Chemother 2012, 56:2524–2529.PubMedCentralPubMedCrossRef 13. Varanasi NL, Baskaran I, Alangaden GJ, Chandrasekar PH, Manavathu EK: Novel effect of voriconazole on conidiation of Aspergillus species. Int J Antimicrob Agents 2004, 23:72–79.

The predominant spoligotype, widely dispersed geographically (Table 1 &2), was found in the international data base to have a pattern with a spoligotype number SB0120 with the corresponding hexacode of 6F-5F-5F-7F-FF-60. Five out of the six study districts had this predominant spoligotype, and Namwala district accounted for 30% of spoligotype SB0120. The second most predominant spoligotype had a pattern named SB0871 with a corresponding hexacode of 6F-4F-5F-7F-FF-60. Isolates C14 was

named SB1572 with a hexacode number of 6F-5F-5F-7F-FF-40, isolate C16 was CB-839 mouse SB1536 with a hexacode number of 2F-5F-5F-6F-FF-60 and isolate C19 was SB0162 with a hexacode number of 00-00-00-0F-FF-60. The distribution

of these spoligotypes on the international data base is shown in Table 2. Table 2 Major Spoligotypes in Zambia find more Spoligotype1 Shared type2 Geographical distribution Sp1 SB0120 France, Belgium, Brazil, South Africa, Sri Lanka, Iran, The Netherlands, Spain, China, Japan, Portugal, Russia, Denmark, Zambia Sp2 SB0871 France Sp3 SB1763* Zambia Sp4 SB1764* Zambia Sp5 SB1572 Italy Sp6 SHP099 solubility dmso SB1765* Zambia Sp7 SB1536 Italy Sp8 SB1766* Zambia Sp9 SB1767* Zambia Sp10 SB0162 Belgium 1 Arbitrary spoligotype designation 2 Shared type, designation of the spoligotype in the World Spoligotype Database. *New Spoligotype assigned by http://​www.​mbovis.​org Five individually occurring isolates (16.1%) displayed new spoligo patterns that have not yet been described on the international PIK-5 spoligotyping data base (Figure 2 and Table 2). These isolates

originated from Namwala district (isolate C26, 42 and C41); from Mumbwa (isolate C21); and from Monze (isolate C9) (Table 1 and Figure 2). These new patterns were allotted new spoligo numbers as SB1763 (hex code 66-03-5F-6D-FF-60), SB1764 (hex code 60-0F-1F-6C-FF-00), SB1765 (hex code 2F-5F-5F-7F-FF-40), SB1766 (hex code 6F-4F-1F-6F-FF-60) and SB1767 (hex code 62-0E-50-09-FF-40) by http://​www.​mbovis.​org Table 2. The technique showed a good discrimination power; Hunter Gaston Discriminatory Index (HGDI = 0.98) (Table 1 and Figure 2.). Discussion Our results do not agree with what has been found in other parts of Africa [21, 22], where more than 40% of the animals with tuberculous lesions had Non-tuberculous Mycobacteria (NTM). In this study, only two animals had mycobacteria other than M. bovis. However, our findings tie up with a similar study conducted in Algeria [23]. Whereas excluding the differences in bacterial species as accounting for these observations [23], strain isolation has been found to be dependant on the specific type of media used [24]. The usage of specific culture media such as Stonebrink has been shown to increase the recovery and discrimination of strains on culture [25, 26].

In summary, in the context of a still GW-572016 in vivo limited scientific evidence base, our study and meta-analysis provide data supporting a differential role of the estrogen hydroxylation pathway in

prostate cancer development. The small sample size of our original study prevents us from drawing strong conclusions, but the results of our meta-analysis including the second study provide us with greater evidence in support of the investigated association and the need for further studies. References 1. Parkin DM, Bray F, Ferlay J, Pisani P: Global Cancer Statistics, 2002. CA Cancer J Clin 2005, 55: 74–108.CrossRefPubMed 2. Giovannucci E: Epidemiologic characteristics of prostate cancer. Cancer 1995, (75) : 1766–77. 3. Bosland MC: The role of steroid hormones in prostate cancerogenesis. J Natl Cancer Inst Momogr

2000, 27: 39–66. 4. Diamandis EP, Yu H: Does prostate cancer start at puberty? Clin Lab Anal 1996, 10 (6) : 468–9.CrossRef 5. Barba M, Terrenato I, Schünemann H, Fuhrman B, Sperati F, Teter B, Gallucci M, D’Amato A, Muti P: Indicators of Sexual and Somatic Development and Adolescent Body Size in Relation to Prostate Cancer Risk: Results from a Case-control Study. Urology 2008, 72 (1) : 183–7.CrossRefPubMed 6. Carruba: Estrogens and Mechanisms of Prostate Cancer Progression. Ann N Y Acad Sci 2006, 1089: GSK126 research buy 201–7.CrossRefPubMed 7. Bosland MC, Ford H, Horton LI: Induction at high incidence of ductal prostate adenocarcinomas in NBL/Cr and Sprague-Dawley

Hsd:SD rats treated with a combination of testosterone and estradiol-17β or diethylbestrol. Carcinogenesis 1995, 16: 1311–7.CrossRefPubMed 8. Ho SM, Lane K: Sex hormone-induction and dietary modulation of prostatic adenocarcinoma (PA) in animal models. Urol Oncol 1996, 2: 110–5. 9. Ayala AG, Roj Y: Prostatic intraepithelial neoplasia: recent evidence. Arch Pathol Lab Med 2007, 131 (8) : 1257–31.PubMed Cobimetinib 10. Lotinum P, West K, Gibson KJ, Turner RT: Tissue-selective effects of continuous release of 2-hydrohyestrone and 16α-hydroxyestrone on bone, uterus and mammary gland in ovariectorized Luminespib mw growing rats. J Endocrinol 2001, 170: 165–174.CrossRef 11. Suto A, Bradlow H, Wong GY, Osborne MP, Telang NT: Experimental down-regulation of intermediate biomarkers of carcinogenesis in mouse mammary epithelial cells. Breast Cancer Res Treat 1993, 27: 193–202.CrossRefPubMed 12. Telang NT, Suto A, Wong GY, Osborn MP, Bradlow HL: Induction by estrogen metabolite 16α-OHE1 of genotoxic damage and aberrant proliferation in mouse mammary epithelial cells. J Natl Cancer Inst 1992, 84: 634–8.CrossRefPubMed 13. Muti P, Westerlind K, Wu T, Grimaldi T, De Berry J, Schünemann H, Freudenheim JL, Hill H, Carruba G, Bradlow L: Urinary estrogen metabolites and prostate cancer: a case-control study in the United States.

This work aims at tuning these parameters to minimize strain and surface roughness of the PSi stack which, in turn, affects the epitaxial growth and thus the presence of crystalline defects in the epitaxial foils. For monolayers of PSi, our results reveal that strain and surface roughness decrease by decreasing the thickness of the layer. A similar behavior was observed for as-etched monolayers and for annealed monolayers, but with higher absolute values and opposite sign. As expected, annealing has an effect of strain relief related to the morphological changes implied by the sintering. Moreover, surface roughness also increased with layer thickness. This was attributed this website to the bigger pore

formation at the top surfaces

of thicker PSi layers. Therefore, all PS 341 these results suggest that, both in terms of strain and surface roughness, thinner PSi layers would be better and highly preferred for high-quality epitaxial growth. However, for forming detachable epitaxial foils, a HPL is to be included below the seed layer. And, unexpectedly, strain decreased and saturated, by increasing the thickness of the LPL. We explained this by proposing to consider the interaction between the strain in the HPL and the LPL at their interface and that the dominating source of strain in the double layer of PSi is coming from the HPL. Also, our results reveal that strain is released gradually from double layers of PSi by longer annealing times. This was attributed to the disappearing of the inter-connections between the porous seed layer and the Si

substrate. The exposure to longer annealing times of the double layer of PSi results in fact in a lower density of pillars that, in turn, results in a lower out-of-plane compressive strain. TCL This check details interpretation was supported by measurements on samples with higher and lower porosity HPL, with higher and lower density of pillars, respectively. However, if longer annealing times result in lower strain, they may conversely result in a significant increase in surface roughness, due to the occasional opening of pores at the very top surface over time. Finally, for a multi-layer stack of PSi, which is a must to combine ease of foil detachment and good crystalline quality, thicker LPL and longer annealing times help in reducing strain but produce a rougher surfaces. A trade-off between these effects, of lower-strained stack and rougher seed, is required for finding the optimum condition for a better seed template for higher quality epitaxial growth. Further work will therefore focus on investigating directly the crystalline quality of epi-foils grown on seeds of various annealing times and thicknesses, in order to identify the dominating effects. Authors’ information MK is a joint PhD student at Alexandria University, Egypt, and KU Leuven, Belgium. RM is a PhD student at KU Leuven. HSR is a researcher in Silicon Photovoltaics at IMEC, Belgium.