Since tetracycline is used therapeutically in humans and animals, and because most MDR S. click here Typhimurium isolates are LCZ696 nmr resistant to tetracycline, our goal was to determine the effect and extent tetracycline exposure had on the invasiveness of Salmonella isolates from DT104 and DT193.

We examined both cell culture invasion and virulence gene expression in vitro in response to tetracycline under a combination of three conditions: growth phase, tetracycline resistance genotype, and antibiotic concentration. Cellular invasion is a temporally-regulated process in Salmonella that involves the activation of a sequence of genes, most importantly, hilA[21]. The hilA gene is the bottleneck in the process and its deletion prevents invasion from occurring, whereas its over-expression usually results in increased invasion [22]. The invasive response is initiated during early-log growth, and Salmonella is considered maximally invasive during the late-log growth phase MK5108 mw [20]. We found that during early-log growth, tetracycline significantly increased cellular invasion in three isolates,

while it significantly up-regulated the gene expression of virulence factors hilA, prgH, and invF in seven isolates. None of the isolates in the study had an increase in cellular invasion during late-log growth in response to tetracycline, but expression of virulence factors was up-regulated in several isolates. The increased invasiveness of the isolates during early-log was commensurate with the temporally-regulated invasive phenotype observed in each respective 0 μg/ml control isolate during late-log. Therefore, tetracycline exposure induced a shift in the invasion response to an earlier time in the growth cycle (early-log), yet tetracycline did not enhance invasion efficacy when invasion was already at its maximum potential in late-log growth. In addition, an increase in virulence gene expression did not always correlate with a reciprocal increase in invasion. The data demonstrates that the induction of invasion by tetracycline is a growth phase dependent response.

Several tetracycline concentrations were evaluated to determine if invasion induction was dependent on dose, or if the presence of Dynein tetracycline at any level would be effective. Three concentrations of tetracycline that did not inhibit growth of any of the isolates were chosen to study (1, 4, 16 μg/ml). The tetracycline-induced invasion response in the three isolates was only observed at 16 μg/ml. The induction of invasion by tetracycline is a dose dependent response. DT104 and DT193 isolates that encode tetracycline resistance genes commonly found in S. Typhimurium (tetA, B, C, D, and G) were evaluated. The DT104 isolates all had SGI-1 and tetG, but no other tetracycline resistance genes were present. None of the DT193 isolates contained SGI-1. Of the five DT193 isolates, three had only a tetA gene, one had tetA, B, C, and D, and one had tetB, C, and D.

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Semin Oncol 2009, 36 (suppl 3) : S3-S17.PubMedCrossRef 16. Meric-Bernstam F, Gonzalez-Angulo AM: Targeting the mTOR signaling network for cancer therapy. J Clin Oncol 2009, 17: 2278–2287.CrossRef 17. Costa LJ: Aspects of mTOR biology and the use of mTOR inhibitors in Vorinostat price non-Hodgkin’s lymphoma. Cancer Treat Rev 2007, 33: 78–84.PubMedCrossRef 18. Vignot S, Faivre S, Aguirre D, Raymond E: mTOR-targeted therapy of cancer with Rapamycin derivatives. Ann Onc 2005, 16: 525–537.CrossRef 19. Hay N, Sonenberg N: Upstream and downstream of mTOR. Genes Dev 2004, 18: 1926–1945.PubMedCrossRef 20. Guertin DA, Sabatini DM: Defining the

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F, Niemeyer C, Kremens B, Niggli F, Niethammer D, Welte K, Stanulla M, Odenwald E, Riehm H, Schrappe M: Long-term results of five consecutive trials in childhood acute lymphoblastic leukemia performed by the ALL-BFM study group from 1981 to 2000. Leukemia BCKDHA 2010, 24: 265–284.PubMedCrossRef 26. Vega F, Medeiros LJ, Leventaki V, Atwell C, Cho-Vega JH, Tian L, Claret FX, Rassidakis GZ: Activation of mammalian target of rapamycin signaling pathway contributes to tumor cell survival in anaplastic large cell lymphoma kinase-positive anaplatic large cell lymphoma. Cancer Res 2006, 66: 6589–6597.PubMedCrossRef 27. Peponi E, Drakos E, Reyes G, Leventaki V, Rassidakis GZ, Medeiros LJ: Activation of mammalian target of rapamycin signaling promotes cell cycle progression and protects cells from apoptosis in mantle cell lymphoma. Am J Pathol 2006, 169: 2171–2180.PubMedCrossRef 28. Riml S, Schmidt S, Ausserlechner MJ, Geley S, Kofler R: Glucocorticoid receptor heterozygosity combined with lack of receptor auto-induction causes glucocorticoid resistance in Jurkat acute lymphoblastic leukemia cells. Cell Death Differ 2004, 11 (Suppl1) : S65-S72.PubMedCrossRef 29. Almawi WY, Melemedjian OK, Jaoude MM: On the link between Bcl-2 family proteins and glucocorticoid-induced apoptosis.

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for the expression of unfused and fused proteins in Escherichia coli. Gene 1988, 69:301–315.PubMedCrossRef 62. van Aartsen JJ, Rajakumar K: An optimized method for suicide vector-based allelic exchange in Klebsiella pneumoniae. J Microbiol Methods 2011, 86:313–319.PubMedCrossRef 63. O’Toole G, Kolter R: Initiation of biofilm formation in Pseudomonas fluorescens WCS365 proceeds via multiple, convergent signalling pathways: a genetic analysis. Mol

Microbiol 1998, 28:449–461.PubMedCrossRef 64. Licht TR, Krogfelt KA, Cohen PS, Poulsen LK, Urbance J, Molin S: Role of lipopolysaccharide in colonization of the mouse intestine by Salmonella typhimurium studied by in situ hybridization. Infect Immun 1996, 64:3811–3817.PubMed 65. Hvidberg H, Struve C, Krogfelt KA, Christensen N, Rasmussen SN, Frimodt-Møller N: Development of a long-term ascending urinary tract infection mouse model selleck chemicals llc for antibiotic treatment studies. Antimicrob Agents Chemother 2000, 44:156–163.PubMedCrossRef 66. Hemmerich C, Buechlein A, Podicheti R, Revanna KV, Dong Q: An Ergatis-based prokaryotic genome annotation web server. Bioinformatics 2010, 26:1122–1124.PubMedCrossRef Authors’ contributions JJvA carried out the molecular genetic studies, in vitro assays and bioinformatics

analyses. CAS and JJvA carried out the murine infection studies. MC performed Bcl-w the growth curve experiments. EMH and HYO participated in experimental design and bioinformatics analyses. KR and JJvA conceived the study, participated in its design and coordination and drafted the manuscript. SGS, KAK and CS contributed to experimental design and analysis. All authors read, contributed to and approved the final manuscript.”
“Background Selleckchem Ferroptosis inhibitor Borrelia burgdorferi, the spirochetal agent of Lyme disease, possesses a dual-membraned (diderm) architecture, which is composed of a peptidoglycan layer associated with the inner membrane (IM) and an outer membrane (OM) [1, 2]. In Gram-negative bacteria, cytoplasmic precursor outer membrane proteins (OMPs) are synthesized with an amino-terminal signal peptide sequence, which typically targets a protein for Sec-mediated translocation.

Additional polysaccharides were removed following the see more protocol outlined in Wilson [27]. FS ATCC43239 gDNA was isolated following the protocol described in Ausubel et al. [28] and FA UTEX1903 gDNA was extracted following a protocol described in selleck chemicals llc Mustafa [29]. Whole genome sequencing and bioinformatics High molecular weight gDNA from WI HT-29-1 and HW IC-52-3 was sent to BGI (Beijing Genome Institute, China) for genome sequencing via high throughput Illumina sequencing technology. BGI performed genome assembly and gene annotation using Glimmer v3.0. Extracted gDNA from FA UTEX1903 and FS ATCC43239 was submitted to Case Western Reserve Genomics Core Facility for whole genome sequencing. Paired end

DNA libraries were obtained by using Nextera DNA sample preparation kit and sequenced using the Illumina GAIIx platform. Raw reads quality was assessed using FastQC 0.10.1 (Babraham Bioinformatics) with default settings Rabusertib in vivo and trimmed with Seqyclean 1.3.12 (http://​cores.​ibest.​uidaho.​edu/​software/​seqyclean). Filtered

reads were assembled de novo using the velvet package (Version 1.2.08) and a kmer range between 55-63. The optimal assembly based on expected genome size, N50 and contig number was used for downstream annotation and analysis. Gene annotation was performed by BGI using Glimmer v3.2. A Basic Local Alignment Search Tool (BLAST) search was performed to identify the putative function of proteins based on sequence similarity [30]. Nucleotide and protein sequences were organized and visualized using Orotidine 5′-phosphate decarboxylase Geneious v6.1.7 created by Biomatters. Available from http://​www.​geneious.​com/​. Nucleotide alignments were performed using Geneious Alignment with default settings. For protein alignments, Clustal Omega (Version 1.2.1) was used with default settings, except order changed from aligned to input [18]. For phylogenetic analysis, the sequences were first aligned using the Clustal W program built into Geneious. Phylogenetic trees were constructed using the Geneious Tree Builder program, which uses the neighbour-joining method [31]. A 929 bp nucleotide fragment was

used for the phylogenetic analysis of 16S rDNA sequences, while a 315 amino acid sequence alignment was used for phylogenetic analysis of the prenyltransferase. The outgroup was constituted by the distantly related cyanobacterium Synechocystis sp. for 16S rDNA analysis. PCR and sequencing reactions A 50 μL PCR reaction mixture contained 10 pmol of specific forward and reverse primer (Additional file 11) (Geneworks, Australia), 1× PCR Buffer (KAPA Biosystems), 2.5 mM MgCl2, 1 pmol dNTPs (Fisher Biotec), 1 U of KapaTaq polymerase (KAPA Biosystems) and 50 ng of gDNA template. Pfu DNA polymerase (Sigma) was used in addition to KapaTaq at a ratio of 1:10 (v/v). Hotstart PCR was performed by first heating the samples to 95°C.

(2000) Experimental agroforestry systems  Kudzu Pueraria phaseoloides Brazilian Amazon Lieberei et al. (2000)  Achiote Bixa orellana  Brazil nut Bertholletia excelsa  Cupuaçu Theobroma grandiflorum  Coconut Cocos nucifera Brazilian Amazon Clement (1986)  Uvilla Pourouma cecropiaefolia  Cupuassu Theobroma grandiflorum  Graviola Annona muricata  Biriba Rollinia mucosa  Breadfruit Artocarpus

altilis Brazilian Amazon (“food forest” experiment) Arkoll (1982)  Jackfruit Artocarpus heterophyllus  Cacao www.selleckchem.com/products/sbe-b-cd.html Theobroma cacao Bahia, Brazil Alvim et al. (1992)  Black pepper Piper nigrum  Cassava Manihot esculenta Pucallpa, Peru Pérez and Loayza (1989)  Chiclayo Vigna sinensis  Pigeon pea Cajanus cajan  Pineapple Ananas comosus  Guava Inga edulis Pucallpa, Peru (natural terraces for erosion control) Vargas and Aubert (1996) In Costa Rica and Colombia,

WH-4-023 purchase peach palm is commonly cultivated with coffee and banana, and in Brazil, it is recommended as a shade tree for cacao (Clement 1986). In the Brazilian Amazon, Lieberei et al. (2000) identified peach palm grown with Pueraria phaseoloides, Bixa orellana, Bertholletia excelsa and Theobroma grandiflorum as a promising multi-strata system for optimal resource cycling. Peach palm can be also cultivated with coconut as well as with various short-cycle crops, such as pineapple, papaya, and passion fruit, which give farmers rapid returns on investment in the early years of production (Clement 1986). In the Colombian Pacific region, farmers typically cultivate peach palm with Borojoa patinoi, Colocasia esculenta, Musa spp. and Eugenia stipitata. In those agroforestry systems peach palm occupies around 38 % of the available space in farmers’ fields (CIAT, unpublished data). In the Peruvian Amazon peach palm is cultivated within agroforestry mosaics that are characterized by several components, such as annual subsistence crops (e.g., manioc, yam and plantain), fruit crops (e.g., pineapple, cashew and guava),

and late-maturing fruit trees (e.g., Pouraqueiba sericea and Theobroma bicolor). In such agroforestry systems peach palm is grown at a density of approximately 290 trees ha−1 Grape seed extract (Coomes and Burt 1997), though in most traditional Amazonian agroforestry systems densities of only 3–20 plants ha−1 have been reported (Clement 1989; Clay and Clement 1993). Peach palm is also commonly cultivated in monoculture, with an average plant density of around 400 plants ha−1 (Mora-Kopper et al. 1997; Clement et al. 2004). Peach palm in monoculture tends to be smaller than in multi-strata systems, primarily because of less competition for light (Schroth et al. 2002a). In PCI-34051 clinical trial Colombia peach palm is planted for fruit production on an estimated 9,580 ha, with 73 % on the Pacific coast, 22 % in the Amazon region, and the rest (5 %) in other regions of the country.

Diabetes Metab 25:11–21PubMed Wold S, Ruhe A, Wold H, Dunn WJ (1984) The collinearity problem in linear regression the partial least squares (PLS) approach to SCH772984 mw generalized inverses. SIAM J Sci Stat Comput 5:735–743CrossRef”
“Erratum to: Med Chem Res DOI 10.1007/s00044-009-9200-1 Due to typographical error, this paper published online with incorrect data in Table 2. The corrected of version Table 2 is as follows. Table 2 Comparison of discriminating power and degeneracy of

proposed TIs using various structures with three, four and five selleck inhibitor vertices   ξc A ξc \( ^SA \xi_3^\textc \) \( ^SA \xi_4^\textc \) \( ^SA \xi_5^\textc \) \( ^SA \xi_6^\textc \) \( ^SA \xi_7^\textc \) For three vertices  Minimum value 6 3 1.25 5 3 2 1.5  Maximum value 6 12 12 48 48 48 48  Ratio 1:1 1:4 1:9.6 1:9.6 1:16 1:24 1:32  Degeneracy ½ 0/2 0/2 0/2 0/2 0/2 0/2 For four vertices  Minimum value 9 3.33 0.3 6.67 2.89 1.30 0.60  Maximum value 16 108 108 2916 2916 2916 2916  Ratio 1:1.78 1:32.4 1:360.7 1:437.4 1:1009.38 1:2249 1:4870  Degeneracy 1/6 0/6 0/6 0/6 0/6 0/6 0/6 For five vertices

 Minimum value 12 4.33 0.32 12.67 5.39 2.42 1.08  Maximum value 28 1280 1280 327680 327680 327680 327680  Ratio 1:2.34 1:295.4 1:4063 1:25869 1:60807 1:135332 1:303407  Degeneracy 11/21 0/21 0/21 0/21 0/21 0/21 1/21 Degeneracy = Number of compounds having same values/total number of compounds

with same number GDC-0994 in vitro of vertices”
“Introduction The genus Actinomyces is an important group of microbes due to their ability to produce commercially valuable secondary metabolites (Abbas and Edwards, 1990; Vučetić et al., 1994; Okami and Hotta, 1988; Prosser and Tough, 1991). The actinomycete Streptomyces hygroscopicus produces a range of polyene antibiotics compounds depending on environmental and nutritional conditions (Vučetić et al., 1994; Karadžić et al., 1991). To make the production of the antibiotic feasible, it is necessary to develop the optimum production, which includes among the other conditions, formation of chemically defined media. There have been some investigations about MycoClean Mycoplasma Removal Kit different nitrogen and carbon sources on growth and production (Abbas and Edwards, 1990; Lee et al., 1997; de Queiroz Sousa et al., 2001; Tripathi et al., 2004), but no data are available about the influence of Schiff base. In the present study, an extensive study has been made on the isatin-Schiff bases as a nitrogen source in chemically defined media on antibiotic production by Streptomyces hygroscopicus as well as on soil morphology. Materials and methods Organism, media, and growth condition A strain Streptomyces hygroscopicus was isolated from a soil sample from Vojvodina, Serbia (Vučetić et al., 1994; Karadžić et al., 1991).

For slide orientation and as additional tissue control, normal pancreas tissue (punched in duplicate) was also included in each TMA. TMA block 2 consisted of the following specimens: 6 node positive breast ductal carcinoma, 6 node negative breast ductal carcinoma, 2 ductal carcinoma in-situ with matched, 2 benign breast tissues as benign controls from the 2 the patients with ductal carcinoma in-situ, and 1 benign breast tissue from a breast reduction surgery. The invasive carcinomas were punched in triplicates. The in-situ carcinoma cases and the matched benign controls were punched in duplicates. TMA

block 3 consisted of the following specimens: 38 invasive ductal carcinoma patients (40 cases punched but 2 had no tumor on the TMA), 3 patients with ductal BMN 673 purchase carcinoma in-situ, and 3 normal breast tissues from breast reduction surgeries. Immunohistochemistry For the immunohistochemical analysis, 5 μm thick find more sections were cut, warmed to 60°C, de-paraffinized in xylene, and then rehydrated with graded ethanol. This step was followed by antigen exposure for 20 minutes in heated antigen check details retrieval solution and then the endogenous peroxide activity was inactivated

by treating with 0.3% H2O2 in methanol. The sections were blocked for 20 min in protein block (normal goat serum in PBS, BioGenex), and incubated with primary antibodies against ODC (Sigma #O1136, diluted 1:500); eIF4E (monoclonal, BD Transduction Laboratories, 1:600 dilution), c-Myc (Abcam, ab31426, 1:500 dilution), TLK1B (from De Benedetti [21], 1:700 dilution), VEGF (Ab-3, JH121, NeoMarker-Labvision, 1:60 dilution), and cyclin D1 (Cell Signaling #2926, 1:100 dilution)

for 1 h using an automated stainer Mirabegron (BioGenex I6000 Automated Staining System, San Ramon, CA). Samples were rinsed 5 times in washing buffer, and incubated in secondary antibody (MultiLink-BioGenex Super Sensitive Link-Label IHC Detection System) for 30 min. Samples were rinsed 3 times in wash buffer, and then incubated in horseradish peroxidase label (BioGenex) for 15 min. Samples were rinsed 3 times in wash buffer and then incubated in diaminobenzidine (Dako Cytomation Liquid DAB Substrate Chromogen System) for 5 min. Samples were rinsed 3 times in wash buffer and counterstained in hematoxylin (Dako Cytomation Automation Hematoxylin) for 2 min. Western Blot Specimens were analyzed for eIF4E and TLK1B as previously described [22, 23]. Briefly protein lysates from each specimen (5–10 μg protein) were separated using 12% denaturing gel Tris-HCL polyacrylamide gel electrophoresis [24]. The proteins were then electroblotted on a nylon membrane (Immun-Blot PVDF, Bio-Rad Laboratory, Hercules, CA) [25]. The membranes were blocked in 3% nonfat milk overnight.

Nucleic Acids Res 2004, 32:1792–1797.PubMedCrossRef 76. Bruen TC, Philippe H, Bryant D: A simple and robust statistical test for detecting the presence of recombination. Genetics 2006, 172:2665–2681.PubMedCrossRef 77. Felsenstein J: PHYLIP (Phylogeny Inference Package) version 3.5c. 1993. 78. Stamatakis A: RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics (Oxford, England) 2006, 22:2688–2690.CrossRef 79. Rannala B, Yang Z: Probability distribution of molecular evolutionary trees: a new method of phylogenetic inference.

J Mol Evol 1996, 43:304–311.PubMedCrossRef 80. Yang Z, Rannala B: Bayesian phylogenetic inference using DNA sequences: a Markov AZD5153 mw Chain Monte Carlo Method. Mol Biol Evol 1997, 14:717–724.PubMedCrossRef 81. selleck kinase inhibitor Ronquist F, Huelsenbeck JP: MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics (Oxford, England) 2003, 19:1572–1574.CrossRef 82. Swofford DL: PAUP*. 2002. 83. Kimura M: A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 1980, 16:111–1120.PubMedCrossRef 84. Darling ACE, Mau B, Perna NT: progressiveMauve: multiple genome alignment with gene gain, loss and rearrangement. PLoS One 2010, 5:e11147.PubMedCrossRef 85. Darling

learn more ACE, Mau B, Blattner FR, Perna NT: Mauve: multiple alignment of conserved genomic sequence with rearrangements.

Genome Res 2004, 14:1394–1403.PubMedCrossRef 86. Tatusov RL, Fedorova ND, Jackson JD, et al.: The COG database: an updated version includes eukaryotes. BMC Adenosine triphosphate Bioinforma 2003, 4:41.CrossRef 87. Sayers EW, Barrett T, Benson DA, et al.: Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 2009, 37:D5-D15.PubMedCrossRef Authors’ contributions LMR participated in the design and coordination of the study, acquired data, carried out the analysis and drafted the manuscript. AG participated in the design and coordination of the study, acquired data and critically revised the manuscript. MLA participated in the design and coordination of the analyses. CS participated in the design and coordination of the study and critically revised the manuscript, while SR participated in the design and coordination and critically revised the manuscript. AB conceived the study, participated in the design and coordination of the study, drafted and critically revised the manuscript. All authors read and approved the final manuscript.”
“Background Lyme borreliosis, caused by the spirochetal bacterium Borrelia burgdorferi, remains the most common vector-borne disease in the United States [1]. B. burgdorferi is transmitted either to its natural mammalian host(s) or inadvertently to humans through the bite of an infected Ixodes tick vector [2, 3]. In humans, B.

At a concentration of 108  M. anisopliae spores/g, Selleckchem PND-1186 an average of 12.3 ± 2.0 termites remained in the treated sand tubes while 23.0 ± 5.9 remained in the controls, but the difference was not significant. With some treatments, ex. I. fumosorosea and M. anisopliae in soil and sawdust, more termites remained in treated tubes after 24 h exposure than in control tubes, but none of the treatments

was significantly different from its respective control. Based on these data the fungi I. fumosorosea and M. anisopliae were shown to not be repellent to FST in sand, soil or sawdust. Table 1 Mean (±SEM) number of C. formosanus in a paired MK-8931 mw choice test where tubes were filled with substrate treated with fungal spores at the indicated concentrations, after 24 h exposure   Number of termite in tubes Treatment Treated Control I. fumosorosea 10 6 spores/g Sand 36.3 ± 13.5a* 60.2 ± 17.3a Soil 96.1 ± 11.1a 77.4 ± 10.6a Sawdust 92.5 ± 9.6a 72.8 ± 10.2a I. fumosorosea 10 8 spores/g Sand 46.0 ± 6.5a 50.8 ± 4.5a Soil 71.3 ± 16.0a 82.7 ± 17.1a Sawdust 49.3 ± 9.8a 56.1 ± 9.7a M. anisopliae 10 6 spores/g Sand 23.9 ± 5.5a 45.0 ± 13.0a Soil 82.3 ± 7.4a 76.0 ± 7.0a Sawdust 93.4 ± 9.2a 62.7 ± 9.3a M. anisopliae 10 8 spores/g Sand 12.3 ± 2.0a 23.0 ± 5.9a Soil 78.3 ± 12.6a 77.6 ± 12.8a Sawdust 31.0 ± 3.9a MLN2238 36.5 ± 4.5a * Values with the same letter

are not significantly different, P ≤ 0.05. When termites were exposed to B. thuringiensis strain 33679 the effect of both cells and spores was determined. All treatments were applied at a concentration of 109 propagules/g. With cells in sand or soil, the treated tube values were not significantly different from the controls (Table 2). With cells in sawdust, the difference was highly significant with only 29.3 ± 6.6 termites remaining

in the treated tubes compared with 130.8 ± 9.6 in the control tubes (Paired choice t-test). These values indicated that the B. thuringiensis cells were strongly repellent to FST in sawdust. FST were also exposed to a B. thuringiensis culture in which the cells had formed spores due to nutrient deprivation. Neither the soil nor sawdust very treatments were significantly different from the respective controls, indicating that B. thuringiensis in these treatments was not repellent to FST. B. thuringiensis was also tested for its effect on FST as a mixture of cells and spores. The culture was incubated in media with a diluted nutrient source and the formation of spores was observed microscopically over time. The termites were exposed when the culture was as close as possible to 50% vegetative cells and 50% spores. In sand, the cell/spore treatment resulted in significantly more termites remaining in the control tubes compared with the treated tubes. Neither the soil or sawdust treatments were significantly different from the controls. Table 2 Mean (±SEM) number of C.