Anticancer Drugs 2005,16(5):551–557.CrossRef 21. Alexander BL, Ali RR, Alton EW, Bainbridge JW, Braun S, Cheng SH, Flotte TR, Gaspar HB, Grez M, Griesenbach U, Kaplitt MG, Ott MG, Seger R, Simons M, Thrasher AJ, Thrasher AZ, Ylä-Herttuala S: Progress and prospects: gene therapy clinical trials

(part 1). Gene Ther 2007, 20:1439–1447. 22. Guinn BA, Mulherkar R: International progress in cancer gene therapy. Cancer Gene Ther 2008, 12:765–775.CrossRef 23. Scherer L, Rossi JJ, Weinberg MS: Progress and prospects: RNA-based therapies for treatment of HIV infection. Gene Ther 2007, 14:1057–1064.CrossRef 24. Androic I, Krämer A, Yan R, Rödel F, Gätje R, Kaufmann M, Strebhardt K, Yuan J: Targeting cyclin B1 inhibits GSK872 molecular weight proliferation and sensitizes breast cancer cells to taxol. BMC Cancer 2008, 8:391.CrossRef 25. Brun A, Albina E, Barret T, Chapman DA, Czub M, Dixon LK, Keil GM, Klonjkowski B, Le Potier MF, Libeau G, Ortego J, Richardson

J, Takamatsu HH: Antigen delivery systems for veterinary vaccine development. Viral-vector based delivery systems. Vaccine 2007, 26:6508–6528.CrossRef 26. Nafee N, Taetz S, Schneider M, Schaefer UF, Lehr CM: Chitosan-coated PLGA nanoparticles for DNA/RNA delivery: effect of the formulation parameters on complexation and transfection of antisense oligonucleotides. Nanomedicine 2007, 3:173–183.CrossRef 27. Geusens B, Lambert J, De Smedt SC, Buyens K, Sanders NN, Van Gele M: Ultradeformable selleck compound cationic liposomes for delivery of small interfering RNA (siRNA) into human primary melanocytes. J Control Release 2009, 133:214–220.CrossRef 28. Zhou J, Wu J, Hafdi N, Behr JP, Erbacher P, Peng L: PAMAM dendrimers for efficient siRNA delivery and potent gene silencing. Chem Commun 2006, 22:2362–2364.CrossRef 29. Park TG, Jeong JH, Kim SW: Current status of polymeric gene delivery

systems. Adv Drug Deliv Rev 2006, 58:467–486.CrossRef 30. Son S, Kim WJ: Biodegradable nanoparticles modified by branched polyethylenimine for plasmid DNA delivery. Biomaterials 2010, 31:133–143.CrossRef 31. Blum JS, Saltzman WM: High loading efficiency and tunable release of plasmid next DNA encapsulated in submicron particles fabricated from PLGA conjugated with poly-L-lysine. J Control Release 2008, 129:66–72.CrossRef 32. Dewey RA, Morrissey G, Cowsill CM, Stone D, Bolognani F, Dodd NJ, Southgate TD, Klatzmann D, Lassmann H, Castro MG, Löwenstein PR: Chronic brain inflammation and persistent herpes simplex virus 1 thymidine kinase expression in survivors of syngeneic glioma treated by adenovirus mediated gene therapy: implications for clinical trials. Nat Med 1999, 11:1256–1263.CrossRef 33. Huang H, Yu H, Tang G, Wang Q, Li J: Low molecular weight polyethylenimine cross-linked by 2-hydroxypropyl-gamma-cyclodextrin coupled to peptide targeting HER2 as a gene delivery vector. Biomaterials 2010,31(7):1830–1838.CrossRef 34.

Infect Immun 1983,41(3):1212–1216.PubMed 12. Paton JC, Rowan-Kelly B, Ferrante A: Activation of human complement by the pneumococcal toxin pneumolysin. Infect Immun 1984,43(3):1085–1087.PubMed 13. Boulnois GJ, Paton JC, Mitchell TJ, Andrew PW: Structure and function of pneumolysin, the multifunctional, thiol-activated

toxin of Streptococcus pneumoniae. Mol Microbiol 1991,5(11):2611–2616.PubMedCrossRef 14. Hammerschmidt S, Bethe G, Remane PH, Chhatwal GS: Identification of pneumococcal surface protein A as a lactoferrin-binding protein of Streptococcus pneumoniae. Infect Immun 1999,67(4):1683–1687.PubMed 15. Janulczyk R, Iannelli F, Sjoholm AG, Pozzi G, Bjorck L: Hic, a novel surface protein of Streptococcus pneumoniae that interferes with complement function. J Biol Chem 2000,275(47):37257–37263.PubMedCrossRef 16.

Romanello V, Marcacci M, Dal Molin F, Moschioni BMN 673 cost M, Censini S, Covacci A, Baritussio AG, Montecucco C, Tonello F: Cloning, expression, purification, and characterization of Streptococcus pneumoniae IgA1 protease. Protein Expr Purif 2006,45(1):142–149.PubMedCrossRef 17. King SJ, Hippe KR, Gould JM, Bae D, Peterson S, Cline RT, Fasching C, Janoff EN, Weiser JN: Phase variable desialylation of host proteins that bind to Streptococcus pneumoniae in C646 molecular weight vivo and protect the airway. Mol Microbiol 2004,54(1):159–171.PubMedCrossRef 18. Holmes AR, McNab R, Millsap KW, Rohde M, Hammerschmidt S, Mawdsley JL, Jenkinson HF: The pavA gene of Streptococcus pneumoniae encodes a fibronectin-binding protein that is essential for virulence. Mol Microbiol 2001,41(6):1395–1408.PubMedCrossRef 19. Zhang JR, Mostov KE, Lamm ME, Nanno M, Shimida S, Ohwaki M, Tuomanen E: The polymeric immunoglobulin receptor translocates pneumococci across human nasopharyngeal epithelial cells. Rutecarpine Cell 2000,102(6):827–837.PubMedCrossRef 20. Anderton JM, Rajam G, Romero-Steiner S, Summer S, Kowalczyk AP, Carlone GM, Sampson JS, Ades EW: E-cadherin is a receptor for the common protein

pneumococcal surface adhesin A (PsaA) of Streptococcus pneumoniae. Microb Pathog 2007,42(5–6):225–236.PubMedCrossRef 21. Lu L, Ma Y, Zhang JR: Streptococcus pneumoniae recruits complement factor H through the amino terminus of CbpA. J Biol Chem 2006,281(22):15464–15474.PubMedCrossRef 22. Hammerschmidt S, Tillig MP, Wolff S, Vaerman JP, Chhatwal GS: Species-specific binding of human secretory component to SpsA protein of Streptococcus pneumoniae via a hexapeptide motif. Mol Microbiol 2000,36(3):726–736.PubMedCrossRef 23. Bergmann S, Rohde M, Chhatwal GS, Hammerschmidt S: alpha-Enolase of Streptococcus pneumoniae is a plasmin(ogen)-binding protein displayed on the bacterial cell surface. Mol Microbiol 2001,40(6):1273–1287.PubMedCrossRef 24. Bergmann S, Rohde M, Hammerschmidt S: Glyceraldehyde-3-phosphate dehydrogenase of Streptococcus pneumoniae is a surface-displayed plasminogen-binding protein. Infect Immun 2004,72(4):2416–2419.PubMedCrossRef 25.

PubMedCrossRef 10. Vaupel P, Mayer A: Hypoxia in cancer: significance EPZ015938 solubility dmso and impact on clinical outcome. Cancer Metastasis Rev 2007, 26:225–239.PubMedCrossRef 11. Yao LQ, Feng YJ, Ding JX, Jing HM, Xu CJ, Chen SF, Su M, Yin LH: Characteristics and differentiated mechanism of vascular endothelial cells-like derived from epithelial ovarian cancer cells induced by hypoxia. Int J Oncol 2007, 30:1069–1075.PubMed 12. Su M, Feng YJ, Yao LQ, Cheng

MJ, Xu CJ, Huang Y, Zhao YQ, Jiang H: Plasticity of ovarian cancer cell SKOV3ip and vasculogenic mimicry in vivo. Int J Gynecol Cancer 2008, 18:476–486.PubMedCrossRef 13. Yao LQ, Feng YJ, Ding JX, Xu CJ, Jin HY, Yin LH: [Primary study of vasculogenic mimicry induced by hypoxia in epithelial ovarian carcinoma]. Zhonghua Fu Chan Ke Za Zhi 2005, 40:662–665.PubMed 14. Zhu Y, Lin JH, Liao HL, Friedli O Jr, Verna L, Marten NW, Straus DS, Stemerman MB: LDL induces transcription factor activator protein-1 in human endothelial cells. Arterioscler Thromb Vasc Biol 1998, 18:473–480.PubMed 15. Sood AK, Seftor EA, Fletcher MS, Gardner LM, Heidger PM, Buller RE, Seftor RE, Hendrix MJ: Molecular determinants of ovarian cancer plasticity. Am J Pathol 2001, 158:1279–1288.PubMedCrossRef 16. Hopfl G, Wenger RH, Ziegler U, Stallmach T, Gardelle O, Achermann R, Wergin M, Kaser-Hotz B, Saunders HM, WIlliams KJ, Stratfrod IJ, Gassmann

M, Desbaillets I: Rescue of hypoxia-inducible factor-1alpha-deficient tumor growth by wild-type cells is independent of vascular endothelial growth factor. Cancer Res 2002, 62:2962–2970.PubMed 17. Zhi X, Chen S, Zhou P, Shao Z, CBL0137 nmr Wang L, Ou Z, Yin L: RNA interference of ecto-5′-nucleotidase (CD73) inhibits human breast cancer cell growth and invasion. Clin Exp Metastasis 2007, 24:439–448.PubMedCrossRef 18. Weljie AM, Jirik FR: Hypoxia-induced metabolic shifts in cancer cells:

Moving beyond the Warburg effect. Int J Biochem Cell Biol 2010, in press. 19. Maniotis AJ, Folberg R, Hess A, Seftor EA, Gardner LM, Pe’er J, Trent JM, Meltzer Immune system PS, Hendrix MJ: Vascular channel formation by human melanoma cells in vivo and in vitro: vasculogenic mimicry. Am J Pathol 1999, 155:739–752.PubMedCrossRef 20. Sood AK, Fletcher MS, Coffin JE, Yang M, Seftor EA, Gruman LM, Gershenson DM, Hendrix MJ: Functional role of matrix metalloproteinases in ovarian tumor cell plasticity. Am J Obstet Gynecol 2004, 190:899–909.PubMedCrossRef 21. Liu JP, Li H: Telomerase in the ovary. Reproduction 2010, 140:215–222.PubMedCrossRef 22. Ozmen B, Duvan CI, Gumus G, Sonmezer M, Gungor M, Ortac F: The role of telomerase activity in predicting early recurrence of epithelial ovarian cancer after first-line chemotherapy: a prospective clinical study. Eur J Gynaecol Oncol 2009, 30:303–308.PubMed 23. Lubin J, Markowska J, Markowska A, Stanislawiak J, Lukaszewski T: Activity of telomerase in ovarian cancer cells. Clinical implications. Clin Exp Obstet Gynecol 2009, 36:91–96.PubMed 24.

The remaining high quality sequences were taxonomically identified using the Classifier tool at a 60% confidence level. The classifier

output was then used for analysis of similarities and difference between herds (Additional files 1, 2, 3, 4, 5). For analysis of the data at the genus level, all genera with fewer than 5 representatives were dropped from the analysis. To identify members of the family Pasteurellaceae and genus Streptococcus MLN2238 to the lowest possible phylogenetic level, we obtained all the 138 near full-length type sequences from family Pasteurellaceae and genus Streptococcus from RDP release 10.22 (August 2010). We also added sequence AF486274 (“”Actinobacillus porcitonsillarum”"). BI 6727 in vitro These 139 sequences were aligned by the Infernal aligner [16] trained by RDP [17].

The final reference set contained the region corresponding to the 454 FLX amplicon (E. coli position 578 to 784) sliced from the alignment. To determine the nearest neighbor, the 454 FLX sequences passing the RDP Pyro initial filtering were aligned by the Infernal aligner and the distance between each FLX sequence and reference sequences was calculated. The reference sequence with the closest distance was reported. In case of tie, all the reference sequences were reported. Statistical analysis For the statistical analyses of sequences, we used a 0.03% cutoff value for clustering. This is consistent with previous analyses

of 454 data [18] as well as the historical value frequently used over the past 15 years [19, 20]. Similarly we used this cutoff in evaluating members of family Pasteurellaceae and genus Streptococcus. For comparative statistical analyses, aligned sequences were clustered using the RDP Complete Linkage Clustering Tool and the resulting cluster files were used to calculate Jaccard and Sørensen indices [17]. Lepirudin For comparative statistical analyses, aligned sequences were clustered using the RDP Complete Linkage Clustering Tool and the resulting cluster files were used to calculate Jaccard and Sørensen indices [17]. Cluster files were also reformatted with the EstimateS Formatter Tool through the RDP website. Principle component analysis followed by centroid calculations with a 95% confidence limit were performed in R (version 2.10; http://​www.​r-project.​org/​) with Vegan package (http://​vegan.​r-forge.​r-project.​org) using the EstimateS formatted files. Chao 1 was calculated using the cluster files derived from each sample and from merged samples for herds using the RDP Pyrosequencing Pipeline. Simpson’s Diversity index was calculated with MOTHUR [21]. Results Community DNA was isolated from whole tonsil tissue (Pigs A-M) or tonsil brushings (Pigs J-M) as described in Methods. Tonsil tissue samples were collected in spring 2007 from two different herds, and again in spring 2009 from Herd 1.

Figure 8 Efficient P53 knockdown in cancer cells increases cellular sensitivity to TAI-1. (A) A549 and HCT116 cells which carry wild-type P53 were transfected with control siRNA (siControl) or P53 siRNA (siP53) for 24 hours and treated with TAI-1 (starting dose 100 μM, 3x serial dilution), incubated for 48 hours and analyzed for viability with MTS. Cellular sensitivity is expressed in GI50 (nM) and RNA from transfected cells were analyzed

for P53 RNA level by quantitative real time PCR. SiP53 reduced GI50s of compound in cells. (B) Selected cell lines which carry wild type P53 (A549, HCT116, ZR-75-1, U2OS) or mutated P53 (HeLa, as control) were transfected with siP53, treated with TAI-1 and analyzed for viability with MTS. Cellular sensitivity is expressed as% growth inhibition and cell lysates from transfected cells were collected and P53 protein levels click here determined by western https://www.selleckchem.com/products/netarsudil-ar-13324.html blotting. Differential Hec1 expression in clinical cancer

subtypes Genome-wide expression profile analysis has shown that Hec1 is upregulated in lung, colorectal, liver, breast, and brain tumors and that Hec1 expression correlates with tumor grade and prognosis [4, 9]. To determine whether HEC1 expression varies between cancer subtypes from the same tissue or organ, the gene expression data of NDC80 (HEC1) between adenocarcinoma and squamous carcinoma was studied for lung cancer. As shown in Figure 9A, NDC80 expression is significantly higher in squamous cell carcinoma of lung than adenocarcinoma in all three independent datasets. One way hierarchical cluster analysis consistently showed that NDC80, NEK2, NUF2 and SPC25 were reproducibly clustered together in three different gene expression datasets (Figure 9B). All these four genes showed higher expression in squamous cell carcinoma of lung.

The results indicate that different subtypes of lung cancer could respond differently to the treatment of Hec1 inhibitor. The predictability of response to Hec1-targeted treatment according to Hec1 associated gene expression remains to be further studied; however, our results suggest Cell press such consideration for HEC1 or related gene expression may be an important factor in the design of personalized Hec1-targets treatment of cancers. Figure 9 Differential expression of NDC80 (Hec1) and genes associated with NDC80 between subtypes of non-small cell lung cancer. (A) NDC80 (Hec1) (Affymetrix Probeset ID 204162_at) expression between adenocarcinoma and squamous cell carcinoma of lung in three different independent datasets (GSE8894, GSE3141 and GSE37745). The unit of Y axis is logarithm of expression intensity to the base 2. ANOVA was used to compare these two subtypes of NSCLC.

Infect Immun 2007, 75:4710–4718.PubMedCrossRef 15. Netea MG, Gijzen K, Coolen N, Verschueren I, Figdor C, Van der Meer JW, Torensma R, Kullberg BJ: Human dendritic cells are less potent at killing Candida albicans than both monocytes and macrophages. Microbes Infect 2004, 6:985–989.PubMedCrossRef 16. Shao X, Mednick A, Alvarez M, van Rooijen N, Casadevall A, Goldman DL: An innate immune system cell is a major determinant

of species-related susceptibility differences to fungal pneumonia. J Immunol 2005, 175:3244–3251.PubMed 17. Zaragoza O, Alvarez M, Telzak A, Rivera J, Casadevall A: The relative susceptibility of mouse strains to pulmonary Cryptococcus neoformans infection SRT2104 is associated with pleiotropic differences in the immune response. Infect Immun 2007, 75:2729–2739.PubMedCrossRef 18. Colonna M, Pulendran B, Iwasaki A: Dendritic cells at the https://www.selleckchem.com/products/AZD8931.html host-pathogen interface. Nat Immunol 2006, 7:117–120.PubMedCrossRef 19. Gacser A, Salomon S, Schafer W: Direct transformation of a clinical isolate of Candida parapsilosis using a dominant selection marker. FEMS Microbiol Lett 2005, 245:117–121.PubMedCrossRef

20. Eissenberg LG, Goldman WE, Schlesinger PH: Histoplasma capsulatum modulates the acidification of phagolysosomes. J Exp Med 1993, 177:1605–1611.PubMedCrossRef 21. Shi L, Albuquerque PC, Lazar-Molnar E, Wang X, Santambrogio L, Gacser A, Nosanchuk JD: A monoclonal antibody to Histoplasma capsulatum alters the intracellular fate

of the fungus in murine macrophages. Eukaryot Cell 2008, 7:1109–1117.PubMedCrossRef 22. Fernandez-Arenas E, Bleck CK, Nombela C, Gil C, Griffiths G, Diez-Orejas R: Candida albicans actively modulates intracellular membrane trafficking in mouse macrophage PI-1840 phagosomes. Cell Microbiol 2009, 11:560–589.PubMedCrossRef 23. Marcil A, Gadoury C, Ash J, Zhang J, Nantel A, Whiteway M: Analysis of PRA1 and its relationship to Candida albicans- macrophage interactions. Infect Immun 2008, 76:4345–4358.PubMedCrossRef 24. Lazzaro BP, Rolff J: Immunology. Danger, microbes, and homeostasis. Science 2011, 332:43–44.PubMedCrossRef 25. Matzinger P: The danger model: a renewed sense of self. Science 2002, 296:301–305.PubMedCrossRef 26. Strieter RM, Kunkel SL, Showell HJ, Remick DG, Phan SH, Ward PA, Marks RM: Endothelial cell gene expression of a neutrophil chemotactic factor by TNF-alpha, LPS, and IL-1 beta. Science 1989, 243:1467–1469.PubMedCrossRef 27. Liu AY, Destoumieux D, Wong AV, Park CH, Valore EV, Liu L, Ganz T: Human beta-defensin-2 production in keratinocytes is regulated by interleukin-1, bacteria, and the state of differentiation. J Invest Dermatol 2002, 118:275–281.PubMedCrossRef Competing interests The authors declare that they have no competing interests. Authors’ contributions FK, TN and AG carried out the phagocytosis and QRT-PCR studies, participated in the protein measurement experiments. ZSH, IN and AG participated in the infection studies.

J Am Chem Soc 2002, 124:10596.CrossRef 17. Sönnichsen C, Reinhard BM, Liphardt J, Alivisatos AP:

A molecular ruler based on plasmon coupling of single gold and silver nanoparticles. Nat Biotechnol 2005, 23:741.CrossRef 18. Jain PK, Huang XH, El-Sayed IH, El-Sayed MA: Noble metals on the nanoscale: optical and photothermal properties and some applications Ilomastat in vivo in imaging, sensing, biology, and medicine. Accounts Chem. Res 2008, 41:1578.CrossRef 19. Jain PK, Huang X, El-Sayed IH, El-Sayed MA: Review of some interesting surface plasmon resonance-enhanced properties of noble metal nanoparticles and their applications to biosystems. Plasmonics 2007, 2:107.CrossRef 20. Zhang JZ, Noguez C: Plasmonic optical properties and applications of metal nanostructures. Plasmonics 2008, 3:127.CrossRef 21. Lal

S, Clare SE, Halas NJ: Nanoshell-enabled photothermal cancer therapy: impending clinical impact. Accounts Chem Res 1842, 2008:41. 22. Huang X, El-Sayed IH, Qian W, El-Sayed MA: Cancer cell imaging and photothermal therapy in the near-infrared region by using gold nanorods. J Am Chem Soc 2006, 128:2115.CrossRef 23. Itoh T, Hashimoto K, Ozakia Y: Direct demonstration for changes in surface plasmon resonance induced by surface-enhanced Raman scattering quenching of dye molecules adsorbed on single Ag nanoparticles. Appl Phys Lett 2003, 83:2274.CrossRef 24. Xu HX, Bjerneld EJ, Käll M, Börjesson L: Spectroscopy of single hemoglobin molecules by surface enhanced Belnacasan concentration Raman scattering. Phys Rev Lett 1999, 83:4357.CrossRef 25. Kondo T, Nishio K, Masuda H: Surface-enhanced Raman scattering in multilayered Au nanoparticles in anodic porous alumina matrix. Appl Phys Exp 2009, 2:32001.CrossRef 26. Ji N, Ruan WD, Wang CX: Fabrication of silver decorated Baf-A1 nmr anodic

aluminum oxide substrate and its optical properties on surface-enhanced Raman scattering and thin film interference. Langmuir 2009, 25:11869.CrossRef 27. Nie S, Emory SR: Probing single molecules and single nanoparticles by surface-enhanced Raman scattering. Science 1997, 275:1102.CrossRef 28. Anger P: Enhancement and quenching of single-molecule fluorescence. Phys Rev Lett 2006, 96:113002.CrossRef 29. Kühn S, Håkanson U, Rogobete L, Sandoghdar V: Enhancement of single-molecule fluorescence using a gold nanoparticle as an optical nanoantenna. Phys Rev Lett 2006, 97:17402.CrossRef 30. Le Ru EC, Etchegoin PG, Grand J, Félidj N, Aubard J, Lévi G: Mechanisms of spectral profile modification in surface-enhanced fluorescence. J Phys Chem C 2007, 111:16076.CrossRef 31. Maier SA, Brongersma ML, Kik PG, Meltzer S, Requicha AAG, Atwater HA: Plasmonics—a route to nanoscale optical devices. Adv Mater 2001, 13:1501.CrossRef 32. Schuller JA, Barnard ES, Cai WS, Jun YC, White JS, Brongersma ML: Plasmonics for extreme light concentration and manipulation. Nat Mater 2010, 9:193.CrossRef 33.

The manufacturer’s software and Adobe Photoshop were used for image processing. Suppressor mutagenesis For transposon mutagenesis, biparental matings were set up between the E. coli donor (S17-1-λpir/pLM1) and the P. aeruginosa recipient strain (ZK lasR mutant) as described [52]. The suicide plasmid pLM1 carries NVP-BGJ398 in vitro a miniTn5 transposon. The transposon insertion

mutants were selected on LB agar plates containing gentamicin (30 μg/ml) and nalidixic acid (20 μg/ml). Colonies were picked manually and patched onto rectangular LB plates containing gentamicin (30 μg/ml) in a 96-well format. Plates were incubated at 37°C for one day and then replica-plated onto rectangular Congo red plates using a 96-well-pin replicator. The ZK wild-type and the lasR mutant were included as controls. These plates were incubated for 3- 5 days at 37°C. Candidate revertants exhibiting a smooth colony morphology identical to the wild-type were streaked for isolated ACY-1215 colonies and subjected to a second screen. This screen involved performing the original colony biofilm assay as described earlier. Mutants which again showed a smooth phenotype were considered to be true revertants. Mapping of transposon insertions Genomic DNA was isolated from the selected transposon mutants (Qiagen PUREGENE kit) and was digested with NcoI. The transposon does not

contain an NcoI restriction site and has an R6K origin of replication. The digested DNA was self-ligated with T4 DNA ligase (New England Biolabs) and electroporated into chemically competent E. coli S17-1/λpir [43]. Plasmid DNA was isolated from gentamicin-resistant colonies and was sequenced using the Tn5 specific primer tnpRL17-1 [53]. Transposon insertions were mapped by comparing sequences to a Pseudomonas protein database using BlastX. Overexpression

of pqsA-E The appropriate strains were transformed with plasmid pLG10 [24] all and pRG10 carrying the pqsA-E operon and pqsA-D operon under the control of native and constitutive promoters, respectively, or with pUCP18 [47], the parent vector from which pLG10 and pRG10 were derived. Thin-layer chromatography (TLC) Samples for TLC analysis were prepared from 3-5 day-old colonies. Two colonies of each strain grown on the same plate were cut out from the agar with minimum possible agar contamination. One colony was used for total protein estimation and the other for AQ extraction. Total protein was estimated by Bradford assay [49] as described earlier for β-galactosidase measurements. For AQ extraction, a colony was harvested and suspended in 5 ml methanol, homogenized with a tissue tearor, and allowed to stand for 10 min. The suspension was centrifuged for 30 min at 4000 r.p.m. at 4°C. The supernatant was filtered through a 0.2 μM syringe filter and the filtrate was collected in glass vials prewashed with acetone.

It is clear that the lowest coefficient of variation and, therefore, lowest polydispersity were found for the SIPPs synthesized with the TDA and DDA, in agreement with the qualitative analysis of the TEM images. It should be noted, though, that the DDA used to synthesize the DDA-SIPPs was corrosive and corroded part of the inside of the septum used with the reflux apparatus. For this reason, the SIPPs synthesized with TDA (TDA-SIPPs) appear to be a better option, striking an appropriate balance between ZD1839 solubility dmso the safety aspects of synthesis and delivering the lowest polydispersity of the final nanoparticles synthesized. learn more Table 1 Structural characterization of SIPPs Value Description Units 18SIPP30 18SIPP60 16SIPP30 16SIPP60 14SIPP30 14SIPP60 12SIPP30 12SIPP60 L Chain length – 18 18 16 16 14 14 12 12 t Reflux time min 30 60 30 60 30 60 30 60 d Diameter nm 11.29 ± 3.22 7.20 ± 1.81 6.83 ± 1.34 5.14 ± 2.13 7.34 ± 1.22 6.14 ± 1.67 7.92 ± 1.29 7.34 ± 1.12 CV Coefficient of variation % 28.49 25.1 19.6 41.5 16.6 27.3 16.3 15.3 V p Particle volume cm3 1.95 × 10−18 1.96 × 10−19 1.67 × 10−19 7.12 × 10−20 2.07 × 10−19 1.21 × 10−19 2.60 × 10−19 2.07 × 10−19 S Surface area cm2 7.55 × 10−12 1.63 × 10−12 1.47 × 10−12 8.31 × 10−13 1.69 × 10−12 1.19 × 10−12 1.97 × 10−12 1.69 × 10−12 C p Suspension concentration mg/mL 9.33 ± 0.70 18.30 ± 0.00 5.36 ± 0.43 4.92 ± 0.13 4.29 ± 0.47 5.68 ± 0.43 3.22 ± 0.25 4.74 ± 0.40 C Fe Iron concentration mg/mL

0.369 ± 0.001 0.315 ± 0.0009 0.163 ± 0.001 0.151 ± 0.001 0.214 ± 0.00007 0.210 ± 0.001 0.080 ± 0.0004 0.139 ± 0.0007 C Pt Platinum concentration mg/mL 0.914 ± 0.001 1.068 ± 0.0007 0.332 ± 0.002 0.534 ± 0.002 0.583 ± 0.0003 Myosin 0.692 ± 0.001 0.205 ± 0.0002 0.463 ± 0.0007 N a Fe Iron atoms in 1.0 mL – 3.98 × 1018 3.40 × 1018 1.76 × 1018 1.63 × 1018 2.31 × 1018 2.26 × 1018 8.63 × 1017 1.50 × 1018 N SIPP Nanoparticles per milliliter SIPP/mL 1.04 × 1014 1.02 × 1015 4.96 × 1014 1.37 × 1015 5.90 × 1014 1.08 × 1015 1.71 × 1014 4.21 × 1014 AFe Atomic percent Fe at.% 58.5 50.8 63.1 49.8 56.2 51.4 57.7 51.1 APt Atomic percent Pt at.% 41.5 49.2 36.9 50.2 43.8 48.6 42.3 48.9 Fe/Pt Fe/Pt stoichiometry – 1.41 1.03 1.71 0.99 1.28 1.06 1.36 1.05 ρ FePt Density g/cm3 14.0 14.0 14.0 14.0 14.0 14.0 14.0 14.0 m p FePt Mass per particle g 2.73 × 10−17 2.74 × 10−18 2.