In this study, we first constructed a novel adenoviral vector tha

In this study, we first constructed a novel adenoviral vector that allowed constitutive expression of human GM-CSF and heat-induced expression of human IL-12. The pharmacokinetics of gene expression Selleck GS-9973 triggered by hyperthermia was then tested in cell culture and in an animal model.

Our study provided insights on tumor therapy by combining gene therapy with hyperthermia. Materials and methods Cell culture A549, a human non-small cell lung carcinoma cell line, and Hep3B, a human hepatoma cell line, were purchased from American Type Culture Collection. All cells were cultured in RPMI 1640 with 10% fetal bovine serum, 100 units/mL penicillin, and 100 μg/mL streptomycin at 37°C, 5% CO2. Adenovirus preparation The adenovirus used to establish constitutively high expression of human

GM-CSF and heat-inducible expression of human IL-12 was constructed according to established protocols [12] using commercially available plasmids (Microbix, Toronto, Canada). To construct the heat-inducible IL-12 expression cassette, cDNAs for both the p40 and p35 subunits of human IL-12 were inserted into the E1 region under control of the human hsp70B gene promoter [13, 14]. The p40 and p35 subunits were connected using an internal ribosome entry site sequence [15] so that both subunits could be transcribed under the control of the same promoter. The human GM-CSF expression cassette was constructed by placing the human GM-CSF gene under the control of a constitutively GF120918 active CMV-IE promoter in the E1 region [16] (see Figure 1). The completed adenovirus called Adcmv-GMCSF-HSP-IL12 will establish constitutive expression of human GM-CSF and heat-inducible expression of human IL-12. Large scale preparation of recombinant Adcmv-GMCSF-HSP-IL12 was accomplished as previously described [17]. The control vector is an adenovirus expressing GFP protein (Figure 1). Figure 1 A schematic diagram of adenovirus

used in this study. HSP70-pro: heat shock protein 70 gene promoter; hIL12: human interleukin 12; CMV-pro: CMV promoter; hGMCSF: granulocyte-macrophage colony-stimulating-factor gene; EGFP: enhanced GFP. In vitro heating experiments A549 and Hep3B cells were seeded in 24-well plates at a density of 6 × 104 cells/well. After cells were cultured for 24 hrs, 100, 500, and 1000vp (viral many particles) of Adcmv-hGMCSF-hsp-hIL12 virus were added into each well. see more Twenty-four hours later, the culture medium was replaced with 1 ml of fresh medium containing 2% FCS and cells were heated in a 45°C water bath for 45 min. Twenty-four hours later, the medium was collected for hGM-CSF and hIL-12 measurement and replaced with 1 ml of fresh medium. Cells were heated again (45°C, 45 min) and the medium was collected 24 hrs post heating. In vivo heating experiments Balb/C nude mice (BALB/c, nu/nu) weighing 20-22 g were provided by the animal center of Shanghai Biological Science Institution and housed in rooms under standard lighting conditions and temperature.

The advantages conferred by these traits have seen Si nanostructu

The advantages conferred by these traits have seen Si nanostructures being Selleckchem PR171 applied in nanoelectronics for transistor miniaturization [1–3], photovoltaics for exceptional light trapping [4–6], and photodetection for ultrahigh photoresponsivity [7]. Si nanostructures such as Si nanowires (SiNWs) have also enabled ultra-sensitivity to be realized in chemical and biological sensing [8], efficient thermoelectric performance [9], enhanced performance in Li-ion batteries [10], and nanocapacitor arrays [11]. Successful realization of Si-nanostructured devices on a manufacturing scale, however,

requires practical techniques of producing the nanostructures with controlled dimensions, patterns, crystalline structures, and electronic qualities. Metal-assisted chemical etching (MACE) or metal-catalyzed electroless etching (MCEE) is a simple technique first demonstrated by Peng et al., which can be used to generate high aspect ratio Si nanostructures [12, 13]. In this manuscript, this technique is referred to as MCEE because this provides a more explicit description of the process. Sidewall inclination common in reactive ion etching (RIE) [14] and scalloping SB431542 datasheet effects typical of deep reactive ion etching [15] are avoided in MCEE. The process does not require the complex precursors used in vapor-liquid-solid growth or chemical vapor deposition, and the expensive equipment

of inductive coupled plasma-RIE or DRIE. Properties such as doping level and type, crystal orientation, and quality are determined simply by the starting Si wafers. Approaches combining nanoscale FHPI clinical trial patterning techniques with MCEE have been reported. The combination allows more control over the order, diameter, and density dipyridamole of the Si nanostructures. This was demonstrated with

nanosphere lithography which is based on the self-assembly of a monolayer of nanospheres (e.g., polystyrene [16] or silica [17]) into ordered hexagonal close-packed arrays. However, ordering of the nanospheres and the resulting Si nanostructures are limited to domains. Huang et al. employed an anodic aluminum oxide (AAO) template and a Cr/Au evaporation step to define the mask for catalytic etching to form SiNWs [18]. While this is a simple and cost-effective method, the positions of the nanostructures are limited to short-ranged hexagonal arrangements, and large-scale production will likely be hampered by inefficient AAO template transfer to the Si substrate. Lately, block copolymer lithography has been paired with MCEE to produce highly dense Si nanostructure arrays. But a distribution of dimensions exists, and ordered arrangement is limited to small areas [19]. In order to fabricate Si nanostructures with various array configurations, cross-sectional shapes, and perfect ordering over large areas, interference lithography (IL) in combination with MCEE has been employed by Choi et al. [20].

Cambridge University Press, UK Lahav, N , White, D , and Chang,

Cambridge University Press, UK. Lahav, N., White, D., and Chang, S. (1978). Peptide formation in the prebiotic era: thermal condensation of glycine

in fluctuating clay environments. Science, 201: 67–69. Ponnamperuma, C., Shimoyama, A., and Friebele, E. (1982). Clay and the origin of life. Orig. Life OICR-9429 nmr Evol. Biosph., 12: 9–40. E-mail: [email protected]​de V.U.V. Irradiation of Interstellar Ice Analogs: A Potential Source for Prebiotic Molecules in Planetary Systems G. Danger1, P. de Marcellus1, Z. Djouadi1, J.B. Bossa2, T. Chiavassa2, L.d’Hendecourt1* 1 Astrochimie et Origines, Institut d’Astrophysique Spatiale, Orsay, France. 2Spectromatries et Dynamique Moléculaire, Physique des Interactions Ioniques et Moléculaires, Université de Provence, Marseille, France The study of astrophysical chemistry is an important task to understand matter evolutions in the Universe and notably evolution pathways from abiotic chemistry

in the interstellar medium (MIS) to prebiotic chemistry in planetary systems. In the dense interstellar medium, the major part of light elements (O,C,N) is adsorbed on interstellar grains. From a schematic point of view, these grains are formed with different layers which included ices of volatile compounds which surround residue of refractory carbon and a nucleus consisting of silicate compounds. The physical and chemical evolution Selleck AZD2281 of these grains is followed by parent body’s aggregation, the first step towards planetary formation. From experimental simulations of astrophysical environments in the laboratory, and particularly conditions see more of molecular ices formation, our aim is to understand the chemical evolution of these ices in order to retrace the chemical evolution toward complex molecule formation in the ISM (e.g. pathways for amino acid synthesis or their precursors). The first results obtained after ice analogs (e.g.

including H2O, CO, NH3, CH3OH…) irradiation have shown the formation of radicals and more complex molecules by infrared in situ analysis. The first step is thus to compare these data with astronomical observations in order to identify the importance of photochemical processes in astrophysical environments. After sample heating, radicals and molecules can rearrange to form a residue which includes complex organic molecules such as amino acids, detected after hydrolysis treatment of the samples (Bernstein et al., 2002; Muñoz-Caro et al., 2002; Nuevo et al., 2008). Without this treatment only very few amounts of amino acids are detected (Nuevo et al., 2008). This observation leads to the hypothesis that amino acids could be included in a complex structure which, after degradation, releases them during hydrolysis. Another possibility is that amino acids could come from precursors such as nitriles (Elesila et al, 2007). The last hypothesis is corroborated by the recent this website aminoacetonitrile detection in the ISM gas phase (Belloche et al., 2008).

The magnitude of increased fracture risk with anti-depressant use

The magnitude of increased fracture risk with anti-depressant use described here is in line with findings from other epidemiological studies [9, 15–17, 24]. Those studies that compared risk with SSRIs HSP inhibitor and TCAs [9, 15, 16] similarly reported no difference in risk. There is also evidence to support our observation of an increased risk during the initial period of exposure [15, 16]. Richards et al. [17] investigated fracture risk with SSRIs and reported a dose effect and

a sustained elevation in risk with prolonged use. Vestergaard et al. reported a dose-dependent increase in fracture risk for sedating TCAs and most SSRIs. Furthermore, they also found an association between the increase in risk of any fracture and the inhibition of the serotonin transporter system [24]. We observed

EGFR inhibition a similar increase in fracture risk for users of SSRIs and TCAs. The explanation for that increased fracture risk may be related simply to an increase in the risk of falls associated with anti-depressant use, especially as there is evidence to suggest that both SSRIs and TCAs are associated with an increased risk of fall. A large study of nursing home residents showed that, compared with non-users and after adjusting for potential confounders, the risk of falls was similar in new users of TCAs and SSRIs. The association was dose dependent and the increased risk persisted through the first 180 days of use and beyond [8]. TCAs are known to inhibit cardiovascular Na+, Ca2+ and K+ channels which can lead to life-threatening arrhythmias. SSRI use has been associated with an increased Parvulin risk of syncope [33], postural hypotension

and dizziness [34] during the early days of exposure, and both SSRIs and TCAs can affect sleep patterns [35, 36], thereby increasing the risk of falls [37]. Another explanation for the increased fracture risk observed here is the effect of anti-depressants on bone physiology. Functional 5-HT receptors are present in bone cells and 5-HT stimulates INK 128 purchase proliferation of osteoblast precursor cells in vitro [23]. There is emerging evidence from animal studies that 5-HT is involved in bone remodelling and can alter bone mineral density (BMD) [18–20, 22]. Indeed, recent findings have shown that SSRIs decrease BMD in animal models [38] and humans [17, 39–41]. Such studies that compared BMD changes with different anti-depressants reported no association between TCA use and BMD [39, 40]. In a recent study of osteoporotic fractures, it was observed that the use of SSRIs (but not TCAs) in older women was independently associated with an increased rate of hip bone loss (0.82% reduction per year) [41], although there was limited information on dose and duration of use. To explore the possibility that fracture risk may be directly related to inhibition of the 5-HTT system, we grouped together the anti-depressants used according to the degree of 5-HTT inhibition afforded.

5, −1 0, −1 5, and −2 0 mA/cm2 simply indicated the growth of ver

5, −1.0, −1.5, and −2.0 mA/cm2 simply indicated the growth of vertically aligned ZnO rods along the c-axis. Meanwhile,

the relatively high peaks corresponding to the ZnO (010) and (011) planes observed in those samples indicated the formation of vertically non-aligned rods and flower-shaped structures. These results are consistent with the SEM images shown in Figure 2. However, the observed weak peaks of the ZnO (002), (010), and (011) planes, particularly for the sample grown at a current density of −0.1 mA/cm2, justified the less formation of vertically aligned/non-aligned rods as well as flower-shaped structures. Figure 3 XRD and PL spectra. (a) XRD spectra and (b) RT PL spectra of grown ZnO structures at different applied current

densities. Figure 3b shows the RT PL spectra of ZnO structures grown at different current densities. Here, two Selleck AZD8931 distinct emission bands were observed. The first band located in the UV region was estimated to be AZD2171 cost around 379, 385, 392, 395, and 389 nm for samples at current densities of −0.1, −0.5, −1.0, −1.5, and −2.0 mA/cm2, respectively. This band is claimed to be due to the near-band edge (NBE) emission or the recombinations of free excitons through an exciton-exciton collision process [6, 29]. The second band appears in the green region of the visible spectrum at approximately 576, 574, 569, 563, and 569 nm, respectively. This band is commonly referred to as a deep-level or trap-state emission. Some researchers suggested that it could be attributed to the recombination of photogenerated holes with single ionized charge states of specific defects such LY3023414 cell line as O vacancies or Zn interstitials [6, 31, 35]. However, Kang et al. reported

that the singly ionized oxygen vacancy is responsible for the green emission and not the ionized Zn interstitials [36]. O-methylated flavonoid It is needed to be proved by post-annealing process of samples. Besides, the intensity of the peak also indicates the level of defects in the samples [31]. Surface state has also been identified as a possible cause of the visible emission in ZnO nanomaterials [37]. There are several reports discussing the relationship of these emission peaks with the quality of the grown structures. As been reported by Djurišić and Leung, the intensity of UV emission is dependent on the nanostructure size [38]. Below a certain size, the luminescence properties of the ZnO nanostructure should be dominated by the properties of the surface. The samples grown at current densities of −0.5 and −1.0 mA/cm2 show highly intense UV emission with the highest aspect ratio (Table 1) compared to other samples. Highly intense UV emission seems to show higher crystallinity and more perfection in surface states as reported by Park et al. [39]. Chen et al. suggested that it may imply a good crystal surface [40]. The enhancement of UV emission is attributed to a larger surface area and fewer defects [41].

In order to exclude the effect of the background magnetoresistanc

In order to exclude the effect of the background magnetoresistance and to extract the SdH oscillations, we used the negative second derivative with respect to the magnetic field of raw magnetoresistance data (-∂2 R xx /∂B 2) (see Figure 1b). As can be easily seen from Equation 1, this method does not change the position of the peak or period of the oscillations and enables to subtract the slowly changing background magnetoresistance and amplifies the short-period

oscillations [18, 19] as depicted in Figure 1b. The thermal damping of the SdH oscillations at a fixed magnetic field is determined by temperature, magnetic field, and effective mass using Equations 1 to 5 as follows [19–22]: (6) where A(T, B n ) and A(T 0, B n ) are the amplitudes of the SdH oscillations at a constant magnetic field B n and at temperatures T and T 0. Using Equation 6 and SdH oscillations data at different temperatures, we derived the effective mass which we plotted in Figure 2. Figure 2 Effective mass values calculated using temperature dependence of SdH oscillations An OICR-9429 nmr enhancement of the electron effective mass compared to the N-free sample is

observed in N-containing as-grown samples, which obeys the band anti-crossing (BAC) model [4]. After thermal annealing, the electron effective mass increases, which can be attributed to the change of bandgap. It is known that incorporation of nitrogen into GaInAs lattice causes a redshift of the bandgap; on the other

hand, thermal annealing blueshifts the bandgap and the amount of blueshift increases with increasing nitrogen content selleck chemicals llc (see Table 1). The origin of the blueshift has been explained in terms of inter-diffusion of In-Ga and restructure of the nearest neighbor configuration of nitrogen [1, 9]. Table 1 PL peak energies and observed blueshift amounts at 30 K Samples PL peak energy (eV) Blueshift (meV) p-type n-type p-type n-type Ga0.68In0.32As As-grown 1.180 1.172 – - Annealed (60 s) 1.182 1.184 2 12 Annealed MG-132 price (600 s) 1.194 1.194 14 22 Ga0.682In0.32 N0.009As0.991 As-grown 1.089 1.120 – - Annealed (60 s) 1.118 1.129 29 9 Annealed (600 s) 1.146 1.137 57 17 Ga0.68In0.32 N0.012As0.988 As-grown 1.033 1.076 – - Annealed (60 s) 1.065 1.088 32 12 Annealed (600 s) 1.103 1.096 70 20 As a result of blueshift of the bandgap, conduction band states approaches localized N level, giving rise a stronger interaction; therefore, electron effective mass increases compared to the values in as-grown N-containing samples. In N-free sample, indium atoms diffuse out from the QW, leading to a decrease in In content and weaker confinement due to the reduction of the conduction band offset as a result of blueshifted bandgap. An enhancement in electron effective mass in compressively strained GaInAs layer with decreasing In content and weaker confinement was also observed by Meyer et al. [23], which is consistent with our result.

05) Figure 2 The total training time (minutes) each week in mean

05). Figure 2 The total training time (minutes) each week in mean ± SD (endurance training time + sprint running time). AKG: α-keto glutarate; BCKA: branched-chain keto acids. Figure 3 The peak maximal isometric torque (Newton meter) in mean ± SD. AKG: α-keto glutarate; BCKA: branched-chain keto acids. Figure 4 The peak isokinetic performance (Watts) in mean ± SD. AKG: α-keto glutarate; BCKA: branched-chain keto acids. The VO2max increased significantly after training and during recovery in all three groups (P<0.01), and there was no significant difference among the three groups at each test time point. The Pmax increased in the groups supplemented with KAS after the recovery

period compared with that before training (P<0.05), while the increase in Pmax in the control group was less and was not statistically significant. The endurance buy HMPL-504 capacity

assessed by PIAT was increased at the end of training in all three groups, but no statistically significant difference was observed among the groups. The muscle function tests showed that the isometric maximum torque was different at the baseline level among the groups, but the difference was not statistically significant (P = 0.27). The torque did not change in the control group after training and recovery, but it increased significantly after the recovery week (P<0.05) in the AKG and BCKA groups (Figure 3). Similar results were observed in muscle performance as assessed by the isokinetic measurement (Figure 4). The baseline level of muscle performance was different among the groups, but the difference was not statistically PLX3397 cell line significant (P = 0.144). Stress-recovery state In the RESTQ-Sport analysis, the general stress was markedly increased in the control group during the third week of the Molecular motor training (P<0.05) (Figure 5a), and it did not change in BCKA group (NS). In the AKG group, the general stress was higher at baseline than in the other groups, but it did not change significantly during the study period (NS). Figure 5 The weekly data from the recovery-stress questionnaire

(RESTQ-scores) for general stress (A), somatic complaints (B), emotional exhaustion (C) and disturbed breaks (D). AKG: α-keto glutarate; BCKA: branched-chain keto acids. CAL-101 research buy RESTQ-Scores 0: never; RESTQ-Scores 5: always. For the somatic complaints (Figure 5b), the baseline RESTQ-scores in the control group were higher (but not statistically significant) than in the other groups. These values were essentially unchanged during the entire observation period in the control group, while increasing in the AKG group (P<0.05) and in the BCKA group (P<0.01) during the training phase. Emotional exhaustion assessed by RESTQ-scores increased and reached the highest level during the third week of the training in the control group (P<0.01) (Figure 5c) but did not change significantly in the BCKA group (NS).

: Haemorrhagic fever with renal syndrome: an analysis of the outb

: Haemorrhagic fever with renal syndrome: an analysis of the outbreaks in Belgium, France, Germany, the Netherlands and Luxembourg in 2005. Euro Surveillance 2007, 12:167–171. check details 7. Penalba C, Galempoix JM, Lanoux P: epidémiologie des infections à hantavirus en France. Med Mal Infect 2001,31(2):272–284.CrossRef 8. Niklasson B, Hörnfeldt B, Lundkvist Å, Björsten S, Leduc J: Temporal dynamics of Puumala virus antibody prevalence in voles and of nephropathia epidemica incidence in humans. Am J Trop Med Hyg 1995, 53:134–140.PubMed 9. Tersago K, Verhagen R, Servais A, see more Heyman P, Ducoffre G, Leirs H: Hantavirus disease (nephropathia epidemica) in Belgium: effects of tree seed

production and climate. Epidemiol Infect 2009,137(2):250–256.PubMedCrossRef 10. Clement J, Vercauteren J, Verstraeten Selleck ACP-196 WW, Ducoffre G, Barrios JM, Vandamme AM, Maes P, Van Ranst M: Relating increasing hantavirus incidences to the changing climate: the mast connection. Int J Health

Geogr 2009, 8:1.PubMedCrossRef 11. Tersago K, Schreurs A, Linard C, Verhagen R, Van Dongen S, Leirs H: Population, environmental, and community effects on local bank vole (Myodes glareolus) Puumala virus infection in an area with low human incidence. Vector Borne Zoonotic Dis 2008,8(2):235–244.PubMedCrossRef 12. Dizney LJ, Ruedas LA: Increased host species diversity and decreased prevalence of Sin Nombre virus. Emerg Infect Dis 2009,15(7):1012–1018.PubMedCrossRef 13. Clay CA, Lehmer EM, St Jeor S, Dearing MD: Testing mechanisms of the dilution effect: deer mice encounter rates, Sin Nombre virus prevalence and species diversity. Ecohealth 2009,6(2):250–259.PubMedCrossRef 14. Clay CA, Lehmer EM, Jeor SS, Dearing MD: Sin Nombre virus and rodent species diversity: a test of the dilution and amplification hypotheses. PLoS One 2009,4(7):e6467.PubMedCrossRef 15. Linard C, Tersago K, Leirs H, Lambin EF: Environmental conditions and

Puumala virus transmission in Belgium. Int J Health Geogr 2007, 6:55.PubMedCrossRef 16. Linard C, Lamarque P, Heyman P, Ducoffre G, Luyasu V, Tersago K, Vanwambeke SO, Lambin EF: Determinants of the geographic distribution of Puumala virus and Lyme borreliosis infections in Belgium. also Int J Health Geogr 2007, 6:15.PubMedCrossRef 17. Escutenaire S, Chalon P, De Jaegere F, Karelle-Bui L, Mees G, Brochier B, Rozenfeld F, Pastoret PP: Behavioral, physiologic, and habitat influences on the dynamics of Puumala virus infection in bank voles ( Clethrionomys glareolus ). Emerg Infect Dis 2002,8(9):930–936.PubMed 18. Sauvage F, Langlais M, Yoccoz NG, Pontier D: Modelling hantavirus in fluctuating populations of bank voles: the role of indirect transmission on virus persistence. J Anim Ecol 2003,72(1):1–13.CrossRef 19. Kallio ER, Klingstrom J, Gustafsson E, Manni T, Vaheri A, Henttonen H, Vapalahti O, Lundkvist A: Prolonged survival of Puumala hantavirus outside the host: evidence for indirect transmission via the environment. J Gen Virol 2006,87(8):2127–2134.PubMedCrossRef 20.

Br J Sports Med 2008, 42:567–73 PubMedCrossRef 30


Br J Sports Med 2008, 42:567–73.Epigenetics inhibitor PubMedCrossRef 30.

Belobrajdic DP, McIntosh GH, Owens JA: A high-whey-protein diet reduces body weight gain and alters insulin sensitivity relative to red meat in wistar rats. J Nutr 2004, 134:1454–8.PubMed 31. Pichon L, Potier M, Tome D, et al.: High-protein diets Selleckchem GW 572016 containing different milk protein fractions differently influence energy intake and adiposity in the rat. Br J Nutr 2008, 99:739–48.PubMedCrossRef 32. Anthony TG, McDaniel BJ, Knoll P, et al.: Feeding meals containing soy or whey protein after exercise stimulates protein synthesis and translation initiation in the skeletal muscle of male rats. J Nutr 2007, 137:357–62.PubMed 33. Inkielewicz-Stepniak I, Czarnowski W: Oxidative stress parameters in rats exposed to fluoride and caffeine. Food Chem Toxicol 2010, 48:1607–11.PubMedCrossRef 34. Inkielewicz-Stepniak I: Impact of fluoxetine on liver damage in rats. Pharmacol Rep 2011, 63:441–7.PubMed 35. Newman JE, Hargreaves M, Garnham A, et al.: Effect of creatine ingestion on glucose tolerance and insulin sensitivity in men. Med Sci Sports Exerc 2003, 35:69–74.PubMedCrossRef 36. Hickner RC, Tanner CJ, Evans CA, et al.: L-citrulline reduces time to exhaustion and insulin response to a graded

exercise test. Med Sci PF-3084014 nmr Sports Exerc 2006, 38:660–6.PubMedCrossRef 37. Afkhami-Ardekani M, Shojaoddiny-Ardekani A: Effect Sirolimus cell line of vitamin c on blood glucose, serum lipids & serum insulin in type 2 diabetes patients. Indian J Med Res 2007, 126:471–4.PubMed 38. Liu Z, Jeppesen PB, Gregersen S, et al.: Dose- and glucose-dependent effects of amino acids on insulin secretion from isolated mouse islets and clonal ins-1e beta-cells. Rev Diabet Stud 2008, 5:232–44.PubMedCrossRef 39. Urista CM, Fernandez RA, Rodriguez FR, et al.: Review: Production and functionality of active peptides from milk. Food Sci Technol Int 2011, 17:293–317.CrossRef Competing interest The authors declare no competing interests.

Authors’ contributions RGT assisted with: 1) data collection; 2) data analysis; 3) statistical analysis; 4) preparing manuscript. TEC assisted with: 1) intellectual contribution throughout experiments; 2) manuscript preparation. SRH Performed histological examination of kidney and liver tissues and provided intellectual contribution throughout experiments. JRC performed leucine analysis. FWB assisted in: 1) study design; 2) intellectual contribution throughout experiments; 3) manuscript preparation. MDR procured grant funding; assisted in: 1) study design; 2) data collection and analysis; 3) preparing manuscript. All authors read and approved the final manuscript.”
“Introduction Disruption in the balance between free radical production and scavenging capability contributes to the accumulation of oxidative damage in muscle tissues.

J Clin Microbiol 2005,43(1):66–73 PubMedCrossRef 29 Johnson JR,

J Clin Microbiol 2005,43(1):66–73.PubMedCrossRef 29. Johnson JR, Owens KL, Clabots CR, Weissman SJ, Cannon SB: Phylogenetic relationships among clonal groups of extraintestinal find more pathogenic Escherichia coli as assessed by multi-locus sequence analysis. Microbes and infection /Institut Pasteur 2006,8(7):1702–1713.PubMedCrossRef 30. Moulin-Schouleur M, Schouler C, Tailliez P, Kao MR, Bree A, Germon P, Oswald E, Mainil J, Blanco M, Blanco J: Common virulence factors and genetic relationships between O18:K1:H7 Escherichia coli isolates of human and avian origin. J Clin Microbiol 2006,44(10):3484–3492.PubMedCrossRef 31. Levy SB,

FitzGerald GB, Macone AB: Spread of antibiotic-resistant selleckchem plasmids from chicken to chicken and from chicken to man. Nature 1976,260(5546):40–42.PubMedCrossRef 32. Linton AH, Howe K, Bennett PM, Richmond MH, Whiteside EJ: The colonization of the human

gut by antibiotic resistant Escherichia coli from chickens. J Appl Bacteriol 1977,43(3):465–469.PubMedCrossRef 33. Ojeniyi AA: Direct transmission of Escherichia coli from poultry to humans. Epidemiol Infect 1989,103(3):513–522.PubMedCrossRef 34. van den Bogaard AE, Willems R, London N, Top J, Stobberingh EE: Antibiotic resistance of faecal enterococci in poultry, poultry farmers and poultry slaughterers. J Antimicrob Chemother 2002,49(3):497–505.PubMedCrossRef 35. Moulin-Schouleur M, Reperant M, Laurent S, Bree A, Mignon-Grasteau STK38 S, Germon P, Rasschaert D, Schouler C:

Extraintestinal pathogenic Escherichia coli strains of avian and human origin: link between phylogenetic relationships and common virulence patterns. J Clin Microbiol 2007,45(10):3366–3376.PubMedCrossRef 36. Hagan EC, Mobley HL: Haem acquisition is facilitated by a novel receptor Hma and required by uropathogenic Escherichia coli for kidney infection. Mol Microbiology 2009,71(1):79–91.CrossRef 37. Bonacorsi SP, Clermont O, Tinsley C, Le Gall I, Beaudoin JC, Elion J, Nassif X, Bingen E: Identification of regions of the Escherichia coli chromosome specific for neonatal meningitis-associated strains. Infect Immun 2000,68(4):2096–2101.PubMedCrossRef 38. Dozois CM, Daigle F, Curtiss R: Identification of pathogen-specific and conserved genes expressed in vivo by an avian pathogenic Escherichia coli strain. Proc Natl Acad Sci U S A 2003,100(1):247–252.PubMedCrossRef 39. Feldmann F, Sorsa LJ, Hildinger K, Schubert S: The salmochelin siderophore receptor IroN contributes to invasion of urothelial cells by extraintestinal pathogenic Escherichia coli in vitro. Infect Immun 2007,75(6):3183–3187.PubMedCrossRef 40. Peigne C, Bidet P, Mahjoub-Messai F, Plainvert C, Barbe V, Medigue C, Frapy E, Nassif X, Denamur E, Bingen E, Bonacorsi S: The plasmid of Escherichia coli strain S88 (O45:K1:H7) that causes neonatal meningitis is closely related to avian pathogenic E.