Laryea MD, Steinhagen F, Pawliczek S, Wendel U: Simple method for the routine determination of betaine and N,N-dimethylglycine in blood and urine. Clin Chem 1998, 44:1937–1941.PubMed 13. Armstrong LE, Pumerantz AC, Fiala KA, Roti MW, Kavouras SA, Casa

DJ, Maresh CM: Human hydration indices: acute and longitudinal reference values. Intern J Sport Nutr Exerc Metab 2010, 20:145–153. 14. Drinkwater EJ, Lane T, Cannon J: Effect of an acute bout of plyometric exercise on neuromuscular fatigue and recovery in recreational athletes. J Strength Cond Res 2009, 23:1181–1186.CrossRefPubMed 15. Ebben WP, Leigh DH, Geiser CF: The effect of remote voluntary contractions on knee extensor toque. Med Sci Sports Exerc 2008, 40:1805–1809.CrossRefPubMed 16. Brigotti M, Petronini PG, Carnicelli D, Alfieri RR,

Bonelli MA, Borghetti AF, Wheeler KP: Effects of osmolarity, ions R788 datasheet and compatible osmolytes on cell-free protein synthesis. Biochem J 2003, 369:369–374.CrossRefPubMed 17. Courtenay ES, Capp MW, Anderson CF, Record MT Jr: Vapor pressure osmometry studies of osmolyte-protein interactions: implications for the action of osmoprotectants in vivo and for the interpretation of “”osmotic stress”" experiments in vitro. Biochem 2000, 39:4455–4471.CrossRef 18. Cronjé PB: Heat stress in livestock – role of the gut in its aetiology and a potential role for betaine in its alleviation. Recent Adv Animal Nutr Australia 2005, 15:107–122. 19. Inoue Y, Havenith G, Kenney WL, Loomis JL, Buskirk ER: Exercise- and methylcholine- induced sweating GSK-3 beta phosphorylation responses in older and younger men: effect of heat acclimation and aerobic fitness. Int J Biometeorol 1999, 42:210–216.CrossRefPubMed 20. Kanter MM, Williams MH: Antioxidants, carnitine, and choline as putative Ureohydrolase ergogenic aids. Int J Sport Nutr 1995,5(Suppl):120–131. 21. Spector SA, Jackman MR, Sabounjian LA, Sakkas C, Landers DM, Willis WT: Effect of choline supplementation on fatigue in trained cyclists. Med Sci Sports Exerc 1995, 27:668–673.PubMed 22. Thompson CH, Kemp GJ, Sanderson AL, Dixon

RM, Styles P, Taylor DJ, Radda GK: Effect of creatine on aerobic and anaerobic metabolism in skeletal muscle in swimmers. Br J Sports Med 1996, 30:222–225.CrossRefPubMed 23. Warber JP, Zeisel SH, Mello RP, Kemnitz CP, Liebermann HR: The effects of choline supplementation on physical performance. Int J Sport Nutr Exerc Metab 2000, 10:170–181.PubMed Competing interests The first nine authors, all associated with the University of Connecticut at the time of this study, declare that they have no competing interests. SASC is employed by Danisco A/S, the company that funded this study. Publication of these findings should not be viewed as endorsement by the investigators, the University of Connecticut, or the editorial board of the Journal of the International Society of Sport Nutrition.

Finally,

as a minor comment, the authors should pay more attention to accuracy in the citation of the pertinent literature. For example, reference #10 is claimed to support a statement Ixazomib on interleukins and cerebral edema, when in fact the citation refers to a publication on programmed cell death in nematodes. Several other examples of inadequate reference to the literature could be mentioned. Finally, the title chosen by the authors appears problematic. The authors claim to provide the “”missing link”" between molecular mechanisms and therapeutic concepts in TBI. Unfortunately, the review article fails to provide a bridge between the two entities. In addition, many of the current therapeutic approaches and promising new strategies in search of the pharmacological “”golden bullet”" are missing [2]. While alterations in gene expression

may be an interesting finding and promising target for future scientific approaches, we are still far from bringing the gene therapy concept from “”bench to bedside”" for an acute traumatic disorder such as TBI. In summary, we realize that providing an encompassing and scientifically accurate review on the topic represents a virtually impossible task. We are therefore grateful for the review by Veenith et al. [1] and we hope to contribute to the authors’ search of the “”missing link”" between molecular pathophysiology and new therapeutic concepts in TBI by the identification of additional pathways of interest (Fig. 1). References MK0683 nmr 1. Veenith T, Goon SH, Burnstein RM: Molecular mechanisms of traumatic brain injury – the missing link in management. World J Emerg Surg 2009,4(1):7.CrossRefPubMed 2. Beauchamp K, Mutlak H, Smith WR, Shohami E, Stahel PF: Pharmacology of traumatic brain injury: where is the “”golden bullet”"? Mol Med 2008,14(11–12):731–740.PubMed Competing interests The authors declare that they have no competing interests. Authors’ contributions MAF and PFS wrote the manuscript. WRS and SJM critically revised the paper. All authors approved the final version of this manuscript.”
“Background Polytraumatized patients often suffer from associated injuries of the spinal column following a major trauma

(1st hit) from direct and indirect mechanical forces that generated soft tissue-, organ injuries and fractures. The consecutive P-type ATPase host reaction is characterized by a local and systemic expression and release of a vast array of pro-inflammatory mediators [1–4] misbalancing the immune system often resulting in a systemic inflammatory response syndrome (SIRS). The extent of the trauma-induced first hit is the major prognostic parameter for the clinical outcome of the patient following multiple trauma. Nevertheless, secondary events including septic complications, and single or multiple organ dysfunction (MOD/MOF) like acute lung injury or acute respiratory distress syndrome (ARDS) determine the beneficial or adverse outcome of polytraumatized patients.

Quantitative data relative to the number of Ehrlichia organisms were calculated [9, 19]. Bioinformatics analysis Sequences upstream from Erismodegib in vitro the protein coding regions of E. chaffeensis p28-Omp 14 and 19 were obtained from the GenBank data base and aligned by using the genetic computer group (GCG) programs PileUp and Pretty [62] to search for sequence homologies. Direct repeats and palindrome sequences in the upstream sequences were identified with the GCG programs Repeat and StemLoop, respectively.

E. coli σ70 promoter consensus sequences (-10 and -35) [63] were used to locate similar elements manually in p28-Omp genes 14 and 19 sequences upstream to the transcription start sites. Promoter constructs Promoter constructs for MK-8669 molecular weight p28-Omp genes 14 and 19 were made with two independent promoterless reporter genes containing

plasmid vectors pPROBE-NT [64] and pBlue-TOPO (Invitrogen Technologies, Carlsbad, CA). The pPROBE-NT vector contains a GFP gene as the reporter gene, whereas a lacZ gene is the reporter gene in the pBlue-TOPO vector. To generate a p28-Omp gene14 promoter region construct, the entire non-coding sequences located between coding sequences of p28-Omp genes 13 and 14 were amplified by using E. chaffeensis genomic DNA as a template and the sequence-specific oligonucleotides (Table 1). A similar strategy was used to prepare the gene 19 promoter constructs by amplifying the DNA segment located between the coding regions of p28-Omp genes 18 and 19. The PCR products were ligated into the promoterless pBlue-TOPO and pPROBE-NT vectors and transformed into second E. coli strain, Top10 (Invitrogen Technologies, Carlsbad, CA) and DH5α strain, respectively [61]. One clone each in forward and reverse orientations was selected for the genes 14 and 19 in the pBlue-TOPO plasmid. For the pPROBE-NT constructs, only forward orientation inserts containing plasmids were selected. In addition, nonrecombinant plasmids transformed in E. coli were selected to serve as negative controls. Promoter deletion constructs

Various deletion fragments of the promoter regions lacking parts of the 5′ or 3′ end segments of genes 14 and 19 were also generated by PCR and cloning strategy in the pBlue-TOPO plasmid. Deletion constructs of gene 14 and 19 promoters that are lacking the predicted -35 or -10 alone or the regions spanning from -35 to -10 were also generated by PCR cloning strategy but by using a Phusion site-directed mutagenesis kit as per the manufacturer’s recommendations (New England Biolabs, MA). Primers used for the deletion analysis experiments are included in Table 1. Presence of correct inserts for the clones was always verified by restriction enzyme and sequence analysis. Assessment of promoter activity in vitro Promoter region and reporter gene segments were amplified by PCR using pBlue-TOPO promoter constructs as the templates.

Cell adherence assays were performed using human liver epithelial cell HepG2. The adherence of wild

type EDL933 to HepG2 cells in tissue culture was two-fold higher than that of rpoS and Suc++ mutants (P < 0.05) (Figure 3B), indicating that Suc++ mutants BGB324 mouse are impaired in cell adherence due to loss of RpoS function. This is consistent with previous results that over-expression of RpoS stimulates cell adherence [47]. Figure 3 Virulence-related traits, RDAR and cell adherence. (A) Development of RDAR morphotype is impaired in Suc++ mutants. Cells were replica-plated on CR (Congo Red) plates and incubated at 25°C for 48 h. (B) Cell adherence to epithelial cells. The adherence was expressed as the percentage of cells surviving the washing process. rpoS designates the constructed rpoS null-deletion mutant. Suc++ mutants with an intact RpoS function (rpoS +) During the screening for the Suc++ phenotype,

we found that a small proportion of Suc++ mutants PLX3397 ic50 from strains EDL933 (8%), CL106 (16%), and EC6-484 (33%) were catalase-positive, a presumptive indication that RpoS was functional. To confirm this, we sequenced the rpoS region of five such Suc++ mutants (three aerobically isolated and the other two anaerobically isolated) of strain EDL933. As expected, there was no mutation in the rpoS gene in these mutant strains. However, these grew much better than wild type when grown on succinate (generation time: 240 ± 31 min) and fumarate (generation time: 306 ± 33 min) (Table 3). These data suggest that non-rpoS mutations are a minor component in the poor carbon selection process. Effect of the rpoS mutation on metabolism by Phenotype Microarray analysis RpoS

is known to negatively Pyruvate dehydrogenase control many genes involved in metabolism [10, 12, 48], and therefore, mutations in rpoS are likely to exert pleiotropic effects on metabolism. To test this, we compared wild type MG1655 and its derivative rpoS deletion mutants [12] using Phenotype Microarray analysis (Biolog, Hayward, CA). The rpoS mutants exhibited better respiration on 8 carbon sources and 92 nitrogen sources but less respiration on four carbon sources and one nitrogen source (Table 4). The substantial impact of rpoS mutations on nutrient utilization suggest that the beneficial effect of loss of RpoS in one selection condition may be extended to other conditions as well. Table 4 Phenotypic Microarray (PM) analyses of growth changes resulted from rpoS mutations.

Gelelectrophoresis and melting curve analysis confirmed the presence of the expected PCR products only, and the absence of unwanted non-specific products (data not shown). Non-inoculated RHE failed to show evidence of gene Sotrastaurin expression (data not shown), confirming that each primer pair was specific for its corresponding C. albicans gene. Using

the optimized real-time PCR assays, we found that HWP1 and all ALS, SAP, LIP and PLB genes were expressed at all time points during biofilm growth in all model systems tested (and also in the start cultures), as evidenced from a detectable Ct value (Ct < 35; data not shown). Expression levels of ALS genes and HWP1 in biofilms The expression levels (expression in biofilms, relative to expression in start cultures) of ALS genes and HWP1 in biofilms at selected time points in the various model systems are shown in Additional file 1. ALS1-5 were overexpressed in biofilms grown in all model systems at several time points or during the entire time course. Furthermore, HWP1 and ALS6 were overexpressed

in all model systems except in the MTP and RHE, respectively. ALS9 was only overexpressed in biofilms grown in the CDC reactor, but the fold upregulations were not particularly high. The fold expressions were model-dependent for most of the genes tested. Overexpression of ALS3 and HWP1 were more pronounced in biofilms grown in the in vivo model, while the expression levels of ALS6 were higher in the two in vitro models. Furthermore, the fold upregulations of ALS4 were more pronounced in biofilms grown in the in vivo and RHE models, while those of ALS1, ALS2 and ALS5 were higher in GSK2118436 the two in vitro models and in the in vivo model. Expression levels of SAP genes in biofilms The expression levels of SAP genes in biofilms at selected time points in the various model systems are shown in Additional file 2. All SAP genes (except SAP3) were upregulated in biofilms grown in

all model systems at one or more time points. The expression Niclosamide levels of SAP3 were rather erratic, and this gene was not considerably upregulated in any of the model systems tested. For most of the SAP genes model-dependent expression levels were observed. In in vitro grown biofilms, SAP1, SAP2, SAP4 and SAP6 were highly upregulated, and the fold expression of SAP2, SAP4 and SAP6 were also high in the vivo model. Furthermore, SAP5 was highly upregulated in biofilms grown in the in vivo and RHE models. Only for SAP9 and SAP10 similar gene expression levels were observed in all model systems, although these genes were not expressed at a high level in biofilms. Expression levels of PLB genes in biofilms The expression levels of PLB genes in biofilms at selected time points in the various model systems are given in Additional file 3. Overall, PLB genes were not considerably upregulated in biofilms, and only model-dependent differences in gene expression levels were observed.

Further experimental analysis will hopefully elucidate the detailed regulatory relationship between SabR and nikkomycin biosynthesis. Conclusions In conclusion, this study presented detailed molecular and genetic analysis for sabR on the production of nikkomycin in S. ansochromogenes. The results revealed that the SabR regulated nikkomycin biosynthesis positively via interaction with the upstream region of sanG. Selumetinib It might be useful to expand the limited understanding of regulation exerted by SabR. Methods Strains, plasmids, media and growth conditions The strains

and plasmids used in this study are listed in Table 2. Escherichia coli DH5α, BL21 (DE3), ET12567 (pUZ8002), and their derivative strains were grown at 37°C in Luria-Bertani (LB) medium containing necessary antibiotics for propagating plasmids. The nikkomycin producer, Streptomyces ansochromogenes 7100 and sabR disruption mutant were incubated at 28°C. For nikkomycin production, SP medium (3 % mannitol, 1 % soluble starch, 0.75 % yeast extract, and 0.5 % soy Cilomilast in vivo peptone, pH 6.0) was used. Liquid medium YEME and solid medium MM were prepared according to standard procedures

[33]. Alternaria longipes was used as indicator strain for nikkomycin bioassay and incubated at 28°C in PDA medium. The plasmid pUC119::kan, pET23b, pIJ8600 and their derivatives were collected in our lab. E. coli-Streptomyces shuttle vector pKC1139 used for gene disruption was kindly provided by Prof.

Keith Chater (John Innes Centre, Norwich, UK). Table 2 Strains and plasmids used in this study Strains or plasmids relevant characteristics Source or reference Strains     S. ansochromogenes 7100 Wild-type strain [40] sabRDM from The sabR disruption mutant [24] E. coli DH5α F- recA f80 dlacZ ΔM15 Gibco BRL BL21(DE3) F- ompT hsdS gal dcm (DE3) Novagen ET12567 (pUZ8002) recE dam dcm hsdS Cmr Strr Tetr Kmr [41] Alternaria longipes Indicator strain for nikkomycin bioassays [40] Plasmids     pBluescript KS+ Routine cloning and subcloning vector Stratagene pET23b Expression vector Novagen pET23b::sabR sabR gene cloned in pET23b This work pIJ8600 ori pUC, oriT RK2, int ΦC31, tipAp, tsr, apr R [33] pIJ8600::sabR sabR gene cloned in the induced vector of pIJ8600 which containing PtipA as promoter This work pKC1139 E.coli-Streptomyces shuttle vector [33] pGARE1 A 974 bp DNA fragment containing the left flank of SARE was inserted into pUC119::kan This work pGARE2 A 806 bp DNA fragment containing the right flank of SARE was inserted into GAREL1 This work pGARE3 A 2.8 kb DNA fragment containing the left and right flanks of SARE and kanamycin resistance gene from pGARE2 was inserted into pKC1139 This work pGARE4 The 1 kb kanamycin resistance gene was deleted from pGARE3 This work pGARE5 A 1.

Recently, PRA and DPRA have been developed for molecular identification of mycobacterial species using different regions of hsp65, 16 S rDNA, 16 S-23 S rDNA spacer, dnaJ, and rpoB as an amplification target [3, 14–17]. The most common method is hsp65 PRA, and 74 patterns for 40 species are available in the PRASITE database ( http://​app.​chuv.​ch/​prasite/​index.​html). Rapamycin mw Previous studies [18, 19] have reported that hsp65 PRA is faster and more accurate for species identification than conventional (phenotypic or biochemical) testing. This is because

more incorrect and ambiguous results are obtained with conventional methods. The results in our study (Tables 1 and 2) also support this finding. Incorrect and ambiguous results are caused by phenotypic homogeneity among different species and phenotypic variability within species [18]. With by hsp65 PRA, some sub-species, such as M. kansasii, can be identified and rapid-growing

MK-2206 mouse mycobacterium can be divided into M. abscessus and M.chelonae, M. fortuitum and M. smegmatis[20], whereas these identifications are difficult with conventional methods [21]. As found in our study (Tables 1 and 2), M. peregrinum was identified as M. fortuitum and M. avium subsp. avium and M. intracellulare were both identified as M. avium complex by the conventional biochemical method. However, hsp65 PRA limitations have been reported in some articles [22, 23]. Failure to identify or incorrect identification of the species may occur because of similarities in band sizes critical for discriminating species, including difficult to distinguish M. tuberculosis complex (M. tuberculosis and M. bovis) [22], and closely related sub-species such as M. avium or M. gordonae, because of sequence heterogeneity [22]. In addition, technical problems can also cause misinterpretation or incorrect identification [23]. Patterns in PRA profiles are complex and difficult CYTH4 to interpret with the naked eye, especially when more detailed sub-types are included [21]. This study combined rpoB DPRA and hsp65 PRA to test both reference strains and clinical respiratory

isolates. The mycobacterial identification flow chart (Figure 1) can identify species to the sub-species level, and final species identification can be obtained instantly with concordant results from the two PRA. M. gordonae has a highly variable gene sequence with 10 sub-types in hsp65 PRA, and there are two groups (G and F) in rpoB DPRA. Most M. gordonae is in the G group, but M. gordonae types 3 and 4 by hsp65 PRA are in the F group (Tables 1 and 2). In addition, there were different rpoB DPRA results (Table 2) for M. simaie type 5 (G group but not E group), M. scrofulaceum type 1 (D group but not H group), and M. intracellulare type 3 (F group but not G group). The identities of all of these isolates were finally confirmed by 16 S rDNA sequencing.

Score as provided by TransTermHP, only terminators with a score above 90 are shown. Features of the JG004 genome A schematic Small molecule library clinical trial representation of the genome, with its predicted CDSs, the tRNA locations, some functional assignments and overall genetic organization is shown in Figure 3 and Additional file 1, Table S1. The genome of phage JG004 shows 11.3% intergenic space. This is comparable with the genome of the host P. aeruginosa PAO1 which has 10.6% non-coding regions [25]. Putative functions could be assigned to

only 30 (18.5%) genes based on sequence similarities (Figure 3). Although phage JG004 and PAK-P1 share strong similarities, we found 19 genes with no similarities to PAK-P1 including 13 genes with no significant similarities to any protein in the Belnacasan mouse database.

The proteins with no similarity to other proteins are small proteins with a size between 47 aa and 112 aa. It is still difficult to accurately predict short genes with computational methods [26], therefore, these predictions are uncertain. Figure 3 Genome of JG004. Schematic representation of the JG004 genome with its assumed tRNAs, genes and some functional assignments. The arrowheads point in the direction of transcription. Gene 46-57 represent the tRNAs of phage JG004. Predicted terminator structures are indicated as hairloop structures. No significant match to proteins annotated as integrase, repressor or transposase was found, suggesting that this phage is a virulent phage which is in concordance with the results of the highly related phage PAK-P1 [27]. Gene 66 has similarities to RNA polymerases (e-value: 6e-41) suggesting that the phage JG004 is probably not dependent on the host transcriptional machinery. Moreover, genes encoding for enzymes of the DNA replication machinery were found, suggesting that the DNA replication is also independent from the host. We found genes with similarities to a DNA polymerase (gene 111; e-value: 0.0), a DNA

helicase/primase (gene 110; e-value: 0.0), a thymidylate synthetase (gene 130; e-value: 6e-70), a ribonucleoside-diphosphate reductase (gene 132, 133; e-values: 0.0) and to a putative exodeoxyribunuclease (gene 117; e-value: 1e-28). A terminase like gene (gene Fossariinae 59; e-value: 0.0) could also be detected. Phage terminases are DNA packaging enzymes and are among the most conserved proteins found in phages. Some terminases also contain endonuclease activity to cut DNA into the genome length of the respective phage [28]. Two putative endonucleases were also detected (gene 36, 70; e-values: 2e-8, 3e-14). Endonucleases could be involved in the DNA packaging process or in host nucleic acid damaging. Interestingly, the putative endonuclease gene 70 has no homologue in phage PAK-P1. Moreover, one putative methyltransferase was found (gene 61; e-value: 4e-8).

5 % and a one-sided type I error of 2.5 %. The primary efficacy variable was the percent change from baseline in lumbar spine BMD at week 52-Endpoint; the last valid post-baseline measurement was used when the week 52 value was missing (LOCF). Predefined secondary outcomes included changes in BMD at the lumbar spine and regions of the proximal femur, changes in biochemical markers of bone turnover, and incidence of morphometric vertebral fractures at week 104. No changes in secondary outcomes were made during the course of the study. Efficacy analyses were performed in the intent-to-treat (ITT) population consisting of all subjects who were randomized, received at least one dose of study drug, and had analyzable

BMD or bone marker data at baseline and at least one posttreatment time point. Ninety-five percent, two-sided confidence intervals (CIs) for the treatment difference were constructed and used to https://www.selleckchem.com/products/gdc-0068.html determine differences between IR daily and each of the DR weekly treatment groups. Nonparametric Olaparib nmr methods were used to perform the statistical analysis of all bone biopsy parameters. The nonparametric Wilcoxon rank sum test was used for between-group comparisons. The nonparametric Hodges–Lehmann CIs (95 %) were constructed for the median differences between groups. Results Subjects A total of 1,859 women were screened; of these, 923 subjects were

randomized, and 922 subjects received at least one dose of study drug (Fig. 1). Baseline characteristics were previously described and were similar across treatment groups [1]. The median daily dose of calcium was 1,000 mg for all three treatment groups, and the median daily dose of vitamin D was 800 IU for all three treatment groups. A similar percentage of subjects in each treatment group completed the 104-week study (IR daily group, 80.8 %; DR FB weekly group, 76.2 %; DR BB weekly group, 77.9 %). The most common reasons given for withdrawal, which occurred at similar incidences across all three treatment groups, were adverse event and voluntary withdrawal. A high percentage of ITT subjects in all groups (96.7 % of

subjects in the IR daily group, 96.7 % MRIP of subjects in the DR FB weekly group, and 95.1 % of subjects in the DR BB weekly group) took at least 80 % of the study tablets. Fig. 1 Disposition of subjects Efficacy assessments As reported previously, all three treatment groups experienced significant improvements from baseline in lumbar spine BMD after 1 year of treatment. The response to both the 35-mg DR groups at week 52 was shown to be non-inferior and not superior to that observed with the 5-mg IR tablet. All three treatment groups continued to show significant improvements from baseline in lumbar spine BMD during the second year of the study with both 35-mg DR groups showing significantly greater increases than the 5-mg IR group (Fig. 2). The least squares mean percent change from baseline in lumbar spine BMD at week 104 was 5.5 % (95 % CI, 5.0 to 6.

In the UV-visible spectrum, a strong, broad peak at about 420 nm was observed for AgNPs (Figure 1). The specific and characteristic

features of this peak, assigned to a surface plasmon, has been well documented for various metal nanoparticles with sizes ranging from 2 to 100 nm [27, 28]. CHIR99021 The silver nanoparticles were formed by adding 10 ml leaf extracts with aqueous AgNO3. After 6 h, the color of the mixed solutions of leaf extract and AgNO3 changed from pale green to deep brown indicating the formation of silver nanoparticles. The change in color of the reaction medium as an effect of presence of reducing potential substances present in the leaf extract. The color of the silver nanoparticles are due to excitation of surface plasmon vibration in silver nanoparticles and this color change is due to redox reaction between the leaf extract and AgNO3. AgNPs have free electrons, which give rise to a surface plasmon resonance AZD8055 absorption due to the combined vibration of electrons of the metal nanoparticles in resonance with the light wave. [29] It is observed from Figure 1 that the synthesized AgNPs display a clear and single surface plasmon resonance (SPR) band located at 420 nm which confirms the reduction of silver ion to metallic silver. In contrast, AgNO3 shows maximum

absorbtion at 220 nm, whereas the leaf extract shows two absorbtion peaks at 450 and 650 nm. The sharp absorption peak of AgNPs indicates that the formation of spherical and homogeneous distribution of silver nanoparticles. The similar observation was reported using leaf extract

of Delonix elata mediated synthesis of silver nanoparticles [26]. XRD analysis of AgNPs Further, the synthesized silver nanoparticles were confirmed using XRD analysis. Figure 2 shows that the XRD patterns of natural dried silver nanoparticles synthesized using leaf extract. A number of Bragg reflections with 2θ values of 24.48°, 30.01°, 33.30°, 34.50°, 46.30° sets of lattice planes are observed which may be indexed to the (111), (200), and (220) faces of silver respectively. The XRD pattern thus clearly illustrates that the silver nanoparticles formed in this present synthesis are crystalline in nature and having face centered cubic (fcc) crystal Cytidine deaminase structure. The XRD pattern confirmed the presence of Ag colloids in the sample. A strong diffraction peak located at 30.01 was ascribed to the (111) facets of Ag. The intensive diffraction peak at a 2θ value of 30.01° from the (111) lattice plane of fcc silver unequivocally indicates that the particles are made of pure silver. Two additional broad bands are observed at 34.50°, 46.30° correspond to the (200) and (220) planes of silver respectively (Figure 2). The Braggs reflections were also observed in the XRD pattern at 2θ = 24.48° and 32.50°. The assigned peaks at 2θ values of 24.48°, 29.0°, and 32.