PA), we investigated the regulation mechanism for urokinase and t‐PA expression and their effect on galanin activation. Additionally, we studied the effect of activated galanin on angiogenesis. To determine the effect of cell density, we measured the expression levels of urokinase and t‐PA using real‐time PCR and plasminogen/gelatin zymography in a cell culture. The urokinase expression increased under both high cell density and presence of cell membrane fractions. However, urokinase increments induced by conditioned medium were low. These results indicate that expression of plasminogen activators is regulated by cell membrane factors. We used tumor‐bearing mice to clarify the expression of plasminogen activators and galanin activation. Real‐time PCR showed that urokinase was substantially higher in the central parts of tumors compared to the periphery, and this was confirmed by plasminogen/gelatin zymography. To evaluate the biological effect of plasminogen activators on tumor growth, we used tranexamic acid as a plasminogen inhibitor. Tranexamic acid decreased galanin (1–20) and the hemoglobin content of tumors and suppressed tumor growth. Additionally, galanin had no effect on the hemoglobin content of tumors derived from cells lacking GALR2. These results demonstrate the regulation of urokinase expression in tumors through progalanin activation in extracellular compartments, and confirm that galanin plays a role in angiogenesis.Small‐cell lung carcinoma releases progalanin. The released progalanin is activated via a nonclassical processing pathway, being processed into an active form of galanin (1–20) by plasmin in extracellular components. Plasmin is produced from plasminogen activators. To clarify the regulation of progalanin via plasminogen activation by urokinase and tissue‐plasminogen activator (t‐ HbhemoglobinHRPhorseradish peroxidaseMMPmatrix metalloproteinaseRIAradioimmunoassaySCLCsmall‐cell lung carcinomat‐PAtissue‐plasminogen activatoru‐PAurokinaseTumors are regulated by several mechanisms, such as growth factors, tumor factors, and hormonal peptides. The tumor tissue environment continues to change during tumor growth Plasmin, a serine protease, is a tryptic protease. There are many reports on the effects of plasmin on tumor growth, invasion, and metastasis, particularly its effect on angiogenesis and cell migration Some ectopic hormone‐producing tumors express neuropeptides 2 and 95% air at 37 °C. When cells reached 80% confluency, they were dispersed with 0.05% (w/v) trypsin in phosphate‐buffered saline (PBS) and harvested at a concentration of 104 cells·mL−1.Human SCLC cell lines SBC‐3A ad libitum. Lights were automatically turned on at 08:00 h and off at 20:00 h.Animal experimental protocols were approved by the ethics committee of the University of Shizuoka and performed in accordance with the guidelines for the Care and Use of Laboratory Animals of the University of Shizuoka. Male KSN/slc mice were purchased from Nippon SLC Ltd.  and housed under standard laboratory conditions  with access to tap water and food 4, 105, or 106 cells/10 cm2. After 24 h, the culture media and cells were collected. The culture media were used to assess plasminogen activator activity with fluorescent substrates and plasminogen/gelatin zymography. The cells were used to measure plasminogen activator mRNA expression, via real‐time PCR.The SBC‐3A cells were seeded in culture dishes at densities of 10g for 30 min. Supernatants were stored at −20 °C and used as conditioned media. The cell membranes were prepared as described below. Briefly, SBC‐3A cells were collected with a scraper. The cells were homogenized using a Teflon glass homogenizer. The homogenate was centrifuged at 1000 g for 30 min and the supernatant collected. The supernatant was centrifuged at 30 000 g at 4 °C for 30 min, and the resulting pellets were used as the cell membrane fraction.Conditioned media were prepared as follows: 50% confluent SBC‐3A cells were cultured for 48 h, after which the cultured media were centrifuged at 3000 SBC‐3A cells were cultured in media containing the conditioned media or the cell membrane fractions for 24 h, after which the cultured cells were collected. The plasminogen activator mRNA expression in the cells was measured via real‐time PCR.6 cells/100 μL Matrigel) subcutaneously on the dorsal side. When the tumors reached a diameter of 7–10 mm, they were excised. The tumors were separated into two parts: central and peripheral. For hemoglobin content measurement, western blot analysis, and plasminogen/gelatin zymography, the samples were homogenized in a protein extraction buffer  using a Polytron homogenizer. The homogenates were centrifuged at 3000 g for 30 min, and the supernatant was used as the tumor extract. The protein concentration of the extract was measured using the Coomassie Brilliant Blue method, with BSA as the standard. For real‐time PCR analysis, total RNA was extracted from the tumor with TriPure Isolation Reagent .Tumor samples were obtained as previously described 6 cells/100 μL Matrigel) subcutaneously on the dorsal side. To suppress plasmin activity, tranexamic acid was administered intraperitoneally at a dose of 30 mg·day−1. When the tumors reached a diameter of 7–10 mm, they were excised. To determine the molecular forms of galanin, the collected samples were heated in a boiling water bath for 10 min in 0.1 m acetic acid. After cooling, the acetic acid concentration was increased to 1 m and samples were homogenized in a Teflon pestle homogenizer. The homogenates were then centrifuged at 3000 g for 30 min. Supernatants were lyophilized and used as tumor extracts. Tumor extracts were eluted on a Sephadex G‐50 fine column  using 1 m acetic acid as the eluent. The eluate was collected in 0.9 mL volumes and lyophilized. The lyophilized fractions were dissolved in the standard RIA diluent. The column was calibrated with BSA , lysozyme (14.4 kDa), human galanin (3 kDa), and dibutyryl cAMP .KSN/slc mice were implanted with SBC‐3A cells (1 × 106 cells/100 μL Matrigel) subcutaneously on the dorsal side. To suppress plasmin activity, tranexamic acid was administered intraperitoneally at a dose of 30 mg·day−1. Stimulation galanin was injected, at a volume of 50 μL and a concentration of 50 ng/50 μL in saline, directly into the tumor. We used a saline control. Ten days after the cells had been implanted, the tumors were collected, weighed, and extracted using homogenizer, for the measurement of the hemoglobin content.KSN/slc mice were implanted with SBC‐3A or SBC‐3A‐Y cells . Genomic DNA was removed with DNase I. cDNA was synthesized using ReverTra Ace  according to the manufacturer's instructions. Specific primers were designed to amplify human t‐PA , human u‐PA , and human β‐actin . Real‐time PCR was performed with Thunderbird SYBR qPCR Mix (Toyobo) using LightCyclerNano (Toyobo) and StepOne systems . The PCR products were evaluated using melting curve analysis.Radioimmunoassay (RIA) was performed at 4 °C as described previously cs analyzer software .Samples (5 μg) of the cell lysates were separated on a 15% (w/v) polyacrylamide gel −1 gelatin. After electrophoresis, the SDS in the gels was removed with Tris/HCl buffer (pH 7.4) containing 2.5% Triton X‐100, then incubated in Tris/HCl containing 12.5 mm MgCl2 buffer for 24 h to allow digestion of the gelatin. The gels were visualized using Coomassie Brilliant Blue R250.We measured plasminogen activator activity using plasminogen/gelatin zymography m Tris/HCl buffer (pH 7.4), after which Pyr‐Gly‐Arg‐MCA  was added to the solution, including the extracts. The solution was incubated at 37 °C for 2 h, and cleaved 7‐amino‐4‐methyl coumarin was measured .We determined plasminogen activator‐like enzyme activity in cell extracts using a Pyr‐Gly‐Arg‐MCA  cleavage assay as follows. The cell extracts were diluted in 50 mm sodium hydroxide, to which were added 20 μL of 2% (w/v) potassium ferricyanide and 20 μL of 0.5% (w/v) sodium cyanide. After 30 min of incubation, Hb concentrations were determined by measuring absorbance at 550 nm.We assessed angiogenesis by measuring hemoglobin (Hb) content. Hb was measured by a slightly modified cyanmethemoglobin method Data are represented as means ± SEM. Tukey's tests were used for statistical analysis program (R).4, 105, or 106 cells/10 cm2. The expression of u‐PA induced by cell membranes, particularly membranes prepared from 106 cells, increased significantly (Fig. We determined the effect of cell seed density on u‐PA and t‐PA expression using real‐time PCR analysis, protease activity, and plasminogen/gelatin zymography. The mRNA contents of u‐PA increased gradually with cell density Fig. B. Additi2 of tumor tissue from each region. The hemoglobin content of the central region was lower than that of the peripheral region, indicating a lower number of blood vessels in the central region (Fig. To evaluate the hypoxic environment, we measured hemoglobin content and HIF‐1 expression. Hemoglobin content was correlated with the number of blood vessels, and HIF‐1 expression was induced under hypoxic conditions. Tumors reaching 7–10 mm were separated into central and peripheral regions, and we collected approximately 2 mmTo determine the expression of plasminogen activators in tumors, we performed real‐time PCR and plasminogen/gelatin zymography. A higher expression of u‐PA mRNA than of t‐PA mRNA was detected in both tumor regions Fig. C. In addWe evaluated tumor growth by measuring cell diameter after implanting small‐cell lung carcinoma cells mixed in Matrigel Fig. A. We usein vitro and in vivo approaches. In the SCLC cell line SBC‐3A, which also expresses u‐PA mRNA, the expression of u‐PA mRNA and u‐PA‐like enzyme activity increased with cell density and tumor factors. We verified this via an in vivo study using SCLC tumor‐bearing model mice. We prepared the central part of the tumor tissue as a hypoxic and malnourished region and the peripheral part under normal conditions. This resulted in higher u‐PA expression in the central than in peripheral tumor region. The mechanism behind this induced u‐PA expression is unclear, but may be more strongly influenced by membrane factors than tumor factors. It is well known that adhesion affects cell condition The plasminogen activation system is composed of two plasminogen activators, t‐PA and u‐PA Neuropeptides mature in intracellular environments such as the Golgi body and secretory vesicles. In some tumor and normal cells, cells released neuropeptides in precursor form The present study showed that GALR2‐deficient SBC‐3A cells did not respond to galanin with an increase in hemoglobin content. This indicates that GALR2 plays an important role in increasing the hemoglobin content, implying that galanin affects angiogenesis via the GALR2 expressed in SCLC cells. There are some reports that GALR2 is expressed in tumors and plays a role in the acceleration or inhibition of tumor growth In summary, we demonstrated that cell membrane factors induce u‐PA expression. The expression of these factors increased with increasing cell density. In addition, u‐PA expression in tumors activated progalanin via plasminogen cleavage. Our results suggest that excessive tumor growth induces progalanin activation via the u‐PA/plasminogen system.HY and KU contributed to the experimental design. HY, RO, and YH performed the experiment. HY wrote the manuscript.Fig. S1. RT‐PCR.Fig. S2. [Ca2+]i response to galanin in SBC‐3A and SBC‐3A‐Y cells.Click here for additional data file.


IV secretion system of Helicobacter pylori (Cag‐T4SS) is composed of ~ 27 components including a VirB8 homolog, CagV. We have characterized CagV and reported that it is an inner membrane protein and, like VirB8, forms a homodimer. Its stability is not dependent on the other Cag components and the absence of cagV affects the stability of only CagI, a protein involved in pilus formation. CagV is not required for the stability and localization of outer membrane subcomplex proteins, but interacts with them through CagX. It also interacts with the inner membrane‐associated components, CagF and CagZ, and is required for the surface localization of CagA. The results of this study might help in deciphering the mechanistic contributions of CagV in the Cag‐T4SS biogenesis and function.The type  DSPdithiobis succinimidyl propionateIFMimmunofluorescence microscopyIPimmunoprecipitationMBPmaltose‐binding proteinRMSDroot mean square deviationT4SStype IV secretion systemTEMtransmission electron microscopyY2Hyeast two hybridHelicobacter pylori (H. pylori) harboring type IV secretion system (Cag‐T4SS) are responsible for the more severe forms of gastric diseases cag‐Pathogenicity Island (cag‐PAI) H. pylori uses this specialized secretion system to translocate the substrate CagA into the host epithelial cells to modulate the host signaling pathways and to induce proinflammatory response Type I strains of tem Cag‐TSS are reAgrobacterium tumefaciens (A. tumefaciens) is composed of 11 VirB proteins (VirB1‐VirB11) and a coupling protein VirD4 The most studied prototypical secretion system, the VirB/D4 T4SS of E. coli, it is predicted to be a VirB8 homolog, an essential component of the VirB/D4 secretion system in A. tumefaciensH. pylori, mutational analysis revealed that CagV is essential for CagA translocation and IL‐8 induction in the host cells In the present study, we have characterized the VirB8 homolog CagV which shares weak sequence homology with its counterpart in other known T4SS. However, on the basis of topological analysis in A. tumefaciens, VirB8 is a bitopic membrane protein and is required for the stability of several other VirB proteins underlining its importance in the biogenesis of the secretion complex cag‐PAI components and compared the findings with its counterpart VirB8 of A. tumefaciens.In H. pylori and mutant strains were grown and maintained as described earlier E. coli cultures were also grown as described earlier All the bacterial strains used in this study are listed in Table E. coli strain BL‐21 (DE3) at 25 °C in LB medium with 0.1 mm IPTG  to induce the expression of proteins in the culture medium. All cag null mutant strains were constructed in H. pylori 26695, as described previously except cagVcagV null mutant strain, mutator DNA was synthesized by overlapping PCR using a cagV upstream fragment containing the first three codons of cagV and the upstream region of cat cassette (using primers DV1 and DV3), the downstream region of cagV containing the termination codon, and the downstream region of cat cassette (using primers DV2 and DV4) and amplified cat cassette (using primers Fcat and Rcat). Finally a linear mutator PCR product was synthesized using primers DV1 and DV2 and phusion polymerase. Next, the resulting linear PCR product was introduced into H. pylori 26695 by natural transformation following a published protocol and selected on chloramphenicol BHI (Brain Heart Infusion) agar plate cagV was performed as described earlier cagV (under cagA promoter)‐containing plasmid was transformed into ΔcagV and expressed in the presence of appropriate antibiotics and tested for CagV expression.All primers used in this study are mentioned in Table cagV was cloned in pET‐28a vector and overexpressed in E. coli strain BL‐21 (DE3). CagV protein band was excised from SDS/PAGE, used for immunization, specificity and titer of rabbit anti‐CagV (α‐CagVr) and mice anti‐CagV antibody (α‐CagVm) were tested by western blotting. Anti‐CagA, anti‐OMP (Outer Membrane Protein), and anti‐HSP (Heat Shock Protein) antibodies were from Santa Cruz, CA, USA . Anti‐MBP antibody was from NEB, USA (Cat. No. E8032L). SDS/PAGE and western blotting were performed as described previously Polyclonal antibodies against Cag proteins such as Cagδ, CagH, CagL, CagE, CagY, CagZ, CagX, CagT, CagM, CagI, and CagF were raised by immunization of rabbit and mice in the laboratory as described previously The present study was approved by the Institutional Animal Ethics Committee‐of Jawaharlal Nehru University (Code no: 23/2007 and 22/2012). The animals  were maintained at Central Animal Facility of the Jawaharlal Nehru University as approved by the Institutional Animal Ethics Committee. After experimental procedures were finished, the animals were maintained until their natural death and every effort was made to minimize their suffering.H. pylori cells was performed as described earlier g in SW‐55 rotor  at 4 °C for 1 h, the supernatant was recovered as cytoplasmic/periplasmic fraction (C/P) and the resulting pellet was recovered as total membrane (TM). Volume of C/P was measured and TM was resuspended in the same volume of PBS. Equal volume of each sample was mixed with 2X‐SDS sample buffer, separated in SDS/PAGE, and subjected to western blotting using an appropriate antibody.Cellular fractionation of the wild‐type Helicobacter pylori cells were immunostained and viewed as described earlier Helicobacter pylori cell extract was used for coimmunoprecipitation study as described previously m EDTA, 2 mm DTT, 1% TritonX‐100, 0.2% sodium deoxycholate, 1 mg·mL−1 lysozyme, and 6 μL of 100X‐protease inhibitor cocktail), sonicated, centrifuged, and the supernatant was collected and precleared with preimmune serum and protein‐A agarose beads . Next, DMP  cross‐linked anti‐CagV antibody with protein‐A agarose beads (20 μL) was added to the precleared supernatant and incubated at 4 °C O/N on rocker. Following brief centrifugation, beads were washed three times with lysis buffer without lysozyme, bound proteins were released by boiling in SDS sample buffer and subjected to western blotting.E. coli cell pellets containing expressed proteins were resuspended in 50 mm Tris‐HCl, pH 8.0, 150 mm NaCl, 2 mm EDTA, 1 mm PMSF, 1% TritonX‐100, 0.2% sodium deoxycholate, 2 mm DTT, and 1 mg·mL−1 lysozyme, lysed by sonication, and centrifuged at 15 700 g for 30 min. The supernatant was diluted with an equal volume of the above buffer without lysozyme (binding buffer), prewashed amylose–agarose beads were added and incubated at 4 °C for 2 h. Beads were washed with binding buffer five times and proteins were eluted with elution buffer , dialyzed against 50 mm Tris‐HCl pH 7.4, 1 mm EDTA, and 5% glycerol, protein concentration was measured using CBXtm kit (Genotech), and analyzed in SDS/PAGE. For pull‐down assay, purified MBP‐tagged CagV and CagF or MBP alone bound to amylose–agarose beads  were mixed with H. pylori cell extract (1 mg·mL−1) prepared in binding buffer , O/N. Next, protein‐bound beads were collected by centrifugation, washed three times with binding buffer, proteins were eluted by boiling in 2X‐SDS sample buffer, separated in SDS/PAGE, and western blotted.For purification of recombinant proteins (MBP‐tagged CagV and CagF), H. pylori cells as described earlier Transmission electron microscopy was performed on an ultrathin section of H. pylori cells were resuspended in 500 μL of lysis buffer . Cells were ruptured by sonication. Thereafter, 0.1% DDM  and 0.2% sarcosine were added to the extract, incubated for 30 min on ice, 5 mm DSP  were added and further incubated on ice for 25 min. The cross‐linking reaction was stopped by adding Tris‐HCl (pH 7.4) to a final concentration of 125 mm, incubated for 15 min on ice, centrifuged at 15 700 g at 4 °C for 15 min, and the supernatant was collected.Plate‐grown fresh H. pylori CagV [(H. pylori‐Cag10) (Uniport ID: Q6VRI3)], A. tumefaciens‐VriB8 (Uniprot ID: P17798), and Brucella suis (B. suis) VirB8 (Uniprot ID: Q7CEG3) was performed using Clustal Omega and the alignment was visualized and analyzed using jalview (v.2.0) to identify conserved regions in the periplasmic domain of CagV Multiple sequence alignment (MSA) of A. tumefaciens‐VirB8 (92‐237 aa) and B. suis‐VirB8 (97‐234 aa) was identified. A multiple template‐based model of the identified region was generated using Modeller (v9.14) A. tumefaciens‐VirB8 (PDB ID: 2CC3) and B. suis‐VirB8 (PDB ID: 4AKZ) were taken as templates gromacs (v5.1) and gromos96 54a7 force field +/Cl−) needed to neutralize the system at pH 7.0. A maximum of 10 000 steps of steepest descent was performed to minimize the energy of the system. Solvent and ionic molecules were equilibrated around the protein under NVT and NPT conditions simultaneously (for 200 ps each), to maintain 300 K temperature and 1 bar pressure. For this step a positional restraint was applied on the protein. Finally, a 70‐ns long unrestrained production MD was run with time step of 2 fs at 300 K and 1 bar pressure. Energy and the co‐ordinates were saved every 10 ps (at every 5000 step) for further analysis. The final step co‐ordinates of CagV obtained after simulation was superimposed on both the chains of A. tumefaciens‐VirB8 , one by one and transformed co‐ordinates were saved and combined to generate the dimer of CagV. Chain Identifier A and B were assigned to the chains. Initial interchain clashes were removed manually by slightly shifting the chains apart and introducing a slight rotational shift in UCSF chimera mdcons package (v2.0). It considers a contact by a cut‐off distance of 5 Å between heavy atoms of two residues of different chains at the interface The sequence of CagV corresponding to the crystallized periplasmic domains of irB8 97‐2 aa was iirB8 92‐2 aa and BirB8 92‐2 aa and Bgromacs tool gmx sasa was used to calculate SASA and the residues having charge between −0.2 and 0.2 were treated as hydrophobic, while others as hydrophilic. The plot of interaction across the interface of final CagV dimer co‐ordinate for A. tumefaciens‐VirB8 and B. suis‐VirB8 was generated using dimplot (v.1.4.5) dcomplex package (http://sparks-lab.org/czhang/complex.html) ucsf chimera  grace software package .The buried solvent accessible surface area throughout simulation at the dimer interface was calculated by subtracting the total solvent accessible surface area (SASA) of the CagV dimer from the sum of total SASA of each individual monomeric units of the dimer. The buried hydrophilic and hydrophobic surface areas were also calculated using the same approach. in silico analysis of the transmembrane domain of CagV and expression of the corresponding gene in E. coli, Buhrdorf et al. predicted that cagV might be a functional virB8 analog H. pylori 26695 into soluble cytoplasmic/periplasmic (C/P) and total membrane fractions (TM). The fractions were separated in SDS/PAGE, western blotted using appropriate antibodies and quantitated  and nonpermeabilized (NP) conditions supported its localization inside the cell  and nonpermeabilized (NP) conditions. As shown in Fig. H. pylori, the CagA‐specific signal was not detected in the ΔcagV under NP condition. However, when IFM was performed under permeabilized condition, the CagA‐specific signal was detected in the ΔcagV cells. These results thus suggest that CagV may be required for the bacterial surface localization of CagA. To further validate the above data, we complemented the cagV function in the ΔcagV, performed IFM, and observed that CagA again reappeared on the bacterial cell surface like in wild‐type H. pylori. We further performed TEM on the wild‐type H. pylori, isogenic ΔcagV and ΔcagV/cagV strains. In agreement with the IFM results, CagA‐specific signals were detected in the cytoplasmic face of the inner membrane along the perimeter in the ΔcagV  juxtaposed by antiparallel β‐sheets   by using ‐236 aa bA. tumefaciens‐VirB8  and the inner membrane‐associated energy‐providing component CagE (VirB4 homolog). Since CagF and CagZ are also inner membrane‐associated proteins like CagE and CagV, we hypothesized that these proteins could also interact with each other. The failure to detect precipitation of these proteins using anti‐CagV antibody could be due to the fact that proteins in a large complex such as T4SS interact with each other with different affinity and during antigen antibody interaction in IP, conformation of the complex might change leading to the dissociation of weakly associated proteins. However, other possibilities cannot be ruled out. It is worth mentioning that interaction between recombinant CagV and GST‐CagZ has been reported earlier H. pylori extract as prey, separately , anti‐CagV antibody failed to coimmunoprecipitate the outer membrane subcomplex proteins suggesting that the interaction between CagV and the outer membrane subcomplex proteins might be through CagX. Previously we have also reported interaction of CagE with the outer membrane‐associated core complex through CagV and CagX following IP using anti‐CagE antibody It is well documented that VirB8 interacts with a number of VirB proteins and helps in the assembly of the VirB/D4 transporter ely Fig.  47. As sact Fig. C. It is A. tumefaciens. However, based on its adaptation of the VirB8 like membrane topology in E. coli, it is considered as a homolog Agrobacterium tumefaciens‐VirB8 plays a key role in the VirB/VirD4 T4SS assembly, substrate transfer, and pilus biogenesis A. tumefaciens‐VirB8 CagV is also an inner membrane protein (Fig. In this study, we have characterized one essential Cag‐T4SS component, CagV, that shares weak sequence similarity with its counterpart VirB8 of ein Fig. A–E.A. tumefaciens‐VirB8 and B. suis‐VirB8 and identified the conserved residues (Fig. A. tumefaciens‐VirB8 and B. suis‐VirB8, a homology model of the periplasmic domain of CagV was generated and found to have similar structure and fold (Fig. Since our initial attempt to identify native CagV dimer failed, we were prompted to perform a comparative sequence analysis of CagV, along with the two of its homologs ues Fig. A. Based old Fig. A. Througold Fig. D.Agrobacterium tumefaciens‐VirB8 has multiple interacting partners like VirB1, VirB4, VirB5, VirB9 etc. Dimerization of a protein provides large interface for multiple protein interactions and stability Agrobacterium tumefaciens‐VirB8 is known to direct the polar localization and stability of several VirB proteins and also stabilizes the secretion system Agrobacterium tumefaciens‐VirB8 interacts with the VirD2 and the single‐stranded T‐DNA substrates, which in turn passage the DNA–protein complex from the cytoplasm to the periplasm A. tumefaciens‐VirB8 requires the energizing ATPase VirD4, VirB4, and VirB11 together with the outer membrane core components VirB7, VirB9 and VirB10 in the periplasm A. tumefaciens‐VirB8, CagV does not interact with the substrate. Nonetheless, Cag‐T4SS substrate CagA interacts with the inner membrane‐associated chaperone CagF and coupling protein Cagβ, respectively et al. demonstrated that CagZ interacts with Cagβ et al. have shown the interactions between CagF and the outer membrane subcomplex proteins et al. also reported an interaction between recombinant CagV and GST‐CagZ cagV function is complemented, CagA regains ability to cross the membrane barrier (Figs ier Figs  and S2. GM, MS, NK, and AK conceived and designed the experiments. NK, MS, AK, and RK performed experiments. GM, MS, NK, AK, and NS analyzed the data. GM and RKT contributed reagents. GM, MS, and NK wrote the manuscript.Fig. S1. Western blots showing specificity of polyclonal anti‐CagV antibody.Fig. S2. IFM showing localization of CagA in wild‐type H. pylori, ΔcagV, and ΔcagV/cagV strains.Fig. S3. SDS/PAGE showing purified MBP‐tagged CagV and CagF.Fig. S4. CagV interacts to the outer membrane subcomplex through CagX.Click here for additional data file.


By comparing the hypoxia-induced elevation in heart rate (HR [bpm]), ventilation (VE [L min−1]) with the change in energy expenditure (EE [W]) at each speed, we were able to determine circulatory and respiratory costs. In a multivariate model combining HR and VE, respiratory costs were 0.44 ± 0.15 W per each L min−1 increase in VE, and circulatory costs were 0.24 ± 0.05 W per each bpm increase in HR . These VE costs were substantially lower than previous studies that ignored the contribution of HR to cardiopulmonary work. Estimated HR costs were consistent with, although somewhat higher than, measures derived from catheterization studies. Cardiopulmonary costs accounted for 23% of resting EE, but less than 5% of net walking costs .Energy expenditure (EE) during walking includes energy costs to move and support the body and for respiration and circulation. We measured EE during walking under three different oxygen concentrations. Eleven healthy, young, male lowlanders walked on a treadmill at seven gait speeds (0.67–1.83 m s The energy cost of walking must include energy expenditure (EE) to move and support the body and to fuel physiological changes, such as increased ventilation and circulation, needed to meet increased metabolic demand. To date, studies of walking cost have largely ignored the costs of ventilation and circulation, focusing instead on the factors known to affect the costs of movement such as walking speed, internal and external work5, gradients7, body mass11, and load carriage15. Locomotor cost is of central importance in human ecology17, behavior19, evolution3, and biomechanics research12, and a full accounting of human walking cost and its determinants requires an understanding of the contribution of cardiopulmonary work to total metabolic cost.Humans’ bipedal walking gait is a defining feature of our lineage, and the metabolic costs of walking have figured prominently in discussions of human evolution and ecology30. Early studies of respiratory cost at rest, measured by having the subject breathe through a long tube to increase the dead space and thus the work needed to breathe, found that ventilation costs in humans at rest were quite low (<1 mlO2 per L VE)27. Subsequent studies reported substantially greater respiratory costs during exercise, though still less than 10% of total exercise energy expenditure30. However, these studies have generally used an experimental design in which respiratory costs are not measured during exercise, but rather during voluntary hyperpnea in which subjects match their respiratory frequency and tidal volume to levels observed during exercise20. The contribution of increased heart rate (HR) is generally ignored, although HR can increase substantially during hyperpnea31 and could contribute substantially to the measured increase in energy expenditure. Further, these studies have typically focused on running and other moderate- or high-intensity exercise. The contribution of cardiopulmonary work to walking cost may be higher, as the total cost of walking is considerably lower32.Respiratory costs have been measured in humans and other vertebrates during rest and exercise2 limits pulmonary O2 diffusion capability, which induces a decrease in arterial O2 saturation (SpO2)34. Under these conditions, pulmonary ventilation (VE) increases within minutes35, followed by increases in HR 36. These responses are generally considered part of the compensatory mechanisms against hypoxia with reduced oxygen delivery to the peripheral tissues. These results suggest that if hypoxic-induced increases in energy cost of ventilation and/or circulation are observed even at resting conditions, differential energy costs during walking under hypoxia would also be observed.Measuring walking costs under hypoxic conditions provides a potential experimental design for measuring cardiopulmonary costs during exercise. At high altitude, and under normobaric hypoxia, a reduction of alveolar POWe developed and tested an experimental model to evaluate the energy cost of ventilation and circulation during walking using acute hypoxic exposure. We used pulmonary ventilation , ΔVE , and ΔHR  in multiple regression.Mean (±SD) values for EE, Vxia Fig. . Both waE and ΔHR , or roughly 1 Watt for every 1 L min−1 increase in VE. This cost is equivalent to 3.3 mlO2 per L VE, assuming 20.1 J per mlO2. Energy expenditure increased with circulation as ΔEE = 0.36 ± 0.04ΔHR , or roughly 1 Watt for every 3 beats per minute increase in HR. Slopes changed less than 3% when the three hypoxia-speed conditions with negative ΔEE values were excluded from analysis  = 2.33, p = 0.036) but ΔHR did not (t(14) = 1.42, p = 0.178). However, when the three hypoxia-speed conditions with negative ΔEE values were excluded from the analysis, both ΔVE (t(11) = 2.87, p = 0.015) and ΔHR (t(11) = 4.65, p < 0.001) were significant, and the fit of the model was very strong . Notably, this multivariate model reduces the estimated individual costs of ventilation and circulation compared to bivariate analyses. Ventilatory costs are approximately 1 Watt for every 2.3 L min−1 increase in VE; circulatory costs are approximately 1 Watt for every 4 beats per minute increase in HR. The fit of this predictive model for all data is shown in Fig. ΔVE and ΔHR  along with VE and HR values at each condition to estimate the energy cost of cardiopulmonary work at rest and during walking under normoxia, moderate hypoxia, and severe hypoxia. At rest, the estimated energy cost of breathing and circulation accounted for approximately one-fourth of total EE across conditions, rising slightly under severe hypoxia compared to normoxia and moderate hypoxia. As walking speed and EE increased, the percentage of EE attributed to cardiopulmonary work decreased under all conditions. This change was similar in moderate hypoxia and severe hypoxia , consistent with hyperpnea studies reporting 2–4 mlO2 per L VE during exercise30. However, HR and VE increase together during exercise  of cardiopulmonary energy cost, when ventilatory and circulatory costs were considered together in our multivariate model. Future studies using forced hyperpnea to estimate ventilation costs should include simultaneous measures of HR in order to assess the potential contribution of circulatory costs.Both breathing and circulation have measureable effects on EE during both resting and walking. While our findings are consistent with studies using hyperpnea at rest to mimic the costs of ventilation during exercise EE Fig.  gives a in vivo measures of the heart’s energy expenditure were conducted by monitoring oxygen concentrations in arterial blood supply and venous return of a catheterized heart37. Catheterization methods produce estimates of 7 W for heart energy expenditure in adult males lying supine, at rest37. Assuming a resting HR of ~60 bpm, this estimate translates to ~7 J per beat. HR cost in our multivariate model was 0.24 ± 0.05 W per bpm, which translates to 14 ± 3 J per beat, twice that of catheterization methods. Given the very different experimental designs, these estimates are reasonably similar. One reason that our approach may produce higher estimates is that our measurements were taken primarily during exercise, which increases blood pressure and stroke volume compared to resting, and presumably increases the energy cost per heartbeat. More work is needed to refine non-invasive estimates of HR cost and to reconcile them with catheterization studies.Measuring cardiopulmonary costs by induced hypoxia, as done here, enabled us to measure the energy expenditure of the heart non-invasively. To our knowledge, the only previous E. Maximum VE in the present study was 59 L min−1, which falls at the very low end of the range examined in most previous works. The lower range of VE in this study may explain why we did not detect the exponential increase in VE cost at higher ventilation rates reported by those studies30.The present study focused on walking, rather than the running or cycling tests typical of previous work on cardiopulmonary cost, e.g., refs 25. These results lend support to analyses of locomotor cost that focus on musculoskeletal energy expenditure, ignoring cardiopulmonary work, e.g., refs Cardiopulmonary effort accounts for a substantial portion of resting EE, approximately 23% in normoxic conditions. In contrast, cardiopulmonary energy expenditure accounts for only 3 to 5% of net walking EE . The small contribution of cardiopulmonary effort to net walking cost is in line with previous work in humans and a range of other vertebrates−1). In our original study41, we found that VO2 and VCO2 in these conditions trended lower . Similarly, the small reductions reported here for EE, which is calculated from VO2 and VCO2, do not reach statistical significance. These results are nonetheless unexpected and we can only speculate regarding the cause of this phenomenon, but there are three general possibilities. One is that these small differences are spurious, reflecting measurement error and the limits of precision in our experimental set up. A second possibility is that the body fueled some small percentage of physiological activity using anaerobic metabolism in these conditions. In this case, the aerobic measures of EE employed here would fail to capture some small portion of total energy expenditure in these (and possibly other) conditions, leading to an underestimation of EE and ΔEE. Third, the body may be adjusting to hypoxic conditions by reducing EE to some unspecified set of physiological activities. Given the small size of the effect (~3% or less of EE), we do not expect that this phenomenon greatly affects the results of the currently analyses. Nonetheless, additional research into this phenomenon is warranted.Of note, we found small (~3%) reductions in EE with moderate hypoxia compared to normoxia at rest and during walking at slow speeds  were male athletes  who engaged in strenuous daily training . Their mean age, height, and body weight were 24 ± 8 years, 174 ± 6 cm, and 70 ± 9 kg, respectively . Before this study, we explained all procedures, possible risks, and benefits of participation to the subjects, and all subjects signed an informed consent form. They were asked to refrain from intense physical activity 2 days before testing and to refrain from drinking any alcohol or caffeinated beverages the day before testing. This study was approved by an ethical committee at the Mount Fuji Research Institute according to the Declaration of Helsinki (No: ECMFRI-03-2014).The present report represents additional data from investigations that were published previously43. They practiced at least three times at several gait speeds to familiarize themselves with treadmill walking while wearing a gas-collection mask. Inspired oxygen concentrations were set at normobaric normoxia (21% room air), moderate hypoxia , and severe hypoxia . Each trial was performed on a different day in random order with a single-blind study design. First, each subject sat on a chair for 10 minutes, then stood for 5 minutes on the treadmill for baseline measurement. Thereafter, he began to walk on the treadmill. As described in our previous study, seven speeds were set incrementally at 0.67, 0.86, 1.06, 1.25, 1.44, 1.64, and 1.83 m s−1, and each speed lasted for 4 minutes44.All experiments were carried out on a motor-driven treadmill, 2.21 m long and 0.88 m wide . During an experiment, the subject was allowed to choose his stride and step frequency freely during walking. Subjects wore underwear, shirts, socks, shorts, and lightweight training shoes2 15.23%, CO2 4.999%, and N2 balance) and room air were used to calibrate the gas analyzer. Inspired and expired gas volumes were measured with a hot wire respiratory flow system. Flow signals were electrically integrated for the duration of each breath to calculate minute ventilation. The expired fractions of O2 and CO2 were analyzed with a zirconium solid electrolyte oxygen analyzer and an infrared carbon dioxide analyzer, respectively. Each oxygen concentration gas was supplied via a 200-L Douglas bag with a hypoxic gas generator system . HR was measured throughout the study with a commercial HR monitor .Pulmonary ventilation .To calculate energy expenditure, EE, at rest and at each gait speed, 46.Energy Expenditure (Watts) = [(3.869 × 2) were averaged for the last 2 minutes of standing prior to the start of walking. During walking, a single sample with an average final 1 minute of physiological data was also obtained.At baseline, all physiological values  was subtracted from values under moderate or severe hypoxia (EEhyp) to calculate a ΔEE value. We then compared ΔEE to the change in ventilation rate, ΔVE = (VE hyp − VE norm) or change in heart rate, ΔHR = (HRhyp − HRnorm) between conditions. First, we examined the change in EE with respect to VE and HR separately, in a bivariate regression model (Ventilation Cost: ΔEE ~ ΔVE. Circulation Cost: ΔEE ~ ΔHR). Next we used multiple regression to test for the independent, additive effects of VE and HR on EE (Cardiopulmonary Cost: ΔEE ~ ΔVE + ΔHR). These regressions were evaluated with the intercept set at 0. This approach assumes that any change in EE between conditions at a given speed is attributable to the change in cardiopulmonary work. This design yielded n = 16 comparisons .To evaluate respiratory and circulatory cost, total walking energy expenditure at each speed (including rest) under normoxia . A P value less than 0.05 was considered statistically significant.All data are presented as mean ± SD. A two-way repeated ANOVA  was conducted for comparison in EE, V


Mock Bacteria ARchaea Community; MBARC-26), composed of 23 bacterial and 3 archaeal strains with finished genomes. These strains span 10 phyla and 14 classes, a range of GC contents, genome sizes, repeat content and encompass a diverse abundance profile. Short read Illumina and long-read PacBio SMRT sequences of this mock community are described. These data represent a valuable resource for the scientific community, enabling extensive benchmarking and comparative evaluation of bioinformatics tools without the need to simulate data. As such, these data can aid in improving our current sequence data analysis toolkit and spur interest in the development of new tools.Generating sequence data of a defined community composed of organisms with complete reference genomes is indispensable for the benchmarking of new genome sequence analysis methods, including assembly and binning tools. Moreover the validation of new sequencing library protocols and platforms to assess critical components such as sequencing errors and biases relies on such datasets. We here report the next generation metagenomic sequence data of a defined mock community ( Similarly, Pabinger et al.11–13 used a mock community to benchmark MEMOSys, a web-based platform for metabolic models. The jumpstart consortium human microbiome project (HMP) data generation working group established a standardized protocol for ensuring high throughput consistency of 16S rRNA gene amplification and sequencing protocols by implementing a synthetic mock community of 21 known organisms, before finalizing their HMP 16S 454 protocol14–16. The HMP DNA and sequence data resources have not only enabled comprehensive characterization of the human microbiota, e.g.17–19, but also the use and development of a variety of advanced analysis tools. For example, chimera screening tools UCHIME and Chimera Slayer3, the OTU construction pipeline UPARSE6–8, and fine-tuned workflows for amplicon gene studies9 used HMP data generated from mock communities.By definition, benchmark studies aim to provide standards that can be used to evaluate the performance of a process. The field of nucleic acid sequencing and sequence data processing has witnessed immense developments towards optimizing the balance of sequencing cost, precision and overall applicability to real-world questions. This progress has routinely relied on experimental setups of defined nature to critically rate novel approaches. In recent years, mock communities have been assisting in a variety of laboratory and computational test experiments, which resulted in quantitative and qualitative evaluation of corresponding studied methods. For example, mock communities were generated for the comparison of DNA extraction methodsMock Bacteria ARchaea Community), is composed of organisms isolated from heterogeneous soil and aquatic environments as well as derived from human, bovine and frog Proteobacteria, Spirochaetes, Thermotogae, Verrucomicrobia and Euryarchaeota. Genome sizes span 1.8–6.5 Mbp, GC contents vary between 28.4–72.7%, and repeat content ranges from 0–18.3% . DNA from Fervidobacterium pennivorans, Thermobacillus composti and Corynebacterium glutamicum was extracted using phenol–chloroform extraction, as described in . DNA from Hirschia baltica was extracted using the Blood and Cell Culture DNA Maxi Kit . DNA from Meiothermus silvanus, Nocardiopsis dassonvillei and Segniliparus rotundus was extracted using the Qiagen Genomic 500 DNA Kit . DNA from Pseudomonas stutzeri was isolated using the Wizard Genomic DNA Purification Kit . DNA from Coraliomargarita akajimensis, Halovivax ruber, Natronobacterium gregoryi and Spirochaeta smaragdinae was extracted using the Masterpure Gram-Positive DNA Purification Kit . All DNA extracts were quantified using the PicoGreen assay and the Qubit 2.0 fluorometer   . Each saCA, USA) .For Illumina library creation, 100 ng of genomic DNA of MBARC-26, brought up to a total of 100 μl using TE, was sheared to 300 bp using the Covaris LE200  and size-selected using AMPure XP beads : 60 μl of beads were added to 100 μl of sample. The sample was then incubated at room temperature (RT) for 5 min. Beads were pelleted using a magnetic particle concentrator (MPC)  until liquid was clear. The supernatant was removed and transferred to a new tube. 30 μl of AMPure XP beads were then added for the second bead size selection. The mixture was pulse vortexed, quickly spun and incubated at RT for 5 min. Beads were pelleted using a magnetic particle concentrator (MPC)  until liquid was clear. The supernatant was then discarded without disturbing the beads and 200 μl of freshly prepared 75% ethanol (EtOH) was added, followed by a 30 s incubation to wash the beads. EtOH was discarded before the wash step with EtOH was repeated for a total of two washes. Afterwards, the sample was placed on a thermocycler  with the lid open and incubated at 37 °C until the beads were dry and residual EtOH had evaporated. The beads were re-suspended in 53 μl of EB buffer , vortexed, quickly spun and incubated at RT for 1 min. Beads were pelleted using an MPC until liquid was clear . 50 μl of supernatant was then transferred to a new tube. The DNA fragment size was assessed using the Agilent Bioanalyzer 2100 High Sensitivity Kit  before proceeding to end repair.The fragments were treated with the Kapa Library Preparation Kit ORIGIN  for the following steps: For end-repair 26 μl MilliQ water, 9 μl 10X End Repair Buffer, and 5 μl End Repair Enzyme were combined in a 1.5 ml tube. The cocktail was vortexed and quickly spun, then stored on ice. 40 μl of End Repair cocktail was added to the 50 μl DNA sample. The mixture was vortexed and quickly spun, before incubation at 30 °C for 30 min in a thermocycler . After incubation, 126 μl of AMPure XP beads  were added to 90 μl of End Repair sample, pulse vortexed, quickly spun, and incubated at RT for 5 min. Beads were pelleted using a MPC until liquid was clear. The supernatant was then discarded without disturbing the beads. The beads were washed twice with 200 μl of freshly prepared 75% EtOH with an incubation time of 30 s. After washing, the sample was incubated at 37 °C in a thermocycler with the lid open until residual EtOH had evaporated. For DNA elution, 17.5 μl of EB buffer was added. The sample was vortexed, quickly spun, and incubated at RT for 1 min, before beads were pelleted on a MPC. 15 μl of supernatant was then transferred to a new tube.For A-tailing, 9 μl of MilliQ water, 3 μl of 10X A-Tailing Buffer and 3 μl of A-Tailing Enzyme were combined in this order in a 1.5 ml tube. The cocktail was vortexed and quickly spun. 15 μl of the A-Tailing cocktail was added to the 15 μl sample. The mixture was vortexed and quickly spun. The samples were then incubated in a thermocycler at 30 °C for 30 min, followed by 5 min at 70 °C.Adaptor ligation was immediately performed thereafter: 9 μl of 5X Ligation Buffer and 5 μl of ligase were combined in a 1.5 ml tube, vortexed and spun. The mixture was pulse vortexed and quickly spun. 14 μl of adaptor ligation cocktail were added to the 30 μl sample, before 1 μl of 18 μM adaptor was added to the ligation mixture for a final concentration of 400 nM. The mixture was incubated in a thermocycler at 20 °C for 15 min.After adaptor ligation, 5 μl of EB Buffer was added to 45 μl of adaptor-ligated sample. The sample was size-selected and washed twice with 45 μl of AMPure XP beads as described previously. After the first clean-up step, the sample was eluted with 52 μl of EB Buffer and 45 μl of supernatant was transferred to a clean tube. After the second clean-up step, the sample was eluted with 25 μl of EB Buffer. 23 μl of supernatant was transferred to a clean tube. The sample was quality-controlled and quantified using an Agilent Bioanalyzer 2100 High Sensitivity Kit.The prepared Illumina library was further quantified by using the Kapa Biosystems next-generation sequencing library qPCR kit according to the manufacturer’s guidelines . The amplification products were run on a Roche LightCycler 480 real-time PCR instrument for quantification . The quantified library was then prepared for sequencing on the Illumina HiSeq sequencing platform . First, the TruSeq paired-end cluster kit, v3, and Illumina’s cBot instrument were used to generate a clustered flowcell for sequencing . Sequencing of the flowcell was performed on the Illumina HiSeq2000 sequencer using a TruSeq SBS sequencing kit 200 cycles, v3, following a 2x150 indexed run recipe  . This reFor PacBio library creation, 5 μg of gDNA was sheared using a Covaris LE220 to generate 2 kb fragments . The sheared DNA fragments were then prepared according to the SMRTbell template preparation kit guidelines . Briefly, DNA fragments were treated with DNA damage repair mix, end-repaired, and 5’ phosphorylated. PacBio hairpin adapters were then ligated to the fragments to create SMRTbell template for sequencing. The SMRTbell templates were purified using exonuclease treatments and size-selected using AMPure PB beads  .Sequencing primers were annealed and v. P4 sequencing polymerase was bound to the SMRTbell templates. The prepared SMRTbell template libraries were then sequenced on a Pacific Biosciences RSII sequencer using v. C2 chemistry and 1x120 min sequencing movie run times . This resulted in 300,584 raw reads .http://jgi.doe.gov/data-and-tools/bb-tools/) to remove Illumina adapters, known Illumina artifacts, phiX, and to quality-trim both ends to Q12. Resulting reads containing more than one ‘N’, or with quality scores (before trimming) averaging less than 8 over the read, or length under 40 bp after trimming, were discarded. Remaining reads were mapped to a masked version of human HG19, dog, cat, and mouse with BBMap (http://jgi.doe.gov/data-and-tools/bb-tools/), discarding all hits exceeding 93% identity. This resulted in 347,963,988 filtered reads with average insert size of 219±43 bp.Illumina shotgun reads were filtered using BBDuk . This resulted in 53,654 quality-filtered subreads with average read length of 1,041±576 bp.23 on May 16, 2016. They include tandem, inverted, flanking, terminal, direct and dispersed repeat types. For phylogenetic tree construction, full-length 16S rRNA gene sequences were aligned using the SINA aligner24 including 10 neighbors at 95% minimum identity for classification against the SILVA, RDP, greengenes, LTP, and EMBL databases25. The alignment was masked using the SILVA-compatible 1,349 Lane mask26. Tree construction was performed using FastTree27.High quality Illumina and PacBio sequences were mapped to their bacterial and archaeal reference genomes using BBMap with parameters bbmap.sh, ambig=toss (Illumina) and mapPacBio.sh, ambig=toss (PacBio), respectively. Numbers of mapped sequences were normalized to the respective whole genome and chromosome lengths of reference organisms . UnmappeFiltered shotgun sequences generated on the Illumina and PacBio platforms are publically available through NCBI (Data Citation 1 and Data Citation 2).To assess the quality of genomic DNA received, we used the PicoGreen assay and the Qubit 2.0 fluorometer . Each sample was quantified in quadruplicate. Samples were pooled at varying ratios to generate the mock community .Both shotgun sequence datasets were screened for adapters, artifacts, according to quality scores , number of ‘N’, read length , and contaminant sequences related to human, dog, cat, and mouse.How to cite: Singer, E. et al. Next generation sequencing data of a defined microbial mock community. Sci. Data 3:160081 doi: 10.1038/sdata.2016.81 (2016).


Information about public gambling attitudes and gambling participation is crucial for the effective prevention of gambling-related harm. This study investigates female and male attitudes towards gambling, gambling participation, and gambling-related harm in the Finnish population aged 15–74.n = 4484) and 2015 (n = 4515). The data were weighted based on gender, age and region of residence. Attitudes were measured using the Attitudes Towards Gambling Scale (ATGS-8). Gambling-related harms were studied using the Problem Gambling Severity Index and the South Oaks Gambling Screen.Cross-sectional random sample data were collected in 2011 (Attitudes towards gambling became more positive from 2011 to 2015. Female attitudes were generally negative, but nonetheless moved in a positive direction except in age groups under 25. Occasional gambling increased among women aged 18–24. Women aged 18–24 and 45–54 experienced more harms in 2015 than in 2011. Both land and online gambling increased among women aged 65–74. Male attitudes towards gambling were generally positive, and became more positive from 2011 to 2015 in all age groups except 15–17. Weekly gambling decreased among males aged 15–17. Gambling overall increased among males aged 18–24. Gambling several times a week decreased among men aged 35–44 and 45–54, and gambling 1–3 times a month increased in the latter age group. Online gambling increased only among men aged 55–64.Attitudes towards gambling became more positive in all except the youngest age groups. Under-age male gambling continued to decrease. We need to make decision-makers better aware of the continuing growth of online gambling among older people and women’s increasing experiences of gambling-related harm. This is vital to ensure more effective prevention. Gambling opportunities have increased significantly in the past two decades, and at the same time gambling-related harm has grown into a public health concern and social issue worldwide. In many countries including Finland , AustralAccording to the theory of planned behaviour (TPB) , 14, behGambling can also bring about different types of harms , 26. ThePublic attitudes can provide importance guidance for governments as they seek to develop responsible gambling policies . AnalyseThis study compares attitudes towards gambling, gambling participation and gambling-related harm in Finland in 2011–2015, separately for men and women and different age groups. In addition, we use PGSI and the South Oaks Gambling Screen (SOGS) to produce a more comprehensive profile of gambling-related harm.The data for this study came from two cross-sectional Finnish gambling surveys in 2011  and 2015The data were obtained using computer-assisted telephone interviews. In 2011, a landline or mobile phone number was available for 11,129 respondents. An additional 120 phone numbers were determined by sending mail invitations to 4870 participants without a phone number. It turned out that 757 phone numbers were invalid. A further 1724 respondents could not be reached after a maximum of 10 attempts, while 4279 people refused to participate. Five respondents discontinued the interview after it had begun [In 2015 , 103 perTwo demographic correlates were drawn from the population register: the respondent’s sex  and age, which was recoded into seven groups . In 2011 and 2015, there were 2367  and 2210  female respondents aged 15–74, respectively. The corresponding figures for men were 2117  and 2305 .Attitudes were measured with the 8-item version of the Attitudes Towards Gambling Scale (ATGS-8) . ATGS-8 Past-year gambling frequency  and online gambling (yes/no) were examined using categorical variables.In 2011 and 2015 gambling-related harm was measured using PGSI  and SOGSη2) was used for ANOVA’s, and phi coefficient (ϕ) and Cramer’s V (ϕC) for categorical variables to measure the strength of the examined associations. Thresholds for η2 were as follows: small (0.01), medium (0.06) and large (0.13) [Two datasets were combined and a new variable reflecting the year was created. The data were analysed with SPSS version 22.0 . Before proceeding with the data analysis, variables were screened for possible outliers and statistical assumption violations with SPSS Frequencies, Explore and Plot procedures. We did not detect univariate outliers that were considered to require deletion. The estimates of skewness, kurtosis and normal probability plots did not indicate significant deviations from normality either . Mean die (0.13) .F = 73.99, p = .001, η2 = .018; F = 50.81, p = .001, η2 = .012, respectively) from 2011 to 2015  except 15–17 and 18–24  in 2015 in all age groups except 15–17.Overall, attitudes towards gambling became more positive among both women and men aged 18–74 . There was an increase in the proportion of males who gambled 1–3 times a month (p ≤ .001). Women who gambled less often than monthly increased (p ≤ .005) in the age group 18–24, while non-gambling decreased (p = .009) among those aged 65–74 (Table p = .021) and several times a week decreased (p ≤ .001), while non-gambling decreased among those aged 18–24 (Table p ≤ .05). Gambling 1–3 times a month increased in the latter age group (p ≤ .001).Past-year gambling frequency did not change statistically significantly from 2011 to 2015 among women aged 18–74. Among men, it did (p = .040) and from 27.2 to 30.1% among males (p = .036) between 2011 and 2015. However, a statistically significant increase in online gambling was only seen among women aged 65–74 . In 2011, 9.2% of female respondents experienced a single harm and 4.3% experienced two or more harms. These figures were higher in 2015: 9.7% experienced a single harm and 7.1% experienced two or more harms. In 2011, 14.6% of males experienced one harm and 13.3% two or more harms. The figures in 2015 were 15.3 and 12.6%. The differences were not statistically significant for males.Past-year gambling-related harm increased among women aged 18–74 (p ≤ .005). However, the proportion of males who endorsed the items “chasing losses” and “claiming to be winning money gambling, but weren’t really”, decreased (p ≤ .005).“Gambling more than one intended to”, “chasing losses” and “feeling guilty” were the three most common harms in both genders Table . The prop ≤ .005; Table p = .014), and the proportion of those aged 18–24 without any harms increased (p = .039) (Table Age group analyses showed that the proportion of two or more harms increased among women aged 18–24 and 45–54 between 2011 and 2015 (ed p = .09 (Table Attitudes towards gambling became significantly more positive in Finland from 2011 to 2015. Female attitudes, though, were still unfavourable: only women aged 25–34 took a positive view on gambling in 2015. Men aged 18–54 had a generally positive attitude in 2011, and by 2015 the age group 55–64 also took a positive view. Overall these results show a clear tendency towards more favourable gambling attitudes and towards a narrowing of gender differences – a major departure from earlier results in Finland, and from results in the UK and Australia , 40.The exceptionally positive attitudes that we found in comparison with the UK and Australia are probably explained by a complex interplay of several factors, such as gambling environment, gambling exposure, gambling types and gambling resources . PerhapsAnother possible explanation for the change in attitudes is the increased public exposure to gambling during the past decade , 43. TodPeople in Finland are also exposed to gambling through marketing campaigns in which gambling operators are keen to emphasise that profits from gaming are used for good causes: “Gambling for the public good”, as one of the slogans says. This has been going on for decades and may well go a long way towards explaining the overall positive attitudes. The liberalisation and normalisation of gambling in general may also be conducive to more positive attitudes towards gambling. In general, in 2011 people in Finland tended to express their views more strongly than was in 2010 the case in the UK . This maGambling frequency remained largely unchanged despite the change in attitudes, yet significant changes were observed within age groups. In a bid to protect young people from potential gambling-related harms, the Finnish government raised the gambling age limit from 15 to 18 years in 2010–2011. This immediately brought a reduction in the prevalence of gambling and problem gambling , 46. OurThe prevalence of problem gambling is typically highest among young males , 8, 30. In older age groups, frequent gambling decreased among women aged 35–44 and 45–54, and occasional gambling increased in the latter age group. This latter trend was already seen in 2007–2011 , 46. In The growth of female gambling seems to be a fairly universal phenomenon , 52, 53.Women have been reported to regard the online internet platform as a safe place to gamble . Online The literature on older individuals’ online gambling as well as on gender differences in online gambling is scarce . In geneTPB provides one possible explanation for the trends we observed in Finnish women’s attitudes and participation in gambling , 14. TheThe question raised by the findings of our study is this: Have men in Finland now reached the point where the excitement and novelty value of gambling has begun to fade? Has male gambling reached saturation point at the same time as women are just beginning to join the bandwagon? Or is the growth of permissive attitudes an indication of an increased prevalence and intensity of gambling, as proposed by the total consumption model , a trendIn both males and females the three most common gambling-related harms in our study were “gambling more than one intended to”, “chasing losses” and “feeling guilty”. This is consistent with the findings of a previous Finnish study , which rIt is noteworthy that SOGS and PGSI items measuring guilt and lending money produced quite widely differing results. Based on SOGS, 6.2% of the respondents reported feelings of guilt, while the corresponding PGSI figure was only 2.4% . FurtherThe conceptual framework of harmful gambling recently proposed by Browne et al. , 68 listOur 2011 and 2015 datasets were collected by different organisations: the first by market research company Taloustutkimus, and the second by Statistics Finland. This may explain the differences in the response rates, which were below the national average in the first survey and over the average in the second. This adversely affects the comparability of our results . TypicalWith the exception of females aged 15–24 and males aged 15–18, attitudes towards gambling became more positive among Finnish women and men from 2011 to 2015. During this period, gambling participation increased most noticeably among females. Our findings for 2015 show for the first time an increase in gambling-related harm among females in Finland.More research is needed on gambling and gamblers, especially women’s gambling motivations. Specific focus must be given to gambling-related harm and gambling-related factors, such as the gambling environment, gambling exposure and gambling types. This is crucial to developing more effective policy measures and to improving gambler protection, prevention and harm reduction efforts.


Sechium edule, which served the purpose of both reducing and capping agent. The designed AgNPs were characterized using UV-Vis spectroscopy, XRD, FTIR, HR-TEM, and TGA techniques. The formation of AgNPs was also confirmed using electrochemistry, which to the best of our knowledge has never been reported before for biosynthesized nanoparticles. The antileishmanial potential of AgNPs was examined on the clinical isolates of Leishmania donovani promastigote cells in an in vitro experimental setting. A dose dependent killing activity of the AgNP was observed with an IC50 value of 51.88 ± 3.51 µg/ml. These results were also compared using commercially available drug, miltefosine. Furthermore, the clinical applicability of AgNP, as antileishmanial agent was proven by testing them against normal mammalian monocyte cell line (U937). The results were statistically analyzed and no significant toxicity of AgNPs on the normal mammalian cells was observed.Nanotherapeutic agents (NTA) play a crucial role in clinical medicine, if their unique properties are well understood and well exploited. In this direction, we report synthesis and characterization of highly potent phytofabricated silver nanoparticles (AgNPs) using  Leishmania is amongst one of the most neglected diseases across the globe. So far, 350 million people in 88 tropical and subtropical countries are living under threat of this disease2. Clinically leishmaniasis is characterized in three different forms viz. cutaneous, muco-cutaneous, and visceral form depending on protozoan spp. responsible for its cause3. Among all the different forms of this disease, cutaneous is more prevalent; however, effects of visceral form are more life threatening5. Albeit certain medications are available to control the disease but their high cost, parenteral drug administration (except miltefosine), narrow spectrum effect, and associated severe side effects limit their usage6. For instance, pentavalent antimonial, once considered a paradigm of standard drug has become incapable of mitigating the disease due to evolution of resistance in parasitic strains7. Miltefosine, another gold standard drug, is incapable of treating visceral leishmaniasis in patients suffering from HIV8. Emergence of resistance towards available antileishmanial drugs has brought in the imperative need for the development of new therapeutics that should not only be cost effective, broad spectrum but also safe and within the reach of underprivileged people who are more vulnerable to leishmaniasis.Leishmaniasis, an emerging disease caused by parasitic protozoan of genus 11. In recent years, nanomedicine, an anticipated ambitious field of nanobiotechnology, has defined the application of nanomaterials in theranostic domain12. Various well established conventional methods are known for synthesizing nanoparticles, however, their usage for biomedical applications is limited due to cellular and environmental toxicity13. In order to overcome these limitations, biosynthesis has played an indispensable role by offering advantage of being simplistic, non-toxic, benign, and commercially viable green approach to obtain nanoparticles14. Owing to exceptional optical and biocompatible properties, AgNPs have found their applications in widespread domains, such as bio-imaging, gene and drug delivery, sensing, and antimicrobial medications to ward off pathogenic microbes15. In few reports, AgNPs have been used as a carrier molecule for drugs against some spp. of Leishmania16. These reports are interesting; however, the strategy followed requires additional drug conjugation and characterization step which limits its rigorous application in treating leishmaniasis. Therefore, synthesizing biocompatible AgNPs which show comparable antileishmanial activity would be interesting to attempt. It is also, possible to anticipate that these NTAs would be much cheaper compared to the commercially available drugs. Amongst numerous biosynthetic approaches, plant extract mediated synthesis is most preferred because they are readily available; possess vast range of phytochemicals, and allow safe handling. However, there are limited reports on AgNP being phytofabricated and used as NTA for curing leishmaniasis. Development of a standard drug is usually very exhaustive procedure, as it involves multiple steps and takes several years. Moreover, some of these drugs also exert cytotoxicity towards non-target cells and have narrow spectrum effects on parasite8. Therefore, phytofabrication could be an approach which may mitigate aforementioned issues and offer a straight forward method to produce highly potent NTA. Inspired by this, we tried to synthesize AgNPs in a simple experimental setting using S. edule fruit extract which contains several potential reducing and capping agents with an objective to find better NTA against leishmaniasis.Nanobiotechnology as a budding field has witnessed outstanding progress in generating nanomaterials and incorporating them for widespread biotechnological applicationsS. edule fruit. These AgNPs were then characterized using various techniques such as; UV-Visible spectroscopy, XRD analysis, FTIR spectroscopy, HRTEM imaging, electrochemistry, and TGA. Further, these AgNPs were studied for their antileishmanial potential using clinical isolates of L. donovani. Schematic representation of NTA preparation and its antileishmanial activity against L. donovani is shown in Figure S. edule extract mediated AgNPs were used as a NTA against L. donovani and the designed nanoparticles were electrochemically characterized which has not been reported so far for any phytofabricated nanoparticles.Herein, we propose a systematic procedure to enable facile and economic preparation of AgNPs by using aqueous extract of 3 and S. edule extract in equal ratio. Figure S. edule extract without AgNO3 was recorded, where no SPR band at 435 nm was observed as shown in Figure 3 without addition of S. edule extract was tested under similar experimental conditions and interestingly again no absorbance was evident at 435 nm  to pale yellow (between 1–5 hr) to yellow (after 12 hr) and finally to yellowish brown was observed after completion of the reaction  + 0.014 (±0.001) [time] with the correlation coefficient of 0.972 which delineates the significance of Figure max18, however, this relation is only valid till 21 hr because after that no change was observed in absorbance at λmax values. The slope of the calibration plot was found to be 0.014 with RMSD <7%, indicating highly reproducible synthetic procedure of AgNP synthesis.The kinetics of AgNP formation was analyzed using UV-Vis spectroscopy and the obtained spectra is shown in Figure e Figure . Figure 19. The crystallite size (D) of AgNPs was calculated by using Debye – Scherrer equation  and biosynthesized AgNPs (b). For sample (a) the broad peak at 3288 cm−1 can be assigned to -OH stretch of alcohols and phenolic compounds, 2930 cm−1 to C-H stretch of alkanes, similarly 1634 cm−1, 1360 cm−1; 1251 cm−1 and 1025 cm−1 can be assigned to C = O stretch of amides, CH3C-H bend of alkanes, and = C-O-C symmetric stretch of aromatic amides, -CH3C-H bend of alkanes, and = C-O-C symmetric stretch of aromatic ethers, C-O stretch of aromatic alcohol, respectively20. Likewise, for sample (b) the 3283 cm− 1 band can be attributed to -OH stretch of alcohols and phenolic compounds, 2918 cm−1 to C-H stretch of alkanes, 1742 cm− 1 to -C = O stretch of esters, 1624 cm−1 to N-H bend of amines, 1532 cm−1 and 1373 cm−1 to N-O symmetric and asymmetric stretch of nitro compounds; and 1219 cm−1 and 1026 cm−1 to =C-O-C symmetric and asymmetric stretch of aromatic ethers. A few variations in the form of peak shift, peak disappearance, and appearance of new peaks were observed in FTIR spectra for the phytofabricated AgNPs. The shift in bands was observed from 3288 to 3283 cm−1, 2930 to 2918 cm−1, 1634 to 1624 cm−1, 1360 to 1373 cm−1, 1251 to 1219 cm−1, and 1025 to 1026 cm−1 which is most likely due to the involvement of phytochemicals in reduction of silver ions and stabilization of AgNPs due to their capping. It is interesting to note the that two new bands 1742 cm−1 and 1532 cm−1 which correspond to C=O stretch and N-O symmetric stretch, respectively appeared for sample (b). We anticipate that the appearance of 1742 cm−1 band could be due to oxidation of aromatic alcohol (e.g. polyphenols) into C=O containing aromatic compound (e.g. Quinones). It has been reported that S. edule fruits are rich in flavonoids (polyphenols)21, which most likely assisted the reduction of Ag+ ions into Ag° in this case, eventually forming AgNPs. We also anticipate that the reduction of amino acids  present in S. edule fruit extract20 resulted in the formation of nitro amine compound i.e., band at 1532 cm−1 which eventually assisted in AgNP stabilization. The involvement of the compounds present in fruit extract in the formation of AgNPs was also confirmed by an additional control experiment, where AgNPs were synthesized by using an earlier reported chemical reduction method23. The FTIR analysis spectrum obtained for chemically synthesized AgNPs, sample (c) is shown in Figure n = 5) which appeared in case of biosynthesized AgNPs, sample (b) (green curve). The peaks observed at 1301 cm−1 and 1137 cm−1 can be assigned to S=O stretch, peak at 961 cm−1 to S-O stretch, and 1045 cm−1 to C-F stretch. These characteristic peaks correspond to the functional groups present in nafion24 which in this case assisted in the stabilization of chemically synthesized AgNPs. This clearly suggests that the peaks observed in case of sample (b) are merely due to compounds present in the S. edule fruit extract.Further, we characterized the AgNPs using FTIR spectroscopy in order to understand the involvement of phytochemicals including macromolecules like proteins, carbohydrates, etc. in their formation. Figure S. edule extract. Further, the average particle size distribution  (black curve). In order to confirm that the peak at +0.21 V arose merely due to Ag0→Ag+, we recorded LSVs with increase in the scan rates between 300 and 500 mV/s Interestingly, the peak currents were directly proportional to scan rates, indicating the surface confined electrochemical process due to AgNPs attached onto the GCE surface. A linear plot for AgNPs oxidation with scan rates was obtained having the regression equation as follows: Ipa = 2.996 (±0.253) + 0.005 (±0.006) [scan rate], with a correlation coefficient of 0.978 (n = 5), indicating high stability of the synthesized nanoparticles. This was also confirmed by performing a negative control experiment, where bare GCE was scanned under the similar potential window under similar experimental conditions. In this case, no peaks were obtained even at higher scan rates, indicating peaks in the earlier case are merely due to the oxidation of AgNPs (Ag0→Ag+) attached onto the electrode surface. It is worthy to mention here that, this is the first report where an electrochemical method has been applied for precise and ultrafast (<30 s) characterization of the AgNPs which has not been reported so far. These results may pave way towards application of this method for quick characterization of other metallic nanoparticles prepared using biological processes.We also confirmed the synthesis of AgNPs using linear sweep voltammetry (LSV). For this purpose, the nafion modified glassy carbon electrode (GCE/AgNPs/Naf) surface was used as working electrode. Figure 29. The predominant loss in AgNPs’ weight started from 200 °C and continued till 450 °C, however, complete weight loss was observed at 500 °C. The overall TGA analysis clearly shows that these AgNPs are reasonably stable up to 80 °C, suggesting their potential application in photo-thermal therapy as NTA30. However, in order to develop a successful NTA other properties and factors should also be considered.After characterizing the AgNPs by various aforementioned techniques, we further studied their thermal stability using TGA Figure . A ceramL. donovani strain isolated from clinical samples was studied using MTT assay. The result of the MTT assay is presented in the form of percentage cell viability which was calculated by using equation , indicating significant cytotoxic effect of AgNPs. In order to confirm this phenomenon, we evaluated AgNP’s cytotoxicity over a range of concentrations, from 10 to 150 µg/ml. It was interesting to note, that with increase in AgNPs concentration there was a decrease in percentage viability of L. donovani, suggesting a dose dependent killing action of AgNPs  −0.992 (±0.074) [AgNP] with the correlation coefficient of 0.983 and RMSD <5.41%, (n = 3) indicating a highly reproducible data in terms of the cytotoxic effect of AgNPs. To confirm the detreimental effect of AgNP, a negative control experiment was performed where cells were not treated with AgNPs. In this case the percentage cell viability was 98.10 ± 2.2% (n = 3), indicating that the cell death in the earlier case was merely due to the killing effect of AgNPs. Further, we evaluated the IC50 value of AgNPs which was found to be 51.88 ± 3.51 µg/ml (n = 3). It is worthwhile to discuss that the IC50 value obtained in our case is comparable with the IC50 value of chemically synthesized AgNPs which has been assayed against L. tropica31. This indicates that the phytofabricated AgNPs synthesized in our case have similar potency to that of chemically synthesized nanoparticles and thus, they can be used as a powerful therapeutic agent.For this purpose, firstly the cytotoxic effect of 100 µg/ml AgNP was tested against the parasite promastigotes. The percentage cell viability observed in this case was 35.21 ± 4.03% s Figure . A calib33. In the view of this important issue, we further investigated the effect of AgNPs on human monocyte U937   −0.608 (±0.066) [AgNP] with the correlation coefficient of 0.942 and RMSD <5.24%, (n = 3). Further, to confirm that AgNPs have no toxic effect on monocytes, we tested their effect even at a higher concentration of 200 µg/ml  whereas, for miltefosine it was merely 59.02 ± 1.12% (n = 4) . This result was also confirmed by microscopic imaging of the monocytes after AgNPs treatment with suitable positive (miltefosine) and negative controls (untreated). It is evident from the bioimaging results that the number of dead cells (red circle) after AgNPs treatment  was procured from SRL India and fresh S. edule fruit was purchased from market complex at Indian Institute of Technology Guwahati, Assam, India. Sodium phosphate monobasic, sodium phosphate dibasic, and potassium chloride for PBS preparation; sodium bicarbonate, 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), M199 media, RPMI-1640 media, 3--2,5-diphenyltetrazolium bromide (MTT) dye, miltefosine, and penstrep antibiotic required for parasite culture were supplied by Sigma-Aldrich, USA. Fetal bovine serum (FBS), antibiotic and antimycotic solution for mammalian U937 cell line, and dimethyl sulphoxide (DMSO) was provided by HiMedia, India. The L. donovani (BHU 1081) strain was provided by Prof. Shyam Sundar, Banaras Hindu University, India and monocyte (U937) cell line was procured from National Centre for Cell Science, Pune, India. Deionized water from Milipore unit  at 18.2 MΩ was used to prepare all the reagents and solutions.Silver nitrate (AgNOS. edule fruit was rinsed twice with tap water followed by deionized water to remove unwanted dirt and epiphytes. 100 g of fruit was roughly cut into large chunks after removing its peel and blended into fine paste. 120 ml of deionized water was added and the paste was centrifuged at 5000 rpm for 5 minutes. The supernatant was filtered using Whatman filter paper (grade 1) and the clear filtrate was stored at 4 °C for further use. Equal volumes (100 ml) of fruit extract and 1 mM aqueous silver nitrate solution were mixed and allowed to react at various temperatures under constant stirring  in dark. The optimized temperature was found to be 90 °C (data not shown). Reaction was continued for 28 hours (optimized) and samples were extracted in between the process to monitor the progression of reaction with time by measuring absorbance in UV-Vis spectrophotometer. Once, the nanoparticle synthesis was complete, reaction mixture was centrifuged  at 4500 rpm for 20 minutes and the pellet was washed thrice with de-ionized water and ethanol successively. Post centrifugation pellet was dried at 75 °C (overnight) in a hot air oven (Labline) and stored in air tight vessel.Fresh +) present in reaction mixture into AgNPs (Ag0) by scanning the aliquots from 300 to 700 nm wavelength range at different time intervals.UV-Vis spectrophotometer (Carry 100 Bio) was used to determine the bio-reduction process of silver ions , where, XRD analysis was performed at 2θ Bragg’s angle by maintaining the range between 30° to 80° with a scan rate 3° per minute.S. edule extract, biosynthesized AgNPs, and chemically synthesized AgNPs was carried out with Perkin Elmer FT-IR spectrometer Spectrum Two and data was recorded between wavenumber ranging from 500–4000 cm−1.The FTIR analysis of The DLS analysis of phytofabricated AgNPs was performed by using Beckman Coulter: Delsa Nano C to analyze their hydrodynamic radius and dispersity of the synthesized nanoparticles.Shape, size, and dispersity analyses of phytofabricated AgNPs were performed with HR-TEM (JEOL JEM-2100F TEM). Samples were prepared by drop casting the well dispersed AgNPs (purified by centrifugation) onto the surface of copper grid (200 mesh) and allowing it to dry at 37 °C for 2–3 hrs.vs. Ag/AgCl using a potentiostat/galvanostat  in 0.1 M PBS. In this case, the AgNPs-Naf modified glassy carbon electrode (GCE) (area 0.07 cm2), Ag/AgCl (in saturated KCl), and a platinum (Pt) wire were used as working, reference, and counter electrodes, respectively.EC analysis of prepared AgNPs was carried out by sweeping the potential in LSV between −0.2 and 0.5 V Netzsch, STA449F3A00) and result was shown in the form of temperature vs. percent weight loss plot.Thermal stability and the weight loss analysis of synthesized AgNP was carried out using TGA (L. donovani (BHU 1081) obtained from a patient suffering from visceral leishmaniasis was cultured using procedure reported in our earlier publications35. The cells were cultured in M199 medium, supplemented with all essential nutrients, such as sodium bicarbonate salt, penstrep antibiotic and heat inactivated 15% FBS to enable proper growth of promastigotes. T25  culture flasks with filter cap were used to allow parasitic growth and these flasks were maintained at 25 °C in a BOD incubator (Scigenics Orbitek). Promastigote cultures were instigated at 2 × 106 cells/ml and allowed to grow for 3 to 4 days after which they were sub-cultured under similar conditions. These cultures were regularly analyzed under inverted microscope  for their health and number and once the media was consumed it was replenished by the fresh media.The clinical isolates of in vitro conditions. These cells were maintained at 37 °C in a 95% humid atmosphere and 5% CO2 in a CO2 incubator  and cultured in RPMI media supplemented with sodium bicarbonate salt, 15% heat inactivated FBS, antibiotic and antimycotic solution, etc. Similar to parasite cultures, these cells were also checked for their health and confluency under inverted microscope.Monocyte U937 mammalian cell line was used as a cellular target to investigate the cytotoxicity of AgNPs against normal cells under 37 and for this purpose, L. donovani was used as model microorganism. Briefly, promastigotes were cultured in T25 tissue culture flasks and maintained at 25 °C in an incubator. These cells were then seeded in distinct wells containing 100 μl of M199 media at a final density of 2 × 106 cells/well in a 96 well microtiter plate. After overnight incubation, the cells were treated with miltefosine (IC50~25 µM), as positive control, untreated cells were used as negative control, and cells treated with NTA i.e., AgNP as test sample in separate experiments. The treated cell samples were incubated overnight at 25 °C and all the experiments were performed in triplicates. Post incubation, cells in microtiter plate were centrifuged (Sigma 3–30 K) at 4500 rpm for 45 minutes and media was discarded to obtain the cells in the form of pellet. After centrifugation, 180 μl of MTT reagent (0.5 mg/ml) was added into each well and the plate was incubated again at 25 °C in dark for 4 hrs. After this, MTT was washed off and the formazan crystals were solubilized in DMSO (100 μl/well). Reduction of MTT was measured by recording the absorbance at 570 nm by using a microtiter plate reader (BioTek Synergy HT).The cytotoxicity analysis was done using MTT assay


The clinical course of idiopathic pulmonary fibrosis (IPF) varies widely. Although the GAP model is useful for predicting mortality, survivals have not yet been validated for each GAP score. We aimed to elucidate how prognosis is related to GAP score and GAP stage in IPF patients.CO measurement. Patients were stratified based on GAP score (0–7): GAP score Group 0 (n = 26), Group 1 (n = 150), Group 2 (n = 208), Group 3 (n = 376), Group 4 (n = 317), Group 5 (n = 138), Group 6 (n = 39), and Group 7 (n = 8).The Korean Interstitial Lung Disease Study Group conducted a national survey to evaluate various characteristics in IPF patients from 2003 to 2007. Patients were diagnosed according to the 2002 criteria of the ATS/ERS. We enrolled 1,685 patients with IPF; 1,262 had undergone DLp < 0.001, respectively). Survival time in Group 3 was lower than those in Groups 1 and 2 , and higher than those in groups 4, 5, and 6 . Gender, age, and DLCO (%) differed significantly between Groups 2 and 3. All four variables in the GAP model differed significantly between Groups 3 and 4.Higher GAP score and GAP stage were associated with a poorer prognosis  contains supplementary material, which is available to authorized users. Idiopathic pulmonary fibrosis (IPF) is a specific form of diffuse interstitial lung disease (DILD) that mainly occurs in adults over the age of 50 . It is aCO [%]). These four variables are commonly measured at the initial visit and are easily followed up. This system has helped clinicians to predict prognosis and decide on management strategies. Although this GAP model is simple-to-use for predicting mortality, prognoses have not yet been evaluated for each GAP score. The purpose of our study was to validate, using national survey data, how prognosis is related to GAP score and GAP stage in patients with IPF.Previous studies have shown that age, gender, lung function change, radiological pattern, histological variability, dyspnoea, cough, pulmonary artery hypertension, amount of elastic fiber, and some molecular biomarkers are associated with prognosis –10. SomeThe study involved patients who had been diagnosed with idiopathic interstitial pneumonia (IIP) at 54 university and teaching hospitals between January 1, 2003 and December 31, 2007. At each hospital, pulmonary specialists  had confirmed the diagnoses, and data were reviewed by the Scientific Committee at the Korean Academy of Tuberculosis and Respiratory Diseases. IPF was diagnosed on the basis of the 2002 criteria of the American Thoracic Society/European Respiratory Society (ATS/ERS) . Initialn = 501) were excluded from the study, as were patients who had not undergone pulmonary function testing (PFT) that included DLCO measurement (n = 423). Ultimately, 1,262 patients were included in the study: 760 at GAP stage I, 455 at stage II, and 47 at stage III , percentage predicted FEV1 (FEV1 [%]), total lung capacity (TLC), percentage predicted TLC (TLC [%]), DLCO, and percentage predicted DLCO (DLCO [%]). In addition, we evaluated patients’ C-reactive protein (CRP) levels, and examined their blood for the positivity of antinuclear antibody (ANA) and rheumatoid factor (RF). The composite physiologic index (CPI), which is a predictive model for IPF prognosis, was calculated as Well et al. reported [http://www.ild.or.kr/).In total, 2,186 patients with idiopathic interstitial pneumonia (IIP) were registered; of these, patients with other forms of ILD than IPF  (0–3 points). We then divided the patients on the basis of GAP score (Groups 0–7): Group 0 (n = 26), Group 1 (n = 150), Group 2 (n = 208), Group 3 (n = 376), Group 4 (n = 317), Group 5 (n = 138), Group 6 (n = 39), and Group 7 (n = 8). In the physiological category, the “cannot perform” classification (3 points) of DLCO measurement had not been recorded in the data used. For this reason, the total GAP score of 8 was not investigated in the current study. Additionally, we excluded patients with total GAP scores of 0 (n = 26), and 7 (n = 8), as these two groups contained much fewer patients than the other groups. The characteristics in Group 0, which contained only women who had never smoked, were significantly different from those in the other groups.Total GAP score was calculated using the method suggested by Ley et al   was used to compare continuous variables, and Bonferroni’s correction was used for To compare the GAP score groups in terms of survival times, Kaplan-Meier survival analysis and the log-rank test were used. In addition, multivariate analysis was conducted with Cox proportional hazard model. C-statistic was also performed for the GAP model at 1-year, 2-year, and 3-year. When performing the survival analysis, we censored the following conditions: (1) still alive at last visit (at last visit date), (2) lost to follow-up loss and (3) had undergone lung transplantation (at surgery date). Statistics were analysed using SPSS™ Version 20 . An adjusted p-value less than 0.05 was regarded as statistically significant.p < 0.001). Although the patients in Group 1 had experienced the longest duration of respiratory symptoms at diagnosis, and those in Group 6 had experienced the shortest, this was not statistically significant (p = 0.133). With regard to smoking status, 83.3 % of patients in Group 6 were ever-smokers; the equivalent values in Groups 1 and 2 were 58.7 and 50.5 %, respectively. Furthermore, smoking duration and amount were higher in Group 6 than in the other score groups . Patients with a higher GAP score tended to have been diagnosed using the clinical method rather than surgical lung biopsy. Specifically, the proportion of clinically diagnosed patients was 87.2 % in Group 6, whereas it was 22.0 % Group 1. The percentages of ANA and RF positivity did not differ significantly among the groups . Increased CRP level was significantly associated with higher GAP score (p < 0.001). CPI also tended to increase as GAP score increased (p < 0.001). The mean value of CPI was significantly different between Group 3 and Group 4, although there was no significant difference between Group 2 and Group 3 after Bonferroni’s correction. The mean follow-up duration of the study population was 19.0 ± 16.0 months.There were 1,228 patients with a GAP score from 1 to 6. The baseline characteristics of these patients are summarized in Table CO (%) were, respectively, 85.6 and 75.8 %, while in Group 6 the values were 55.5 and 31.9 %. ABGA also differed significantly among groups. Resting pulmonary oxygen tension (PaO2) was highest in Group 1, and higher GAP score was significantly associated with lower pulmonary oxygen tension (p < 0.001). In terms of radiological findings, the groups did not differ in any parameter other than reticular pattern.We investigated pulmonary function, ABGA results, and HRCT findings in IPF patients Table . In Group = 0.004, p < 0.001, and p = 0.021, respectively). Although the proportion of patients who suffered dyspnoea of exertion increased as GAP score increased, this association was not statistically significant.Co-morbidities and initial presenting respiratory symptoms are shown in Additional file p < 0.001). At GAP stages I and II (Groups 1–5), Group 3 differed significantly from all other groups in terms of cumulative survival . The causes of death are shown in Table All GAP variables showed significant association with prognosis except gender (G) Table  and b. AGroups 1–, Group 3CO (%) differed significantly between Groups 2 and 3, and all four variables in the GAP model differed significantly between Groups 3 and 4.Table The GAP model is simple to use in planning treatment or providing prognosis information to IPF patients. However, prognosis in relation to individual score groups have not been studied until now. This study attempted to undertake external validation of the GAP model in a relatively large cohort of IPF patients. Herein, we found that GAP score groups differed in terms of survival: in particular, survival in Group 3 patients differed from the other stage I groups, as well as the stage II groups.2 at max exercise. However, it did not make clear that gender was significantly associated with mortality. Furthermore, it was too complex to use in a clinical setting, and cardio-pulmonary exercise testing was essential to calculating the score. Wells et al. [1 (%), and DLCO (%); these factors are determined using pulmonary function testing (PFT). Physicians could calculate CPI using PFT results only, rendering CT findings unnecessary in predicting prognosis. Besides these models, du Bois et al. [For a long time, clinicians who care for IPF patients have been struggling to make accurate prognoses, because IPF is a heterogeneous disease that lacks a validated predictive model , 15. Mans et al.  then pros et al.  developes et al.  used bioCO can be replaced by HRCT fibrosis score in the GAP model (CT-GAP model) [Ley et al. developed the GAP model in 2012. Its straightforward nature has allowed the GAP index to be widely studied, –28 and iP model) .p < 0.001).Interestingly, the duration of respiratory symptoms at diagnosis was longest in Group 1 and shortest in Group 6, although this was not a significant difference. This may be due to variations in individual perception of respiratory symptoms . HiwatarThe most common cause of death in IPF patients is respiratory failure, which results from the progression of lung fibrosis, rather than comorbidities . FurtherIn the present study, prognosis in Group 3 differed significantly from that in the other score groups, as shown using Kaplan-Meier analysis. This result suggests that the GAP score of 3 could be divided from the other stage I scores, thus creating a more refined prognostic system. Although the GAP model is simple to use and has proven effective in other chronic ILDs, the staging system amounts basically to a rough grouping of the GAP scores ; the GAP stages I, II, and III were designed to have lowest 40 % risk, middle 40 % risk, and highest 20 % risk, respectively. In our study, Group 3 differed significantly from the other stage I groups, and from the stage II groups, in terms of all four predictive variables that contribute to GAP score; the only exception was FVC (%), which did not differ between Groups 2 and 3. Although the mean value of lung function results was similar, age and gender composition were significantly different between Group 2 and 3. Ley et al.  mentioneCO measurement. We also excluded patients who had not undergone PFT that included DLCO. This considerable number of excluded groups may have led to selection bias. Finally, the Korean ILD group did not investigate the radiologic scoring of fibrosis, dyspnea scale, and pulmonary artery hypertension, which could have provided more information on prognosis in IPF patients.Our study did have some limitations. Firstly, patients were diagnosed using the 2002 ATS/ERS guidelines, which place more importance on surgical lung biopsy results than do the 2011 updated guidelines. Also in this study, the HRCT findings were not quantified as scores, or classified according to updated guidelines. In addition, in radiologic findings, traction bronchiectasis was not investigated. However, Ley et al.  created In summary, this study was designed as a national validation study to evaluate GAP scores in relation to the prognosis of patients with IPF. On the basis of our study results, we suggest that Group 3 could be separated from other GAP stage I patients and that reporting this score separately would improve mortality prediction.