2b). Immediately after being produced and over 3 weeks of storage, both formulations 4 (16 μg/mL) and 5 (11 μg/mL) presented a monomodal distribution (in terms of volume and number of particles), with a mean diameter less than 1 μm (Fig. 3a and b). The volume-weighted mean diameters (D4,3) observed in formulations 4 and 5 were 208 and 163 nm, with span values of 1.397 and 1.271, respectively. Span values are related to the particle distributions. Low span values indicate

a narrowed particles size distribution (more homogeneous sizes). Thus, formulation 5 may be considered to be more homogeneous because it presented a narrower particle size distribution than that of formulation AZD5363 cell line 4. The results of the cumulative distribution show that 90% of the nanocapsules in formulations 4 and 5 exhibited diameters (D0,9) smaller than 126 and 127 nm, respectively ( Fig. 3c and d). After 3 weeks of storage, no changes were observed in the mean diameter of the nanocapsules in formulations 4 and 5, and both formulations were considered physically stable. However, formulation 4 was chosen for further experiments because of the higher concentration of bixin measured, in addition to having satisfactory size and distribution characteristics.

Neratinib The concentration of bixin in the nanocapsules affected the physical characteristics of the nanocapsules, such as their diameter, particle-size distribution and stability, hence, the results of our preliminary

tests show that there is a limit of bixin solubilisation. Determining the particle size distribution with respect to particle volume allowed us to verify the presence of particles with diameters greater than 1 μm. This verification is practically void when analysing the distributions in terms of number of particles because these particles (diameter >1 μm) are present in small amounts. The bixin nanocapsule suspension was prepared in triplicate CYTH4 with a mean bixin concentration of 16.92 ± 0.16 μg/mL. Venturini et al. (2011) produced lipid-core nanocapsules with higher concentration of indomethacin ethyl ester (1 mg/mL) using the same formulation components, which indicated that the type of compound which is encapsulated affected the amount incorporated into the formulation. However, the concentration of bixin was not considered low because food dyes are normally used in low concentrations. The quantity of a compound that can be incorporated into nanoencapsulated systems is affected by the type of formulation and technique used (Ribeiro et al., 2008, Tan and Nakajima, 2005 and Yuan et al., 2008). In the aqueous phase of the bixin nanocapsules formulation, the bixin concentration was below the limit of detection of 0.231 μg/mL (None bixin peak was found). The mean total concentration of bixin in the formulations was of 16.92 ± 0.16 μg/mL.

, 1990). The non-covalent interactions involve intermolecular hydrogen bonding between unsubstituted regions and/or ionic forces between ionising substituents of AX chain (Fincher & Stone, 1986). While the gas retention ability of rye dough can be related to high viscosity of its aqueous phase (Hoseney, 1984 and Meuser and Suckow, 1986), the water economy in dough selleck chemicals llc and

bread is mainly controlled by absorbing properties of both starch and AX (Drews & Seibel, 1976). However, the AX water-binding potential may affect water availability for starch in the rye dough and bread, and thus its rate of retrogradation and bread staling (Gudmundsson, Eliasson, Bengtsson, & Åman, 1991). It has been shown that the oxidatively cross-linked AX usually exhibit an increased viscosity and water binding

capacity (Izydorczyk et al., 1990, Meuser and Suckow, 1986 and Vinkx et al., 1993). This may be explained by an increase in their asymmetric conformation, in which bridging structures such as di-ferulic acid, ferulic acid-tyrosine and ferulic acid-cysteine, reinforce gelation and swelling capacity. The AX water-binding ability, however, decreases upon addition of endo-(1 → 4)-β-d-xylanse (endoxylanase) that depolymerises their chains (Aulrich & Flachowsky, 2001). Nevertheless, a relatively small adjustment in AX macromolecular characteristics may cause significant changes in their physicochemical properties, oxyclozanide Selleck Y-27632 which influence the characteristics of wheat- and rye-based products (Cyran and Saulnier, 2012 and Redgwell et al., 2001). The physicochemical properties of AX, and subsequently, their functionality in wheat and rye flours and end-products are mostly dependent on

a polymer concentration, molecular size and proportion and spatial distribution of various β-d-xylopyranosyl residues over the backbone. Generally, they include the un-substituted and mono-substituted with single α-l-arabinofuranosyl residues mainly through O-3 and a little at O-2 as well as di-substituted residues through O-2,3 linkages ( Izydorczyk and Biliaderis, 1995 and Vinkx and Delcour, 1996). It is assumed that the distribution of the α-l-arabinofuranosyl residues along the xylan backbone, which alters an asymmetry of macromolecule, may have a greater importance in determining the AX properties than its substitution degree. Furthermore, the AX interactions with other cell wall components mediated through other minor side substituents, particularly feruloyl, α-d-glucuronopyranosyl and acetyl residues may contribute to modification of their physicochemical characteristics ( Fincher & Stone, 1986).

Ferreyra et al. (2007) also observed higher antioxidant activity during the initial maturation stages of strawberry cv. Selva. The reduction in antioxidant capacity can be in part explained by the decrease in caffeic acid levels; since this phenolic acid has been shown to possess high antioxidant potential ( Marinova & Yanishlieva, 1992). In addition, Tabart, Kevers, Pincemail, Defraigne, and Dommes (2009) GDC0199 observed a higher antioxidant potential from catechins, such as gallocatechin and epigallocatechin, in comparison to other phenolic compounds or ascorbic acid. Enzymes corresponding to ADH and AAT act in

a coordinated process in the reduction of aldehydes to alcohols, as well as the transfer of an acetyl group from acetyl-CoA and an acyl group from acyl-CoA to the corresponding alcohols during the biosynthesis of ester volatiles ( Aharoni et al., 2000). Ethyl butanoate, ethyl acetate, and butyl acetate relative content increased during fruit development ( Fig. 3). The increase in the levels of ester volatiles was expected since the aroma of fruit tends to be enhanced during maturation ( Folta and Davis, 2006 and Pérez et al., 1996). Among other volatiles, methyl butanoate, 2-methyl butyl acetate, and hexyl acetate presented less variation throughout development. In agreement click here with Pérez et al. (1996) who observed an increase in AAT enzyme activity in strawberry cv. Oso Grande and Tudla

during a maturation stage corresponding to stage 4 of the current experiment, the increase in ester production was accompanied by an increase in ADH and AAT transcript accumulation ( Fig. 2E and F). Collectively, results of the present study provide supporting evidence of a synchrony between transcription

and physiological responses Sclareol related to sensorial and nutritional changes in strawberry. In addition, these genes involved in cell wall polysaccharides solubilisation (Exp, PL, PME, PG, β-Gal), biosynthesis of phenolic compounds (PAL, ANS), ascorbic acid (LGalDH, GLDH) and aromas (ADH, AAT), emerge as candidate markers for postharvest studies associated with nutritional and sensorial quality changes. To CAPES and CNPq for financial support. “
“The use of propolis is ancient in traditional medicine dating back at least to 300 BC (Ghisalberti, 1979). Today, this resinous bee product continues to be used worldwide, and a broad spectrum of biological activities for propolis has been reported, including anticancer, antioxidant, anti-inflammatory, antibiotic, and antifungal activities (Burdok, 1998 and Marcucci, 1995). The biological effect of propolis is attributed to its natural bioactive chemicals, such as polyphenols, flavonoid aglycones, phenolic acid and their esters, caffeic acid and their esters and phenolic aldehydes and ketones (Orsˇolic & Basˇic, 2003). Recently, attention is being focused on the anti-cancer activity of propolis.

The final sample included 491 women (n = 866 urine samples). Urinary BPA concentrations were available from 407 women at the first prenatal visit and 459 at the second prenatal visit; 375 women contributed BPA measurements at both prenatal visits. Demographic characteristics

were similar between women who provided one urine sample and women who provided two urine samples (data not http://www.selleckchem.com/products/jq1.html shown). Bilingual study staff conducted interviews in Spanish or English at each prenatal visit to collect maternal information on demographic characteristics, general dietary habits, and health. During the second prenatal visit, study staff also administered a modified version of the Block food frequency selleck chemical questionnaire to document participants’ dietary nutritional intake throughout the pregnancy (Harley et al., 2005). Spot urine samples were collected in polypropylene urine cups and aliquoted into glass vials. Samples were stored at − 80 °C until shipment to the CDC in Atlanta, GA for analysis. Concentration of total (free plus conjugated) species of urinary BPA was quantified

using automated online solid-phase extraction-high performance liquid chromatography-isotope-dilution tandem mass spectrometry using previously validated methods (Ye et al., 2005). Analytical runs included quality control (QC) samples (~ 3 μg/L and ~ 10 μg/L), which were analyzed with standards, blanks, and study samples. The coefficients of variation of repeated measurements of the QC materials ranged between 3.9 and 5.8%, depending on the concentration. An analysis of field blanks showed no detectable BPA contamination using our collection protocol; an analysis of reagent blanks indicated no BPA contamination during the laboratory sample processing. The limit of detection (LOD) was 0.4 μg/L. Concentrations below the LOD for which a signal was detected were reported as measured. Concentrations below the LOD with no signal detected were randomly imputed Phosphatidylinositol diacylglycerol-lyase based on a log-normal probability distribution

using maximum likelihood estimation (Lubin et al., 2004). Although some previous studies of BPA have accounted for urine dilution by adjusting urine concentrations by creatinine (Braun et al., 2011 and Calafat et al., 2008), this may not be appropriate particularly in populations undergoing rapid physiologic changes, such as pregnant women, due to high intra-individual variability in creatinine concentrations (Boeniger et al., 1993). Furthermore, as reported by Mahalingaiah et al. (2008), creatinine adjustment may not be appropriate for organic compounds such as BPA which are glucuronidated in the liver and eliminated by active tubular secretion. Other factors may also confound creatinine concentrations (e.g., muscularity, urine flow, age, exercise, diet, and diurnal variation) (Mahalingaiah et al., 2008).

2, Fig. 3, Fig. 4 and Fig. 5). In general, the very large height:diameter ratios of young stands are underestimated by the models (Fig. 2, Fig. 3, Fig. 4 and Fig. 5), except for BWIN and Silva for pine growing at Litschau ( Fig. 5b, e). The regression coefficients and the plots indicate that the age trend for spruce in Arnoldstein is underestimated by Silva ( Fig.

2e). On the other hand, both Moses (Arnoldstein and Litschau) and Prognaus (Arnoldstein) underestimate the age trend for pine ( Fig. 3 and Fig. 5). All four models on both sites confirmed the hypothesis that dominant trees have lower height:diameter ratios than mean trees. The differences between height:diameter I-BET-762 cost ratios of dominant and average trees are larger for spruce than for pine for both observed and predicted values ( Fig. 2, Fig. 3, Fig. 4 and Fig. 5). With respect to the 80:1 reference line indicating stand stability, the following can be seen from the figures: for spruce in Arnoldstein (Fig. 2a), the dominant trees are almost all below the 80:1 threshold

and the mean tree is above the threshold. This pattern is predicted well by all four growth models. A similar pattern is observed for spruce in Litschau, although here the deviations of the growth models from the observed values were larger (Fig. 4). Only Prognaus classifies the plots reasonably well with respect to the stability Cilengitide price threshold ( Fig. 4d). For pine, the performance of BWIN and Silva is good and many plots are correctly classified with respect to the 80:1 threshold. However, BWIN and Silva do tend to overerestimate height:diameter ratios for stands 40-years and younger ( Fig. 5b, e). Prognaus yields acceptable results, whereas Moses underestimates the height:diameter ratios, in particular those of young stands ( Fig. 5c). From Table 10 the following can be observed with respect to stand density: an increase of 100 units of SDI corresponds to an increase of height:diameter ratios of 4.9 and 7.9 for dominant trees and of about 20 units for mean stems for spruce and pine. Predicted effects range from 1.2 units and 26 units for dominant trees and from 9.5 to 32 click here units for the mean stem. For

both spruce and pine, BWIN and Moses overestimate the effect of density, while Prognaus and Silva underestimate the effect of density. For the mean stem, predicted effects are 0.5–2.0 times as high as the observed effects. For dominant trees, the predicted effects are 0.15–5.3 times as high as the observed effect. Fig. 6 compares the height:diameter ratios predicted by the forest growth models to the reference equations of Stampfer (1995). The height:diameter ratios obtained from the forest growth models are in most cases higher than the reference equations. The largest discrepancies are found for spruce and pine on poor sites, where the height:diameter ratios predicted by Silva and BWIN are lower than the reference equations for almost all diameters.

, 2012). Species with high fecundity, small seeds capable of long distance dispersal and short generation times – characteristic of many pioneer tree species – are more likely to both adapt and migrate more quickly (Aitken et al., 2008) than those producing few, large seed. Hence, when designing connectivity networks and strategies, attention needs to be paid to dispersal mode. At a large scale, connectivity between different biotic elements of both natural and cultivated landscapes that cover environmental gradients and in particular steep ecological clines Cilengitide ic50 and areas with recent environmental change,

will increase the long-term ability to sustain large populations, allow for migration and maximise in situ adaptation potential

( Alfaro et al., 2014, Dawson et al., 2013 and Sgrò et al., 2011). Today, most restoration efforts focus explicitly on restoration of the tree component of forest ecosystems, perhaps because trees form the basic habitat matrix, facilitating the occurrence and evolution of other less prominent organisms (cf. Lamit et al., 2011). However, during their growth and development, trees themselves interact with and depend on many other species –pollinators and seed dispersers, as well as herbivores, and symbiotic organisms such as mycorrhizal fungi or nitrogen-fixing bacteria. There is also increasing evidence that the genetic buy CHIR-99021 variation in one species affects that in another species, resulting in complex co-evolutionary processes within entire ecosystems (community genetics; mafosfamide cf. Whitham et al., 2003 and Whitham et al., 2006). In some cases, species and genotype relationships may have significant impacts on successful establishment of a population ( Ingleby et al., 2007 and Nandakwang et al., 2008), for example, by ameliorating negative impacts of abiotic or biotic stresses such as herbivory ( Jactel and Brockerhoff, 2007). Restoration should, as far as possible, create appropriate conditions to foster re-establishment of the interactions and associations between species and genotypes. This should improve success rates

for restoration, and promote associated biodiversity benefits. Overall, higher species and genetic diversity are known to improve ecosystem stability, resilience, productivity and recovery from climate extremes, which is of increasing importance under environmental change (Gregorius, 1996, Elmqvist et al., 2003, Reusch et al., 2005, Thompson et al., 2010, Alexander et al., 2011a, Isbell et al., 2011, Sgrò et al., 2011, Kettenring et al., 2014 and Alfaro et al., 2014). Despite an accumulation of experience of ecosystem restoration over recent decades, it is still common to measure the success of restoration efforts primarily in terms of the number of seedlings planted or their survival in the short term (Menges, 2008 and Le et al., 2012).

Forensic parameters were calculated for all samples (n = 19,630) and for all 23 markers of the PPY23 kit. To this end, DYS389II alleles were encoded by the difference, henceforth labeled DYS389II.I, between the total repeat number at DYS389II and the repeat number at DYS389I. DYS385ab haplotypes were treated as single alleles thereby ignoring the internal order of its two component alleles. Forensic parameters were calculated for the study as a whole and for meta-populations defined according to the continental or ethnic origin of the samples (see above). In particular, allele frequencies and haplotype

frequencies were estimated using the counting method. Single-marker genetic diversity (GD) was calculated as GD=n1−∑pi2/(n−1), following Nei [13] and [14], where n and www.selleckchem.com/products/PF-2341066.html pi denote the total number of samples and the relative frequency of the i-th allele, respectively. Haplotype

diversity (HD) was calculated analogous to GD. Match Compound C probability (MP) was calculated as the sum of squared haplotype frequencies. The discrimination capacity (DC) was defined as the ratio between the number of different haplotypes and the total number of haplotypes. To benchmark the practical utility of the PPY23 panel for forensic casework, all haplotype-based analyses were repeated for various subsets of Y-STRs, namely the MHT (9 loci), SWGDAM (11 loci), PPY12 (12 loci) and Yfiler marker panels Chlormezanone (17 loci). The Yfiler and PPY23 panels also were compared to one another after confining both panels to Y-STRs with an amplicon length <220 bp. The extent of

population genetic structure in our data was assessed by means of analysis of molecular variance (AMOVA). More specifically, genetic distances between groups of males were quantified by RST, thereby taking the evolutionary distance between individual Y-STR haplotypes into account [15] and [16]. The DYS385ab marker was not included in the AMOVA because it does not allow easy calculation of evolutionary distances. Samples carrying a deletion, a null allele, an intermediate allele (i.e. an incomplete repeat unit), a duplication or a triplication at one or more markers were excluded from the AMOVA (n = 705, 3.6%), leaving 18,925 haplotypes for analysis (Supplementary Table S2). RST values resulting from continental grouping were compared among the PPY23, Yfiler, PPY12, SWGDAM, and MHT panels. Multidimensional scaling (MDS) analysis served to visualize differences in Y-STR genetic variation between populations and was based upon pairwise linearized RST values for PPY23, that is RST/(1 − RST). MDS is commonly used to investigate genetic similarities between populations and has been described in detail elsewhere [17]. First, MDS analyses were performed for one to 10 dimensions considering either all 129 populations or the 68 European populations alone.

Further, this virus is amenable to assays in a 96-well format with excellent Z′-factors, can be used at very low infectious doses if required, has modest instrument requirements, and was successfully used to

MK-2206 price assess the effect of both antibodies and siRNAs directed against EBOV in a proof-of-concept study. Vero E6 (African green monkey kidney, ATCC CRL-1586) (Earley and Johnson, 1988) and 293 (human embryonic kidney) cells were maintained in Dulbecco’s modified Eagle medium (DMEM; Life Technologies) supplemented with 10% fetal bovine serum (FBS; Life Technologies), 2 mM l-glutamine (Q; Life Technologies), and 100 U/ml penicillin and 100 g/ml streptomycin (PS; Life Technologies) and grown at 37 °C with 5% CO2. An

additional transcriptional unit was inserted into a full-length clone plasmid (pAmp-rgEBOV) (Shabman et al., 2013) containing a cDNA copy of the EBOV genome (strain Mayinga, accession SB203580 in vitro number AF086833.2) using standard cloning techniques (Fig. 1A). The open reading frame for a codon-optimized Firefly luciferase (luc2, Promega) or eGFP was then inserted into this additional transcriptional unit. Detailed cloning strategies can be found as Supplementary material. Rescue was performed as previously described (Hoenen et al., 2012). Briefly, Vero cells were transfected with 250 ng of full-length clone plasmid and expression plasmids for the EBOV proteins NP (125 ng), VP35 (125 ng), VP30 (75 ng) and L (1000 ng) as well as T7 polymerase (125 ng). 24 h post transfection the medium was exchanged, and 7 days post-transfection 1 ml of supernatant was

passaged onto fresh Vero cells for growth of a virus stock. This stock was harvested upon development of CPE. The genomes of the rescued viruses were fully sequenced, with no unwanted mutations being identified. Stock titers were determined by CPE-based TCID50 assay (see below). Infections were performed as previously described (Hoenen et al., 2012). For time-course analysis of luciferase expression infections were performed in 6-well format on until ice, and the supernatant was removed and cells scraped into 1 ml cold PBS at the indicated time-points after shifting the cells to 37 °C. 400 μl of these cells were spun down for 5 min at 1000g and 4 °C, and the pellet was resuspended in 200 μl 1x passive lysis buffer (Promega). Luciferase activity was measured in a GloMax-Multi Microplate Multimode Reader (Promega) 10 min after adding 100 μl lysate (equivalent to approximately 200,000 cells) to an equal amount of BrightGlo (Promega) in an opaque white 96-well plate.

3). These results suggest that KRG prevents Dex-induced apoptosis in MC3T3-E1 cells in a dose-dependent manner. Apoptosis is a regulated cellular suicide mechanism that was characterized by nuclear condensation, cell shrinkage, and DNA fragmentation. The increase in MC3T3-E1 cell viability upon treatment with both KRG and Dex suggests that KRG modulates the expression of cell death-related selleck chemicals llc genes. Caspases, a family of cysteine proteases, are the central regulators of apoptosis. To examine the possibility that the expression of these proteins may be modulated, expression levels of both proapoptotic genes (caspase-3, -6, -7, and -9) and antiapoptotic genes (BCL-2, IAPs, and XIPA) were confirmed by

quantitative real-time PCR. The treatment of MC3T3-E1 cells with 100μM Dex for 48 h increased the mRNA levels of caspases, whereas cells exposed to Dex and KRG decreased the mRNA levels of caspase-3 and caspase-9 ( Fig. 4). However, Dex failed to repress the expression of antiapoptotic genes (BCL-2, IAPs, and XIPA). In fact, Dex significantly upregulated the expression of Bcl-XL, IAP-2, and XIAP ( Fig. 5). Therefore, Dex Pexidartinib price may induce apoptosis by upregulating proapoptotic gene expression. To survey the molecular mechanism by which KRG exerts its antiapoptotic effects, activation of the MAPK/AKT signaling pathway was examined. MC3T3-E1 cells were incubated with 100μM Dex in the presence

or absence of KRG (1 mg/mL) for 24 h. The JNK, p38, and AKT activation states were reviewed by Western blot analysis. When cells were exposed to 100μM Dex, the

JNK phosphorylation level increased significantly compared to that of the control, whereas it decreased significantly when treated with both Dex and KRG. Given that AKT activation protects cells from cell apoptosis and cell death, we also investigated whether KRG could induce AKT phosphorylation in Dex-exposed MC3T3-E1 cells or not. When cells were exposed to 100μM Dex, AKT phosphorylation decreased significantly Thalidomide compared to that of the control, whereas it increased significantly when cells were treated with both Dex and KRG (Fig. 6). To determine the effects of KRG on the expression of osteogenic gene markers and ALP activity, cells were treated with various concentrations of KRG and Dex in osteogenic differentiation conditions for 5 d and 7 d. Osteoblastic differentiation was assessed by using quantitative real-time PCR, by measuring the mRNA expression levels of ALP, bone morphogenic proteins (BMPs), osteopontin (OPN), RUNX2, and osteocalcin (OCN). DEX-treated cells showed decreased ALP activity, but in cells treated with Dex and KRG (30 μg/mL and 60 μg/mL; Fig. 7A) this activity was increased significantly. Based on quantitative real-time PCR, cells treated with 100μM Dex exhibited decreased mRNA expression levels of ALP, OCN, OPN, RUNX2, BMP-2, -6, -7, and -9, whereas these expression levels increased in cells treated with both Dex and KRG (Fig.

Stratigraphic sequences on Tikopia reveal extensive burning (marked by charcoal in sediments), erosion of the volcanic slopes, and deposition of terrigenous sediments on the coastal plain as the island’s forest was cleared for gardening during the Kiki Phase (950–100 B.C.). During the island’s Sinapupu Phase (∼100 B.C. to A.D. 1200) the use of fire in agriculture gradually declined as the population developed the sophisticated system of arboriculture GSK1349572 chemical structure or “orchard gardening” for which Tikopia is known ethnographically. This arboricultural system mimics the multi-story layering of the tropical rainforest, allowing for extremely high population

densities (∼250 persons/km2). Virtually every hectare of the Tikopia land surface consists of intensively managed orchard gardens, a classic case of the total transformation of an island landscape into an anthropogenic ecosystem.

Mangaia, like other islands within central Eastern Polynesia, was not colonized by Polynesians until ca. A.D. 900–1000. With a land area of 52 km2, the island consists of a 20-million year old central volcanic core surrounded by a ring of upraised coral limestone or makatea. The old, laterized volcanic terrain is nutrient depleted and was highly vulnerable to intensive human land use activities. Archeological investigation of several stratified rockshelters (especially the large MAN-44 site) and sediment coring and palynological analysis of valley-bottom BIBF 1120 ic50 swamps and lakes revealed a detailed history of land Methane monooxygenase use and human impacts on Mangaia ( Steadman and Kirch, 1990, Ellison, 1994, Kirch et al., 1995 and Kirch, 1996). The sediment cores and pollen records reveal rapid deforestation following Polynesian colonization, with an initial spike in microscopic charcoal particles indicative of anthropogenic burning, probably in an effort to cultivate the volcanic slopes

using shifting cultivation. Once the thin organic A horizon had been stripped off of hillslopes through erosion, the lateritic soils were incapable of supporting forest regrowth; the island’s interior became a pyrophytic fernland dominated by Dicranopteris linearis fern and scrub Pandanus tectorius. Agricultural efforts were then directed at the narrow valley bottoms, which were developed into intensive pondfield irrigation systems for taro (Colocasia esculenta) cultivation. The faunal record from the Mangaia rockshelters, especially site MAN-44, exhibits an especially well-documented sequence of significant impacts on the native biota, as well as the introduction of invasive and domestic species (Steadman and Kirch, 1990 and Steadman, 2006). Of 17 species of native land birds present in the early phases of the sequence, 13 became extinct or extirpated.