The tree of life is significantly asymmetrical - a result of differential speciation and extinction - but general causes of such asymmetry are unclear. Differences in niche partitioning are thought to be one possible general explanation. Ecological specialization might lead to increases in diversification rate or, alternatively, specialization might limit the evolutionary potential of specialist lineages and increase their extinction risk. Here we compare the diversification rates of gall-inducing and non-galling insect lineages. Compared with other insect herbivores feeding on the same host plant, gall-inducing insects feed on plant tissue that is more nutritious and less defended, and they do so in a favorable microhabitat that may also provide some protection from natural enemies. We use sister-taxon comparisons to test whether gall-inducing lineages are more host-specific than non-galling lineages, and more or less diverse than non-gallers. We evaluate the significance of diversity bipartitions under Equal Rates Markov models, and use maximum likelihood model-fitting to test for shifts in diversification rates.Apiomorpha scale insects on Eucalytpus), and one gall-inducing lineage is exceptionally species-poor .We find that, although gall-inducing insect groups are more host-specific than their non-galling relatives, there is no general significant increase in diversification rate in gallers. However, gallers are found at both extremes - two gall-inducing lineages are exceptionally diverse (Euurina sawflies on Salicaceae and The effect of ecological specialization on diversification rates is complex in the case of gall-inducing insects, but host range may be an important factor. When a gall-inducing lineage has a host range approximate to that of its non-galling sister, the gallers are more diverse. When the non-galler clade has a much wider host range than the galler, the non-galler is also much more diverse. There are also lineage-specific effects, with gallers on the same host group exhibiting very different diversities. No single general model explains the observed pattern. The tree of life is significantly less balanced than expected under a stochastic process of lineage divergence and extinction  - some lNot all adaptive traits are expected to result in an increased rate of net diversification; on the contrary, some adaptive traits may result in a dramatic depression of the diversification rate e.g. in-bred sociality in theridiid spiders . ReducedThe evolution of gall-induction on plants is a major trophic shift that has occurred multiple times among insects, with over 13,000 described species with this habit . Galls aQuercus are the single most diverse lineage of herbivores associated with a single host genus (about 1000 described species [Ficus [Asphondylia (Diptera: Cecidomyiidae) inducing galls on the leaves, stems, buds and flowers of a single plant species (Larrea tridentate) [Calophya  associated with Schinus (Anacardiaceae) are known to develop on more than one host species - there are eight species of Schinus [Gall-inducing taxa appear to be exceptionally host- and tissue-specific. For example, less than 1% of the described species of gall wasps (Cynipidae) have been recorded from more than one host genus , and gal species ). All ofs [Ficus . Within-s [Ficus ,39 with,dentate) . Only th Schinus . Gall-in Schinus -45.These observations of host-specificity, and the intimate relationship between gall-inducer and host, have led to the idea that gall-inducers are specialized relative to their externally-feeding progenitors ,47. GallHere, we examine phylogenies of gall-inducing insects and their non-galling relatives, including a total of approximately 1,650 species . All five significant differences in host range favored gallers being more host specific than their non-galling sister group.The gall-inducing sister-clade was more diverse in seven of thirteen comparisons, and the non-galling sister was more diverse in the other six. We cannot reject the null model in which each sister has an equal chance of being more diverse with the binomial test  or the signed-rank test .Apiomorpha . Two gall-inducing taxa were more diverse with marginal non-significance: Cerataphidini aphids , sawflies in the subtribe Euurina . Two gall-inducing taxa were markedly less diverse than expected: the armored scale insect genus Maskellia  and the sawfly genus Micronematus .One gall-inducing taxon was more diverse than expected under an Equal Rates Markov (ERM) null model: the scale insect genus Acacia thrips, we were unable to reject the fixed-rate null model. In the LASER analysis, under no extinction (ϵ = 0), the likelihood ratio test (LRT) p-value was 0.096. Under high rates of extinction (ϵ = 0.95) the LRT p-value was 0.17. The MEDUSA analysis selected a one-rate model with a net diversification rate of 0.042 and a relative extinction rate of 0.13. All more complicated models had higher Akaike information criterion (AIC) scores.Only two data sets were sufficiently sampled to satisfy criteria for tests of rate shifts along lineages. For the r) and relative extinction (ϵ) were estimated as 0.048 and 0.69 respectively. Within Euurina both the net diversification rate and relative extinction rate increased dramatically .For the nematine sawflies, the LASER analysis strongly favored the flexible-rate model  with an increase in diversification rate along the stem branch of the Salicaceae-galling Euurina. The MEDUSA analysis selected a model with 4 shift points. As in the LASER analysis, the single shift point resulting in the largest increase in likelihood was at the stem node of the Euurina. Background rates of net diversification  is also the comparison with the greatest disparity in host range, as measured by the estimated age of the most recent common ancestor of the hosts. The importance of host breadth as a determinant of diversification rate is consistent with the assumed importance of host-switching in speciation of phytophagous and parasitic lineages [We confirm that, as expected and commonly stated, gall-inducing taxa are more host-specific than their non-galling relatives. The effect of ecological specialization in gall-inducing insects on diversification rates is complex, but host range appears to be a critical factor. When a gall-inducing lineage has a host range approximate to that of the non-galling sister, the gallers are more diverse. These include the Salicaceae-galling Euurina gall wasps that are sister to a group restricted to Salicaceae and Betulaceae, the lineages ,50.Thus adaptive zone dimensions may be of more fundamental importance to diversification rate variation than is the degree of ecological specialization. When clade host breadth was roughly equivalent between gall-inducing and non-galling sister groups, the gall-inducing group was more diverse. This could result from uneven diversification rates stemming from differences in species-level ecological specificity, or because, for a given set of hosts, the adaptive space available to a gall-inducing lineage is larger than that presented to a non-galling species.Apiomorpha, occur on host taxa  that are persistent and locally abundant over vast geographic spaces, traits thought to reduce a lineage's probability of extinction. On the other hand, the most strikingly species-poor gall-inducing taxon included in this study, Maskellia, also occurs on Eucalyptus, and the gall-inducing thrips on Acacia are not as diverse as might be expected given the diversity of the host , althouf Acacia .Apiomorpha experience extremely high mortality rates .Gall-inducer diversification rates could also be profoundly affected by top-down pressure from parasitoids and pathogens. Gall-inducing Euurina sawflies have been shown to have a depauperate fauna of natural enemies and suffer lower enemy-caused mortality than closely related external feeders. In contrast, species of Gall-inducing lineages tend to be more host-specific than their non-galling sister groups. A gall almost certainly represents an expansion of the ecological resource pool , but the gall-inducer's niche space may not be expanded. The effect of the evolution of gall-induction on net diversification rate appears to have been lineage-specific; no general trend was detected, but some gall-inducers were exceptionally diverse and others were exceptionally under-diverse. Although this study was not designed explicitly to test the effect of a lineage's host-breadth on its net diversification, our results suggest that host-breadth may be a general factor influencing the net diversification of phytophagous insect groups.We surveyed the literature for published phylogenies containing gall-inducing taxa and their non-galling relatives. We also used the PhyLoTA Browser rel. 1.01  to surveUnaligned FASTA files were downloaded from PhyLoTA, and aligned using MUSCLE v.3.6 . RibosomIn order to remove taxonomic bias from measures of host breadth, host range was measured as the age (Ma) of the most recent common ancestor (MRCA) of the hosts. This approach to quantifying host breadth is akin to phylogenetic diversity (PD) , the minFor each of 13 pairs of gall-inducing and non-galling insect sister pairs, we recorded the host range of each sister. In cases for which each sister in a comparison was restricted to a single host genus or family, and our knowledge of host phylogeny and/or insect host breadth was insufficient to identify an age for the MRCA, we assumed there was no difference in host range. We used the Wilcoxon Signed-Rank Test to assess if the observed disparity in host breadth departed significantly from that expected under a null model in which each sister has an equal chance of having a broader host range. The test was one-tailed, reflecting our prior expectation, derived from the literature, that gall-inducing taxa would be more host-specific.Some tree imbalance is expected under null models of stochastic diversification , and thiFor each individual diversity bipartition we also calculated equal rates Markov (ERM) probabilities (using the equation 3 of Slowinski and Guyer ) for altOptimal phylogenies were made ultrametric with nonparametric rate smoothing using r8 s v.1.70 . As onlyWe also sought shifts in diversification rates using a stepwise birth-death model fitting approach based on the AIC implemented as MEDUSA in the R package GEIGER ,66. The We provide a Python program, Systers (Additional file AIC: Akaike information criterion; ERM: equal rates markov; GTR: general time reversible; LRT: likelihood ratio test; ML: maximum likelihood; MRCA: most recent common ancestor; PD: phylogenetic diversity.NBH and LGC cooperated in the conception and design of the study as well as the drafting of the manuscript. NBH carried out the data-mining and analyses and wrote the Python program Systers. Each read and approved the final manuscript.Phylogenetic datasets and results. Survey of DNA sequence-based phylogenetic studies including gall-inducing groups, and details of phylogenetic estimates performed here.Click here for fileML tree estimated from aphid DNA sequence data. Aphidoidea ML phylogeny estimated from analysis of EF1α, long-wavelength opsin, COI, COII, cytochrome b, NADH dehydrogenase 1, ATP synthase subunit 6, and mitochondrial ribosomal subunits 12 S and 16 S dataset partitioned by genome and codon position. Major lineages are labeled following the classification used by Blackman and Eastop.Click here for fileML tree estimated from cynipoid DNA sequence data. Cynipoidea ML phylogeny estimated from analysis of 28 S, 18 S, and COI dataset partitioned by genome and codon position. Deep relationships supported by >70% bootstrap proportions denoted by stars. Empty circle indicated clade of unpublished Cynipini sequences assumed to be misidentifications of synergine inquilines.Click here for fileML tree estimated form chalcidoid DNA sequence data. Chalcidoidea ML phylogeny estimated from analysis of 28 S sequences. Deep relationships supported by >70% bootstrap proportions denoted by stars. Group A composed of exemplars of the following families: Aphelinidae, Chalcididae, Encyrtidae, Eucharitidae, Leucospidae, Mymaridae, Pteromalidae, Perilampidae, Tetracampidae; Group B composed of exemplars of: Aphelinidae, Eurytomidae, Ormyridae, Perilampidae, Pteromalidae, Tanaostigmatidae, Tetracampidae, Torymidae.Click here for filePython script to automate sister taxon comparisons. A program that reads sister clade species diversities in a CSV file, calculates diversity contrasts with multiple metrics, and evaluates significance with either Siegel's randomization test for matched pairs, the Wilcoxon signed rank test, or normal approximation of the Wilcoxon signed rank test.Click here for file


DC-SIGNR  has been extensively studied on its role in host genetic predisposition to viral infection. In particular, variable number tandem repeat (VNTR) of the neck-region of DC-SIGNR is highly polymorphic and the polymorphism has been investigated for genetic predisposition to various infectious diseases, though conflicting results had been reported. As infection is a major cause of human death and a mechanism of natural selection, we hypothesized that VNTR polymorphism of DC-SIGNR might have an effect on human life span.Here we collected 361 peri-centenarian individuals  and 342 geographically matched controls  from Han Chinese. The VNTR polymorphism of the neck region was determined by PCR and genotype was called by separating the PCR products in agarose gel.A total of 11 genotypes and 5 alleles were found in our population. The genotype distribution, allele frequencies and homozygote proportion did not show a significant difference between peri-centenarian and control group. As gender differences in lifespan are ubiquitously observed throughout the animal kingdom, we then stratified the samples by gender. There was more 6/7 genotypes in female peri-centenarian group than that in female control group, at a marginal level of significance . The difference was not significant after correction by Bonferroni method. It suggests a possible differential effect of DC-SIGNR VNTR genotypes between sexes. Further studies are warranted to confirm our preliminary findings and investigate the mechanisms of the underlying functions.Our study indicated that there was absence of association between the neck region polymorphism of DC-SIGNR and longevity in Han Chinese population. But the question of whether the DC-SIGNR could affect longevity in a gender-specific pattern remains open. Mycobacterium tuberculosis, Helicobacter pylori, and certain Klebsiela pneumonia strains, as well as virus, such as HIV-1, HIV-2, Ebola virus, cytomegalovirus, hepatitis C virus(HCV), Dengue virus, and SARS-coronavirus [Dendritic cell-specific intracellular adhesion molecular-3-grabbing nonintegrin (DC-SIGN) and DC-SIGN related (DC-SIGNR) are C-type lectins involved in both innate and adaptive immunity. As DC-SIGN and DC-SIGNR originated from the duplication of the same ancestral gene, they are located side-by-side within a ~26-kb segment of chromosome 19p13.2-3 and they share similar functions as cell adhesion receptors and pathogen recognition receptors[onavirus . One difonavirus .DC-SIGNR is a type II transmembrane protein composed of three domains: an N-terminal cytoplasmic domain, a neck region made up of a highly conserved 23-amino-acid repeat, and a C-terminal extracellular C-type carbohydrate recognition domain (CRD) involved in pathogen binding. The necIt has been suggested that polymorphisms in immune-related genes not only affect susceptibility to infectious diseases, but alsThis elderly Han Chinese cohort composed of 485 unrelated peri-centenarian individuals  were recruited from Dujiangyan in Sichuan province of China. As reported in previous publication, ages ofAn interview was carried out for each peri-centenarian subjects at their homes by physicians during a home visit session. A brief medical history and examination was carried out to exclude participants with clinically apparent diseases . More than 500 peri-centenarian individuals  have been interviewed but only 485 individuals  who fulfilled all inclusion criteria, were included into this peri-centenarian cohort.As we have more samples to fit into four 96-well plates for genotyping , we blindly pull out a block of 180 male and 180 female samples for genotyping. One additional male sample was used for reaction optimization and his genotype results was also included, which led to a total of 181 male genotyping results.Meanwhile, 342 healthy younger individuals, which included 156 females and 186 males, were also recruited from the same area, to serve as a control group . The demographic characteristics of these samples have been described in our previous work. All paret al. [Peripheral blood was collected from the participants and genomic DNA was extracted using the standard phenol/chloroform method. The VNTR polymorphism of the neck region was genotyped using the assay described in Chan et al. . The genhttp://wbiomed.curtin.edu.au/genepop/index.html. Homozygote proportions, genotype distribution and allele frequencies were compared by two-tailed chi-square test or Fisher's exact test  . When P value < 0.05, it was considered to be statistically significant and further subjected to Bonferroni correction for multiple testing.Hardy-Weinberg equilibrium (HWE) test for VNTR in the peri-centenarian and control groups was performed by GENEPOP software Allele and genotype distribution of encoding VNTR in DC-SIGNR gene in Chinese populations of different parts of China have been surveyed and the data have been published in our previous work. Based oWe genotyped the VNTR polymorphism of DC-SIGNR neck region among 361 peri-centenarian individuals and 342 matched young individuals in Han Chinese. The homozygote proportion, genotype and allele frequencies of the VNTR were listed in Table Genetic factors are crucial in the ageing process and thus, also influence longevity. Mitchell et al. estimated a 25% heritability for the life-span in an Amish population in Lancaster County, Pennsylvania,27. HereA total of 11 genotypes and 5 alleles in neck region tandem repeat of DC-SIGNR were investigated in this population. The distributions of genotype and allele frequencies were similar to previous reports on Han Chinese populations. AlthougAnother explanation for our result might be the relative small sample size in our study, especially when the samples were stratified by gender, which is also a handicap in many association studies. Therefore, replication with a larger sample size may improve our understanding on the consequence of this polymorphism and provide more explorative data about the potential influence of this gene on human longevity. After all, it was equally likely that DC-SIGNR gene did not have a role in healthy aging of human beings.We studied the association between VNTR polymorphism of DC-SIGNR neck region and longevity among peri-centenarian individuals in Han Chinese. Our results did not imply that the VNTR polymorphism was associated with longevity in our population. While, there was more 6/7 genotypes in female peri-centenarian group than that in female control group, with a marginal level of significance . The question of whether the DC-SIGNR could affect longevity in a gender-specific pattern remains unknown.The authors declare that they have no competing interests.HL, CW and YZ conceived the idea of the study and drafted the manuscript. JW conducted the genotyping of the VNTR and statistical analysis. NT assisted in revising the manuscript. LX, YG, ZY and LX collected the blood samples. YZ and QK supervised the study and obtained the funding. All authors read the paper and approved the final version.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/10/134/prepubSupplementary tables. Table S1. Allele and Genotype distribution of encoding VNTR in DC-SIGNR gene in Chinese population samples collected from different parts of China. Table S2. Supplementary table of sample size required to detect an association caused by alleles at various allelic frequencies and allelic odd ratios.Click here for file


After trauma, articular cartilage often does not heal due to incomplete bonding of the fractured surfaces. In this study we investigated the ability of chemical cross-linkers to facilitate bonding of articular cartilage, either alone or in combination with a pre-treatment with surface-degrading agents. Articular cartilage blocks were harvested from the femoropatellar groove of bovine calves. Two cartilage blocks, either after pre-treatment or without, were assembled in a custom-designed chamber in partial apposition and subjected to cross-linking treatment. Subsequently, bonding of cartilage was measured as adhesive strength, that is, the maximum force at rupture of bonded cartilage blocks divided by the overlap area. In a first approach, bonding was investigated after treatment with cross-linking reagents only, employing glutaraldehyde, 1-ethyl-3-diaminopropyl-carbodiimide (EDC)/N-hydroxysuccinimide (NHS), genipin, or transglutaminase. Experiments were conducted with or without compression of the opposing surfaces. Compression during cross-linking strongly enhanced bonding, especially when applying EDC/NHS and glutaraldehyde. Therefore, all further experiments were performed under compressive conditions. Combinations of each of the four cross-linking agents with the degrading pre-treatments, pepsin, trypsin, and guanidine, led to distinct improvements in bonding compared to the use of cross-linkers alone. The highest values of adhesive strength were achieved employing combinations of pepsin or guanidine with EDC/NHS, and guanidine with glutaraldehyde. The release of extracellular matrix components, that is, glycosaminoglycans and total collagen, from cartilage blocks after pre-treatment was measured, but could not be directly correlated to the determined adhesive strength. Cytotoxicity was determined for all substances employed, that is, surface degrading agents and cross-linkers, using the resazurin assay. Taking the favourable cell vitality after treatment with pepsin and EDC/NHS and the cytotoxic effects of guanidine and glutaraldehyde into account, the combination of pepsin and EDC/NHS appeared to be the most advantageous treatment in this study. In conclusion, bonding of articular cartilage blocks was achieved by chemical fixation of their surface components using cross-linking reagents. Application of compressive forces and prior modulation of surface structures enhanced cartilage bonding significantly. Enzymatic treatment in combination with cross-linkers may represent a promising addition to current techniques for articular cartilage repair. AftFor bonding, the cartilage blocks within the chamber were placed in a 24-well culture plate and each sample was subjected to one of the following cross-linking agents for 2 h at room temperature (750 μl per sample): glutaraldehyde  at a concentration of 20 mg/ml, buffered in PBS; 1-ethyl-3-diaminopropyl-carbodiimide (EDC) and N-hydroxysuccinimide (NHS)  at concentrations of 20 mg/ml and 5 mg/ml, respectively, in morpholinoethanesulfonic acid buffered solution (pH 5.5); genipin  at a concentration of 5 mg/ml in PBS; transglutaminase  at a final concentration of 60 U per gram dry weight of cartilage block in 0.01 M acetic acid, adjusted to pH 6  at a concentration of 0.5 μg/ml in PBS, pH 7.4 for 30 minutes at room temperature ; pepsin The adhesive shear strength after cross-linking was investigated under uniaxial tensile loading, as first described by Reindel and colleagues . All expAll tests were run at an extension rate of 0.5 mm/minute. The displacement was continuously measured as the increase in distance between the two fixings by means of a linear variable differential transformer with an accuracy of 0.01 mm . The load was recorded using a 100 N load cell, which was limited to 5 N effective range . The accuracy was in the order of 0.01 N. The displacement and the load signal were digitized using a data acquisition card , yielding an accuracy of 0.08 N for the load signal and 0.06 mm for the strain signal. The sampling rate of the data was 10 Hz.Adhesive strength was determined as the maximum shear force at rupture divided by the measured overlap area. Samples that failed to adhere, which became obvious during removal from the culture chamber or during placement into clamps, were assigned an adhesive strength of 0 kPa.To assess the effects of the surface degradation treatment, the extracellular matrix content of cartilage blocks was analysed after being subjected to the respective agents. Additionally, the supernatant was analysed for released extracellular matrix components. Before analysis, cartilage samples were digested with 1 ml of a papainase solution (3.2 U/ml in buffer) for 18 h at 60°C. Sulfated GAG content was determined spectrophotometrically at 525 nm after the reaction with dimethylmethylene blue dye, using bovine chondroitin sulfate as standard . Total cSample pairs were fixed in 2% glutaraldehyde and 4% formaldehyde in 0.1 M phosphate buffer, pH 7.3, for 30 minutes, and again fixed for 60 minutes in 4% formaldehyde, washed in buffer, embedded in Tissue Tek and frozen. Cryostat sections were cut perpendicular to the height of the articular cartilage block to a thickness of 5 μm and stained with toluidine blue for GAGs [The relative cytotoxicity of degrading and cross-linking reagents was tested by a resazurin reduction test obtained from Serotec Limited , which was used according to the manufacturer's instructions; a 10% resazurin solution was employed . The oxipost hoc comparisons made by Tukey's test. Throughout, statistical significance was accepted for p < 0.05.The statistical analysis was carried out using SPSS 12.0 G . Of the free analysed parameters, adhesive strength (kPa), GAG content (μg), collagen content (μg), and relative fluorescence unit (RFU), the Kolmogorov-Smirnov test showed evidence against normal distribution for adhesive strength. Thus, the non-parametric Kruskal Wallis test for overall testing and the Mann-Whitney-U test for pairwise testing was applied to test for differences in adhesive strength between groups. For analysis of the GAG and collagen content of the cartilage blocks or cytotoxicity (RFU) of the applied agents, which were normally distributed, overall difference in the groups was assessed by analysis of variance (ANOVA) followed by At first, cartilage blocks of the two different geometries were fixed in partial apposition in the custom-made chamber. The relaxation behaviour of the G1 and G2 cartilage blocks is shown in Figure To compare the two geometries G1 and G2 with regard to cartilage bonding, the cross-linking agents were applied without prior surface degradation. The Kruskal Wallis test showed significant difference in adhesive strength (kPa) between the groups, which motivated us to perform pairwise testing. Compression to 83% of initial thickness during incubation (G2) resulted in strongly enhanced bonding after treatment with glutaraldehyde and EDC/NHS compared to no compression Figure . Using tThe four cross-linking reagents glutaraldehyde, genipin, EDC/NHS, and transglutaminase were each combined with the pre-treatments trypsin, pepsin, and guanidine; the resulting bonding quality measured as adhesive strength is shown in Figure p < 0.001). Trypsin treatment strongly decreased the GAG content of cartilage samples to 31% of the control group . Among the degrading reagents, pepsin had only small cytotoxic effects whereas guanidine exhibited strong effects in comparison to the non-treated control group  had any effect on bonding between them. Although the cross-linking reagents EDC/NHS and glutaraldehyde led to measurable bonding of cartilage blocks in the absence of compressive strain, large increases in adhesive strength were achieved by additional compressive load during the bonding procedure. Therefore, all experiments investigating combinations of cross-linking reagents with a pre-treatment with surface degrading agents were carried out under compressive load conditions.in vitro has been correlated with cell metabolism [in vitro.EDC/NHS can non-specifically catalyse covalent binding of the amino or carboxyl groups of collagen; furthermore, carboxylic groups of GAGs may also be involved. In our study, EDC/NHS was the best cross-linking reagent with regard to bonding of articular cartilage blocks in all investigations, that is, when comparing the cross-linkers alone and in combination with degrading pre-treatment. The combinations of EDC/NHS with pepsin or guanidine pre-treatment led to the highest adhesive strengths detected in this study. To date, cell-based articular cartilage repair tabolism , collagetabolism  and colltabolism ,31. HoweWith regard to cytoxicity, even after exposure for two hours, EDC/NHS elicited no significant effects, whereas glutaraldehyde and genipin compromised cell vitality considerably. In previous investigations, EDC/NHS has also been observed to be advantageous in this respect, compared to glutaraldehyde . FurtherGlutaraldehyde and genipin cross-link amino groups of proteins; glutaraldehyde molecules can cross-link to each other and the chain building properties may have beneficial effects in comparison to genipin, which can only cross-link in pairs . In thisin vitro and in vivo integrative repair. Transglutaminase has been previously shown to be biocompatible [Transglutaminase, a naturally occurring enzyme in articular cartilage, catalyses a specific collagen cross-linking reaction between lysine and glutamine residues. This enzyme has been previously introduced, combined with compressive load, to enhance integrative bonding of articular cartilage wounds . In our mpatible , which win vitro, but in vivo fibrin glue did not provide enough mechanical strength to hold the periosteum flap in place [For many years, soft tissue adhesives like fibrin  have beein place . As a fuin place . In genein vitro [Degradation or swelling of articular cartilage surfaces have been reported to be beneficial in cell-based integrative repair in vitro ,9-12. InPre-treatment with guanidine led to the highest adhesive strengths in combination with all cross-linkers compared to the endopeptidase pre-treatments. Unfortunately, guanidine elicited the strongest cytotoxic effects of all reagents in the study. It is noteworthy that the achieved mechanical bonding is comparable to previous studies employing a similar model. Reindel and colleagues  first rePreviously, it was assumed that degrading surface treatment led to cell proliferation or stimulation of cell metabolism . The obsClarification of the mechanisms involved appears to be a worthwhile subject for further investigation. Future studies should also address the fact that immature and mature cartilage differ in extracellular matrix content, structure and mechanical properties -45. In aThis study clearly demonstrates that immediate bonding of articular cartilage blocks can be achieved by means of chemical cross-linking. Adhesive strength was superior under compressive conditions compared to no compression. In general, pre-treatment with surface-degrading enzymes or swelling by guanidine salt led to distinct enhancement of cartilage bonding after chemical cross-linking. Taking both the observed bonding and the cell vitality after treatment into account, the combination of pepsin pre-treatment and cross-linking with EDC/NHS appears to be the most favourable with regard to this study. The presented work suggests that a combination of selected surface-degrading agents and chemical cross-linkers is a promising option for enhancing bonding of opposed surfaces in cartilage repair.EDC = 1-ethyl-3-diaminopropyl-carbodiimide; G = geometry (of cartilage blocks); GAG = glycosaminoglycan; NHS = N-hydroxysuccinimide; PBS = phosphate-buffered saline; RFU = relative fluorescence unit.The authors declare that they have no competing interests.CE conceived of the study and its design, participated in the bonding experiments, and helped to draft the manuscript. TB participated in the design of the study and drafted the manuscript. RM participated in the design of the study, specifically with regard to chemical cross-linking. SSvG carried out the bonding experiments and the cytotoxicity assay. JB carried out the analysis of the extracellular matrix content. JF carried out the analysis of the relaxation behaviour and participated in the bonding experiments. IH helped to perform the statistical analysis. MN and JH participated in the design and coordination of the study. All authors read and approved the final manuscript.


Surface waters quality has declined in developing countries due to rapid industrialization and population growth. The microbiological quality of river Ganga, a life-sustaining surface water resource for large population of northern India, is adversely affected by several point and non-point sources of pollution. Further, untreated surface waters are consumed for drinking and various household tasks in India making the public vulnerable to water-borne diseases and outbreaks. Enterococci, the 'indicator' of water quality, correlates best with the incidence of gastrointestinal diseases as well as prevalence of other pathogenic microorganisms. Therefore, this study aims to determine the distribution of species diversity, dissemination of antimicrobial-resistance and virulence-markers in enterococci with respect to rural-urban landscape along river Ganga in northern India.2: 1900, df: 1; p < 0.0001) increased from up-to-down gradient sites in the landscape. Species diversity exhibit significant  and progressive distribution of E. faecalis, E. faecium, E. durans and E. hirae down the gradient. Statistically discernible (p: 0.0156 – < 0.0001) background pool of resistance and virulence was observed among different Enterococcus spp. recovered from five sites in the up-to-down gradient landscape. A significant correlation was observed in the distribution of multiple-antimicrobial-resistance  and multiple-virulence-markers  among different Enterococcus spp.Enterococci density (χEnterococcus spp. The observed high background pool of resistance and virulence in enterococci in river waters of populous countries has the potential to disseminate more alarming antimicrobial-resistant pathogenic bacteria of same or other lineage in the environment. Therefore, the presence of elevated levels of virulent enterococci with emerging vancomycin resistance in surface waters poses serious health risk in developing countries like India.Our observations show prevalence of multiple-antimicrobial-resistance as well as multiple-virulence traits among different  Enterococcus faecalis  and E. faecium are the two major pathogenic species in human, with sporadic infections caused by E. durans, E. hirae and other enterococci [gelE), enterococcal surface protein (esp), collagen binding protein (ace) and endocarditis-associated antigen (efaA) have been considered as possible factors to play an important role in making enterococci a potential pathogen [Enterococci, commensal organisms in gastrointestinal tract of human and animals have emerged as a leading cause of nosocomial infections . Enterocerococci . The preerococci ,4. Variopathogen -7. The epathogen . Severalpathogen ,9-13. Hopathogen ,15.E. coli) and ETEC (Enterotoxigenic E. coli) specific virulence genes and E. coli resistant to multiple antimicrobials has been reported from selected locations of river Ganga [The surface waters in populous countries have become reservoirs of antimicrobial-resistant pathogenic microbes due to indiscriminate use of antimicrobials in human and veterinary medicine and addition of fecal contamination through point as well as non-point sources, storm drain infrastructure and malfunctioning septic trenches . The proer Ganga . Howeverer Ganga . About 2er Ganga . FurtherThe goal of current study was to contextualize the dissemination of species diversity, antimicrobial-resistance and virulence-markers in enterococci with respect to rural-urban landscape along river Ganga in northern India.2: 1900, df: 1; p < 0.0001) in the river Ganga surface waters from up-to-down-gradient sites in the landscape  heterogeneity and diversity was observed in Enterococcus spp. recovered from river Ganga surface water samples collected from five different sites  or nonpoint sources .E. faecalis (64%) was found to be the most prevalent species followed by E. faecium (24%) throughout the landscape. A gamut of factors appears to complement the increase of E. faecalis and E. faecium coexistence towards the down-gradient sites in the similar environmental niche. The coexistence of these two genotypes in one niche may be due to their differential affinity and efficiency of resource utilization complementing similar phenomenon reported elsewhere for Vibrio cholerae serogroups; O139 Bengal and O1 E1 Tor [V. cholerae O1 E1 Tor to colonize copepods was observed to be a contributory factor for its dominance in cholera epidemic. Likewise E. faecalis, the most prevalent species observed in this study has been implicated in ca. 67% and 90% of enterococcal infection cases associated with multiple-antimicrobial-resistance in different clinical studies conducted in India and USA respectively [E. durans and E. hirae were not evenly distributed throughout the landscape. The presence of E. hirae (2%) was observed only at the locations which receive tannery effluents contaminated with heavy metals. The prevalence of E. durans (8%) appears to be affected by urban wastewater point-source contamination. The "other Enterococcus spp." was present at site 5 only. Moreover, it appears that the environmental factors account for the spatial variation of Enterococcus spp. in the landscape.A significant  towards downstream in the landscape  in the landscape. High frequency of multiple-antimicrobial-resistance (MAR) was recorded among enterococci tested. The number (median) of antimicrobials against which resistance was observed in each pe Table . The preEnterococcus spp. isolates [Figure E. faecium resistant to β-lactam class of antimicrobials including methicillin was recorded to be higher in this landscape. A large scale dissemination of aminoglycoside resistance was observed along the landscape gradient; higher percentage of gentamicin resistant enterococci were prevalent at site 3 which reflects its frequent use in human medicine as this site receives wastes from hospital located just upstream. Our observations indicate that streptomycin and gentamicin resistance are distributed extensively in the environmental gene pool. The resistance to erythromycin, a macrolide and rifampicin in association with vancomycin, a glycopeptide was also distributed significantly. Hasman et al. [E. faecium strains isolated from pigs in Denmark during 1997–2003, contemplating persistence of BPAR in that geographic region. A number of studies have reported the phenomenon of sustained BPAR in poultry and local population [Statistically detectable MAR was recorded among s Figure . E. faecn et al. , reportepulation ,29.vanA gene (for vancomycin resistance) in surface waters of river Ganga and its tributary and discussed the possible consequences of BPAR, its environmental carriage by plasmid maintenance systems or postsegregational killing (PSK) systems.Though the frequency of VRE is only 21% in the landscape, its association with other widely disseminated antimicrobials and virulence determinants may lead to evolution of pathogenic VRE and thus reduce the chances for synergistic therapy in case of failure of single antimicrobial . RecentlgelE, ace, efaA and esp among different Enterococcus spp. Statistically discernible distribution of virulence-markers along the up-to-down-gradient landscape was observed  followed by gelE+efaA+ (7.14%). The only exception was site 3 with median value of one which otherwise exhibited the range of one to four virulence-markers gelE+efaA+, gelE+efaA+esp+,gelE+ace+efaA+ and gelE+ace+efaA+esp+. The impact of landscape and associated environmental factors seem to affect the dissemination of all four virulence-markers at site 3 which receives contamination from hospital wastes, municipal sewage and tannery effluents. Enterococci isolates from the most polluted downstream site exhibited a range of two to three virulence-markers per isolate; gelE+esp+ and gelE+efaA+esp+ combinations were the most prevalent multiple-virulence-traits.This study also explored the dynamic and complex facet of landscape and its effects on the dissemination of virulence-markers ed Table . In addiEnterococcus spp. diversity from river Ganga surface waters  conventional culture based methodology opted for isolation of environmental strains; influenced by the dominance of culturable bacteria and does not consider viable but non-culturable (VBNC) entities which carry potential pathogenic and MAR traits to impart serious infections. The molecular metagenome based approach has been taken into account for our ongoing studies to overcome the limitation. (ii) Limiting landscape to a small geographic region due to financial constrains; consequently the most upstream location in the landscape does not hold the merit of pristine location to be considered for absolute estimation of background level or pool of resistance or virulence-determinants, only relative estimation of background level of resistance is the feasible option. More collaboration between the national and international labs is needed for the purpose. (iii) Lack of exact data on usage pattern of antimicrobials in human and veterinary medicine which further limits the study as the quantitative nature of cause-effect relationship remains partially explored. Strict rule codes needed to be set and maintained by the regulatory agency for local counterparts to keep the track record of supply as well as nature and mode of consumption. However, the intricacies in retrieving specific antimicrobial usage data based on individual consumption continue to be a global challenge for environmental health researchers in the absence of national and or state regulations that require consumers to report their consumption to the local authority as earlier mentioned by Sapkota et al .Enterococcus spp. and other bacteria. Therefore, the presence of antimicrobial-resistant pathogenic enterococci in surface waters of populous nations demand improved surveillance for risk assessment and pre-emptive strategies for protection of public health.In the present study, the spread of potential pathogenic enterococci appears to be the manifestation of complex network of ecological processes and associated factors in the landscape of river Ganga. Enterococci recognized as hardy and rogue microbe may cause very serious infections with limited options of treatment. Surface waters with emerging VRE and background pool of multiple-antimicrobial-resistant and multi-virulent enterococci can contribute to the dissemination of resistance and virulence-determinants in the diverse 2, estimated population: 4,864,674) located on the banks of river Ganga in up-to-down-gradient fashion  from five locations situated in up-to-down-gradient fashion  technique. The presence of  earlier ,43. An iA panel of thirteen antimicrobials  impregnated on paper discs  belonging to eight different group of antimicrobials as Fluoroquinolone: Norfloxacin (Nx:10 mcg), β-lactam: Ampicillin (A:10 mcg), Oxacillin (Ox:1 mcg), PenicillinG (P:10 units), Methicillin (M:5 mcg), Aminoglycoside: Gentamicin (G:10 mcg), Streptomycin (S:10 mcg), Tetracycline: Tetracycline (T:30 mcg), Phenicol: Chloramphenicol (C:30 mcg), Macrolide: Erythromycin (E:15 mcg), Rifamycin: Rifampicin (R:5 mcg), Glycopeptides: Vancomycin (Va:30 mcg), Teicoplanin (Te:30 mcg) were used for testing the sensitivity of isolated organisms by Kirby-Bauer disc diffusion test as described by CLSI ,44. The gelE, ace, efaA and esp encoding gelatinase, adhesion collagen factor, endocarditis factor antigen and enterococcal surface protein, respectively in different Enterococcus spp. was examined by PCR as reported earlier [E. faecalis ATCC 51229, E. faecium ATCC 35667, 27270, E. durans ATCC 49470, E. hirae ATCC 9790 were used throughout the study as reference/standard strains.Polymerase Chain Reaction technique was used to generate a profile for virulence-markers' distribution in enterococci. The presence of genes  earlier ,45. The  earlier . E. faecEnterococcus spp. and its association with the landscape was evaluated using Chi-square test. The prevalence and distribution of antimicrobial-resistance and virulence-markers among isolates from up-to-down-gradient landscape was assessed using Wilcoxon rank-sum tests. Wilcoxon matched pair test was conducted to investigate correlation between dissemination of antimicrobial-resistance and virulence-markers in different Enterococcus spp. All statistical analyses were performed using GraphPad Prism version 5.0 for Windows .We compared concentrations of enterococci obtained using MPN analysis test and membrane filtration method from up-to-down-gradient surface water samples. Chi-square test for trend was applied for the purpose. The distribution of PL carried out the phenotypic antimicrobial susceptibility profiling, determination of gelatinase activity, PCR characterization for determination of enterococcal species diversity and virulence marker's distribution, analysed the data and wrote the manuscript. SR contributed to sample collection and microbiological analysis. MA provided direction on available means of data analyses. RS conceived the study, analysed the data and wrote the manuscript. All authors contributed to the general content and structure of the final manuscript.Enterococcus species diversity in the landscapeTable A1- Correlation observed between the prevalence of single/multiple-antimicrobial-resistance and . Presentation of correlation between the single or multiple-antimicrobial-resistance and different Enterococcus species recovered from the landscape.Click here for fileTable A2- Site wise elaborated profile of species diversity, antimicrobial-resistance and virulence-markers in enterococci isolates from river Ganga at Kanpur city. Depiction of investigated enterococcal species diversity, antimicrobial-resistance and virulence-markers' profile of all isolates recovered from the landscape.Click here for file


Most of the tools use parallel computing (via MPI) and run on a server with 60 CPUs for computation; compared to a desktop or server-based but not parallelized application, parallelization provides speed ups of factors up to 50. Most of our applications allow the user to obtain additional information for user-selected genes  by using clickable links in tables and/or figures. Our tools include: normalization of expression and aCGH data (DNMAD); converting between different types of gene/clone and protein identifiers (IDconverter/IDClight); filtering and imputation (preP); finding differentially expressed genes related to patient class and survival data (Pomelo II); searching for models of class prediction (Tnasas); using random forests to search for minimal models for class prediction or for large subsets of genes with predictive capacity (GeneSrF); searching for molecular signatures and predictive genes with survival data (SignS); detecting regions of genomic DNA gain or loss (ADaCGH). The capability to send results between different applications, access to additional functional information, and parallelized computation make our suite unique and exploit features only available to web-based applications.The analysis of expression and CGH arrays plays a central role in the study of complex diseases, especially cancer, including finding markers for early diagnosis and prognosis, choosing an optimal therapy, or increasing our understanding of cancer development and metastasis. Asterias ( Gene expression data from DNA microarrays have had a central role in the study of complex diseases, especially cancer and, in the last 10 years, hundreds of papers using gene expression data from microarray studies of cancer patients have been published . HoweverA large number of web applications for genomic data are available but many have been developed for a single task e.g. , MIDAW , Gepas ; 2003, aOur suite Asterias, as some of the other available suites, offers integrated analysis, the possibility to use either the full suite or just specific applications, and access to additional functional information. Asterias’ unique features are: a) Asterias is explicitly designed to take advantage of web-based applications running on a multi-server site, by using load-balancing and, more importantly, parallelized execution. Parallel computing  can resuAsterias provides an integrated set of freely-available tools that allows for comprehensive analysis of expression and aCGH data, from normalization to searching for class and survival prediction models and integration of additional functional information. DNMAD Diagnosis and normalization of array data (both expression and aCGH).Diagnostic plots to identify possible spatial patterns, arraying problems, and differences in spread among arrays and subarrays.Print-tip and global loess-based normalization.Use of flags to determine points to exclude and points to normalize but not use for determining the normalization curve.Three options for background correction.User-specified color ratio (red(Cy5)/green(Cy3) vs. green(Cy3)/red(Cy5)).Input as GPR files or custom formatted files, and upload of uncompressed or compressed files.preP Preprocessing of array data.Filtering genes with missing data.Data imputation using KNN .Merging of replicate spots in the array.Elimination of constant genes/clones/spots.IDconverter Mapping of clone, gene and protein ids to known public databases.Output ids: 8 gene ids, 3 clone ids, 5 protein ids, plus PubMed references, GO terms, and KEGG and Reactome pathways. Chromosomal location from two sources.Several output formats: HTML, tab separated text file and spreadsheet file.IDClight Same as IDconverter, but input coming-directly from URL.Pomelo II Finding differentially expressed genes.For differential expression associated to class differences , a continuous variable (linear regression), or survival time (via Cox models).Unadjusted and FDR-adjusted p-values.For t-test, ANOVA, and regression, p-values can be obtained by data permutation.Empirical bayes moderated statistics for t-test and ANOVA.Addition of clinical covariates in linear models.Heatmaps with gene dendrograms of user-selected subsets of genes .Tnasas Searching for models of class prediction.Five different class-prediction algorithms .Three different gene ranking methods .Honest assessment of prediction error rate using double cross-validation.Assessment of the relationship between number of genes in class prediction models and error rate.Comprehensive analysis of stability of solutions for both “best” number of genes and identity of selected genes.GeneSrF Gene selection for classification problems using random forest. Targeted towards identifying both small, non-redundant sets of genes with good predictive performance , very similar to the one used in Honest assessment of model quality using cross-validation.Full details on models fitted and steps used, including detailed dendrograms, steps of variable selection, and correlation between signatures for FCMS.Comprehensive analysis of stability of solutions for both “best” number of genes, identity of selected genes, and signatures.Option to use validation data to obtain assessments of model quality.ADaCGH Analysis of data from aCGH: calling gains and losses and estimating the number of copy changes in genomic DNA.Implements four methods that have been shown to perform well in previous studies : circulaDiagnostic plots and overimposed plots to help determine suitability of methods and number of levels of gain/loss.Asterias runs on a computing and web-serving cluster with 30 nodes, each with two Xeon CPUs. This cluster uses Debian GNU/Linux as OS. We use Apache as web server, with web service load-balanced using Linux Virtual Server (LVS); because most computations are parallelized using MPI (see below), we use round-robin for webservice load-balancing. High-availability is achieved using redundancy in both LVS (two directors monitored with heartbeat) and storage (via a set of custom scripts). The database server for IDconverter and IDClight is MySQL.http://www.lam-mpi.org) of MPI. Pomelo II is parallelized in C++, whereas the rest of the applications are parallelized in R using the library Rmpi (http://www.stats.uwo.ca/faculty/yu/Rmpi), and snow (http://www.stat.uiowa.edu/~luke/R/cluster/cluster.html) or papply (http://cran.rproject.org/src/contrib/Descriptions/papply.html). The MPI universe is created new for each run of each application, and the actual nodes to use in the MPI universe are determined at run-time after excluding possible non-responding nodes. This ensures that MPI can be used even if a node fails or is taken down for maintenance. When the parallelization does not involve all CPUs in the cluster, the CPUs used in the MPI universe are balanced: the configuration file for MPI depends on the master node of a run .All applications  are parallelized using the LAM/MPI implementation (http://bioinformatics.org/asterias/wiki/Main/DevelopersDocumentation). As many other popular tools, we make extensive use of R and BioConductor packages, but many functions have been rewritten to allow for parallel computing. Full details on R/BioConductor packages used are provided on the help pages for each application.Computations are carried out using R and C/C++, either stand-alone or called from R. CGIs, data entry verification, MPI and cluster monitorization, and application counter and monitorization are written with Python, except for DNMAD (which use Perl). JavaScript is used for some of the dynamic output . Further details about design, implementation, and software and hardware organization, of interest mainly to developers, are provided at the Asterias project’s page (http://funkload.nuxeo.org/), is available from the the Asterias download page (http://bioinformatics.org/asterias/wiki/Main/DownloadPage) or from Launchpad (https://launchpad.net/projects/asterias). By using these tests we verify CGIs (including JavaScript), numerical output, the handling of error conditions and incorrectly formatted input files, and the setting up of MPI universes. For Pomelo II (currently the application that uses the most JavaScript and Ajax) we have also built tests (available from http://pomelo2.bioinfo.cnio.es/tests.html), using Selenium (http://www.openqa.org/selenium/), that verify that the application runs correctly under different operating systems and browsers.Testing that applications work as expected  and the most recent applications  have been running since January 2006. The number of average daily uses (in the six-month period from 1-March-2006 to 1-September-2006) ranges from 5 per day for Pomelo II to 0.5 per day for SignS . For IDconverter the average daily uses are about 75 . Please note that the above are successful uses . Asterias now includes a bug-tracking and feature-requests page at EDF)  are formatted with genes in rows and patients or arrays in columns. The first column should be a column of identifiers, which can be of arbitrary length and include any character except tab (since tab is used for column separation). The array data can include a row with array/subject identifiers. It can also include an arbitrary number of comment lines  anywhere in the file. Comment lines are a convenient way to record all transformations suffered by a file in DNMAD and preP.All applications use plain text files, with tab-separated columns for input. Missing values, in the applications that accept them, can be specified as either “NA” or by not filling the corresponding entry. The expression data files (http://www.moleculardevices.com/pages/software/gn_genepix_file_formats.html#gpr) as produced directly by many microarray scanners, or non-GPR files, if they have a specified set of columns (see DNMAD help).DNMAD, IDconverter and IDClight have unique data entry requirements/flexibilities. For IDconverter the entry is a column of one or more identifiers. IDClight is designed for automated, programmable access, and accepts “data entries” via URL , survival time and censored status , and chromosome location information (ADaCGH) such as is returned by IDconverter. All these input files are also tab-separated, plain-text files. Further details are shown in A summary of the output of each application can be seen in http://www.creativecommons.org), thus allowing for redistribution and classroom use. In addition, courses on the use of our tools are taught occasionally.All applications have online help, most of them also include tutorials, detailed and commented examples, and sample data files, and Pomelo II also has additional tutorials as flash movies. Tutorials and examples are licensed under a Creative Commons license (http://bioinformatics.org/asterias/wiki/Main/DownloadPage or https://launchpad.net/projects/asterias), and we are using a general purpose web framework (Pylons: http://pylonshq.com) to ease distribution and installation. Releasing all of the code and making installation straightforward might draw other developers into Asterias. Another current effort focuses on increasing the use of parallelization and distributed computing to allow for faster responses and more efficient use of computational resources.Our biggest development efforts are currently focused on two areas. We want to make Asterias easy to deploy at other places; to accomplish this, we are making available all of the source code as soon as it is ready for distribution (right now, all the testing code and some application’s code is available from Asterias is a freely-accessible suite of tools for the analysis of microarray data, both expression and aCGH, including normalization, missing data handling and imputation, differential gene expression, class prediction, survival analysis, and aCGH analysis. Asterias fully exploits its deployment in a cluster by using web-serving load-balancing and, more importantly, parallel computing for most of the computationally intensive tasks. Asterias also emphasizes sound and tested statistical approaches, provides careful analysis of the “multiplicity of solutions” problem, and integration of additional functional information.


Pink gingival esthetic especially on the anterior teeth has been an important success criterion in implant-supported restoration. Inter-implant papillae are a critical factor for implant esthetics, and various techniques for inter-implant papilla reconstruction have been introduced. The aim of this study is to suggest and evaluate a surgical technique for reconstructing inter-implant papillae.A 28-year-old man had an implant placed on the #13 and #14 area. Four months after implant placement, a second stage surgery was planned for inter-implant papilla reconstruction. At the time of the abutment connection, I-type incisions were performed on the #13i & #14i area followed by full-thickness flap elevation and connection of a healing abutment on underlying fixtures without suture.Two weeks after the second stage implant surgery, soft tissue augmentation between the two implants was achieved.I-shaped incisions for papilla reconstruction performed during the second stage implant surgery were useful for inter-implant papilla reconstruction and showed a good esthetic result. Dental implants are now considered a routine treatment modality for replacing missing teeth in the majority of dental applications . HoweverVarious techniques for reconstructing inter-implant papillae are suggested at the time of second-stage surgery. Palacci  suggesteThis case modified the method introduced by Shahidi et al.  Four monA 28-year-old male who was in good systemic health visited the Department of Periodontology, School of Dentistry, Kyung Hee University, to have implants placed in the edentulous area of #13, #14, #26, #37, #43, #44. Number 13 was in the root rest state and immediate implant placement surgery was planned . The resGingival esthetics has become an important success criterion for implant-supported restoration. Unesthetic implant restoration, therefore, is considered to be a failure. Especially for the anterior maxilla, esthetic results are quite an important factor for successful restoration and establishment of intact papilla between implant and tooth, or between adjacent implants. The level of inter-implant papilla is influenced by the previous bone level, soft tissue quantity and quality, peri-implant biotypes, implant position, and inter-implant distance . TherefoIn this case, we tried to reconstruct inter-implant papilla with I-shaped incisions and the sutureless technique, which is a modification of the method suggested by Shahidi et al. . AccordiIn this case, we suggest a new method including an I-shaped incision which was done over every implant for our case. To minimize the possibility of labial gingival tissue recession, labial horizontal incision lines were positioned 0.5-1.0 mm inside from the labial border of implants. Also, the horizontal incision is limited to the mesiodistal distance of the implant neck. The flaps were minimally elevated and healing abutments were connected. Each flap was supported by the healing abutments and able to plump up stably.The advantages of this new method, compared to old ones, are decreased chair time, less postoperative discomfort and improved esthetics. This sutureless method with minimal incision does not decrease blood flow to the overlying flap and it minimized the probability of trauma or inflammatory reaction . Therefo


Unambiguous interpretation of ordered rating scale response categories requires distinct meanings of category labels. Also, summation of item responses into total scores assumes equal intervals between categories. While studies have identified problems with rating scale response category functioning there is a paucity of empirical studies regarding how respondents interpret response categories. We investigated the interpretation of commonly used rating scale response categories and attempted to identify distinct and roughly equally spaced response categories for patient-reported rating scales in Parkinson's disease (PD) and age-matched control subjects.Never - Always, Not at all - Extremely, and Totally disagree - Completely agree. VAS values were compared between groups, and response categories with mean values and non-overlapping 95% CIs corresponding to equally spaced locations on the VAS line were sought to identify the best options for three-, four-, five-, and six-category scales.Twenty-one rating scale response categories representing frequency, intensity and level of agreement were presented in random order to 51 people with PD  and 36 age-matched controls . Respondents indicated their interpretation of each category on 100-mm visual analog scales (VAS) anchored by VAS values did not differ between the PD and control samples (P = 0.286) or according to educational level (P = 0.220), age (P = 0.220), self-reported physical functioning (P = 0.501) and mental health (P = 0.238), or (for the PD sample) PD duration (P = 0.213) or presence of dyskinesias (P = 0.212). Attempts to identify roughly equally spaced response categories for three-, four-, five-, and six-category scales were unsuccessful, as the 95% CIs of one or several of the identified response categories failed to include the criterion values for equal distances.This study offers an evidence base for selecting more interpretable patient-reported rating scale response categories. However, problems associated with raw rating scale data, primarily related to their ordinal structure also became apparent. This argues for the application of methodologies such as Rasch measurement. Rating scale response categories need to be treated with rigour in the construction and analysis of rating scales. Patient-reported rating scales are gaining increasing importance in determining patient status and effectiveness of therapies. In such scales, responses to a number of items are typically summed to yield a total score intended to locate the respondent on a continuum from less to more on the variable of interest. Following the tradition of Likert , this isAlthough the summed rating scale approach may appear simple and straight forward, its appropriateness and legitimacy rests on some fundamental assumptions that often appear overlooked. First, for respondents to be able to communicate their positions accurately (and for investigators and clinicians to accurately interpret those responses), the descriptive response category labels need to have distinct and unambiguous meanings that reflect differences in amount . Second,Although attention has been paid to these and related issues in the behavioral and social sciences ,6-8, lesThe objective of this study was to investigate the interpretation of commonly used rating scale response categories and to identify distinct and roughly equally spaced response categories for patient-reported rating scales in PD and age-matched control subjects.Two samples were used: 51 consecutive Swedish speaking people with neurologist diagnosed PD  without Never - Always (frequency), Not at all - Extremely (intensity), and Totally disagree - Completely agree (agreement) [Participants were interviewed regarding demographic characteristics and self-completed the physical functioning and mental health scales of the SF-36 ,22. Peopreement) ,10. Catereement) -29. RespThe study was reviewed by the institutional ethics advisory committee and was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent.Statistical analyses were conducted using SPSS 14 for Windows . P-values were adjusted for multiple testing using the Benjamini-Hochberg procedure , and conNonparametric multivariate analysis of variance (MANOVA)  was usedTo determine the best response options for the three types of ratings, the mean, standard deviations (SD) and 95% confidence intervals (CIs) of the VAS values were examined . The criSample characteristics are reported in Table MANOVA of overall differences among VAS values between PD and control groups was not significant (P = 0.286). Similarly, MANOVAs of VAS values for the pooled sample did not display any significant differences between educational levels (P = 0.220), age groups (P = 0.220), or between people with lower and higher physical functioning (P = 0.501) and mental health (P = 0.238) scores. In the PD sample, there were no differences between people with shorter and longer disease durations (P = 0.213) or between those with or without dyskinesias (P = 0.212).Results from the VAS evaluations of the 21 rating scale response categories from the pooled sample are presented in Table Don't know. Difficulties were also expressed by one or two respondents each for the categories Sometimes, Somewhat, Moderately, and Do not agree or disagree.One third (n = 12) of the control group and 43% (n = 22) of the PD group expressed difficulties interpreting the response category Based on these observations the best three-, four-, five and six-category response scales according to the pre-defined criteria are provided in Figure This appears to be the first controlled study on the interpretation of patient-reported rating scale response categories in the clinical neurosciences. As such, it provides a first evidence base and initial guidance for selection of rating scale response categories when developing new or modifying available patient-reported rating scales for PD. This is highly relevant as clarity, distinctiveness and equality of response category intervals represent fundamental assumptions underpinning traditional rating scale construction ,32 that Some of the time and A good bit of the time are clearly different from those between A good bit of the time and Most of the time. Extrapolating data from this study to response categories in commonly used scales reveals similar problems. For example, the three non-extreme response options in the original PDQ-39  [The identified best categories for three-, four-, five and six-category response scales were not optimal, as they failed to fulfill the assumption of equal inter-category distances also when considering their 95% CIs. For example, the distances between - Often)  correspo- Often) , FACIT-F- Often) , SF-36 [- Often) , PDQL [2- Often) , and PDQ- Often) .Conceivably, this has at least two consequences. First, it may contribute to respondent difficulties in using the response options. Second, it is unknown what a certain difference in raw rating scale scores represents and by how much more someone has changed compared to people with smaller change scores. This illustrates the ordinal nature of raw rating scale data and argues against the legitimacy of analyzing and interpreting summed integral numerals from item responses as linear measures ,33,34. TAlways as well as Never [There are a number of aspects that need to be taken into consideration when interpreting the results presented here. First, the appropriateness of using VAS to evaluate participants' interpretation of response categories may be questioned since evidence speaks against the linearity of VAS data . Howeveras Never ,39.The samples studied here were not randomly selected, which may limit the generalizability of results. Furthermore, the sample sizes were somewhat limited, which influences the precision of observations and, therefore, renders the reported 95% CIs wider than otherwise would have been the case. However, given that data failed to support the assumption of equal inter-category distances even with consideration of the observed CIs, increasing the number of observations would presumably have yielded even stronger evidence against legitimate raw score summation of the response categories studied here. Similarly, the lack of differences between people with PD and control subjects, as well as between other subgroups also needs to be interpreted in view of the sample size. That is, with increasing numbers of observations, statistically significant differences are increasingly likely to be detected. However, statistical significance says nothing about the practical significance of differences, which is not known for the current type of data.The variability in interpretations of response categories was wide between individuals . This does not appear to be limited to patient-reported data, as studies regarding physicians' interpretation of various probability related expressions (including some of the response categories studied here) have shown similar variability . This vaOur observations concern the interpretation of response categories without reference to a particular context. This is different from the use of response categories in rating scales where items articulate the context within which responses are requested. Studies have shown that the meaning of descriptors of, e.g. frequency differ according to context as well as respondents' experiences within the context ,40. WhilDon't know. This observation is in accordance with previous studies of neutral middle categories  in Likert type response scales [A large proportion of respondents expressed difficulties with the response category e scales ,41,42. TThe ordinal nature of rating scale response categories challenges the legitimacy of summing individual item scores into total scores, as well as their interpretability ,4,34. HoAlthough in need of replication and extension, this study offers an evidence base for selecting more interpretable patient-reported rating scale response categories. As such, it provides guidance when developing new or modifying existing rating scales. However, it must be stressed that the selection of response categories also should be guided by additional considerations, so that they express levels of the construct articulated by the items in a meaningful way that is congruent with the intention of the scale. In this perspective, response categories alternative to those primarily identified here may be appropriate, particularly since the difference between identified and alternative categories in some cases were marginal. Our observations also illustrate problems associated with raw rating scale data that clinicians and investigators need to be aware of and that argue for the application of newer rating scale methodologies such as Rasch measurement. Response categories need to be treated with rigour in the construction and application of rating scales.CI: Confidence interval; COMT: Catechol-O-methyl transferase; FACIT-F: Functional Assessment of Chronic Illness Therapy - Fatigue; FDA: Food and Drug Administration; MANOVA: Multivariate analysis of variance; MAO: Monoamine oxidase; mm: Millimeter; PD: Parkinson's disease; PDQ-39: 39-item Parkinson's disease questionnaire; PDQUALIF: Parkinson's disease quality of life scale; PFS-16: 16-item Parkinson fatigue scale; SD: Standard deviation; SF-36: Medical Outcomes Study 36-item Short Form health survey; VAS: Visual analog scale;The authors declare that they have no competing interests.IK participated in designing the study, data collection, data analyses and interpretation, and drafting of the manuscript. HR participated in designing the study, data collection, data analyses and interpretation. JR participated in data collection, and drafting of the manuscript. PN participated in designing the study, conducted data analyses, participated in data interpretation, and drafting of the manuscript. PH conceptualized and designed the study, participated in data collection, conducted data analyses, participated in data interpretation and drafted the manuscript. All authors read and approved the final manuscript.Descriptive response category VAS data separately for people with Parkinson's disease and control subjects.Click here for file


Calpastatin is an endogenous inhibitor of calpain, intracellular calcium-activated protease. It has been suggested to be involved in molecular mechanisms of long-term plasticity and excitotoxic pathways. However, functions of calpastatin in vivo are still largely unknown. To examine the physiological roles of calpastatin, we subjected calpastatin-knockout mice to a comprehensive behavioral test battery.Calpastatin-knockout mice showed decreased locomotor activity under stressful environments, and decreased acoustic startle response, but we observed no significant change in hippocampus-dependent memory function.These results suggest that calpastatin is likely to be more closely associated with affective rather than cognitive aspects of brain function. In other words, calpain is bidirectionally regulated by Ca2+ and CS, and this is called the "calpain-CS system". CS inhibits two forms of calpain: μ-calpain  and m-calpain , which are activated by micromolar and millimolar Ca2+ in vitro, respectively . Seattle (WA): Allen Institute for Brain Science. Click here for file


Identification of global livestock diversity hotspots and their importance in diversity maintenance is essential for making global conservation efforts. We screened 52 sheep breeds from the Eurasian subcontinent with 20 microsatellite markers. By estimating and weighting differently within- and between-breed genetic variation our aims were to identify genetic diversity hotspots and prioritize the importance of each breed for conservation, respectively. In addition we estimated how important within-species diversity hotspots are in livestock conservation.Bayesian clustering analysis revealed three genetic clusters, termed Nordic, Composite and Fat-tailed. Southern breeds from close to the region of sheep domestication were more variable, but less genetically differentiated compared with more northern populations. Decreasing weight for within-breed diversity component led to very high representation of genetic clusters or regions containing more diverged breeds, but did not increase phenotypic diversity among the high ranked breeds. Sampling populations throughout 14 regional groups was suggested for maximized total genetic diversity.During initial steps of establishing a livestock conservation program populations from the diversity hot-spot area are the most important ones, but for the full design our results suggested that approximately equal population presentation across environments should be considered. Even in this case, higher per population emphasis in areas of high diversity is appropriate. The analysis was based on neutral data, but we have no reason to think the general trend is limited to this type of data. However, a comprehensive valuation of populations should balance production systems, phenotypic traits and available genetic information, and include consideration of probability of success. Ovis aries) has been an economically and culturally important farm animal species since its domestication in the Near East approximately 9,000 years B.P. )Kinghorn  suggesteKinghorn  proposedlgorithm .MT supervised the molecular analysis, consistency of allele calling, coordinated or performed statistical analysis and wrote the final drafts of the paper. MO did the genotyping and most of the writing and statistical analyses for the first draft. IT had significant contribution both to statistical analyses and manuscript writing. MAT contributed to analysis design and molecular co-ancestry based analyses. NM, MC, GG, TK and MM have collaborated in study design, sampling and interpretation of the results. In addition, MC and TK did part of the molecular analyses. JK was in charge of the overall study including it's design, sample collection, statistical analysis, manuscript writing and coordinating the author contributions. All authors read and approved the final manuscript.Table S1 - Marker diversity parameters. PDF file with list of microsatellites and their chromosomal location, total number of alleles, expected unbiased heterozygosity, and estimates of within-population (f) and among-population (θ) fixation indices.Click here for fileTable S2 - Table of the name of sheep breeds, their origin, demographic status and diversity parameters. PDF file with data on per population sample size, expected heterozygosity, within-breed fixation index (f), allelic richness, and number of private alleles.Click here for fileFigure S1 - Additional synthetic maps. PDF file synthetic maps for within-breed diversity and breed differentiation.Click here for fileTable S3 - Breed-wise optimal contributions to a core-set for different weightings of the within-breed variation. PDF file with detailed data summarized in Table Click here for fileTable S4 - Distribution of core-set contributions using genetic clustering. PDF file with table similar to Table Click here for fileTable S5 - Breeds, having equal contributions to the core set when the number of breeds conserved is fixed. PDF file with table of included breeds when the number of included breeds is fixed at 5, 10, 15 or 20.Click here for file


Determinants of exhaled nitric oxide (FeNO) need to be understood better to maximize the value of FeNO measurement in clinical practice and research. Our aim was to identify significant predictors of FeNO in an initial cross-sectional survey of southern California schoolchildren, part of a larger longitudinal study of asthma incidence.During one school year, we measured FeNO at 100 ml/sec flow, using a validated offline technique, in 2568 children of age 7–10 yr. We estimated online (50 ml/sec flow) FeNO using a prediction equation from a separate smaller study with adjustment for offline measurement artifacts, and analyzed its relationship to clinical and demographic characteristics.FeNO was lognormally distributed with geometric means ranging from 11 ppb in children without atopy or asthma to 16 ppb in children with allergic asthma. Although effects of atopy and asthma were highly significant, ranges of FeNO for children with and without those conditions overlapped substantially. FeNO was significantly higher in subjects aged > 9, compared to younger subjects. Asian-American boys showed significantly higher FeNO than children of all other sex/ethnic groups; Hispanics and African-Americans of both sexes averaged slightly higher than non-Hispanic whites. Increasing height-for-age had no significant effect, but increasing weight-for-height was associated with decreasing FeNO.FeNO measured offline is a useful biomarker for airway inflammation in large population-based studies. Further investigation of age, ethnicity, body-size, and genetic influences is needed, since they may contribute to substantial variation in FeNO. The fractional concentration of exhaled nitric oxide (FeNO) is associated with the degree of airway inflammation and oxidative/nitrosative stress -5. MeasuSubjects were drawn from a CHS cohort of public-school students in 13 Southern California communities with different levels and types of air pollution, originally recruited in the 2002–3 school year when they were in kindergarten or grade 1. Informed assent was sought from each child, and informed consent from a parent or guardian, for FeNO testing. The protocol was reviewed and approved by the University of Southern California Institutional Review Board. Consent was obtained and testing was performed successfully on 2792 subjects out of 3544 available cohort members. As described in Additional file Questionnaires, distributed to children at school and completed by parents, were used to determine children's demographic and allergy/asthma characteristics ,16. Usin2O respectively. The subject took 2–3 initial deep breaths through the kit's NO scrubber – which was less than 100% effective [Exhaled breath collection was performed at schools, usually from midmorning to noon to avoid traffic-related peaks of ambient NO and possible effects of recent eating on FeNO. Each community was visited at least twice in different seasons, to minimize confounding of location and season effects. Health status at testing was evaluated by a brief questionnaire; subjects with symptoms of acute respiratory infection within the past 3 days were excluded or rescheduled. The methodology for offline measurement of FeNO was validated by a small-scale a priori comparison against conventional online measurements , and by ffective ,20 – folffective ,20, whicCommercial software  was used for data quality checking and subsequent analysis. After exclusion of samples that developed problems after collection and subjects with incomplete demographic or clinical information  curves (not shown) were examined to determine how well the FeNO measurement could discriminate individuals with allergy or asthma from those without these conditions. To minimize confounding by nonclinical factors, ROC analyses were limited to non-Hispanic white and Hispanic subjects, and performed separately for subjects below and above age 9. Areas under ROC curves were 0.60 or less for allergy versus no allergy, or for any asthma versus no asthma.  The ability to classify active asthma with recurrent clinically significant wheezing, or with medication use in the past year, was slightly better, with areas under ROC curves of 0.66 to 0.68.Table Asthma/allergy groups showed highly significant (P < 0.0001) overall differences in FeNO. Asthma-without-allergy and allergy-without-asthma groups showed roughly similar increments relative to healthy subjects, while children with both respiratory allergy and asthma showed substantially larger increments. The asthma-without-allergy group, considered by itself, was not significantly different from healthy subjects, possibly because its small size limited statistical power of the group-comparison test. In a model including separate and interactive effects of allergy and asthma, both main effects were significant (P < 0.001) but the interaction did not reach statistical significance. Again, the interaction test had low power due to the small number of non-allergic asthmatics. Other 2-way interactions of grouping factors were nonsignificant, with the exception of sex and ethnicity, discussed below.To investigate the relationship of asthma activity and medication use to FeNO, we examined geometric mean FeNO for subgroups of physician-diagnosed asthmatic or asthma-medication-using subjects, adjusted for nonclinical factors as above. Detailed results are given in Additional file Age and ethnic group were significantly associated with FeNO (P < 0.0001 for either main effect). Point estimates for both younger age strata were about 11% lower than that for the 9 year-and-older stratum, after adjustment for other factors. Compared to the non-Hispanic white reference group, Asian-Americans showed a relatively large significant increase. Hispanics and African-Americans showed smaller increases, significant in Hispanics but not significant in African-Americans, probably because their smaller numbers limited statistical power. Elevated FeNO in Asian-Americans occurred primarily in boys. Figure Weight was associated with FeNO levels, while height was not, after accounting for effects of age. Residual weight-for-height  showed a small statistically significant P < 0.01) negative effect, estimated at 0.7% decrease in FeNO per kilogram. For example, in healthy >9-year-old non-Hispanic white boys of typical height, an increase of 20 kg above typical weight would predict a decrease in FeNO from 12.5 to 10.8 ppb. An alternative analysis by quartiles of residual weight-for-height (data not shown) indicated that this effect was present over most or all of the weight range, i.e. not driven by a minority of overweight or underweight individuals. Although weight-for-height was significantly higher in Hispanics than in Non-Hispanic whites, the weight effect did not explain those groups' significant difference in FeNO , but slightly higher than in subjects of similar age in the Finnish study. Some difference in FeNO readings between studies may be expected, given inherent variability of NO analyzers ,28 and sA potentially important finding, which is not new but seems to have received little attention, is that an appreciable percentage of clinically healthy subjects have FeNO levels in the range usually associated with poorly controlled asthma. For our Hispanic and non-Hispanic white subjects reported to be free from allergy or asthma, the 95th and 99th percentiles of FeNO were near 30 and 60 ppb respectively, and the highest values were near 100 ppb. We cannot entirely rule out the possibility that some of these high values resulted from artifacts, similar to the known incidents described in Additional file Previous studies of children have agreed that FeNO increases with growth, but have disagreed concerning the relative importance of age, height, and weight or body mass index to this increase. These apparent inconsistencies may reflect different age ranges and different clinical exclusion criteria in different studies, as well as different strategies for statistical modeling with multiple positively correlated predictor variables. Our cross-sectional analysis of a population with a narrow age range has limited ability to detect growth effects. Nevertheless, we have shown a highly significant age-related increase beginning around age 9, in general agreement with previous studies in North America and Europe -26. We fWe found higher adjusted mean FeNO in Hispanic children than in non-Hispanic white children. To our knowledge, this ethnic difference has not been reported previously. Our observation of elevated FeNO in Asian-descended boys, relative to European-descended boys and Asian-descended girls, is consistent with previous findings in Canada  and HongWe used an offline technique for measurement of FeNO. We have reported elsewhere a strong correlation of offline and online FeNO measurements in our study and have developed a calibration equation to convert offline measurement at 100 ml/s to the equivalent of online FeNO measured at 50 ml/s ,20. We fThis study has demonstrated the feasibility of large-scale field surveys of FeNO using offline breath collection and delayed laboratory analysis. In our population-based study, children's FeNO varied by respiratory allergy, asthma, ethnic origin (particularly in boys of Asian descent), and increasing age, as has been previously reported. An apparently new finding of elevated FeNO in Hispanic children relative to non-Hispanic white children warrants further investigation. The results reemphasize that FeNO may depend importantly on host factors other than respiratory health. These other sources of variation may complicate the interpretation of clinical FeNO tests.The authors declare that they have no competing interests.WL wrote the manuscript, performed statistical analyses, and oversaw field and laboratory work. ER performed data management, statistical analyses, and manuscript review. KB provided statistical review and oversight, and manuscript review. TB and EA provided project scientific oversight and manuscript review. FG had primary responsibility for scientific design, scientific oversight of this and related projects, and manuscript review.Additional Details of Methodology and Results. Gives details of offline FeNO prediction model, excluded data, weight effects on measured FeNO, medication effects on measured FeNO.Click here for file


PROCARB is an open-access database comprising three independently working components, namely, (i) Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB), (ii) Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii) CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins) as well as noncovalently (protein-carbohydrate complexes) is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools  Carbohydrates play a key role in a variety of important biological recognition processes like infection, immune response, cell differentiation, and neuronal development. All of these biological phenomena may be regulated by the interaction of these carbohydrates with proteins –4. One aIn spite of their numerous important biological roles, there is no appropriate database dedicated to these protein-carbohydrate complexes. Although, the Protein Data Bank (PDB)  stores aStructure-based approach to drug design has become a standard protocol in the pharmaceutical industry where large databases of potential small drug candidates may be docked into an active site of a particular target molecule . StructuFinally, functional annotation of proteins and understanding of functions in cases were only an amino acid sequence of protein is available requires predicting potential carbohydrate-binding sites, which experimentalists can then verify. Based on our previous work in this direction , we deveOverall organization of the database is illustrated in Figures The PROCARB core module is developed by systematically locating protein-carbohydrate complexes in the protein data bank (PDB) and manual verification of existence and identification of carbohydrate ligand. A protein is considered as a carbohydrate binding if any atom of its amino acid is within a 3.5 Å cutoff distance from any atom of the sugar in the protein-carbohydrate complex . VariousFASTA formatted sequences and 3D coordinates for both raw and nonredundant datasets are also stored in the database. These data sets are scheduled to be regularly updated as new entries become available from the PDB. For a quick analysis a set of four residue-wise structural features, namely, contact with carbohydrate, secondary structure, and solvent accessibility is included. These features are computed using standard software such as DSSP , ASAViewInformation on each complex is stored in an MYSQL database where the central protein table contains information regarding the protein, its bound ligand, function, and literature reference. Web interface uses PHP and JavaScript and allows searches by a variety of text-based options like PDB code, ligand name, protein name, and source organism. Data entries are displayed using dynamically generated pages which describe the relevant information including protein name, source, ligands, Pfam  descriptIn this module, we have attempted to generate the three-dimensional structures of a large number of glycoproteins (both N- and O-linked) with hitherto unknown structure, using automated web-based homology modeling. As a case study, a detailed project model-based 3D-structure of Hev b 4, a latex allergen N-glycoprotein has also been completed which is described elsewhere in our earlier work .To select proteins for modeling, Swissprot  search wSelected glycoprotein sequences, having at least one experimentally verified glycosylation site, were used as an input for the web server 3D-JIGSAW . This seThough this is based on using automated web-based homology modeling, most of the models are within the acceptable ranges of Ramachandran score Tables and 4 andMany proteins which interact with carbohydrates  are known without the knowledge of residues that participate in these interactions. Only few computational methods have been described till date which predict the covalently attached Glycosylation sites , 41 in pWe also tested the CBS-Pred on Area under the ROC curve (AUC)  for protPROCARB30: A nonredundant dataset of protein-carbohydrate complexes submitted to PDB between January 2007 and November 2008.PROCARB61: A redundant dataset of protein-carbohydrate complexes submitted to PDB between January 2007 and November 2008.A BLAST  sequenceDue to the enormous diversity of carbohydrates, it is always difficult to identify whether a given ligand in a PDB coordinate file is a carbohydrate or not. Carbohydrate Finder identifies diverse types of carbohydrates in a given protein-carbohydrate complex. Currently, it can recognize 100 different types of carbohydrates.Contact Calculator calculates the contacting pairs in a given protein-carbohydrate complex at different cutoff distances and can also recognize 100 different types of carbohydrates that may be in contact with the amino acid residues . A database of protein-carbohydrate complexes and models of unknown glycoprotein structures was developed, and an associated sequence-based prediction module was compiled. We expect that PROCARB will facilitate functional annotation, designing of site-directed mutagenesis experiments, and modeling protein-carbohydrate interactions which in turn will help the experimental and bioinformatics research on understanding protein-carbohydrate interactions.http://www.procarb.org or http://procarb.netasa.org.PROCARB can be accessed at