susceptibility loci

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Genome-wide linkage screen for testicular germ cell tumour susceptibility loci.

Genome-wide linkage screen for testicular germ cell tumour susceptibility loci.

Abstract A family history of disease is a strong risk factor for testicular germ cell tumour (TGCT). In order to identify the location of putative TGCT susceptibility gene(s) we conducted a linkage search in 237 pedigrees with two or more cases of TGCT. 179 pedigrees were evaluated genome-wide with an average inter-marker distance of 10cM. An additional 58 pedigrees were used to more intensively investigate several genomic regions of interest. Genetic linkage analysis was performed with the ALLEGRO software using two model-based parametric analyses and a non-parametric analysis. Six genomic regions on chromosomes 2p23, 3p12, 3q26, 12p13-q21, 18q21-q23 and Xq27 showed heterogeneity LOD (HLOD) scores of greater than 1, with a maximum HLOD of 1.94 at 3q26. Genome-wide simulation studies indicate that the observed number of HLOD peaks greater than one does not differ significantly from that expected by chance. A TGCT locus at Xq27 has been previously reported. Of the 237 pedigrees examined in this study 66 were previously unstudied at Xq27, no evidence for linkage to this region was observed in this new pedigree set. Overall, the results indicate that no single major locus can account for the majority of the familial aggregation of TGCT, and suggests that multiple susceptibility loci with weak effects contribute to the disease.
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Genome-wide association study identifies novel restless legs syndrome susceptibility loci on 2p14 and 16q12.1.

Genome-wide association study identifies novel restless legs syndrome susceptibility loci on 2p14 and 16q12.1.

Restless Legs Syndrome Susceptibility Loci on 2p14 and 16q12.1 Juliane Winkelmann 1,2,3 *, Darina Czamara 4. , Barbara Schormair 1,3. , Franziska Knauf 1,3 , Eva C. Schulte 2 , Claudia Trenkwalder 5 , Yves Dauvilliers 6 , Olli Polo 7,8 , Birgit Ho¨gl 9 , Klaus Berger 10 , Andrea Fuhs 10 , Nadine Gross 2 , Karin Stiasny-Kolster 11,12 , Wolfgang Oertel 12 , Cornelius G. Bachmann 13 , Walter Paulus 13 , Lan Xiong 14 , Jacques Montplaisir 15,16 , Guy A. Rouleau 14 , Ingo Fietze 17 , Jana Va´vrova´ 18 , David Kemlink 18 , Karel Sonka 18 , Sona Nevsimalova 18 , Siong-Chi Lin 19 , Zbigniew Wszolek 19 , Carles Vilarin˜o-Gu¨ell 19 , Matthew J. Farrer 19 , Viola Gschliesser 9 , Birgit Frauscher 9 , Tina Falkenstetter 9 , Werner Poewe 9 , Richard P. Allen 20 , Christopher J. Earley 20 , William G. Ondo 21 , Wei-Dong Le 21 , Derek Spieler 1,3 , Maria Kaffe 2,3 , Alexander Zimprich 22 , Johannes Kettunen 23,24 , Markus Perola 23,24 , Kaisa Silander 23,24 , Isabelle Cournu- Rebeix 25,26,27 , Marcella Francavilla 25,26,27 , Claire Fontenille 25,26,27 , Bertrand Fontaine 25,26,27 , Pavel Vodicka 28 , Holger Prokisch 1,3 , Peter Lichtner 1,3 , Paul Peppard 29 , Juliette Faraco 30 , Emmanuel Mignot 30 , Christian Gieger 31 , Thomas Illig 32 , H.-Erich Wichmann 33,34,35 , Bertram Mu¨ller-Myhsok 4 , Thomas
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Detection of susceptibility loci by genome-wide linkage analysis.

Detection of susceptibility loci by genome-wide linkage analysis.

Determination of the susceptibility loci To identify the number and location of the susceptibility loci involved in the simulated disorder, a pooled linkage analysis of all 100 replicates in a given population was performed with the nonparametric linkage (NPL) statis- tics [1] using the ~7-cM microsatellite map and the ~3.5- cM SNP map. The affection status for KPD was as indi- cated by the clinicians in each population. The NPL was calculated using ALLEGRO [2] for the 3 populations AI, DA, and KA. Due to large family sizes and memory limita- tions, the NPL for the NY population was obtained using
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Type 1 diabetes susceptibility loci from genome scans in multiplex families

Type 1 diabetes susceptibility loci from genome scans in multiplex families

In addition, the current study reported the absence or very little support for linkage to type 1 diabetes of previously reported loci including chromosome 8q, IDDM4 (11q13), IDDM6 (18q12–q21), IDDM9 (3q22–q25), IDDM11 (14q24–q31), IDDM16 (14q32), IDDM17 (10q25) and IDDM18 (5q33). As suggested by Concannon et al., these putative type 1 diabetes susceptibility loci may represent either false-pos- itive results or have very small effects that may be more easily detected in certain populations (because of variation in allele frequencies or other factors such as the possibility of popula- tion-specific genetic or environmental effects).
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Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations.

Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations.

DISCUSSION We identified 38 additional IBD susceptibility loci by adding an extra 11,535 individuals of European descent and 9,846 individuals of non- European descent to our previously reported European-only cohort of 75,105 samples. Given that trans-ancestry association studies prin- cipally identify risk loci shared across populations, we would expect to identify a similar number of associated loci had all the individuals in this study been of the same ancestry. Our analyses suggest that significant differences in effect size are minimal at all but a handful of associated loci, further indicating that trans-ancestry association studies represent a powerful means of identifying new loci in com- plex diseases such as IBD. Furthermore, the nearly complete sharing of genetic risk among individuals of diverse ancestry has important consequences for association studies and disease risk prediction in non-European populations. First, a significant association in one population makes the locus in question a very strong candidate for involvement in IBD risk worldwide. Second, our data suggest that odds ratios estimated from a very large association study are likely to better represent the effect size of the associated variants in a second, ancestrally diverse population than those estimated from a substan- tially smaller study in the second population itself (because of the larger sampling variance in the second study). Finally, because rare alleles are more likely than common variants to be specific to a partic- ular population, the substantial number of IBD risk loci shared across ancestral populations implies that the underlying causal variants at these loci are common. This adds further weight to the grow- ing number of arguments against the ‘synthetic association’ model explaining a large proportion of GWAS loci 20–22 .
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Meta-analysis identifies seven susceptibility loci involved in the atopic march

Meta-analysis identifies seven susceptibility loci involved in the atopic march

The role of eczema loci and asthma loci in the atopic march. Next, we evaluated whether previously reported susceptibility loci for eczema or asthma were associated with the atopic march in our discovery meta-analysis. From the catalog of published GWASs 27 , we selected all SNPs which were associated with asthma or eczema at genome-wide significance level (Supplementary Tables 4 and 5), and examined association in our discovery set. All five GWAS loci previously associated with both traits (IL6R, IL1RL1/IL18R1, RAD50, human leukocyte antigen (HLA) region and C11orf30) replicated at Po0.001 in our data set. For the European susceptibility loci that were previously identified only in studies on eczema, we found the same risk alleles in our study; seven out of eight were associated with the atopic march (Po0.05; Supplementary Table 4). In contrast, only 3 out of 12 European loci identified only in GWAS on asthma were associated at Po0.05 (Supplementary Table 5). Moreover, ranking the known risk variants, which were specific for asthma or eczema according to their statistical significance in the discovery meta-analysis yielded a significant enrichment of eczema loci among the SNPs associated with the atopic march (P ¼ 0.0078; Fig. 2).
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On the use of haplotype phylogeny to detect disease susceptibility loci.

On the use of haplotype phylogeny to detect disease susceptibility loci.

The variability of the results obtained with the cladistic method is due for a minor part to the LD between the sus- ceptibility site(s) and the other sites and for the major part to parameters specific to the tree. Among these parame- ters, the position of the mutation in the tree (near the root or the leaves, sample size of the clades near the muta- tions...) has already been reported to have an influence on the power of cladistic methods to detect association [27]. Apart from the position of the mutation, the presence of sites that co-mutate with the susceptibility site, the degree of multiple mutations of the susceptibility site in the tree, and the existence of one or more reversions for the suscep- tibility site influence the power of the cladistic test to detect an association, and they have an even greater impact on the efficiency of the cladistic test to localize the susceptibility site. As all these factors are not independent, the evaluation of their own effects remains problematic. The four methods compared here (CT, HT, SbST and CLADHC) suppose that haplotypic data are available, which is not usually the case. The most likely haplotypes for an individual have to be reconstructed using numeri- cal methods (for a review of these methods, see [34,35]). The availability of familial data may help to determine the phase of the markers and then, to obtain the most likely haplotypes by using the genetic information of the two parents. However, even when these familial data are not available, the numerical methods have been shown to be
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Alzheimer's loci: epigenetic associations and interaction with genetic factors

Alzheimer's loci: epigenetic associations and interaction with genetic factors

significant association, and the remaining loci had no CpGs meeting the threshold of significance (Figs. S1–S3). Altogether, the 17 CpGs across the six gene regions that meet the threshold of significance explain 16.8% of the variability in NP. By reducing the analysis to the subset of subjects who were cognitively nonimpaired at the time of death, we see that the effect size of many of the associ- ated CpGs is not altered (Table S2), indicating that the association of DNA methylation at certain sites with AD pathology is not a feature only of the demented state. These alterations in DNA methylation within known AD susceptibility loci therefore occur early in the pathologic process with BIN1, CD2AP, ABCA7, and APOE primarily in the positive direction and CLU and MS4A6A in the negative direction, but we cannot, at this time, distinguish whether they are a cause or an effect of NP pathology. AD susceptibility alleles influence DNA methylation in the aging brain (SNP ? CpG) Given that the selected loci all harbor genetic variation associated with AD susceptibility in published literature,
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Interpretation of Variation Across Marker Loci as Evidence of Selection

Interpretation of Variation Across Marker Loci as Evidence of Selection

b F ST and mean heterozygosity. The percentiles were determined as described in Beaumont and Nichols (1996). Surprisingly , none of these 3 loci were detected as outliers using our method. There may be several reasons for this: W e suspect that, in the present case, the inclusion of a very distant insular population (Seychelle Island) may bias their analysis. Indeed, populations heterogeneous with respect to their demographic parameters (eective pop- ulation sizes and migration rates) have been shown to strongly aect their method (Beaumont and Nichols, 1996). Isolation (low migration rates) together with population bottlenecks, can introduce a further bias. Con- sider as an extreme case, the xation of a private allele at some locus in one population. This may be unexpected for a polymorphic locus in a mutation- migration-drift equilibrium model, unless there is a strong asymmetry , with some populations being smaller and receiving less immigrants than others. However, this is not unexpected for a model of separation and isolation, where there has been population bottlenecks. This may boost the F
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Tien Shan Geohazards Database: Landslide susceptibility analysis

Tien Shan Geohazards Database: Landslide susceptibility analysis

4. Conclusions In this paper we analysed landslide susceptibility for a large part (1200 ∗ 600 km) of the Tien Shan, Central Asia. This study is based on a new landslide inventory and a recently compiled set of hazard- relevant morphological, geological, climatic –hydrologic and seismo- tectonic information. Landslide susceptibility was analysed with respect to the aforementioned factors using the Landslide Factor analysis. The correlations between landslide occurrences and the various factors show that the distances to rivers as well as to faults and past earth- quakes most strongly constrain the susceptibility of slopes to landslides. For a series of zones, it could be observed that the landslide susceptibil- ity computed by considering the additional seismo-tectonic factors fits better the observed concentration of landslides than those computed for the other factors alone. Here, it should be noted that only the short-distance spatial relationship between landslide location and earthquake epicentres and fault lines (outcrops) was analysed in this paper. There are also a series of examples of remote effects of earth- quakes on slope failure activation that were not considered here. The strongest remote effects are known for several deep focal Mw N 6.5 earthquakes in the Hindu Kush and Pamir that caused extensive activa- tion of monitored landslides in the Angren mining region, Uzbekistan ( Niyazov and Nurtaev, 2014 ), in former mining in Kyrgyzstan ( Torgoev et al., 2013 ) and near the Baipaza Hydropower station in Tajikistan ( Havenith et al., 2013 ), at distances of more than 200 km up to 700 km from the hypocentre. One reason for the triggering of various observed geomechanical processes could be related to the particularly low frequency shaking induced earthquakes at those distant sites. However, more detailed investigations and numerical simulations are required to understand these phenomena and to incorporate them into a coupled earthquake-landslide hazard assessment.
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Calibration of in situ magnetic susceptibility measurements

Calibration of in situ magnetic susceptibility measurements

The second step of calibration is to consider non-homogeneous sam- ples, and in particular horizontal layering of magnetic susceptibility as can be found in soils or in the case of a rock sample lying on a soil. The response of the SM30 over its integration volume was evaluated by performing measurement of an infinite homogeneous body with increasing distance. This homogeneous body was a con- crete cylinder (40 cm in diameter, 20 cm high) described in Lecoanet et al. (1999). The SM30 was mounted on a retort stand equipped with a millimetre scale. The measurements with increasing distance are displayed on Fig. 5. It appears that the penetration depth of this instrument is about 6 cm and that 90 per cent of the signal come from the first 2.5 cm. It could be easily increased by using a larger coil, the penetration depth being comparable to the diameter of the coil. The curve in Fig. 5 has been parametrized by a sixth-degree
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Identification de loci suppresseurs du phénotype diabétique lié à la déficience en Hnf1a chez la souris

Identification de loci suppresseurs du phénotype diabétique lié à la déficience en Hnf1a chez la souris

proches et, en particulier, sont identiques concernant la séquence du locus majeur ModA (séquences de référence disponibles en ligne sur le site de l’Institut Sanger). 4.3 Identification d’un locus de résistance au diabète Notre modèle de rétrocroisements permettant la ségrégation du phénotype diabétique est relativement classique en dehors du choix de la production de souris « pseudo-N2 » en raison de la vigueur de l’hybride. En effet, les animaux "N2" portent sur tout le génome un allèle B6 (sensible) en regard d’un allèle 129 (sensible) ou CBA (résistant) ou bien encore un allèle recombinant 129/CBA. Ainsi la population de souris N2 présentait une croissance importante avec une ségrégation du phénotype diabétique et nous avons sélectionné les phénotypes les plus clairement identifiés comme sensibles ou résistants au diabète pour le balayage du génome. Le phénotypage a été particulèrement soigneux et orienté par les résultats obtenus dans les archétypes (lignées mutantes pures ou F1). Le choix des puces à haute densité Illumina présentant 1449 SNP a permis d’étudier un nombre conséquent de SNP (707) pour lesquels les séquences de référence étaient différentes entre souches 129 (sensible) et CBA (résistante) permettant d’étudier la contribution allélique de chacune des deux lignées. Le nombre important de SNP mais surtout le phénotypage fin des souris N2 expliquent que le locus ModA ait été identifié avec un LOD score aussi important : au-delà de 20 dans la première analyse chez les 86 souris du balayage du génome avec la puce à ADN Illumina et ensuite au-delà de 30 dans la seconde analyse qui comprenait 26 marqueurs et 55 souris additionnels. Grâce à ce second criblage, le locus majeur identifié sur le chromosome 3 (ModA) a pu être restreint dans son intervalle à environ 8 Mb (intervalle compris entre 27 et 34 Mb avec un intervalle de confiance de 95%). En sus de l’importance du LOD score qui permet d’identifier le QTL avec une certaine probabilité statistique, on peut évaluer la force de l’effet de ce QTL sur le caractère étudié en mesurant la part de la variance génétique qu’il contrôle. Dans notre cas, ce QTL semble très important car il contrôle plus de 60 % de la variance de la moyenne des glycémies à jeun. De plus, grâce à l’analyse des interactions génétiques, nous avons pu observer que présenter un locus ModA B6/CBA est nécessaire mais non suffisant pour que l’ensemble des souris présente un phénotype de résistance au diabète. Ainsi les cinq loci ancillaires identifiés interagissent avec ModA pour conférer la résistance au diabète.
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Quantitative trait loci (QTL) detection in multicross inbred designs

Quantitative trait loci (QTL) detection in multicross inbred designs

Manuscript received March 18, 2004 Accepted for publication August 10, 2004 ABSTRACT Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the parameter estimates depend largely on the choice of the two parental lines. Thus, the QTL detected in such populations represent only a small part of the genetic architecture of the trait. In addition, the effects of only two alleles are characterized, which is of limited interest to the breeder, while common pedigree breeding material remains unexploited for QTL mapping. In this study, we extend QTL mapping methodology to a generalized framework, based on a two-step IBD variance component approach, applicable to any type of breeding population obtained from inbred parents. We then investigate with simulated data mimicking conventional breeding programs the influence of different estimates of the IBD values on the power of QTL detection. The proposed method would provide an alternative to the development of specifically designed recombinant populations, by utilizing the genetic variation actually managed by plant breeders. The use of these detected QTL in assisting breeding would thus be facilitated.
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Rôles des interactions entre loci dans l'organisation spatiale fonctionnelle et l'évolution des génomes de mammifères

Rôles des interactions entre loci dans l'organisation spatiale fonctionnelle et l'évolution des génomes de mammifères

En particulier, nous avons démontré que les interactions entre séquences en répétition directe et situées en proximité linéaire les unes des autres peuvent conduire à des modifications h[r]

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Pore structure and frost susceptibility of building materials

Pore structure and frost susceptibility of building materials

/ La version de cette publication peut être l’une des suivantes : la version prépublication de l’auteur, la version acceptée du manuscrit ou la version de l’éditeur.. Access and use of[r]

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Ancient acquisition of “alginate utilization loci” by human gut microbiota

Ancient acquisition of “alginate utilization loci” by human gut microbiota

to be polyspecific and most of them have also been divided into subfamilies 10 . In contrast to the GH families however, PL families contain fewer members and the conservation of function within subfamilies is probably less robust 11 , making functional predictions from sequence data alone less reliable. In bacteria belonging to phylum Bacteroidetes, genes involved in the degradation of a given polysaccharide are often clustered on the genome and coregulated. These gene clusters have been termed “polysaccharide utili- zation loci” (PULs) 12 , 13 . This colocalization offers an additional lever for the prediction of the function of other polysaccharide-degrading enzymes when one or several members of a PUL have been biochemically character- ized. Over 26,000 predicted PULs are listed in the CAZy database ( http://www.cazy.org/PULDB/ ) based on the analysis of 820 bacteria from the human gut microbiote and from the environment 14 , 15 . Analysis of the marine bacterial genomes or metagenomes suggests a large diversity of PULs for the breakdown of marine polysaccha- rides 16 – 22 . However, the precise function (specificity) of the PULs can only be hypothesized based on sequence similarity of protein sequences found in the PUL with characterized, but distantly related, carbohydrate-active enzymes. Hypotheses on the specificity of marine PULs are usually formulated by confronting the putative func- tion of genes with the available literature on the composition or structure of marine polysaccharides. The function of several PULs involved in the degradation of marine polysaccharides has been demonstrated by transcriptom- ics, proteomics or enzymology methods. There are marine PULs that target laminaran and alginate 18 (the storage and cell wall polysaccharides of brown algae, respectively), ulvan 22 (the cell wall polysaccharide of the green algae
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Association mapping of inflammatory bowel disease loci to single variant resolution.

Association mapping of inflammatory bowel disease loci to single variant resolution.

1 3 j u l y 2 0 1 7 | V O l 5 4 7 | N A T u R E | 1 7 5 LRRK2, NOD2, and RTEL1/TNFRSF6B), and six intergenic variants (located 3.7 kilobases (kb) downstream of GPR35; 3.9 kb upstream of PRDM1; within a EP300 binding site 39.9 kb upstream of IKZF1; 500 base pairs (bp) before the transcription start site of JAK2; 9.4 kb upstream of NKX2-3; and 3.5 kb downstream from HNF4A) (Table 1). Of note, while physical proximity did not guarantee functional rele- vance, the credible set of variants for 30 associated loci now implicated a specific gene either because it resided within 50 kb of only that gene or had a coding variant with > 50% probability—improved from only 3 so refined using an earlier HapMap-based definition. Using the same definitions, the total number of potential candidate genes was reduced from 669 to 233. Examples of IBD candidate genes clearly prioritized in our data are described in the Supplementary Box, and a customizable browser (http://finemapping.broadinstitute.org/) is available to review the detailed fine-mapping results.
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Nod2 mediates susceptibility to Yersinia pseudotuberculosis in mice

Nod2 mediates susceptibility to Yersinia pseudotuberculosis in mice

Abstract Nucleotide oligomerisation domain 2 (NOD2) is a component of the innate immunity known to be involved in the homeostasis of Peyer patches (PPs) in mice. However, little is known about its role during gut infection in vivo. Yersinia pseudotuberculosis is an enteropathogen causing gastroenteritis, adenolymphitis and septicaemia which is able to invade its host through PPs. We investigated the role of Nod2 during Y. pseudotuberculosis infection. Death was delayed in Nod2 deleted and Crohn’s disease associated Nod2 mutated mice orogastrically inoculated with Y. pseudotuberculosis. In PPs, the local immune response was characterized by a higher KC level and a more intense infiltration by neutrophils and macrophages. The apoptotic and bacterial cell counts were decreased. Finally, Nod2 deleted mice had a lower systemic bacterial dissemination and less damage of the haematopoeitic organs. This resistance phenotype was lost in case of intraperitoneal infection. We concluded that Nod2 contributes to the susceptibility to Y. pseudotuberculosis in mice.
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The magnetic susceptibility in soft magnetic composite materials

The magnetic susceptibility in soft magnetic composite materials

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r]

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Microsatellite flanking region similarities among different loci within insect species

Microsatellite flanking region similarities among different loci within insect species

A further problem in Lepidoptera and in many other spe- cies (Keyghobadi et al ., 1999; Harper et al ., 2003; Meglécz et al ., 2004; Zhang, 2004; van’t Hof et al ., 2005) is the fre- quent presence of null alleles, even for apparently clearly amplifying and interpretable microsatellite loci. This prob- lem still has to be addressed in future research. Hardison et al . (2003) have demonstrated the covariance of substitu- tion rate and transposition frequency among different genomic regions in human and mouse genomes. One possibility is that transposition frequencies and substitution rates also covary among species, such that some species or groups of species have both a high number of trans- posable elements and high average mutation rates. In these species, the association between microsatellites and trans- posable elements can lead to many microsatellites that are not unique; but, even if amplification is successful, the high mutation rate in the flanking regions may lead to a high likeli- hood of null alleles.
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