scholarly journals Microbial community with predictive power can be a new non-invasive substitute for clinical and pathological identification of diabetic nephropathy

2020 ◽  
Author(s):  
Jin Shang ◽  
Zhigang Ren ◽  
Ang Li ◽  
Ruixue Guo ◽  
Yiding Zhang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Gut Microbiome ◽  
Alpha Diversity ◽  
Short Chain Fatty Acids ◽  
Diagnostic Methods ◽  
Microbial Composition ◽  
Fecal Microbiome ◽  
Non Invasive ◽  
Microbial Biomarkers ◽  
Functional Relevance

Abstract Background Diabetic nephropathy is characterized by increased incidence, deficient diagnostic methods and poor prognosis. New idea about altered gut microbiome associated with diagnosis and development of diabetic nephropathy remains to be verified. The major aim of our study is to relate fecal microbiome to clinically diagnosed diabetic kidney disease (DKD) or pathologically identified diabetic nephropathy (defined as DN) and further evaluate diagnosis potential of microbial markers for DKD/DN. We carried out 16S rRNA sequencing on a discovery cohort consisting of 352 patients (DKD = 120, DM = diabetes mellitus = 92, Con = healthy controls = 140) to identify microbial taxa and construct DKD classifier. Functional relevance and clinic correlation of microbiome changes were performed using PICRUSt and Spearman analysis, respectively. Independent 60 DKDs and 116 non-DKDs (DM = 46, Con = 70) were used to validate the results. The same analysis was performed on DKD pathologic subtypes (DN = 22, MN = membranous nephropathy = 22). Results DKD/DM samples had a distinct microbiome signature with lower alpha-diversity and significantly different microbial composition compared with Con (P < 0.001). Expansion of opportunistic pathogens (Peptostreptococcaceae_incertae_sedis, Clostridium_sensu_stricto_1, Streptococcus, Enterococcus, Erysipelotrichaceae_incertae_sedis), sulphate-reducing bacteria (Desulfovibrio) and depletion of bacteria producing short-chain fatty acids (SCFA) (Bacteroides, Faecalibacterium, Blautia and Roseburia) were major contributors to above differences. Interestingly, mucosa-associated bacteria including Akkermansia and Ruminococcus were also increased in DKD. The combination of 11 microbial markers could separate 120 DKDs from 232 non-DKDs with an area under curve (AUC) of 88.12%. Correspondingly, diagnostic power of microbial biomarkers was evaluated in a validation cohort of 60 patients and 116 non-DKDs (AUC = 79.75%). Besides DKD-related lipid and arginine metabolism, we also observed an increase of metabolism of aromatic amino acid in DM. Additionally, microbial comparison was carried out between pathologic subtypes of DKD, which could be used to distinguish DN from MN with 77.69% AUC. Conclusion Gut microbiome-related changes were associated with pathogenesis of DKD/DN; Microbiota-targeted markers could be an alternative test for DKD diagnosis and a non-invasive choice to differentiate DKD pathologic subtypes.

scholarly journals Changes of Human Gut Microbiome Correlated with Metabolomics After Cranberry Juice Consumption in a Double-Blinded, Placebo Controlled, Crossover Study

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 497-497
Author(s):  
Shaomin Zhao ◽  
Gary Wang ◽  
Haiyan Liu ◽  
Christina Khoo ◽  
Liwei Gu
Keyword(s):  
Gut Microbiome ◽  
Alpha Diversity ◽  
Short Chain Fatty Acids ◽  
Cranberry Juice ◽  
Microbial Composition ◽  
Urine Metabolites ◽  
Funding Sources ◽  
Before And After ◽  
Ocean Spray ◽  
Double Blinded

Abstract Objectives 1) To investigate the changes of gut microbiome after 3 days and 21 days of cranberry juice consumption; 2) to correlate changes of microbiome with metabolome. Methods A double blinded, placebo-controlled, cross-over intervention study were conducted in 17 healthy young women aged 18–29 with normal BMI. Fecal, urine, and plasma samples were collected at baseline, after 3 days, and after 21 days consumption of double strength cranberry juice or a placebo juice. DNA was extracted from fecal samples and 16s rRNA was sequenced. Discriminant metabolites in urine and plasma was analyzed by UHPLC-Q-Orbitrap-HRMS and 0 identified using OPLS-DA models. Results 21-days but not 3 days of cranberry juice consumption significantly increased alpha diversity of colon microbiome compared to baseline. Significant increase in the abundance of Firmicutes, Ruminococcaceae, Faecalibacterium, and F/B (Firmicutes to Bacteroidetes) ratios were found after 21-days of cranberry juice intake. This was accompanied by decreases in Bacteroidetes, Proteobacteria, Clostridia, Enterobacteriaceae, Veillonellaceae, Bacteroides, Parabacteroides, and Enterobacter. Gut microbial composition before and after 21-days of cranberry juice consumption was significantly per Bray-Curtis dissimilarity analysis. However, cranberry consumption did not alter fecal content of short chain fatty acids, ammonia, or mucin. Spearman's correlation analysis showed significant positive or negative correlations between selected strains of bacteria and discriminant metabolites. 4-O-methylgallic acid was a discriminant metabolite in urine after 21-days of cranberry juice consumption. Its content positively correlated with Parabacteroides but negatively correlated with Faecalibacterium (P &lt; 0.05). 3-(Hydroxyphenyl) propionic acid was a discriminant metabolite in plasma after cranberry juice consumption. Its content negatively correlated with Enterobacteriaceae (P &lt; 0.05). Conclusions 21-days but not 3 days of cranberry juice consumption significantly altered colon microbiome. Correlation between gut bacteria and plasma, urine metabolites suggested interaction between gut microbiome and serum and urine metabolome. Funding Sources This research is funded in part by Ocean Spray Cranberries, inc.

scholarly journals Xylitol enhances synthesis of propionate in the colon via cross-feeding of gut microbiota

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Shasha Xiang ◽  
Kun Ye ◽  
Mian Li ◽  
Jian Ying ◽  
Huanhuan Wang ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Lactobacillus Reuteri ◽  
Carbon Sources ◽  
Short Chain Fatty Acids ◽  
Microbial Composition ◽  
Key Enzymes ◽  
Rrna Sequencing ◽  
Phosphate Acetyltransferase

Abstract Background Xylitol, a white or transparent polyol or sugar alcohol, is digestible by colonic microorganisms and promotes the proliferation of beneficial bacteria and the production of short-chain fatty acids (SCFAs), but the mechanism underlying these effects remains unknown. We studied mice fed with 0%, 2% (2.17 g/kg/day), or 5% (5.42 g/kg/day) (weight/weight) xylitol in their chow for 3 months. In addition to the in vivo digestion experiments in mice, 3% (weight/volume) (0.27 g/kg/day for a human being) xylitol was added to a colon simulation system (CDMN) for 7 days. We performed 16S rRNA sequencing, beneficial metabolism biomarker quantification, metabolome, and metatranscriptome analyses to investigate the prebiotic mechanism of xylitol. The representative bacteria related to xylitol digestion were selected for single cultivation and co-culture of two and three bacteria to explore the microbial digestion and utilization of xylitol in media with glucose, xylitol, mixed carbon sources, or no-carbon sources. Besides, the mechanisms underlying the shift in the microbial composition and SCFAs were explored in molecular contexts. Results In both in vivo and in vitro experiments, we found that xylitol did not significantly influence the structure of the gut microbiome. However, it increased all SCFAs, especially propionate in the lumen and butyrate in the mucosa, with a shift in its corresponding bacteria in vitro. Cross-feeding, a relationship in which one organism consumes metabolites excreted by the other, was observed among Lactobacillus reuteri, Bacteroides fragilis, and Escherichia coli in the utilization of xylitol. At the molecular level, we revealed that xylitol dehydrogenase (EC 1.1.1.14), xylulokinase (EC 2.7.1.17), and xylulose phosphate isomerase (EC 5.1.3.1) were key enzymes in xylitol metabolism and were present in Bacteroides and Lachnospiraceae. Therefore, they are considered keystone bacteria in xylitol digestion. Also, xylitol affected the metabolic pathway of propionate, significantly promoting the transcription of phosphate acetyltransferase (EC 2.3.1.8) in Bifidobacterium and increasing the production of propionate. Conclusions Our results revealed that those key enzymes for xylitol digestion from different bacteria can together support the growth of micro-ecology, but they also enhanced the concentration of propionate, which lowered pH to restrict relative amounts of Escherichia and Staphylococcus. Based on the cross-feeding and competition among those bacteria, xylitol can dynamically balance proportions of the gut microbiome to promote enzymes related to xylitol metabolism and SCFAs.

scholarly journals Gut Microbiome in Psoriasis: An Updated Review

Pathogens ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 463
Author(s):  
Mariusz Sikora ◽  
Albert Stec ◽  
Magdalena Chrabaszcz ◽  
Aleksandra Knot ◽  
Anna Waskiel-Burnat ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Beta Diversity ◽  
Large Scale ◽  
Skin Diseases ◽  
Intestinal Barrier ◽  
Alpha Diversity ◽  
Current Data ◽  
Intestinal Microbiome ◽  
Microbial Composition ◽  
Alpha And Beta Diversity

(1) Background: A growing body of evidence highlights that intestinal dysbiosis is associated with the development of psoriasis. The gut–skin axis is the novel concept of the interaction between skin diseases and microbiome through inflammatory mediators, metabolites and the intestinal barrier. The objective of this study was to synthesize current data on the gut microbial composition in psoriasis. (2) Methods: We conducted a systematic review of studies investigating intestinal microbiome in psoriasis, using the PRISMA checklist. We searched MEDLINE, EMBASE, and Web of Science databases for relevant published articles (2000–2020). (3) Results: All of the 10 retrieved studies reported alterations in the gut microbiome in patients with psoriasis. Eight studies assessed alpha- and beta-diversity. Four of them reported a lack of change in alpha-diversity, but all confirmed significant changes in beta-diversity. At the phylum-level, at least two or more studies reported a lower relative abundance of Bacteroidetes, and higher Firmicutes in psoriasis patients versus healthy controls. (4) Conclusions: There is a significant association between alterations in gut microbial composition and psoriasis; however, there is high heterogeneity between studies. More unified methodological standards in large-scale studies are needed to understand microbiota’s contribution to psoriasis pathogenesis and its modulation as a potential therapeutic strategy.

scholarly journals Probiotic Supplementation in a Clostridium difficile-Infected Gastrointestinal Model Is Associated with Restoring Metabolic Function of Microbiota

2019 ◽  
Vol 8 (1) ◽  
pp. 60
Author(s):  
Mohd Baasir Gaisawat ◽  
Chad W. MacPherson ◽  
Julien Tremblay ◽  
Amanda Piano ◽  
Michèle M. Iskandar ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Alpha Diversity ◽  
Gastrointestinal Disorder ◽  
Short Chain Fatty Acids ◽  
Rrna Gene ◽  
Metabolic Function ◽  
Microbial Composition ◽  
Single Strain ◽  
Fecal Samples ◽  
Metabolic Functions

Clostridium (C.) difficile-infection (CDI), a nosocomial gastrointestinal disorder, is of growing concern due to its rapid rise in recent years. Antibiotic therapy of CDI is associated with disrupted metabolic function and altered gut microbiota. The use of probiotics as an adjunct is being studied extensively due to their potential to modulate metabolic functions and the gut microbiota. In the present study, we assessed the ability of several single strain probiotics and a probiotic mixture to change the metabolic functions of normal and C. difficile-infected fecal samples. The production of short-chain fatty acids (SCFAs), hydrogen sulfide (H2S), and ammonia was measured, and changes in microbial composition were assessed by 16S rRNA gene amplicon sequencing. The C. difficile-infection in fecal samples resulted in a significant decrease (p < 0.05) in SCFA and H2S production, with a lower microbial alpha diversity. All probiotic treatments were associated with significantly increased (p < 0.05) levels of SCFAs and restored H2S levels. Probiotics showed no effect on microbial composition of either normal or C. difficile-infected fecal samples. These findings indicate that probiotics may be useful to improve the metabolic dysregulation associated with C. difficile infection.

scholarly journals Almond Snacking for 8 wk Increases Alpha-Diversity of the Gastrointestinal Microbiome and Decreases Bacteroides fragilis Abundance Compared with an Isocaloric Snack in College Freshmen

2019 ◽  
Vol 3 (8) ◽  
Author(s):  
Jaapna Dhillon ◽  
Zhaoping Li ◽  
Rudy M Ortiz
Keyword(s):  
Gut Microbiome ◽  
College Freshmen ◽  
Bacteroides Fragilis ◽  
Alpha Diversity ◽  
Control Group ◽  
Dietary Regimen ◽  
Unifrac Distance ◽  
Fecal Microbiome ◽  
Microbiome Diversity ◽  
Cardiometabolic Disorders

ABSTRACT Background Changes in gut microbiota are associated with cardiometabolic disorders and are influenced by diet. Almonds are a rich source of fiber, unsaturated fats, and polyphenols, all nutrients that can favorably alter the gut microbiome. Objectives The aim of this study was to examine the effects of 8 wk of almond snacking on the gut (fecal) microbiome diversity and abundance compared with an isocaloric snack of graham crackers in college freshmen. Methods A randomized, controlled, parallel-arm, 8-wk intervention in 73 college freshmen (age: 18–19 y; 41 women and 32 men; BMI: 18–41 kg/m2) with no cardiometabolic disorders was conducted. Participants were randomly allocated to either an almond snack group (56.7 g/d; 364 kcal; n = 38) or graham cracker control group (77.5 g/d; 338 kcal/d; n = 35). Stool samples were collected at baseline and 8 wk after the intervention to assess primary microbiome outcomes, that is, gut microbiome diversity and abundance. Results Almond snacking resulted in 3% greater quantitative alpha-diversity (Shannon index) and 8% greater qualitative alpha-diversity (Chao1 index) than the cracker group after the intervention (P < 0.05). Moreover, almond snacking for 8 wk decreased the abundance of the pathogenic bacterium Bacteroides fragilis by 48% (overall relative abundance, P < 0.05). Permutational multivariate ANOVA showed significant time effects for the unweighted UniFrac distance and Bray–Curtis beta-diversity methods (P < 0.05; R2 ≤ 3.1%). The dietary and clinical variables that best correlated with the underlying bacterial community structure at week 8 of the intervention included dietary carbohydrate (percentage energy), dietary fiber (g), and fasting total and HDL cholesterol (model Spearman rho = 0.16; P = 0.01). Conclusions Almond snacking for 8 wk improved alpha-diversity compared with cracker snacking. Incorporating a morning snack in the dietary regimen of predominantly breakfast-skipping college freshmen improved the diversity and composition of the gut microbiome. This trial was registered at clinicaltrials.gov as NCT03084003.

scholarly journals Usefulness of Machine Learning-Based Gut Microbiome Analysis for Identifying Patients with Irritable Bowels Syndrome

2020 ◽  
Vol 9 (8) ◽  
pp. 2403
Author(s):  
Hirokazu Fukui ◽  
Akifumi Nishida ◽  
Satoshi Matsuda ◽  
Fumitaka Kira ◽  
Satoshi Watanabe ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Gut Microbiome ◽  
Clinical Symptoms ◽  
Short Chain Fatty Acids ◽  
Gas Chromatography Mass Spectrometry ◽  
Healthy Controls ◽  
Fecal Microbiome ◽  
Microbiome Analysis ◽  
Model Based

Irritable bowel syndrome (IBS) is diagnosed by subjective clinical symptoms. We aimed to establish an objective IBS prediction model based on gut microbiome analyses employing machine learning. We collected fecal samples and clinical data from 85 adult patients who met the Rome III criteria for IBS, as well as from 26 healthy controls. The fecal gut microbiome profiles were analyzed by 16S ribosomal RNA sequencing, and the determination of short-chain fatty acids was performed by gas chromatography–mass spectrometry. The IBS prediction model based on gut microbiome data after machine learning was validated for its consistency for clinical diagnosis. The fecal microbiome alpha-diversity indices were significantly smaller in the IBS group than in the healthy controls. The amount of propionic acid and the difference between butyric acid and valerate were significantly higher in the IBS group than in the healthy controls (p < 0.05). Using LASSO logistic regression, we extracted a featured group of bacteria to distinguish IBS patients from healthy controls. Using the data for these featured bacteria, we established a prediction model for identifying IBS patients by machine learning (sensitivity >80%; specificity >90%). Gut microbiome analysis using machine learning is useful for identifying patients with IBS.

Alterations of gut microbiome in autoimmune hepatitis

Gut ◽  
2019 ◽  
Vol 69 (3) ◽  
pp. 569-577 ◽  
Author(s):  
Yiran Wei ◽  
Yanmei Li ◽  
Li Yan ◽  
Chunyan Sun ◽  
Qi Miao ◽  
...  
Keyword(s):  
Autoimmune Hepatitis ◽  
Gut Microbiome ◽  
Alpha Diversity ◽  
Disease Status ◽  
16S Rrna Gene Sequencing ◽  
Rrna Gene ◽  
Healthy Controls ◽  
Microbial Composition ◽  
Cross Sectional ◽  
Treatment Naïve

ObjectiveThe significance of the liver-microbiome axis has been increasingly recognised as a major modulator of autoimmunity. The aim of this study was to take advantage of a large well-defined corticosteroids treatment-naïve group of patients with autoimmune hepatitis (AIH) to rigorously characterise gut dysbiosis compared with healthy controls.DesignWe performed a cross-sectional study of individuals with AIH (n=91) and matched healthy controls (n=98) by 16S rRNA gene sequencing. An independent cohort of 28 patients and 34 controls was analysed to validate the results. All the patients were collected before corticosteroids therapy.ResultsThe gut microbiome of steroid treatment-naïve AIH was characterised with lower alpha-diversity (Shannon and observed operational taxonomic units, both p<0.01) and distinct overall microbial composition compared with healthy controls (p=0.002). Depletion of obligate anaerobes and expansion of potential pathobionts including Veillonella were associated with disease status. Of note, Veillonella dispar, the most strongly disease-associated taxa (p=8.85E–8), positively correlated with serum level of aspartate aminotransferase and liver inflammation. Furthermore, the combination of four patients with AIH-associated genera distinguished AIH from controls with an area under curves of approximately 0.8 in both exploration and validation cohorts. In addition, multiple predicted functional modules were altered in the AIH gut microbiome, including lipopolysaccharide biosynthesis as well as metabolism of amino acids that can be processed by bacteria to produce immunomodulatory metabolites.ConclusionOur study establishes compositional and functional alterations of gut microbiome in AIH and suggests the potential for using gut microbiota as non-invasive biomarkers to assess disease activity.

scholarly journals Influence of Fermented Vegetable Consumption on Gut Microbiome Diversity

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 1188-1188
Author(s):  
Sina Ullrich ◽  
Kerstin Thriene ◽  
Nadine Binder ◽  
Lena Amend ◽  
Till Strowig ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Vegetable Consumption ◽  
Statistical Significance ◽  
Alpha Diversity ◽  
Shannon Index ◽  
Fermented Foods ◽  
Post Intervention ◽  
Microbial Composition ◽  
Short Period ◽  
Fermented Vegetables

Abstract Objectives The effects of fermented foods on the gut microbiome are of great interest, yet evidence regarding its potential to increase gut microbial diversity, a measure likely associated with health, is lacking. Therefore, we analyzed the microbial composition (bacteria and yeasts) of commercially available fermented vegetables. Furthermore, we conducted a pilot study to assess the feasibility of studying effects of regular consumption of fermented vegetables on the gut microbiome. Methods Six healthy male volunteers (age: 25.5 ± 2.9yrs, BMI: 24.3 ± 1.2kg/m2) participated in a randomized crossover trial, with two 2-week intervention phases each of which was preceded by a 2-week washout phase. Participants consumed 150g/d of either sauerkraut (intervention 1) or a variety of six different fermented vegetables (intervention 2). We used 16S rRNA sequencing to assess the effects of each dietary regime on the composition, diversity and dynamics of the gut microbiome, as well as the composition and diversity of the fermented vegetable microbiome. Results Lactobacillus was the dominant genus in all fermented vegetables; still, the alpha diversity, richness and evenness of the microbiota differed substantially among the different products. Among our study participants, we observed an increase in alpha diversity (Shannon index) after both, consumption of sauerkraut (pre intervention: 3.31 ± 0.74, post intervention: 3.58 ± 0.68) and the selection of fermented vegetables (pre: 3.60 ± 0.93, post: 3.84 ± 0.81). However, the results did not reach statistical significance, due to the high inter- and intra-individual variability as evaluated by beta diversity of the gut microbial communities. Conclusions A longer-term intervention study with fermented vegetables and/or sauerkraut seems feasible. Consumption of fermented vegetables appears to increase the diversity of the gut microbiome, even after a relatively short period of time. However, further studies with a larger sample size are warranted to verify our observations. Funding Sources Institutional budget.

scholarly journals Characterizing the Skin and Gut Microbiome of Alopecia Areata Patients

2020 ◽  
Vol 4 (1) ◽  
pp. 23-30
Author(s):  
Margit Juhasz ◽  
Siwei Chen ◽  
Arash Khosrovi-Eghbal ◽  
Chloe Ekelem ◽  
Yessica Landaverde ◽  
...  
Keyword(s):  
Alopecia Areata ◽  
Gut Microbiome ◽  
Healthy Controls ◽  
Healthy Individuals ◽  
Microbial Composition ◽  
Future Directions ◽  
Fecal Microbiome ◽  
Autoimmune Attack ◽  
Significant Difference ◽  
Control Study

Background: Alopecia areata (AA) is caused by autoimmune attack of the hair follicle. The exact pathogenesis is unknown, but hypotheses include innate immunity imbalance, environmental exposures, genetic predisposition, and possibly the microbiome. The objective of this study was to characterize the skin and gut microbiome of AA patients, and compare microbial composition to healthy individuals. Methods: This was a pilot, case-control study. Scalp and fecal microbiome samples were collected from 25 AA patients, and 25 age, gender, and race-matched healthy controls in Southern California with no significant difference in demographic characteristics. After library preparation and identification of bacterial and fungal taxonomy, multivariant analysis was performed to compare AA and healthy microbiomes. Results: The AA scalp microbiome was significant for decreased Clostridia and Malasseziomycetes, and the gut microbiome was significant for decreased Bacteroidia and increased Bacilli (p<0.05) compared to healthy controls. Conclusions: The composition of the AA bacterial and fungal, scalp and gut microbiome is significantly different than healthy individuals. Future directions include using this data to characterize microbial changes associated with AA patient diet, relating to disease severity, and predicting disease progression, prognosis and/or therapeutic response.

scholarly journals Genetics of human gut microbiome composition

2020 ◽  
Author(s):  
Alexander Kurilshikov ◽  
Carolina Medina-Gomez ◽  
Rodrigo Bacigalupe ◽  
Djawad Radjabzadeh ◽  
Jun Wang ◽  
...  
Keyword(s):  
Association Study ◽  
Gut Microbiome ◽  
Genome Wide Association Study ◽  
Food Preferences ◽  
Microbial Composition ◽  
Fecal Microbiome ◽  
Microbiome Composition ◽  
Genome Wide ◽  
A Genome ◽  
Gwas Signal

AbstractTo study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed whole-genome genotypes and 16S fecal microbiome data from 18,473 individuals (25 cohorts). Microbial composition showed high variability across cohorts: we detected only 9 out of 410 genera in more than 95% of the samples. A genome-wide association study (GWAS) of host genetic variation in relation to microbial taxa identified 30 loci affecting microbome taxa at a genome-wide significant (P<5×10-8) threshold. Just one locus, the lactase (LCT) gene region, reached study-wide significance (GWAS signal P=8.6×10−21); it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.94×10−10<P<5×10−8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization analyses identified enrichment of microbiome trait loci SNPs in the metabolic, nutrition and environment domains and indicated food preferences and diseases as mediators of genetic effects.

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