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Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts
Open accessAbstract
Aging is a major risk factor in many forms of late-onset neurodegenerative disorders. The ability to recapitulate age-related characteristics of human neurons in culture will offer unprecedented opportunities to study the biological processes underlying neuronal aging. Here, we show that using a recently demonstrated microRNA-based cellular reprogramming approach, human fibroblasts from postnatal to near centenarian donors can be efficiently converted into neurons that maintain multiple age-associated signatures. Application of an epigenetic biomarker of aging (referred to as epigenetic clock) to DNA methylation data revealed that the epigenetic ages of fibroblasts were highly correlated with corresponding age estimates of reprogrammed neurons. Transcriptome and microRNA profiles reveal genes differentially expressed between young and old neurons. Further analyses of oxidative stress, DNA damage and telomere length exhibit the retention of age-associated cellular properties in converted neurons from corresponding fibroblasts. Our results collectively demonstrate the maintenance of age after neuronal conversion.
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“emphasizing the necessity of partial de-differentiation for rejuvenation (Box 1) to occur [22][23][24][25] .”
From Mechanisms, pathways and strategies for rejuvenation through epigenetic reprogramming (2023) · cites this paper as [23]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
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“Direct cellular reprogramming retains age-related signatures stored in pre-reprogrammed non-neural somatic cells such as fibroblasts, including the epigenetic age, telomere length, and gene expression changes (22, 23).”
From Modeling late-onset Alzheimer’s disease neuropathology via direct neuronal reprogramming (2024) · cites this paper as [22]
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“Conversely, other works have shown that aging-associated DNA methylation patterns and biomarkers persisted when cells were transdifferentiated (Box 1) to different cell types, emphasizing the necessity of partial de-differentiation for rejuvenation (Box 1) to occur [22][23][24][25] .”
From Mechanisms, pathways and strategies for rejuvenation through epigenetic reprogramming (2023) · cites this paper as [23]
In the citing paper
“Fibroblast-derived iNs preserve substantial signatures of human aging, including transcriptomic, nuclear pore, mitochondrial, epigenetic, and other aspects of aging (Herdy et al., 2019; Huh et al., 2016; Kim et al., 2018; Mertens et al., 2015a; Traxler et al., 2019).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
In the citing paper
“Clearly, iN DNAm ages reflect the adult and old chronological ages of their donors, whereas pluripotent stem cells and their derivatives reflect pre-natal DNAm ages (Figure 7H; Huh et al., 2016; Kim et al., 2014; Lo Sardo et al., 2017).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
In the citing paper
“Clearly, iN DNAm ages reflect the adult and old chronological ages of their donors, whereas pluripotent stem cells and their derivatives reflect pre-natal DNAm ages (Figure 7H; Huh et al., 2016; Kim et al., 2014; Lo Sardo et al., 2017).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
In the citing paper
“AD iNs did not display signs of accelerated epigenetic aging over control iNs (Figures 7I and 7J; Figure S6; Horvath, 2013; Huh et al., 2016).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
In the citing paper
“Cellular aging features (Huh et al., 2016; Mertens et al., 2015a, 2018; Tang et al., 2017; Victor et al., 2014) and adult-like neuronal identity of iNs (Luo et al., 2019) are likely critical for the emergence of such phenotypes in sporadic AD neurons, because erasure of aging signatures and re-gaining of fetal identity represents a potent rescue in this study (Miller et al., 2013; Ocampo et al., 2”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
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Citations
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BackgroundMicroRNA-mediated conversion of human fibroblasts to neurons
Yoo, A. S., Sun, A. X., Li, L., Shcheglovitov, A., Portmann, T., Li, Y., Lee-Messer, C., Dolmetsch, R. E., Tsien, R. W., & Crabtree, G. R. (2011) · Nature · doi:10.1038/nature10323 · Cited by 989 · cited 2×
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BackgroundMethodInfluentialLow-level processing of Illumina Infinium DNA Methylation BeadArrays
Triche, T. J., Weisenberger, D. J., Berg, D. V. D., Laird, P. W., & Siegmund, K. D. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt090 · Cited by 909 · cited 1×
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BackgroundInfluentialModelling pathogenesis and treatment of familial dysautonomia using patient-specific iPSCs
Lee, G., Papapetrou, E. P., Kim, H., Chambers, S. M., Tomishima, M. J., Fasano, C. A., Ganat, Y. M., Menon, J., Shimizu, F., Viale, A. J., et al. (2009) · Nature · doi:10.1038/nature08320 · Cited by 893 · cited 2×
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BackgroundInfluentialDirect Reprogramming of Terminally Differentiated Mature B Lymphocytes to Pluripotency
Hanna, J. H., Markoulaki, S., Schorderet, P., Carey, B. W., Beard, C., Wernig, M., Creyghton, M. P., Steine, E. J., Cassady, J. P., Foreman, R. K., et al. (2008) · Cell · doi:10.1016/j.cell.2008.03.028 · Cited by 830 · cited 3×
“Washington University School of Medicine Digital Commons@Becker Open Access Publications 2016 Maintenance of age in human neurons generated by microRNAbased neuronal conversion of fibroblasts Christine J. Huh Washington University School of Medicine in St. Louis Bo Zhang Washington University School of Medicine in St.…”
BackgroundHuman iPSC-based modeling of late-onset disease via progerin-induced aging
Miller, J. D., Ganat, Y. M., Kishinevsky, S., Bowman, R. L., Liu, B., Tu, E. Y., Mandal, P. K., Vera, E., Shim, J.-W., Kriks, S., et al. (2013) · Cell stem cell · doi:10.1016/j.stem.2013.11.006 · Cited by 777 · cited 5×
“Cell sorting was performed on a FACSCalibur and LsrFortessa (BD Biosciences), while quantification of the percent of the population of MitoSOX positive cells was performed using FlowJo X 10.0.7r2.”
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“1Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States; 2Program in Molecular and Cellular Biology, Washington University School of Medicine, St. Louis, United States; 3Program in Neuroscience, Washington University School of Medicine, St. Louis, United States; 4Depart…”
BackgroundResultInfluentialObesity accelerates epigenetic aging of human liver
Horvath, S., Erhart, W., Brosch, M., Ammerpohl, O., Schönfels, W. V., Ahrens, M., Heits, N., Bell, J. T., Tsai, P.-C., Spector, T. D., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1412759111 · Cited by 760 · cited 1×
“The utility of the epigenetic clock method has been demonstrated in applications surrounding cognitive function (Levine et al., 2015), obesity (Horvath et al., 2014), Down syndrome (Horvath et al., 2015b), HIV infection (Horvath and Levine, 2015), and Parkinson’s disease (Horvath and Ritz, 2015).”
MethodMeta-analysis of age-related gene expression profiles identifies common signatures of aging
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Aging effects on DNA methylation modules in human brain and blood tissue
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“generated by microRNA-based neuronal conversion of fibroblasts”
BackgroundGene expression changes in the course of normal brain aging are sexually dimorphic
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“‘Aging’ transcriptome and microRNAs in reprogrammed neurons Given the broad variability in gene expression with age in multiple cell types (Berchtold et al., 2008; Lu et al., 2004; Fraser et al., 2005; Glass et al., 2013) and a recent demonstration of main- tenance of age-associated transcriptomic…”
BackgroundPrigione, A., Fauler, B., Lurz, R., Lehrach, H., & Adjaye, J. (2010) · Stem Cells · doi:10.1002/stem.404 · Cited by 611 · cited 1×
“Oxidative stress has been reported to increase with age, in part due to the accumulation of reactive oxygen species (ROS) (Keating, 2008; Prigione et al., 2010; Suhr et al., 2010; Cui et al., 2012).”
BackgroundRejuvenating senescent and centenarian human cells by reprogramming through the pluripotent state
Lapasset, L., Milhavet, O., Prieur, A., Besnard, E., Babled, A., Aït-Hamou, N., Leschik, J., Pellestor, F., Ramirez, J.-M., De Vos, J., et al. (2011) · Genes & Development · doi:10.1101/gad.173922.111 · Cited by 570 · cited 2×
“…at: https://digitalcommons.wustl.edu/open_access_pubs Recommended Citation Huh, Christine J.; Zhang, Bo; Victor, Matheus B.; Dahiya, Sonika; Batista, Luis FZ; Horvath, Steve; and Yoo, Andrew S., ,"Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts."”
BackgroundHIV-1 infection accelerates age according to the epigenetic clock
Horvath, S., & Levine, A. J. (2015) · Journal of Infectious Diseases · doi:10.1093/infdis/jiv277 · Cited by 556 · cited 1×
“The utility of the epigenetic clock method has been demonstrated in applications surrounding cognitive function (Levine et al., 2015), obesity (Horvath et al., 2014), Down syndrome (Horvath et al., 2015b), HIV infection (Horvath and Levine, 2015), and Parkinson’s disease (Horvath and Ritz, 2015).”
MethodAccelerated epigenetic aging in Down syndrome
Horvath, S., Garagnani, P., Bacalini, M. G., Pirazzini, C., Salvioli, S., Gentilini, D., Blasio, A. M. D., Giuliani, C., Tung, S., Vinters, H. V., et al. (2015) · Aging Cell · doi:10.1111/acel.12325 · Cited by 487
Telomeres acquire embryonic stem cell characteristics in induced pluripotent stem cells
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“…which is virtually unchanged (Figure 4C), in contrast to the progressive increase in length commonly observed with iPSC reprogramming, where telomeres reach a plateau of around 12–14 kilobases after a few cellular passages (Agarwal et al., 2010; Batista et al., 2011; Marion et al., 2009).”
ResultLevine, M. E., Lu, A. T., Bennett, D. A., & Horvath, S. (2015) · Aging · doi:10.18632/aging.100864 · Cited by 455 · cited 1×
“The utility of the epigenetic clock method has been demonstrated in applications surrounding cognitive function (Levine et al., 2015), obesity (Horvath et al., 2014), Down syndrome (Horvath et al., 2015b), HIV infection (Horvath and Levine, 2015), and Parkinson’s disease (Horvath and Ritz, 2015).”
MethodSelf-citationIncreased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients
Horvath, S., & Ritz, B. R. (2015) · Aging · doi:10.18632/aging.100859 · Cited by 445 · cited 1×
“The utility of the epigenetic clock method has been demonstrated in applications surrounding cognitive function (Levine et al., 2015), obesity (Horvath et al., 2014), Down syndrome (Horvath et al., 2015b), HIV infection (Horvath and Levine, 2015), and Parkinson’s disease (Horvath and Ritz, 2015).”
MethodFang, Y. H., Shi, C., Manduchi, E., Civelek, M., & Davies, P. F. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002120107 · Cited by 427 · cited 2×
“cesses including inflammation, senescence, metabolism and telomerase activity (Kondo et al., 2016; Qin et al., 2012; Fang et al., 2010).”
BackgroundThe microRNA miR-34 modulates ageing and neurodegeneration in Drosophila
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BackgroundTelomere elongation in induced pluripotent stem cells from dyskeratosis congenita patients
Agarwal, S., Loh, Y., McLoughlin, E. M., Huang, J., Park, I., Miller, J. D., Huo, H., Okuka, M., dos Reis, R. M., Loewer, S., et al. (2010) · Nature · doi:10.1038/nature08792 · Cited by 334 · cited 2×
“…which is virtually unchanged (Figure 4C), in contrast to the progressive increase in length commonly observed with iPSC reprogramming, where telomeres reach a plateau of around 12–14 kilobases after a few cellular passages (Agarwal et al., 2010; Batista et al., 2011; Marion et al., 2009).”
BackgroundResultImpaired intrinsic immunity to HSV-1 in human iPSC-derived TLR3-deficient CNS cells
Lafaille, F. G., Pessach, I. M., Zhang, S.-Y., Ciancanelli, M. J., Herman, M., Abhyankar, A., Ying, S.-W., Keros, S., Goldstein, P. A., Mostoslavsky, G., et al. (2012) · Nature · doi:10.1038/nature11583 · Cited by 318
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Mitochondrial Rejuvenation After Induced Pluripotency
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“Oxidative stress has been reported to increase with age, in part due to the accumulation of reactive oxygen species (ROS) (Keating, 2008; Prigione et al., 2010; Suhr et al., 2010; Cui et al., 2012).”
BackgroundDNA damage and rpair with age in individual human lymphocytes
Singh, N. P., Danner, D. B., Tice, R. R., Brant, L. J., & Schneider, E. L. (1990) · Mutation Research/DNAging · doi:10.1016/0921-8734(90)90018-m · Cited by 217 · cited 1×
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MethodAging and Gene Expression in the Primate Brain
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BackgroundDefining the nature of human pluripotent stem cell progeny
Patterson, M., Chan, D. N., Ha, I., Case, D., Cui, Y., Handel, B. V., Mikkola, H. K., & Lowry, W. E. (2012) · Cell Research · doi:10.1038/cr.2011.133 · Cited by 145 · cited 2×
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MicroRNAs as Mediators of the Ageing Process
Harries, L. W. (2014) · Genes · doi:10.3390/genes5030656 · Cited by 101 · cited 2×
“…of Medicine, Washington University School of Medicine, St. Louis, United States; 6Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States; 7Department of Biostatistics, Fielding School of Public Health, University of”
BackgroundRole of microRNAs in endothelial inflammation and senescence
Qin, B., Yang, H., & Xiao, B. (2011) · Molecular Biology Reports · doi:10.1007/s11033-011-1241-0 · Cited by 90 · cited 1×
“While the exact role of these microRNAs in aging is unknown, miR-10a and miR-497 have been previously implicated in aging-associated cellular pro- cesses including inflammation, senescence, metabolism and telomerase activity (Kondo et al., 2016; Qin et al., 2012; Fang et al., 2010).”
BackgroundMicroRNA-based conversion of human fibroblasts into striatal medium spiny neurons
Richner, M., Victor, M. B., Liu, Y., Abernathy, D. G., & Yoo, A. S. J. (2015) · Nature Protocols · doi:10.1038/nprot.2015.102 · Cited by 89 · cited 7×
“…in age from 3 days to 96-year old were transduced with a lentiviral preparation of the Doxycline-inducible synthetic cluster of miR-9/9* and miR-124 (miR-9/9*-124), alongside transcription factors CTIP2, DLX1, DLX2, and MYT1L as previously described (Richner et al., 2015; Victor et al., 2014).”
BackgroundMethodInfluentialTomlinson, R. L., Abreu, E. B., Ziegler, T. D., Ly, H., Counter, C. M., Terns, R. M., & Terns, M. P. (2008) · Molecular Biology of the Cell · doi:10.1091/mbc.e08-02-0184 · Cited by 71 · cited 1×
“The data were normalized using the ’Noob’ normalization method (Triche et al., 2013).”
Back and forth in time: Directing age in iPSC-derived lineages
Cornacchia, D., & Studer, L. (2017) · Brain Research · doi:10.1016/j.brainres.2015.11.013 · Cited by 56 · cited 2×
“Recently, experimental manipulations to accelerate aging in iPSC-derived cells have been explored, for instance, by overexpressing progerin, a mutant form of lamin A observed in progeria syndrome, to force the detection of agerelated pathophysiology of neurodegenerative disease (Arbab et al., 2014; Cornacchia and Stud…”
BackgroundSenescence: the good the bad and the dysfunctional
Pazolli, E., & Stewart, S. A. (2008) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2007.12.002 · Cited by 52 · cited 1×
“…population doubling level (PDL) to elimi- nate any confounding variability introduced by sequential passaging (Campisi and d’Adda di Fagagna, 2007; Pazolli and Stewart, 2008), then subsequently transduced with miR-9/9*-124 with CTIP2, DLX1/2, and MYT1L (CDM) following our established protocol…”
MethodWhen rejuvenation is a problem: challenges of modeling late-onset neurodegenerative disease
Vera, E., & Studer, L. (2015) · Development · doi:10.1242/dev.120667 · Cited by 45 · cited 4×
“…we previously described a reprogramming paradigm using neuronal microRNAs (miRNAs), miR-9/9* and miR-124 (miR-9/9*-124), that exert reprogramming activities to directly convert human fibroblasts to specific mature neuronal subtypes (Richner et al., 2015; Victor et al., 2014; Yoo et al., 2011).”
BackgroundMethodInfluentialKondo, H., Kim, H. W., Wang, L., Okada, M., Paul, C., Millard, R. W., & Wang, Y. (2015) · Aging Cell · doi:10.1111/acel.12411 · Cited by 39 · cited 1×
“While the exact role of these microRNAs in aging is unknown, miR-10a and miR-497 have been previously implicated in aging-associated cellular pro- cesses including inflammation, senescence, metabolism and telomerase activity (Kondo et al., 2016; Qin et al., 2012; Fang et al., 2010).”
BackgroundTranslational gene mapping of cognitive decline
Wilmot, B., McWeeney, S. K., Nixon, R. R., Montine, T. J., Laut, J., Harrington, C. A., Kaye, J. A., & Kramer, P. L. (2006) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2006.11.008 · Cited by 35 · cited 1×
“…we previously described a reprogramming paradigm using neuronal microRNAs (miRNAs), miR-9/9* and miR-124 (miR-9/9*-124), that exert reprogramming activities to directly convert human fibroblasts to specific mature neuronal subtypes (Richner et al., 2015; Victor et al., 2014; Yoo et al., 2011).”
BackgroundModeling motor neuron disease: the matter of time
Arbab, M., Baars, S., & Geijsen, N. (2014) · Trends in Neurosciences · doi:10.1016/j.tins.2014.07.008 · Cited by 33 · cited 2×
“Recently, experimental manipulations to accelerate aging in iPSC-derived cells have been explored, for instance, by overexpressing progerin, a mutant form of lamin A observed in progeria syndrome, to force the detection of agerelated pathophysiology of neurodegenerative disease (Arbab et al., 2014; Cornacchia and Stud…”
Background
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DNA methylation-based biomarkers and the epigenetic clock theory of ageing
Horvath, S., & Raj, K. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0004-3 · Cited by 3,095
The ageing epigenome and its rejuvenation
Zhang, W., Qu, J., Liu, G.-H., & Belmonte, J. C. I. (2020) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0204-5 · Cited by 458
Modeling Alzheimer’s disease with iPSC-derived brain cells
Penney, J., Ralvenius, W. T., & Tsai, L.-H. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0468-3 · Cited by 471
Building Models of Brain Disorders with Three-Dimensional Organoids
Amin, N. D., & Paşca, S. P. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.007 · Cited by 312
Chen, X., & Mobley, W. C. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00659 · Cited by 296
Metadata
- Authors
- Huh, C. J., Zhang, B., Victor, M. B., Dahiya, S., Batista, L. F., Horvath, S., & Yoo, A. S.
- Affiliations
- Washington University in St. Louis (US)
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States
- University of California, Los Angeles (US)
- Corresponding author
- Yoo, Andrew S
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2016-09-20
- Volume
- 5
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC5067114
- OpenAlex
- W2521543069
- Cited by
- 213
- References
- 57
- Citations by year
- 2026: 16 · 2025: 18 · 2024: 23 · 2023: 22 · 2022: 17 · 2021: 33 · 2020: 29 · 2019: 17 · 2018: 26 · 2017: 11
- FWCI
- 9.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institute on Drug Abuse (R25 DA027995)
- National Institutes of Health (K99/R00, 4R00HL114732-03, 1U34AG051425-01, 5R01, AG042511-02, DP2NS083372-01)
- Washington University in St. Louis (DDRCC, NIDDK P30 DK052574)
- Ellison Medical Foundation (AG-NS-0878-12)
- Cure Alzheimer's Fund
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Pluripotent Stem Cells Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
- Keywords
- neuronal aging, fibroblast-to-neuron conversion, epigenetic clocks, DNA methylation, age-related gene expression, oxidative stress, DNA damage, telomere length, neurodegenerative diseases, human neurons
- MeSH terms
- Aging, Cytological Techniques, DNA Damage, Fibroblasts, Humans, Neurons, Telomere, Oxidative Stress, Gene Expression Profiling, MicroRNAs, Epigenesis, Genetic, Cell Transdifferentiation
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