Репозиторий OAI—PMH
Репозиторий Российская Офтальмология Онлайн по протоколу OAI-PMH
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Suber S. Huang
Зрение будущего: 2020 и выше – 5 важнейших тенденций в научных исследованиях в области офтальмологии
1. Available at: https://www.fda.gov/files/ vaccines%2C%20blood%20 %26%20biologics/published/Clinical-Review–December-16–2017– LUXTURNA.pdf
2. Russsell S., Bennett J., Wellman J.A., et al. Efficacy and safety of voretigene neparvovec (AAV2-hRPE65v2) in patients with RPE65-mediated inherited retinal dystrophy: a randomized, controlled, open-label, phase 3 trial. Lancet. 2017;390: 849–860.
3. Acland G.M., Aquirre G.D., Ray J., et al. Gene therapy restores vision in a canine model of childhood blindness. Nat Genet. 2001;28: 92–95.
4. Jacobson S.G., Cideciyan A.V., Ratnakaram R., et al. Gene therapy for Leber congenital amaurosis caused by RPE65 mutations: safety and efficacy in 15 children and adults followed up to 3 years. Arch Ophthalmol. 2012;130: 9–24.
5. Testa F., Maguire A.M., Rossi S., et al. Three-year follow-up after unilateral subretinal delivery of adeno-associated virus in patients with Leber congenital amaurosis type 2. Ophthalmology. 2013;120: 1283–1291.
6. Bainbridge J.W., Smith A.J., Barker S.S., et al. Effect of gene therapy on visual function in Leber congenital amaurosis. N Engl J Med. 2008;358: 2231– 2239.
7. Bennett J., Wellman J., Marshall K.A., et al. Safety and durability of effect of contralateral-eye administration of AAV2 gene therapy in patients with childhood-onset blindness caused by RPE65 mutations: a follow-on phase 1 trial. Lancet. 2016;388: 661–672.
8. Heier J. Regenxbio to present interim phase I/II2 Trial update for RGX-314 for the treatment of Wet AMD. American Academy of Ophthalmology; 2019.
9. Ali R.R., Reichel M.B., Thrasher A.J., et al. Gene transfer into the mouse retina mediated by an adeno-associated viral vector. Hum Mol Genet. 1996;5: 591–594.
10. Flannery J.G., Zolotukhin S., Vaquero M.I., LaVail M.M., Muzyczka N., Hauswirth W.W. Efficient photoreceptor-targeted gene expression in vivo by recombinant adeno-associated virus. Proc Natl Acad Sci U S A. 1997;94: 6916–6921.
11. Trapani I., Puppo A., Auricchio A., et al. Vector platforms for gene therapy of inherited retinopathies. Prog Retin Eye Res. 2014;43: 108–128.
12. Salganik M., Hirsch M.L., Samulski R.J. Adeno-associated virus as a mammalian DNA vector. Microbiol Spectr. 2015;3: 4. doi:10.1128/ microbiolspec.MDNA3-0052-2014
13. Puppo A., Cesi G., Marrocco E., et al. Retinal transduction profiles by highcapacity viral vectors. Gene Ther. 2014;21: 855–865.
14. Gruter O., Kostic C., Crippa S.V., et al. Lentiviral vector-mediated gene transfer in adult mouse photoreceptors is impaired by the presence of a physical barrier. Gene Ther. 2005;12: 942–947.
15. Chung D.C., McCague S., Yu Z.F., et al. Novel mobility test to assess functional vision in patients with inherited retinal dystrophies. Clin Exp Ophthalmol. 2018;46: 247–259.
16. Mammadzada P., Corredoira P.M., Andre H. The role of hypoxia-inducible factors in neovascular age-related macular degeneration: a gene therapy perspective. Cell Mol Life Sci. 2020;77: 819–833.
17. Trapani I., Auricchio A. Seeing the light after 25 years of retinal gene therapy. Trends Mol Med. 2018;24: 669–681.
18. Saadane A., Mast N., Charvet C.D., et al. Retinal and non-ocular abnormalities in cyp27a cyp46a mice with dysfunctional metabolism of cholesterol. Am J Pathol. 2014;184: 2403–2419.
19. Zhang R., Perlman E., Huang S.S. Immunomodulation of Murine Infectious Keratitis by MSC (poster), Charleston, SC; February 26, 2015.
20. Huang S.S., et al. Reduction of neovascular response in a laser injury model of choroidal neovascularization in a rat model. Unpublished data. Abstract; 2012.
21. Ankrum J.A., Ong J.F., Karp J.M. Mesenchymal stem cells: immune evasive, not immune privileged. Nat Biotechnol. 2014;32: 252–260.
22. Mahla R.S. Stem cell applications in regenerative medicine and disease therapeutics. Int J Cell Biol. 2016;2016: 6940283.
23. Guan Y., Cui L., Qu Z., et al. Subretinal transplantation of rat MSCs and erythropoietin gene modified rat MSCs for protecting and rescuing degenerative retina in rats. Curr Mol Med. 2013;13: 1419–1431.
24. Teh S.W., Mok P.L., Abd Rashid M., et al. Recent updates on treatment of ocular microbial infections by stem cell therapy: a review. Int J Mol Sci. 2018;19: 558–584.
25. Shukla S., Shanbhag S.S., Tavakkoli F., Varma S., Singh V., Basu S. Limbal epithelial and mesenchymal stem cell therapy for corneal regeneration. Curr Eye Res. 2019;43: 3265–3277.
26. Li Y., Smith D., Li Q., et al. Antibody-mediated retinal pericyte injury: implications for diabetic retinopathy. Invest Ophthalmol Vis Sci. 2012;53: 5520–5526.
27. Tu Z., Li Y., Smith D.S., et al. Retinal pericytes inhibit activated T cell proliferation. Invest Ophthalmol Vis Sci. 2011;52: 9005–9010.
28. Cheng L., Bu H., Portillo J.A., et al. Modulation of retinal Muller cells by complement receptor C5aR. Invest Ophthalmol Vis Sci. 2013;54: 8191–8198.
29. Ding S.S.L., Subbiah S.K., Khan M.S.A., Farhana A., Mok P.L. Empowering mesenchymal stem cells for ocular degenerative disorders. Int J Mol Sci. 2019;20: 1784.
30. Banderia F., Goh T.W., Setiawan M., Yam G.H., Mehta J.S. Cellular therapy of corneal epithelial defect by adipose mesenchymal stem cell-derived epithelial progenitors. Stem Cell Res Ther. 2020;11: 14–27.
31. Jensen T.I., Axelgaard E., Bak R.O. Therapeutic gene editing in haematological disorders with CRISPR/Cas9. Br J Haematol. 2019;185: 821–835.
32. Srivastava S., Riddell S.R. Engineering CAR-T cells: design concepts. Trends Immunol. 2015;36: 494–503.
33. Stern J.H., Tian Y., Funderburgh J., et al. Regenerating eye tissues to preserve and restore vision. Cell Stem Cell. 2018;22: 834–849.
34. M’Barek K.B., Monville C. Cell therapy for retinal dystrophies: from cell suspension formulation to complex retinal tissue bioengineering. Stem Cells Int. 2019;2019: 4568979.
35. Singh M.S., Park S.S., Albini T.A., et al. Retina stem cell transplantation: balancing safety and potential. Prog Retin Eye Res. 2019;75: 100779.
36. Kashani A.H., Lebkowski J.S., Rahhal F.M., et al. A bioengineered retinal pigment epithelial monolayer for advanced, dry age-related macular degeneration. Science Trans Med. 2018;10: eaao4097.
37. McGill T.J., et al. Modelling early retinal development with human embryonic and induced pluripotential stem cells. Investig Ophthalmol Vis Sci. 2018;59: 1374–1383.
38. Sohn E.H., Jiao C., Kaalberg E., et al. Allogenic iPSC derived RPE cell transplants induce immune response in pigs: a pilot study. Sci Rep. 2015;5: 11791.
39. Trujillo C.A., Gao R., Negraes P.D., et al. Complex oscillatory waves emerging from cortical organoids model early human brain network development. Cell Stem Cell. 2019;25: 558–569.e7.
40. World Economic Forum. The fourth industrial revolution: what it means, how to respond. 2016. Available at: https://www.weforum.org/ agenda/2019/01/the-fourth-industrial-revolution-and-what-it-means/
41. Ting D.S.W., Pasquale L.R., Peng L, et al. Artificial intelligence and deep learning in ophthalmology. Br J Ophthalmol. 2019;103: 167–175.
42. Schmidt-Erfurth U., Sadeghipour A., Gerendas B.S., Waldstein S.M., Bogunovi H. Artificial intelligence in retina. Prog Retin Eye Res. 2018;67: 1–29.
43. Fenner B.J., Wong R.L.M., Lam W.C., Tan G.S.W., Cheung G.C.M. Advances in retinal imaging and applications in diabetic retinopathy screening: a review. Ophthalmol Ther. 2018;7: 333–346.
44. Esteva A., Kuprel B., Novoa R.A., et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542: 115–118.
45. Wang X., Peng Y., Lu L., et al. Chest X-ray8: hospital scale chest X-ray database and benchmarks on weakly supervised classification of chest and thorax diseases. 2017;arXiv:1705.02315.
46. Fei X., Zhao J., Zhao H., et al. Deblurring adaptive optics retinal images using deep convolutional using deep convolutional neural networks. Biomed Optic Express. 2017;8(12): 5675–5687.
47. Lee C.S., Tyring A.J., Wu Y., et al. Generating retinal flow maps from structural optical coherence tomography with artificial intelligence. Sci Rep. 2019;9: 5694.
48. Silver D., Hubert T., Schrittwieser J., et al. AlphaZero – a general reinforcement learning algorithm that masters Chess, Shogi, and Go through self-play. Science. 2018;362: 1140–1144.
2. Russsell S., Bennett J., Wellman J.A., et al. Efficacy and safety of voretigene neparvovec (AAV2-hRPE65v2) in patients with RPE65-mediated inherited retinal dystrophy: a randomized, controlled, open-label, phase 3 trial. Lancet. 2017;390: 849–860.
3. Acland G.M., Aquirre G.D., Ray J., et al. Gene therapy restores vision in a canine model of childhood blindness. Nat Genet. 2001;28: 92–95.
4. Jacobson S.G., Cideciyan A.V., Ratnakaram R., et al. Gene therapy for Leber congenital amaurosis caused by RPE65 mutations: safety and efficacy in 15 children and adults followed up to 3 years. Arch Ophthalmol. 2012;130: 9–24.
5. Testa F., Maguire A.M., Rossi S., et al. Three-year follow-up after unilateral subretinal delivery of adeno-associated virus in patients with Leber congenital amaurosis type 2. Ophthalmology. 2013;120: 1283–1291.
6. Bainbridge J.W., Smith A.J., Barker S.S., et al. Effect of gene therapy on visual function in Leber congenital amaurosis. N Engl J Med. 2008;358: 2231– 2239.
7. Bennett J., Wellman J., Marshall K.A., et al. Safety and durability of effect of contralateral-eye administration of AAV2 gene therapy in patients with childhood-onset blindness caused by RPE65 mutations: a follow-on phase 1 trial. Lancet. 2016;388: 661–672.
8. Heier J. Regenxbio to present interim phase I/II2 Trial update for RGX-314 for the treatment of Wet AMD. American Academy of Ophthalmology; 2019.
9. Ali R.R., Reichel M.B., Thrasher A.J., et al. Gene transfer into the mouse retina mediated by an adeno-associated viral vector. Hum Mol Genet. 1996;5: 591–594.
10. Flannery J.G., Zolotukhin S., Vaquero M.I., LaVail M.M., Muzyczka N., Hauswirth W.W. Efficient photoreceptor-targeted gene expression in vivo by recombinant adeno-associated virus. Proc Natl Acad Sci U S A. 1997;94: 6916–6921.
11. Trapani I., Puppo A., Auricchio A., et al. Vector platforms for gene therapy of inherited retinopathies. Prog Retin Eye Res. 2014;43: 108–128.
12. Salganik M., Hirsch M.L., Samulski R.J. Adeno-associated virus as a mammalian DNA vector. Microbiol Spectr. 2015;3: 4. doi:10.1128/ microbiolspec.MDNA3-0052-2014
13. Puppo A., Cesi G., Marrocco E., et al. Retinal transduction profiles by highcapacity viral vectors. Gene Ther. 2014;21: 855–865.
14. Gruter O., Kostic C., Crippa S.V., et al. Lentiviral vector-mediated gene transfer in adult mouse photoreceptors is impaired by the presence of a physical barrier. Gene Ther. 2005;12: 942–947.
15. Chung D.C., McCague S., Yu Z.F., et al. Novel mobility test to assess functional vision in patients with inherited retinal dystrophies. Clin Exp Ophthalmol. 2018;46: 247–259.
16. Mammadzada P., Corredoira P.M., Andre H. The role of hypoxia-inducible factors in neovascular age-related macular degeneration: a gene therapy perspective. Cell Mol Life Sci. 2020;77: 819–833.
17. Trapani I., Auricchio A. Seeing the light after 25 years of retinal gene therapy. Trends Mol Med. 2018;24: 669–681.
18. Saadane A., Mast N., Charvet C.D., et al. Retinal and non-ocular abnormalities in cyp27a cyp46a mice with dysfunctional metabolism of cholesterol. Am J Pathol. 2014;184: 2403–2419.
19. Zhang R., Perlman E., Huang S.S. Immunomodulation of Murine Infectious Keratitis by MSC (poster), Charleston, SC; February 26, 2015.
20. Huang S.S., et al. Reduction of neovascular response in a laser injury model of choroidal neovascularization in a rat model. Unpublished data. Abstract; 2012.
21. Ankrum J.A., Ong J.F., Karp J.M. Mesenchymal stem cells: immune evasive, not immune privileged. Nat Biotechnol. 2014;32: 252–260.
22. Mahla R.S. Stem cell applications in regenerative medicine and disease therapeutics. Int J Cell Biol. 2016;2016: 6940283.
23. Guan Y., Cui L., Qu Z., et al. Subretinal transplantation of rat MSCs and erythropoietin gene modified rat MSCs for protecting and rescuing degenerative retina in rats. Curr Mol Med. 2013;13: 1419–1431.
24. Teh S.W., Mok P.L., Abd Rashid M., et al. Recent updates on treatment of ocular microbial infections by stem cell therapy: a review. Int J Mol Sci. 2018;19: 558–584.
25. Shukla S., Shanbhag S.S., Tavakkoli F., Varma S., Singh V., Basu S. Limbal epithelial and mesenchymal stem cell therapy for corneal regeneration. Curr Eye Res. 2019;43: 3265–3277.
26. Li Y., Smith D., Li Q., et al. Antibody-mediated retinal pericyte injury: implications for diabetic retinopathy. Invest Ophthalmol Vis Sci. 2012;53: 5520–5526.
27. Tu Z., Li Y., Smith D.S., et al. Retinal pericytes inhibit activated T cell proliferation. Invest Ophthalmol Vis Sci. 2011;52: 9005–9010.
28. Cheng L., Bu H., Portillo J.A., et al. Modulation of retinal Muller cells by complement receptor C5aR. Invest Ophthalmol Vis Sci. 2013;54: 8191–8198.
29. Ding S.S.L., Subbiah S.K., Khan M.S.A., Farhana A., Mok P.L. Empowering mesenchymal stem cells for ocular degenerative disorders. Int J Mol Sci. 2019;20: 1784.
30. Banderia F., Goh T.W., Setiawan M., Yam G.H., Mehta J.S. Cellular therapy of corneal epithelial defect by adipose mesenchymal stem cell-derived epithelial progenitors. Stem Cell Res Ther. 2020;11: 14–27.
31. Jensen T.I., Axelgaard E., Bak R.O. Therapeutic gene editing in haematological disorders with CRISPR/Cas9. Br J Haematol. 2019;185: 821–835.
32. Srivastava S., Riddell S.R. Engineering CAR-T cells: design concepts. Trends Immunol. 2015;36: 494–503.
33. Stern J.H., Tian Y., Funderburgh J., et al. Regenerating eye tissues to preserve and restore vision. Cell Stem Cell. 2018;22: 834–849.
34. M’Barek K.B., Monville C. Cell therapy for retinal dystrophies: from cell suspension formulation to complex retinal tissue bioengineering. Stem Cells Int. 2019;2019: 4568979.
35. Singh M.S., Park S.S., Albini T.A., et al. Retina stem cell transplantation: balancing safety and potential. Prog Retin Eye Res. 2019;75: 100779.
36. Kashani A.H., Lebkowski J.S., Rahhal F.M., et al. A bioengineered retinal pigment epithelial monolayer for advanced, dry age-related macular degeneration. Science Trans Med. 2018;10: eaao4097.
37. McGill T.J., et al. Modelling early retinal development with human embryonic and induced pluripotential stem cells. Investig Ophthalmol Vis Sci. 2018;59: 1374–1383.
38. Sohn E.H., Jiao C., Kaalberg E., et al. Allogenic iPSC derived RPE cell transplants induce immune response in pigs: a pilot study. Sci Rep. 2015;5: 11791.
39. Trujillo C.A., Gao R., Negraes P.D., et al. Complex oscillatory waves emerging from cortical organoids model early human brain network development. Cell Stem Cell. 2019;25: 558–569.e7.
40. World Economic Forum. The fourth industrial revolution: what it means, how to respond. 2016. Available at: https://www.weforum.org/ agenda/2019/01/the-fourth-industrial-revolution-and-what-it-means/
41. Ting D.S.W., Pasquale L.R., Peng L, et al. Artificial intelligence and deep learning in ophthalmology. Br J Ophthalmol. 2019;103: 167–175.
42. Schmidt-Erfurth U., Sadeghipour A., Gerendas B.S., Waldstein S.M., Bogunovi H. Artificial intelligence in retina. Prog Retin Eye Res. 2018;67: 1–29.
43. Fenner B.J., Wong R.L.M., Lam W.C., Tan G.S.W., Cheung G.C.M. Advances in retinal imaging and applications in diabetic retinopathy screening: a review. Ophthalmol Ther. 2018;7: 333–346.
44. Esteva A., Kuprel B., Novoa R.A., et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542: 115–118.
45. Wang X., Peng Y., Lu L., et al. Chest X-ray8: hospital scale chest X-ray database and benchmarks on weakly supervised classification of chest and thorax diseases. 2017;arXiv:1705.02315.
46. Fei X., Zhao J., Zhao H., et al. Deblurring adaptive optics retinal images using deep convolutional using deep convolutional neural networks. Biomed Optic Express. 2017;8(12): 5675–5687.
47. Lee C.S., Tyring A.J., Wu Y., et al. Generating retinal flow maps from structural optical coherence tomography with artificial intelligence. Sci Rep. 2019;9: 5694.
48. Silver D., Hubert T., Schrittwieser J., et al. AlphaZero – a general reinforcement learning algorithm that masters Chess, Shogi, and Go through self-play. Science. 2018;362: 1140–1144.
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