[1]Pauling L, Itano H A. Sickle cell anemia, a molecular disease[J]. Science, 1949, 109(2835): 443.
[2]Ingram V M. A specific chemical difference between the globins of normal human and sickle-cell anaemia haemoglobin[J]. Nature, 1956, 178(4537): 792-794.
[3]Trent R J. Molecular medicine: genomics to personalized healthcare[M]. 4th ed. Boston: Elsevier, 2012: 1-2.
[4]Blaese R M, Culver K W, Miller A D, et al. T lymphocyte-directed gene therapy for ADA-SCID: initial trial results after 4 years[J]. Science, 1995, 270(5235): 475-480.
[5]Stolberg S G. The biotech death of Jesse Gelsinger[J]. N Y Times Mag, 1999: 136-140, 149-150.
[6]Frangoul H, Altshuler D, Cappellini M D, et al. CRISPR-Cas9 gene editing for sickle cell disease and β-thalassemia[J]. N Engl J Med, 2021, 384(3): 252-260.
[7]Sharma A, Boelens J J, Cancio M, et al. CRISPR-Cas9 editing of the HBG1 and HBG2 promoters to treat sickle cell disease[J]. N Engl J Med, 2023, 389(9): 820-832.
[8]Xu M J, Papageorgiou D P, Abidi S Z, et al. A deep convolutional neural network for classification of red blood cells in sickle cell anemia[J]. PLoS Comput Biol, 2017, 13(10): e1005746.
[9]Cai S, Han I C, Scott A W. Artificial intelligence for improving sickle cell retinopathy diagnosis and management[J]. Eye (Lond), 2021, 35(10): 2675-2684.
[10]Sachdev V, Tian X, Gu Y, et al. A phenotypic risk score for predicting mortality in sickle cell disease[J]. Br J Haematol, 2021, 192(5): 932-941.
[11]Gabriel I. Artificial intelligence, values, and alignment[J]. Minds Mach (Dordr), 2020, 30(3): 411-437.
[12]van Dis E A M, Bollen J, Zuidema W, et al. ChatGPT: five priorities for research[J]. Nature, 2023, 614(7947): 224-226.
|