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References

  1. Griffith, B.P., Goerlich, C.E., Singh, A.K., Rothblatt, M., Lau, C.L., Shah, A., Lorber, M., Grazioli, A., Saharia, K.K., Hong, S.N., et al. (2022). Genetically Modified Porcine-to-Human Cardiac Xenotransplantation. N Engl J Med 387, 35-44. 10.1056/NEJMoa2201422.
  2. Cooper, D.K., Good, A.H., Koren, E., Oriol, R., Malcolm, A.J., Ippolito, R.M., Neethling, F.A., Ye, Y., Romano, E., and Zuhdi, N. (1993). Identification of alpha-galactosyl and other carbohydrate epitopes that are bound by human anti-pig antibodies: relevance to discordant xenografting in man. Transpl Immunol 1, 198-205. 10.1016/0966-3274(93)90047-c.
  3. Cooper, D.K. (2003). Clinical xenotransplantion--how close are we? Lancet 362, 557-559. 10.1016/S0140-6736(03)14118-9.
  4. Lu, T., Yang, B., Wang, R., and Qin, C. (2019). Xenotransplantation: Current Status in Preclinical Research. Front Immunol 10, 3060. 10.3389/fimmu.2019.03060.
  5. Racle, J., Guillaume, P., Schmidt, J., Michaux, J., Larabi, A., Lau, K., Perez, M.A.S., Croce, G., Genolet, R., Coukos, G., et al. (2023). Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes. Immunity 56, 1359-1375 e1313. 10.1016/j.immuni.2023.03.009.
  6. Yu, X., Negron, C., Huang, L., and Veldman, G. (2023). TransMHCII: a novel MHC-II binding prediction model built using a protein language model and an image classifier. Antib Ther 6, 137-146. 10.1093/abt/tbad011.
  7. Nilsson JB, Kaabinejadian S, Yari H, Kester MGD, van Balen P, Hildebrand WH, Nielsen M. Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning. Sci Adv. 2023 Nov 24;9(47):eadj6367. doi: 10.1126/sciadv.adj6367. Epub 2023 Nov 24. PMID: 38000035; PMCID: PMC10672173.
  8. Randi Vita, Nina Blazeska, Daniel Marrama, IEDB Curation Team Members , Sebastian Duesing, Jason Bennett, Jason Greenbaum, Marcus De Almeida Mendes, Jarjapu Mahita, Daniel K Wheeler, Jason R Cantrell, James A Overton, Darren A Natale, Alessandro Sette, Bjoern Peters, The Immune Epitope Database (IEDB): 2024 update, Nucleic Acids Research, 2024;, gkae1092, https://doi.org/10.1093/nar/gkae1092
  9. Dominic J Barker, Giuseppe Maccari, Xenia Georgiou, Michael A Cooper, Paul Flicek, James Robinson, Steven G E Marsh, The IPD-IMGT/HLA Database, Nucleic Acids Research, Volume 51, Issue D1, 6 January 2023, Pages D1053–D1060, https://doi.org/10.1093/nar/gkac1011
  10. Morton, J.J., Bird, G., Refaeli, Y., and Jimeno, A. (2016). Humanized Mouse Xenograft Models: Narrowing the Tumor-Microenvironment Gap. Cancer Res 76, 6153-6158. 10.1158/0008-5472.CAN-16-1260.
  11. Pukazhenthi, B.S., Nagashima, J., Travis, A.J., Costa, G.M., Escobar, E.N., Franca, L.R., and Wildt, D.E. (2015). Slow freezing, but not vitrification supports complete spermatogenesis in cryopreserved, neonatal sheep testicular xenografts. PLoS One 10, e0123957. 10.1371/journal.pone.0123957.
  12. Oh, J.Y., Kim, M.K., Ko, J.H., Lee, H.J., Park, C.G., Kim, S.J., Wee, W.R., and Lee, J.H. (2009). Histological differences in full-thickness vs. lamellar corneal pig-to-rabbit xenotransplantation. Vet Ophthalmol 12, 78-82. 10.1111/j.1463-5224.2008.00680.x.
  13. Zhuang, F., Qi, Z., Duan, K., Xi, D., Zhu, Y., Zhu, H., Xiong, H., and He, Q. (2021). A Comprehensive Survey on Transfer Learning. Proceedings of the IEEE 109, 43-76. 10.1109/jproc.2020.3004555.
  14. Abramson, J., Adler, J., Dunger, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024). https://doi.org/10.1038/s41586-024-07487-w
  15. Chai Discovery team, Jacques Boitreaud, Jack Dent, Matthew McPartlon, Joshua Meier, Vinicius Reis, Alex Rogozhonikov, Kevin Wu
  16. Jeremy Wohlwend, Gabriele Corso, Saro Passaro, Mateo Reveiz, Ken Leidal, Wojtek Swiderski, Tally Portnoi, Itamar Chinn, Jacob Silterra, Tommi Jaakkola, Regina Barzilay
  17. Everly, M.J., Rebellato, L.M., Haisch, C.E., Ozawa, M., Parker, K., Briley, K.P., Catrou, P.G., Bolin, P., Kendrick, W.T., Kendrick, S.A., et al. (2013). Incidence and impact of de novo donor-specific alloantibody in primary renal allografts. Transplantation 95, 410-417. 10.1097/TP.0b013e31827d62e3.
  18. Kim, K., Kim, H.S., Kim, J.Y. et al. Predicting clinical benefit of immunotherapy by antigenic or functional mutations affecting tumour immunogenicity. Nat Commun 11, 951 (2020). https://doi.org/10.1038/s41467-020-14562-z