vtioВестник трансплантологии и искусственных органовRussian Journal of Transplantology and Artificial Organs1995-1191Academician V.I.Shumakov National Medical Research Center of Transplantology and Artificial Organs", Ministry of Health of the Russian Federation10.15825/1995-1191-2026-2-238-249vtio-2078Research ArticleЭКСПЕРИМЕНТАЛЬНЫЕ ИССЛЕДОВАНИЯEXPERIMENTAL RESEARCHЭволюция моделей в урологической хирургии и трансплантологии: от лабораторных животных до искусственного интеллектаEvolution of models in urological surgery and transplantology: from laboratory animals to artificial intelligenceПоповС. В.PopovS. V.

Попов Сергей Валерьевич.

Санкт-Петербург

St. Petersburg

info@lucaclinic.ruГусейновР. Г.HuseynovR. G.

Гусейнов Руслан Гусейнович.

Санкт-Петербург

St. Petersburg

info@lucaclinic.ruСтосманК. И.StosmanK. I.

Санкт-Петербург

St. Petersburg

info@lucaclinic.ruСивакК. В.SivakK. V.

Санкт-Петербург

St. Petersburg

info@lucaclinic.ruСаватеева-ЛюбимоваТ. Н.Savateeva‑LyubimovaT. N.

Санкт-Петербург

St. Petersburg

info@lucaclinic.ruМалышевЕ. А.MalyshevE. A.

Санкт-Петербург

St. Petersburg

info@lucaclinic.ruБештоевА. Х.BeshtoevA. Kh.

Санкт-Петербург

St. Petersburg

info@lucaclinic.ruЛелявинаТ. А.LelyavinaT. A.

Лелявина Татьяна Александровна.

198515, Санкт-Петербург, Стрельна, ул. Декабристов, д. 6

Тел. (981) 908-90-18

Tatiana A. Lelyavina.

6, Dekabristov str., Strelna, St. Petersburg, 198515

Phone: (981) 908-90-18

tatianalelyavina@mail.ruСПб ГБУЗ «Клиническая больница Святителя Луки»; ФГБВОУ ВО «Военно-медицинская академия имени С.М. Кирова» Минобороны России; ЧОУ ВО «Санкт-Петербургский медико-социальный институт»РоссияSt. Luke’s Clinical Hospital; Kirov Military Medical Academy; St. Petersburg Medical and Social InstituteRussian FederationСПб ГБУЗ «Клиническая больница Святителя Луки»; ЧОУ ВО «Санкт-Петербургский медико-социальный институт»РоссияSt. Luke’s Clinical Hospital; St. Petersburg Medical and Social InstituteRussian FederationФГБУ «Научно-исследовательский институт гриппа имени А.А. Смородинцева»РоссияSmorodintsev Research Institute of InfluenzaRussian FederationСПб ГБУЗ «Клиническая больница Святителя Луки»; ФГБУ «Научно-исследовательский институт гриппа имени А.А. Смородинцева»РоссияSt. Luke’s Clinical Hospital; Smorodintsev Research Institute of InfluenzaRussian FederationСПб ГБУЗ «Клиническая больница Святителя Луки»РоссияSt. Luke’s Clinical HospitalRussian FederationСПб ГБУЗ «Клиническая больница Святителя Луки»; ФГБУ «Национальный медицинский исследовательский центр имени В.А. Алмазова» Минздрава РоссииРоссияSt. Luke’s Clinical Hospital; Almazov National Medical Research CentreRussian Federation202628062026282238249Copyright © Попов С.В., Гусейнов Р.Г., Стосман К.И., Сивак К.В., Саватеева-Любимова Т.Н., Малышев Е.А., Бештоев А.Х., Лелявина Т.А., 20262026Попов С.В., Гусейнов Р.Г., Стосман К.И., Сивак К.В., Саватеева-Любимова Т.Н., Малышев Е.А., Бештоев А.Х., Лелявина Т.А.Popov S.V., Huseynov R.G., Stosman K.I., Sivak K.V., Savateeva‑Lyubimova T.N., Malyshev E.A., Beshtoev A.K., Lelyavina T.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://journal.transpl.ru/vtio/article/view/2078

Актуальность. Эксперименты на животных играют важную роль в современной хирургии, позволяют разработать новые операционные техники, материалы для трансплантатов и др. Помимо животных в современной хирургии и трансплантологии активно используются роботизированные системы и искусственный интеллект, способные минимизировать интраоперационные кровопотери, частоту раневых инфекций, осуществить подбор «донор–реципиент», прогнозировать выживаемость трансплантата и многое др. Цель: анализ эволюции хирургических моделей in vivo и оценка современных стратегий трансплантации и эксплантации. Материалы и методы. Поиск литературы в базе данных Scopus, PubMed и РИНЦ с использованием поискового запроса «хирургические модели на животных», «трансплантация почки», «ксенотрансплантация», «искусственный интеллект в трансплантологии и хирургии», «роботизированная хирургия». Проанализировано 430 публикаций в отечественных и зарубежных журналах за 2006–2025 гг. В результате отбора в обзор были включены 87 публикаций. Прослежена трансформация от анатомических исследований к сложным хирургическим системам. Ключевым этапом стало внедрение моделей для трансплантации почки на крупных животных (свиньях). Современный этап характеризуется интеграцией роботических систем и искусственного интеллекта, обеспечивающих минимальную инвазивность и точность. Заключение. Проведение испытаний на лабораторных животных необходимо, особенно при выполнении хирургических операций, моделирование которых математически невозможно.

Background. Animal experiments play a vital role in modern surgery, enabling the development of new surgical techniques, transplant materials, and more. In addition, modern surgery and transplant medicine utilize robotic systems and artificial intelligence to minimize intraoperative blood loss and wound infections, facilitate donor– recipient matching, and predict graft survival. Objective: to analyze the evolution of in vivo surgical models and evaluate modern strategies for transplantation and explantation. Materials and methods. A literature search was conducted in the SCOPUS, PubMed, and the Russian Science Citation Index (RSCI) databases using the following search terms: «хирургические модели на животных» (meaning «animal surgical models» in English), «трансплантация почки» (kidney transplantation), «ксенотрансплантация» (xenotransplantation), «искусственный интеллект в трансплантологии и хирургии» (artificial intelligence in transplantology and surgery) and «роботизированная хирургия» (robot-assisted surgery). A total of 430 publications from Russian and international journals published between 2006 and 2025 were analyzed. Following the selection process, 87 publications were included in the review. The evolution from anatomical studies to complex surgical systems was traced, with a key milestone being the introduction of kidney transplantation models in large animals (pigs). The current stage is characterized by integration of robotic systems and artificial intelligence, ensuring minimal invasiveness and high precision. Conclusion. Testing on laboratory animals remains essential, particularly for surgical procedures that cannot be adequately modeled mathematically.

хирургические модели in vivoтрансплантация почкироботизированная хирургияискусственный интеллектмашинная перфузияксенотрансплантацияэксплантация ex vivoin vivo surgical modelskidney transplantationrobot‑assisted surgeryartificial intelligencemachine perfusionxenotransplantationex vivo explantationReferencesHaam S, Noda K, Philips BJ, Harano T, Sanchez PG, Shigemura N. Cyclosporin A administration during ex vivo lung perfusion preserves lung grafts in rat transplant model. Transplantation. 2020; 104 (9): e252–e259. doi: 10.1097/TP.0000000000003237.Haam S, Noda K, Philips BJ, Harano T, Sanchez PG, Shigemura N. Cyclosporin A administration during ex vivo lung perfusion preserves lung grafts in rat transplant model. Transplantation. 2020; 104 (9): e252–e259. doi: 10.1097/TP.0000000000003237.Woillard JB, Labriffe M, Debord J, Marquet P. Mycophenolic acid exposure prediction using machine learning. Clin Pharmacol Ther. 2021; 110 (2): 370–379. doi: 10.1002/cpt.2216.Woillard JB, Labriffe M, Debord J, Marquet P. Mycophenolic acid exposure prediction using machine learning. Clin Pharmacol Ther. 2021; 110 (2): 370–379. doi: 10.1002/cpt.2216.Divard G, Raynaud M, Tatapudi VS, Abdalla B, Bailly E, Assayag M et al. Comparison of artificial intelligence and human-based prediction and stratification of the risk of long-term kidney allograft failure. Commun Med (Lond). 2022; 2 (1): 150. doi: 10.1038/s43856-022-00201-9.Divard G, Raynaud M, Tatapudi VS, Abdalla B, Bailly E, Assayag M et al. Comparison of artificial intelligence and human-based prediction and stratification of the risk of long-term kidney allograft failure. Commun Med (Lond). 2022; 2 (1): 150. doi: 10.1038/s43856-022-00201-9.Li H, Han Z, Wu H, Musaev ER, Lin Y, Li S et al. Artificial intelligence in surgery: evolution, trends, and future directions. Int J Surg. 2025; 111 (2): 2101–2111. doi: 10.1097/JS9.0000000000002159.Li H, Han Z, Wu H, Musaev ER, Lin Y, Li S et al. Artificial intelligence in surgery: evolution, trends, and future directions. Int J Surg. 2025; 111 (2): 2101–2111. doi: 10.1097/JS9.0000000000002159.Shan J. Surgical Robotics: Recent Development Trends and Challenges. In: 2025 IEEE International Conference on Robotics and Technologies for Industrial Automation (ROBOTHIA). 2025: 1–6. doi: 10.1109/ROBOTHIA63806.2025.10986348.Shan J. Surgical Robotics: Recent Development Trends and Challenges. In: 2025 IEEE International Conference on Robotics and Technologies for Industrial Automation (ROBOTHIA). 2025: 1–6. doi: 10.1109/ROBOTHIA63806.2025.10986348.Cole BJ, Chahla JA, Chubinskaya SG, Gilat R, Frank RM, Yanke AB. Optimizing Patient Outcomes Following Osteochondral Allograft Transplantation: The Impact of 25 Years of Translational and Clinical Research. J Orthop Res. 2025; 43 (10): 1705–1723. doi: 10.1002/jor.26089.Cole BJ, Chahla JA, Chubinskaya SG, Gilat R, Frank RM, Yanke AB. Optimizing Patient Outcomes Following Osteochondral Allograft Transplantation: The Impact of 25 Years of Translational and Clinical Research. J Orthop Res. 2025; 43 (10): 1705–1723. doi: 10.1002/jor.26089.Ali H, Shroff A, Soliman K, Molnar MZ, Sharif A, Burke B et al. Improved survival prediction for kidney transplant outcomes using artificial intelligence-based models: development of the UK Deceased Donor Kidney Transplant Outcome Prediction (UK-DTOP) Tool. Ren Fail. 2024; 46 (2): 2373273. doi: 10.1080/0886022X.2024.2373273.Ali H, Shroff A, Soliman K, Molnar MZ, Sharif A, Burke B et al. Improved survival prediction for kidney transplant outcomes using artificial intelligence-based models: development of the UK Deceased Donor Kidney Transplant Outcome Prediction (UK-DTOP) Tool. Ren Fail. 2024; 46 (2): 2373273. doi: 10.1080/0886022X.2024.2373273.Sundaram V, Infant SS, Saravanan A, Bhavani SB, Gulothungan G, Arora S, Chopra H. Innovative animal models for surgical interventions and implant biocompatibility: a translational perspective. Ann Med Surg (Lond). 2025 Jul 18; 87 (10): 6496–6509. doi: 10.1097/MS9.0000000000003610.Sundaram V, Infant SS, Saravanan A, Bhavani SB, Gulothungan G, Arora S, Chopra H. Innovative animal models for surgical interventions and implant biocompatibility: a translational perspective. Ann Med Surg (Lond). 2025 Jul 18; 87 (10): 6496–6509. doi: 10.1097/MS9.0000000000003610.Kovesdy CP. Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl. 2022; 12 (1): 7–11. doi: 10.1016/j.kisu.2021.11.003.Kovesdy CP. Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl. 2022; 12 (1): 7–11. doi: 10.1016/j.kisu.2021.11.003.Flythe JE, Watnick S. Dialysis for chronic kidney failure: a review. JAMA. 2024; 332 (18): 1559–1573. doi: 10.1001/jama.2024.16338.Flythe JE, Watnick S. Dialysis for chronic kidney failure: a review. JAMA. 2024; 332 (18): 1559–1573. doi: 10.1001/jama.2024.16338.Lewis A, Koukoura A, Tsianos GI, Gargavanis AA, Nielsen AA, Vassiliadis E. Organ donation in the US and Europe: the supply vs demand imbalance. Transplant Rev (Orlando). 2021; 35 (2): 100585. doi: 10.1016/j.trre.2020.100585.Lewis A, Koukoura A, Tsianos GI, Gargavanis AA, Nielsen AA, Vassiliadis E. Organ donation in the US and Europe: the supply vs demand imbalance. Transplant Rev (Orlando). 2021; 35 (2): 100585. doi: 10.1016/j.trre.2020.100585.Meier RPH, Ben Nasr M, Fife BT, Finger EB, Fiorina P, Luo X, Bromberg JS. Best practices in islet transplantation in mice. Am J Transplant. 2025; 25 (7): 1399–1409. doi: 10.1016/j.ajt.2025.03.008.Meier RPH, Ben Nasr M, Fife BT, Finger EB, Fiorina P, Luo X, Bromberg JS. Best practices in islet transplantation in mice. Am J Transplant. 2025; 25 (7): 1399–1409. doi: 10.1016/j.ajt.2025.03.008.Garcia Valencia OA, Thongprayoon C, Jadlowiec CC, Mao SA, Leeaphorn N, Budhiraja P et al. Evaluating Global and Temporal Trends in Pancreas and Islet Cell Transplantation: Public Awareness and Engagement. Clin Pract. 2024; 14 (2): 590–601. doi: 10.3390/clin-pract14020046.Garcia Valencia OA, Thongprayoon C, Jadlowiec CC, Mao SA, Leeaphorn N, Budhiraja P et al. Evaluating Global and Temporal Trends in Pancreas and Islet Cell Transplantation: Public Awareness and Engagement. Clin Pract. 2024; 14 (2): 590–601. doi: 10.3390/clin-pract14020046.Son J, Shin JY, Kim HD, Jung KH, Park KH, Park SJ. Development and validation of deep learning models for screening multiple abnormal findings in retinal fundus images. Ophthalmology. 2020; 127 (1): 85–94. doi: 10.1016/j.ophtha.2019.05.029.Son J, Shin JY, Kim HD, Jung KH, Park KH, Park SJ. Development and validation of deep learning models for screening multiple abnormal findings in retinal fundus images. Ophthalmology. 2020; 127 (1): 85–94. doi: 10.1016/j.ophtha.2019.05.029.Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021; 372: n71. doi: 10.1136/bmj.n71.Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021; 372: n71. doi: 10.1136/bmj.n71.Ilevbare IM, Phaal R, Probert DR. A review of TRIZ, and its benefits and challenges in practice. Technovation. 2013; 33 (2–3): 30–37. doi: 10.1016/j.technovation.2012.11.003.Ilevbare IM, Phaal R, Probert DR. A review of TRIZ, and its benefits and challenges in practice. Technovation. 2013; 33 (2–3): 30–37. doi: 10.1016/j.technovation.2012.11.003.Seifalian A, Digesu A, Khullar V. The use of animal models in preclinical investigations for the development of a surgical mesh for pelvic organ prolapse. Int Urogynecol J. 2024; 35 (4): 741–758. doi: 10.1007/s00192-024-05741-3.Seifalian A, Digesu A, Khullar V. The use of animal models in preclinical investigations for the development of a surgical mesh for pelvic organ prolapse. Int Urogynecol J. 2024; 35 (4): 741–758. doi: 10.1007/s00192-024-05741-3.He YJ, Liu PL, Wei T, Liu T, Li YF, Yang J, Fan WX. Artificial intelligence in kidney transplantation: a 30-year bibliometric analysis of research trends, innovations, and future directions. Ren Fail. 2025; 47 (1): 2458754. doi: 10.1080/0886022X.2025.2458754.He YJ, Liu PL, Wei T, Liu T, Li YF, Yang J, Fan WX. Artificial intelligence in kidney transplantation: a 30-year bibliometric analysis of research trends, innovations, and future directions. Ren Fail. 2025; 47 (1): 2458754. doi: 10.1080/0886022X.2025.2458754.Rojas Burbano JC, Ruiz NI, Rojas Burbano GA, Guacho Inca JS, Arragan Lezama CA, González MS. Robot-Assisted Surgery: Current Applications and Future Trends in General Surgery. Cureus. 2025; 17 (4): e82318. doi: 10.7759/cureus.82318.Rojas Burbano JC, Ruiz NI, Rojas Burbano GA, Guacho Inca JS, Arragan Lezama CA, González MS. Robot-Assisted Surgery: Current Applications and Future Trends in General Surgery. Cureus. 2025; 17 (4): e82318. doi: 10.7759/cureus.82318.Barandiaran Cornejo JF, Chin LT, Angelis M. From Carrel to Robotics: Renal Transplantation and the Evolution of its Surgical Technique. Curr Urol Rep. 2025; 26 (1). doi: 10.1007/s11934-025-01265-5.Barandiaran Cornejo JF, Chin LT, Angelis M. From Carrel to Robotics: Renal Transplantation and the Evolution of its Surgical Technique. Curr Urol Rep. 2025; 26 (1). doi: 10.1007/s11934-025-01265-5.Zeuschner P, Friedersdorff F, Siemer S, Stöckle M. Aktuelles zur robotischen Nierentransplantation – quo vadis? Urologie. 2024; 63 (4): 361–366. doi: 10.1007/s00120-024-02293-8.Zeuschner P, Friedersdorff F, Siemer S, Stöckle M. Aktuelles zur robotischen Nierentransplantation – quo vadis? Urologie. 2024; 63 (4): 361–366. doi: 10.1007/s00120-024-02293-8.Kalyan KS, Rajasekharan A, Sangeetha S. AMMU: a survey of transformer-based biomedical pretrained language models. J Biomed Inform. 2022; 126: 103982. doi: 10.1016/j.jbi.2021.103982.Kalyan KS, Rajasekharan A, Sangeetha S. AMMU: a survey of transformer-based biomedical pretrained language models. J Biomed Inform. 2022; 126: 103982. doi: 10.1016/j.jbi.2021.103982.Dave T, Athaluri SA, Singh S. ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations. Front Artif Intell. 2023; 6: 1169595. doi: 10.3389/frai.2023.1169595.Dave T, Athaluri SA, Singh S. ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations. Front Artif Intell. 2023; 6: 1169595. doi: 10.3389/frai.2023.1169595.Xie C, Piao M, Zhou L, Tao X, Yao Y, Jiang B et al. Emerging trends and hotspots in animal experimental research on lung transplantation from 2004 to 2023: a bibliometric analysis. J Thorac Dis. 2025; 17 (2): 796–815. doi: 10.21037/jtd-24-1451.Xie C, Piao M, Zhou L, Tao X, Yao Y, Jiang B et al. Emerging trends and hotspots in animal experimental research on lung transplantation from 2004 to 2023: a bibliometric analysis. J Thorac Dis. 2025; 17 (2): 796–815. doi: 10.21037/jtd-24-1451.Heinis FI, Merani S, Markin NW, Duncan KF, Moulton MJ, Fristoe L et al. Considerations for the use of porcine organ donation models in preclinical organ donor intervention research. Anim Model Exp Med. 2024; 7 (3): 283–296. doi: 10.1002/ame2.12411.Heinis FI, Merani S, Markin NW, Duncan KF, Moulton MJ, Fristoe L et al. Considerations for the use of porcine organ donation models in preclinical organ donor intervention research. Anim Model Exp Med. 2024; 7 (3): 283–296. doi: 10.1002/ame2.12411.Matar AJ, Crepeau RL, Mundinger GS, Cetrulo CL Jr, Torabi R. Large Animal Models of Vascularized Composite Allotransplantation: A Review of Immune Strategies to Improve Allograft Outcomes. Front Immunol. 2021; 12: 664577. doi: 10.3389/fimmu.2021.664577.Matar AJ, Crepeau RL, Mundinger GS, Cetrulo CL Jr, Torabi R. Large Animal Models of Vascularized Composite Allotransplantation: A Review of Immune Strategies to Improve Allograft Outcomes. Front Immunol. 2021; 12: 664577. doi: 10.3389/fimmu.2021.664577.Byrne GW, McGregor CGA. 2025: status of cardiac xenotransplantation including preclinical models. Front Transplant. 2025; 4: 1568910. doi: 10.3389/frt-ra.2025.1568910.Byrne GW, McGregor CGA. 2025: status of cardiac xenotransplantation including preclinical models. Front Transplant. 2025; 4: 1568910. doi: 10.3389/frt-ra.2025.1568910.Niroomand A, Nita GE, Lindstedt S. Machine Perfusion and Bioengineering Strategies in Transplantation. Beyond the Emerging Concepts. Transpl Int. 2024; 37: 13215. doi: 10.3389/ti.2024.13215.Niroomand A, Nita GE, Lindstedt S. Machine Perfusion and Bioengineering Strategies in Transplantation. Beyond the Emerging Concepts. Transpl Int. 2024; 37: 13215. doi: 10.3389/ti.2024.13215.Beagan MLC, Dreyer CH, Jensen LK, Jensen HE, Andersen TE, Overgaard S, Ding M. The potential of sheep in preclinical models for bone infection research. A systematic review. J Orthop Transl. 2024; 45: 120–131. doi: 10.1016/j.jot.2024.02.002.Beagan MLC, Dreyer CH, Jensen LK, Jensen HE, Andersen TE, Overgaard S, Ding M. The potential of sheep in preclinical models for bone infection research. A systematic review. J Orthop Transl. 2024; 45: 120–131. doi: 10.1016/j.jot.2024.02.002.Cutrone AM, Ozgur OS, Lyon A, Longchamp A, Madsen JC, Yeh H, Uygun K. Cryopreservation Strategies to Improve Access to Organ Transplantation. Transplantation. 2026 Jan 1; 110 (1): e42–e54. doi: 10.1097/TP.0000000000005494.Cutrone AM, Ozgur OS, Lyon A, Longchamp A, Madsen JC, Yeh H, Uygun K. Cryopreservation Strategies to Improve Access to Organ Transplantation. Transplantation. 2026 Jan 1; 110 (1): e42–e54. doi: 10.1097/TP.0000000000005494.Kawai T, Williams WW, Elias N, Fishman JA, Crisalli K, Longchamp A et al. Xenotransplantation of a Porcine Kidney for End-Stage Kidney Disease. N Engl J Med. 2025; 392 (19): 1933–1940. doi: 10.1056/NEJ-Moa2412747.Kawai T, Williams WW, Elias N, Fishman JA, Crisalli K, Longchamp A et al. Xenotransplantation of a Porcine Kidney for End-Stage Kidney Disease. N Engl J Med. 2025; 392 (19): 1933–1940. doi: 10.1056/NEJ-Moa2412747.Nykänen AI, Keshavjee S, Liu M. Creating superior lungs for transplantation with next-generation gene therapy during ex vivo lung perfusion. J Heart Lung Transplant. 2024; 43 (5): 838–848. doi: 10.1016/j.hea-lun.2024.01.016.Nykänen AI, Keshavjee S, Liu M. Creating superior lungs for transplantation with next-generation gene therapy during ex vivo lung perfusion. J Heart Lung Transplant. 2024; 43 (5): 838–848. doi: 10.1016/j.hea-lun.2024.01.016.Biswas P, Sikander S, Kulkarni P. Recent advances in robot-assisted surgical systems. Biomed Eng Adv. 2023; 6: 100109. doi: 10.1016/j.bea.2023.100109.Biswas P, Sikander S, Kulkarni P. Recent advances in robot-assisted surgical systems. Biomed Eng Adv. 2023; 6: 100109. doi: 10.1016/j.bea.2023.100109.Intuitive Surgical. Da Vinci X: a foundational entry point to robotic surgery. 2025. https://www.intuitive.com/enus/products-and-services/da-vinci/x.Intuitive Surgical. Da Vinci X: a foundational entry point to robotic surgery. 2025. https://www.intuitive.com/enus/products-and-services/da-vinci/x.Krebs TF, Kayser T, Lorenzen U, Grünewald M, Kayser M, Saltner A et al. Evaluation of the Versius robotic system for infant surgery – a study in piglets of less than 10 kg body weight. Children (Basel). 2023; 10 (5): 831. doi: 10.3390/children10050831.Krebs TF, Kayser T, Lorenzen U, Grünewald M, Kayser M, Saltner A et al. Evaluation of the Versius robotic system for infant surgery – a study in piglets of less than 10 kg body weight. Children (Basel). 2023; 10 (5): 831. doi: 10.3390/children10050831.Hancock KJ, Klimberg VS, Nunez‑Lopez O, Gajjar AH, Gomez G, Tyler DS, Rashidi L. Optimizing outcomes in colorectal surgery: cost and clinical analysis of robotic versus laparoscopic approaches to colon resection. J Robot Surg. 2022; 16: 107–112. doi: 10.1007/s11701-021-01205-8.Hancock KJ, Klimberg VS, Nunez‑Lopez O, Gajjar AH, Gomez G, Tyler DS, Rashidi L. Optimizing outcomes in colorectal surgery: cost and clinical analysis of robotic versus laparoscopic approaches to colon resection. J Robot Surg. 2022; 16: 107–112. doi: 10.1007/s11701-021-01205-8.Reddy K, Gharde P, Tayade H, Patil M, Reddy LS, Surya D. Advancements in robotic surgery: a comprehensive overview of current utilizations and upcoming frontiers. Cureus. 2023; 15 (12): e50415. doi: 10.7759/cureus.50415.Reddy K, Gharde P, Tayade H, Patil M, Reddy LS, Surya D. Advancements in robotic surgery: a comprehensive overview of current utilizations and upcoming frontiers. Cureus. 2023; 15 (12): e50415. doi: 10.7759/cureus.50415.Sheetz KH, Claflin J, Dimick JB. Trends in the adoption of robotic surgery for common surgical procedures. JAMA Netw Open. 2020; 3 (1): e1918911. doi: 10.1001/jamanetworkopen.2019.18911.Sheetz KH, Claflin J, Dimick JB. Trends in the adoption of robotic surgery for common surgical procedures. JAMA Netw Open. 2020; 3 (1): e1918911. doi: 10.1001/jamanetworkopen.2019.18911.Liu Q, Zhang W, Zhao JJ, Syn NL, Cipriani F, Alzoubi M et al. Propensity-score matched and coarsened-exact matched analysis comparing robotic and laparoscopic major hepatectomies: an international multicenter study of 4822 cases. Ann Surg. 2023; 278: 969–975. doi: 10.1097/SLA.0000000000005855.Liu Q, Zhang W, Zhao JJ, Syn NL, Cipriani F, Alzoubi M et al. Propensity-score matched and coarsened-exact matched analysis comparing robotic and laparoscopic major hepatectomies: an international multicenter study of 4822 cases. Ann Surg. 2023; 278: 969–975. doi: 10.1097/SLA.0000000000005855.Rivero‑Moreno Y, Echevarria S, Vidal‑Valderrama C, Pianetti L, Cordova‑Guilarte J, Navarro‑Gonzalez J et al. Robotic surgery: a comprehensive review of the literature and current trends. Cureus. 2023; 15 (7): e42370. doi: 10.7759/cureus.42370.Rivero‑Moreno Y, Echevarria S, Vidal‑Valderrama C, Pianetti L, Cordova‑Guilarte J, Navarro‑Gonzalez J et al. Robotic surgery: a comprehensive review of the literature and current trends. Cureus. 2023; 15 (7): e42370. doi: 10.7759/cureus.42370.Cepolina F, Razzoli RP. An introductory review of robotically assisted surgical systems. Int J Med Robot. 2022; 18 (4): e2409. doi: 10.1002/rcs.2409.Cepolina F, Razzoli RP. An introductory review of robotically assisted surgical systems. Int J Med Robot. 2022; 18 (4): e2409. doi: 10.1002/rcs.2409.AlSajri AA, Hariry N. The future of surgery: robotic-assisted procedures and their impact. SHIFAA. 2024; 2024: 52–55.AlSajri AA, Hariry N. The future of surgery: robotic-assisted procedures and their impact. SHIFAA. 2024; 2024: 52–55.Lunardi N, Abou‑Zamzam A, Florecki KL, Chidambaram S, Shih IF, Kent AJ et al. Robotic technology in emergency general surgery cases in the era of minimally invasive surgery. JAMA Surg. 2024; 159 (5): 493–499. doi: 10.1001/jamasurg.2024.0016.Lunardi N, Abou‑Zamzam A, Florecki KL, Chidambaram S, Shih IF, Kent AJ et al. Robotic technology in emergency general surgery cases in the era of minimally invasive surgery. JAMA Surg. 2024; 159 (5): 493–499. doi: 10.1001/jamasurg.2024.0016.Perry R, Barbosa JP, Perry I, Barbosa J. Short-term outcomes of robot-assisted versus conventional minimally invasive esophagectomy for esophageal cancer: a systematic review and meta-analysis of 18,187 patients. J Robot Surg. 2024; 18: 123. doi: 10.1007/s11701-024-01880-3.Perry R, Barbosa JP, Perry I, Barbosa J. Short-term outcomes of robot-assisted versus conventional minimally invasive esophagectomy for esophageal cancer: a systematic review and meta-analysis of 18,187 patients. J Robot Surg. 2024; 18: 123. doi: 10.1007/s11701-024-01880-3.Picozzi P, Nocco U, Labate C, Gambini I, Puleo G, Silvi F et al. Advances in robotic surgery: a review of new surgical platforms. Electronics. 2024; 13 (23): 4675. doi: 10.3390/electronics13234675.Picozzi P, Nocco U, Labate C, Gambini I, Puleo G, Silvi F et al. Advances in robotic surgery: a review of new surgical platforms. Electronics. 2024; 13 (23): 4675. doi: 10.3390/electronics13234675.Bobade S, Asutkar S. Current trends and future directions in surgery: a brief scoping review. Multidiscip Rev. 2025; 8: 2025028. doi: 10.31893/multirev.2025028.Bobade S, Asutkar S. Current trends and future directions in surgery: a brief scoping review. Multidiscip Rev. 2025; 8: 2025028. doi: 10.31893/multirev.2025028.Wehrle CJ, Chang JH, Gross AR, Woo K, Naples R, Stackhouse KA et al. Comparing oncologic and surgical outcomes of robotic and laparoscopic pancreatoduodenectomy in patients with pancreatic cancer: a propensity-matched analysis. Surg Endosc. 2024; 38 (5): 2602–2610. doi: 10.1007/s00464-024-10783-1.Wehrle CJ, Chang JH, Gross AR, Woo K, Naples R, Stackhouse KA et al. Comparing oncologic and surgical outcomes of robotic and laparoscopic pancreatoduodenectomy in patients with pancreatic cancer: a propensity-matched analysis. Surg Endosc. 2024; 38 (5): 2602–2610. doi: 10.1007/s00464-024-10783-1.Paquette FX, Ghassemi A, Bukhtiyarova O, Cisse M, Gagnon N, Della Vecchia A et al. Machine learning support for decision-making in kidney transplantation: step-by-step development of a technological solution. JMIR Med Inform. 2022; 10 (6): e34554. doi: 10.2196/34554.Paquette FX, Ghassemi A, Bukhtiyarova O, Cisse M, Gagnon N, Della Vecchia A et al. Machine learning support for decision-making in kidney transplantation: step-by-step development of a technological solution. JMIR Med Inform. 2022; 10 (6): e34554. doi: 10.2196/34554.Alowidi N, Ali R, Sadaqah M, Naemi FMA. Advancing kidney transplantation: a machine learning approach to enhance donor-recipient matching. Diagnostics (Basel). 2024; 14 (19): 2119. doi: 10.3390/diagnostics14192119.Alowidi N, Ali R, Sadaqah M, Naemi FMA. Advancing kidney transplantation: a machine learning approach to enhance donor-recipient matching. Diagnostics (Basel). 2024; 14 (19): 2119. doi: 10.3390/diagnostics14192119.Zingraf G, Derkowski DM, Pizarro YI, Woodard A. U.S. Organ Transplantation System – its history, present, and future. Nephrol Nurs J. 2023; 50 (3): 197–202. doi: 10.37526/1526-744X.2023.50.3.197.Zingraf G, Derkowski DM, Pizarro YI, Woodard A. U.S. Organ Transplantation System – its history, present, and future. Nephrol Nurs J. 2023; 50 (3): 197–202. doi: 10.37526/1526-744X.2023.50.3.197.Dagnino G, Kundrat D. Robot-assistive minimally invasive surgery: trends and future directions. Int J Intell Robot Appl. 2024; 8: 812–826. doi: 10.1007/s41315-024-00340-3.Dagnino G, Kundrat D. Robot-assistive minimally invasive surgery: trends and future directions. Int J Intell Robot Appl. 2024; 8: 812–826. doi: 10.1007/s41315-024-00340-3.Liu H, Ren L, Fan B, Wang W, Hu X, Zhang X. Artificial intelligence algorithm-based MRI in the diagnosis of complications after renal transplantation. Contrast Media Mol Imaging. 2022; 2022: 8930584. doi: 10.1155/2022/8930584.Liu H, Ren L, Fan B, Wang W, Hu X, Zhang X. Artificial intelligence algorithm-based MRI in the diagnosis of complications after renal transplantation. Contrast Media Mol Imaging. 2022; 2022: 8930584. doi: 10.1155/2022/8930584.Mata‑Lima A, Paquete AR, Serrano‑Olmedo JJ. Remote patient monitoring and management in nephrology: a systematic review. Nefrologia. 2024; 44 (5): 639–667. doi: 10.1016/j.nefroe.2024.10.011.Mata‑Lima A, Paquete AR, Serrano‑Olmedo JJ. Remote patient monitoring and management in nephrology: a systematic review. Nefrologia. 2024; 44 (5): 639–667. doi: 10.1016/j.nefroe.2024.10.011.Yeter HH, Manani SM, Ronco C. The utility of remote patient management in peritoneal dialysis. Clin Kidney J. 2021; 14 (12): 2483–2489. doi: 10.1093/ckj/sfab111.Yeter HH, Manani SM, Ronco C. The utility of remote patient management in peritoneal dialysis. Clin Kidney J. 2021; 14 (12): 2483–2489. doi: 10.1093/ckj/sfab111.Raynaud M, Aubert O, Divard G, Reese PP, Kamar N, Yoo D et al. Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study. Lancet Digit Health. 2021; 3 (12): e795– e805. doi: 10.1016/S2589-7500(21)00209-0.Raynaud M, Aubert O, Divard G, Reese PP, Kamar N, Yoo D et al. Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study. Lancet Digit Health. 2021; 3 (12): e795– e805. doi: 10.1016/S2589-7500(21)00209-0.Thongprayoon C, Miao J, Jadlowiec C, Mao SA, Mao M, Leeaphorn N et al. Distinct clinical profiles and post-transplant outcomes among kidney transplant recipients with lower education levels: uncovering patterns through machine learning clustering. Ren Fail. 2023; 45 (2): 2292163. doi: 10.1080/0886022X.2023.2292163.Thongprayoon C, Miao J, Jadlowiec C, Mao SA, Mao M, Leeaphorn N et al. Distinct clinical profiles and post-transplant outcomes among kidney transplant recipients with lower education levels: uncovering patterns through machine learning clustering. Ren Fail. 2023; 45 (2): 2292163. doi: 10.1080/0886022X.2023.2292163.Badrouchi S, Bacha MM, Ahmed A, Ben Abdallah T, Abderrahim E. Predicting long-term outcomes of kidney transplantation in the era of artificial intelligence. Sci Rep. 2023; 13 (1): 21273. doi: 10.1038/s41598-023-48645-w.Badrouchi S, Bacha MM, Ahmed A, Ben Abdallah T, Abderrahim E. Predicting long-term outcomes of kidney transplantation in the era of artificial intelligence. Sci Rep. 2023; 13 (1): 21273. doi: 10.1038/s41598-023-48645-w.Garcia Valencia OA, Thongprayoon C, Miao J, Bruminhent J, Craici IM, Cheungpasitporn W. Perspectives on AI-based recommendations for mask-wearing and COVID-19 vaccination for transplant recipients in the post-COVID-19 era. Ren Fail. 2024; 46 (1): 2337291. doi: 10.1080/0886022X.2024.2337291.Garcia Valencia OA, Thongprayoon C, Miao J, Bruminhent J, Craici IM, Cheungpasitporn W. Perspectives on AI-based recommendations for mask-wearing and COVID-19 vaccination for transplant recipients in the post-COVID-19 era. Ren Fail. 2024; 46 (1): 2337291. doi: 10.1080/0886022X.2024.2337291.Fu Q, Agarwal D, Deng K, Matheson R, Yang H, Wei L et al. An unbiased machine learning exploration reveals gene sets predictive of allograft tolerance after kidney transplantation. Front Immunol. 2021; 12: 695806. doi: 10.3389/fimmu.2021.695806.Fu Q, Agarwal D, Deng K, Matheson R, Yang H, Wei L et al. An unbiased machine learning exploration reveals gene sets predictive of allograft tolerance after kidney transplantation. Front Immunol. 2021; 12: 695806. doi: 10.3389/fimmu.2021.695806.Halloran PF, Reeve J, Madill‑Thomsen KS, Demko Z, Prewett A, Billings P. The Trifecta Study: comparing plasma levels of donor-derived cell-free DNA with the molecular phenotype of kidney transplant biopsies. J Am Soc Nephrol. 2022; 33 (2): 387–400. doi: 10.1681/ASN.2021091191.Halloran PF, Reeve J, Madill‑Thomsen KS, Demko Z, Prewett A, Billings P. The Trifecta Study: comparing plasma levels of donor-derived cell-free DNA with the molecular phenotype of kidney transplant biopsies. J Am Soc Nephrol. 2022; 33 (2): 387–400. doi: 10.1681/ASN.2021091191.Li Y, Zhang J, Qiu X, Zhang Y, Wu J, Bi Q et al. Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA sequencing and molecular docking. Ren Fail. 2024; 46 (2): 2435487. doi: 10.1080/0886022X.2024.2435487.Li Y, Zhang J, Qiu X, Zhang Y, Wu J, Bi Q et al. Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA sequencing and molecular docking. Ren Fail. 2024; 46 (2): 2435487. doi: 10.1080/0886022X.2024.2435487.Buscher K, Heitplatz B, van Marck V, Song J, Loismann S, Rixen R et al. Data-driven kidney transplant phenotyping as a histology-independent framework for biomarker discovery. J Am Soc Nephrol. 2021; 32 (8): 1933–1945. doi: 10.1681/ASN.2020121685.Buscher K, Heitplatz B, van Marck V, Song J, Loismann S, Rixen R et al. Data-driven kidney transplant phenotyping as a histology-independent framework for biomarker discovery. J Am Soc Nephrol. 2021; 32 (8): 1933–1945. doi: 10.1681/ASN.2020121685.Yang S, Hou W, Liu L. Progress in preservation of intestinal grafts by oxygenated hypothermic machine perfusion. Transplant Rev. 2024; 38 (1): 100802. doi: 10.1016/j. trre.2023.100802.Yang S, Hou W, Liu L. Progress in preservation of intestinal grafts by oxygenated hypothermic machine perfusion. Transplant Rev. 2024; 38 (1): 100802. doi: 10.1016/j. trre.2023.100802.Srivastava PK, Kittleson MM. Modern advances in heart transplantation. Prog Cardiovasc Dis. 2024; 82: 147–156. doi: 10.1016/j.pcad.2024.01.012.Srivastava PK, Kittleson MM. Modern advances in heart transplantation. Prog Cardiovasc Dis. 2024; 82: 147–156. doi: 10.1016/j.pcad.2024.01.012.Cheng H, Cui Z, Guo S, Zhang X, Huo Y, Mao S. Mucoadhesive versus mucopenetrating nanoparticles for oral delivery of insulin. Acta Biomater. 2021; 135: 506–519. doi: 10.1016/j.actbio.2021.08.046.Cheng H, Cui Z, Guo S, Zhang X, Huo Y, Mao S. Mucoadhesive versus mucopenetrating nanoparticles for oral delivery of insulin. Acta Biomater. 2021; 135: 506–519. doi: 10.1016/j.actbio.2021.08.046.Alexander S, Moghadam MG, Rothenbroker M, Chou LYT. Addressing the in vivo delivery of nucleicacid nanostructure therapeutics. Adv Drug Deliv Rev. 2023; 199: 114898. doi: 10.1016/j.addr.2023.114898.Alexander S, Moghadam MG, Rothenbroker M, Chou LYT. Addressing the in vivo delivery of nucleicacid nanostructure therapeutics. Adv Drug Deliv Rev. 2023; 199: 114898. doi: 10.1016/j.addr.2023.114898.Coutance G, Chong AS, Habal MV. Novel pretransplant desensitization strategies in heart transplantation. JHLT Open. 2025; 8: 100242. doi: 10.1016/j.jhl-to.2025.100242.Coutance G, Chong AS, Habal MV. Novel pretransplant desensitization strategies in heart transplantation. JHLT Open. 2025; 8: 100242. doi: 10.1016/j.jhl-to.2025.100242.Marfil‑Garza BA, Hefler J, Bermudez De Leon M, Pawlick R, Dadheech N, Shapiro AMJ. Progress in Translational Regulatory T Cell Therapies for Type 1 Diabetes and Islet Transplantation. Endocr Rev. 2021; 42 (2): 198–218. doi: 10.1210/endrev/bnaa028.Marfil‑Garza BA, Hefler J, Bermudez De Leon M, Pawlick R, Dadheech N, Shapiro AMJ. Progress in Translational Regulatory T Cell Therapies for Type 1 Diabetes and Islet Transplantation. Endocr Rev. 2021; 42 (2): 198–218. doi: 10.1210/endrev/bnaa028.Tian Q, Wu C, Xu Y, Zhao Y. Experimental research progress on immunology of organ transplantation in 2020. Organ Transplant. 2021; 12 (2): 143–154. doi: 10.3969/j.issn.1674-7445.2021.02.004.Tian Q, Wu C, Xu Y, Zhao Y. Experimental research progress on immunology of organ transplantation in 2020. Organ Transplant. 2021; 12 (2): 143–154. doi: 10.3969/j.issn.1674-7445.2021.02.004.Cramer EEA, Ito K, Hofmann S. Ex vivo Bone Models and Their Potential in Preclinical Evaluation. Curr Osteoporos Rep. 2021; 19 (1): 75–87. doi: 10.1007/s11914-020-00649-5.Cramer EEA, Ito K, Hofmann S. Ex vivo Bone Models and Their Potential in Preclinical Evaluation. Curr Osteoporos Rep. 2021; 19 (1): 75–87. doi: 10.1007/s11914-020-00649-5.Ravi K, Manoharan TJM, Wang KC, Pockaj B, Nikkhah M. Engineered 3D ex vivo models to recapitulate the complex stromal and immune interactions within the tumor microenvironment. Biomaterials. 2024; 305: 122428. doi: 10.1016/j.biomaterials.2023.122428.Ravi K, Manoharan TJM, Wang KC, Pockaj B, Nikkhah M. Engineered 3D ex vivo models to recapitulate the complex stromal and immune interactions within the tumor microenvironment. Biomaterials. 2024; 305: 122428. doi: 10.1016/j.biomaterials.2023.122428.Guo W, Zhang X, Zhai J, Xue J. The roles and applications of neural stem cells in spinal cord injury repair. Front Bioeng Biotechnol. 2022; 10: 966866. doi: 10.3389/fbioe.2022.966866.Guo W, Zhang X, Zhai J, Xue J. The roles and applications of neural stem cells in spinal cord injury repair. Front Bioeng Biotechnol. 2022; 10: 966866. doi: 10.3389/fbioe.2022.966866.Faria I, Canizares S, Viana P, Kueht M. II. Navigating the changing landscape of transplant research: Trends, topics, and gender disparities. Am J Surg. 2025; 239: 116003. doi: 10.1016/j.amjsurg.2024.116003.Faria I, Canizares S, Viana P, Kueht M. II. Navigating the changing landscape of transplant research: Trends, topics, and gender disparities. Am J Surg. 2025; 239: 116003. doi: 10.1016/j.amjsurg.2024.116003.Carneiro CFD, Drude N, Hülsemann M, Collazo A, Toelch U. Mapping strategies towards improved external validity in preclinical translational research. Expert Opin Drug Discov. 2023; 18 (11): 1273–1285. doi: 10.1080/17460441.2023.2251886.Carneiro CFD, Drude N, Hülsemann M, Collazo A, Toelch U. Mapping strategies towards improved external validity in preclinical translational research. Expert Opin Drug Discov. 2023; 18 (11): 1273–1285. doi: 10.1080/17460441.2023.2251886.Zgoura P, Seibert FS, Waldecker C, Doevelaar A, Bauer F, Rohn B et al. Psychological Responses to the Coronavirus Disease 2019 Pandemic in Renal Transplant Recipients. Transplant Proc. 2020; 52 (9): 2671–2675. doi: 10.1016/j.transproceed.2020.08.043.Zgoura P, Seibert FS, Waldecker C, Doevelaar A, Bauer F, Rohn B et al. Psychological Responses to the Coronavirus Disease 2019 Pandemic in Renal Transplant Recipients. Transplant Proc. 2020; 52 (9): 2671–2675. doi: 10.1016/j.transproceed.2020.08.043.Martins PNA. Kidney Transplantation in the rat: A modified technique using hydrodissection. Microsurgery. 2006; 26: 543–546.Martins PNA. Kidney Transplantation in the rat: A modified technique using hydrodissection. Microsurgery. 2006; 26: 543–546.Ahmadi AR, Qi L, Iwasaki K, Wang W, Wesson RN, Cameron AM, Sun Z. Orthotopic Rat Kidney Transplantantation: A Novel and Simplified Surgical Approach. J Vis Exp. 2019 May 7; (147): e59403. doi: 10.3791/59403.Ahmadi AR, Qi L, Iwasaki K, Wang W, Wesson RN, Cameron AM, Sun Z. Orthotopic Rat Kidney Transplantantation: A Novel and Simplified Surgical Approach. J Vis Exp. 2019 May 7; (147): e59403. doi: 10.3791/59403.Gueler F, Shushakova N, Mengel M, Hueper K, Chen R, Liu X et al. A Novel Therapy to Attenuate Acute Kidney Injury and Ischemic Allograft Damage after Allogenic Kidney Transplantantation in Mice. PLoS One. 2015; 10 (1): e0115709. doi: 10.1371/journal.pone.0115709.Gueler F, Shushakova N, Mengel M, Hueper K, Chen R, Liu X et al. A Novel Therapy to Attenuate Acute Kidney Injury and Ischemic Allograft Damage after Allogenic Kidney Transplantantation in Mice. PLoS One. 2015; 10 (1): e0115709. doi: 10.1371/journal.pone.0115709.Mirioglu S, Morelle J, Efe O. Thrombotic microangiopathy after kidney transplantation: diagnosis and management strategies. Clin Kidney J. 2026 Jan 24; 19 (3): sfag018. doi: 10.1093/ckj/sfag018.Mirioglu S, Morelle J, Efe O. Thrombotic microangiopathy after kidney transplantation: diagnosis and management strategies. Clin Kidney J. 2026 Jan 24; 19 (3): sfag018. doi: 10.1093/ckj/sfag018.Zhao D, Liao T, Li S, Zhang Y, Zheng H, Zhou J et al. Mouse Model Established by Early Renal Transplantantation After Skin Allograft Sensitization Mimics Clinical Antibody-Mediated Rejection. Front Immunol. 2018; 9: 1356. doi: 10.3389/fimmu.2018.01356.Zhao D, Liao T, Li S, Zhang Y, Zheng H, Zhou J et al. Mouse Model Established by Early Renal Transplantantation After Skin Allograft Sensitization Mimics Clinical Antibody-Mediated Rejection. Front Immunol. 2018; 9: 1356. doi: 10.3389/fimmu.2018.01356.Al‑Shalawi FD, Mohamed Ariff AH, Jung DW, Mohd Ariffin MKA, Seng Kim CL, Brabazon D, Al‑Osaimi MO. Biomaterials as implants in the orthopedic field for regenerative medicine: metal versus synthetic polymers. Polymers (Basel). 2023; 15 (12): 2601. doi: 10.3390/polym15122601.Al‑Shalawi FD, Mohamed Ariff AH, Jung DW, Mohd Ariffin MKA, Seng Kim CL, Brabazon D, Al‑Osaimi MO. Biomaterials as implants in the orthopedic field for regenerative medicine: metal versus synthetic polymers. Polymers (Basel). 2023; 15 (12): 2601. doi: 10.3390/polym15122601.Versteegden LRM, de Jonge PKJD, IntHout J, van Kuppevelt TH, Oosterwijk E, Feitz WFJ et al. Tissue engineering of the urethra: a systematic review and meta-analysis of preclinical and clinical studies. Eur Urol. 2017; 72 (4): 594–606. doi: 10.1016/j.eururo.2017.03.026.Versteegden LRM, de Jonge PKJD, IntHout J, van Kuppevelt TH, Oosterwijk E, Feitz WFJ et al. Tissue engineering of the urethra: a systematic review and meta-analysis of preclinical and clinical studies. Eur Urol. 2017; 72 (4): 594–606. doi: 10.1016/j.eururo.2017.03.026.Кабанова СА, Богопольский ПМ. Пересадка почки: история, итоги и перспективы (к 50-летию первой успешной пересадки почки в России). Трансплантология. 2015; (2): 49–58. https://doi.org/10.23873/2074-0506-2015-0-2-104.Kabanova SA, Bogopol’skiy PM. Kidney transplant: history, results and perspectives (The 50th anniversary of the first successful kidney transplant in Russia). Transplantologiya. The Russian Journal of Transplantation. 2015; (2): 49–58. https://doi.org/10.23873/2074-0506-2015-0-2-104.Шабунин АВ, Дроздов ПА, Макеев ДА, Нестеренко ИВ, Журавель ОС, Астапович СА, Лиджиева ЭА. Влияние элиминации вторичной тепловой ишемии на функцию почечного трансплантата: эксперимент и клиническое исследование. Вестник трансплантологии и искусственных органов. 2023; 25 (2): 26–37. doi: 10.15825/1995-1191-2023-2-26-37.Shabunin AV, Drozdov PA, Makeev DA, Nesterenko IV, Zhuravel OS, Astapovich SA, Lidjieva EA. Effect of second warm ischemia elimination on kidney graft function: an experiment and clinical study. Russian Journal of Transplantology and Artificial Organs. 2023; 25 (2): 26–37. doi: 10.15825/1995-1191-2023-2-26-37.Гусев АА. Какие нейросети и как может использовать врач-уролог в своей ежедневной работе: практические рекомендации. Вестник урологии. 2025; 13 (1): 99–109. doi: 10.21886/2308-6424-2025-13-1-99-109.Gusev AA. What neural networks and how a urologist can utilize in his routine tasks: practical tips. Urology Herald. 2025; 13 (1): 99–109. (In Russ.). doi: 10.21886/2308-6424-2025-13-1-99-109.Щамхалова КК, Меринов ДС, Артемов АВ, Гурбанов ШШ. Искусственный интеллект и нейронные сети в урологии. Экспериментальная и клиническая урология. 2023; 16 (2): 32–37. https://doi.org/10.29188/2222-8543-2023-16-2-32-37.Shamkhalova KK, Merinov DS, Artemov AV, Gurbanov ShSh. Artificial intelligence and neural networks in urology. Experimental and Clinical Urology. 2023; 16 (2): 32–37. https://doi.org/10.29188/2222-8543-2023-16-2-32-37.Кобринский БА. Системы искусственного интеллекта в хирургии: возможности, ограничения и перспективы. Обзор литературы. Российский вестник детской хирургии, анестезиологии и реаниматологии. 2023; 13 (3): 385–404. https://doi.org/10.17816/psaic1547.Kobrinskii BA. Artificial intelligence systems in surgery: A review of opportunities, limitations, and prospects. Review. Russian Journal of Pediatric Surgery, Anesthesia and Intensive Care. 2023; 13 (3): 385–404. https://doi.org/10.17816/psaic1547.

The authors declare that there are no conflicts of interest present.