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1.
Clin Exp Immunol ; 213(1): 23-39, 2023 07 05.
Artículo en Inglés | MEDLINE | ID: mdl-37119279

RESUMEN

Innate lymphoid cells (ILCs) are a family of lymphocytes with essential roles in tissue homeostasis and immunity. Along with other tissue-resident immune populations, distinct subsets of ILCs have important roles in either promoting or inhibiting immune tolerance in a variety of contexts, including cancer and autoimmunity. In solid organ and hematopoietic stem cell transplantation, both donor and recipient-derived ILCs could contribute to immune tolerance or rejection, yet understanding of protective or pathogenic functions are only beginning to emerge. In addition to roles in directing or regulating immune responses, ILCs interface with parenchymal cells to support tissue homeostasis and even regeneration. Whether specific ILCs are tissue-protective or enhance ischemia reperfusion injury or fibrosis is of particular interest to the field of transplantation, beyond any roles in limiting or promoting allograft rejection or graft-versus host disease. Within this review, we discuss the current understanding of ILCs functions in promoting immune tolerance and tissue repair at homeostasis and in the context of transplantation and highlight where targeting or harnessing ILCs could have applications in novel transplant therapies.


Asunto(s)
Enfermedad Injerto contra Huésped , Trasplante de Células Madre Hematopoyéticas , Humanos , Linfocitos , Inmunidad Innata , Trasplante Homólogo , Enfermedad Injerto contra Huésped/prevención & control
2.
J Craniofac Surg ; 31(4): 898-903, 2020 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-32168124

RESUMEN

Machine learning (ML) revolves around the concept of using experience to teach computer-based programs to reliably perform specific tasks. Healthcare setting is an ideal environment for adaptation of ML applications given the multiple specific tasks that could be allocated to computer programs to perform. There have been several scoping reviews published in literature looking at the general acceptance and adaptability of surgical specialities to ML applications, but very few focusing on the application towards craniofacial surgery. This study aims to present a detailed scoping review regarding the use of ML applications in craniofacial surgery.


Asunto(s)
Cara/cirugía , Aprendizaje Automático , Cráneo/cirugía , Bibliometría , Atención a la Salud , Humanos , Prevalencia
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