Identificación de proteínas osteogénicas mediante análisis In Sílico para su aplicación en el diseño de un implante mandibular hecho a la medida

López Porras, Angie Kamila

Identificación de proteínas osteogénicas mediante análisis In Sílico para su aplicación en el diseño de un implante mandibular hecho a la medida

dc.contributor.advisor	Rodríguez Sáenz, Álvaro Andrés
dc.contributor.advisor	Munévar Niño, Juan Carlos
dc.contributor.advisor	Romero Oyuela, Amparo Stefanny
dc.contributor.advisor	Montoya Hernández, Jenny Andrea
dc.contributor.author	López Porras, Angie Kamila
dc.contributor.orcid	López Porras, Angie Kamila [0009-0000-6339-1254]
dc.date.accessioned	2024-12-13T19:56:20Z
dc.date.available	2024-12-13T19:56:20Z
dc.date.issued	2024-11
dc.description.abstract	Antecedentes: La reconstrucción de defectos críticos en el complejo craneofacial presenta desafíos importantes debido a la ausencia de métodos efectivos para optimizar la regeneración ósea. Actualmente, existe una brecha en el uso de células madre dentales humanas (hDPSCs) combinadas con andamios biocompatibles y señales bioquímicas. Este estudio aborda estas limitaciones mediante un análisis in silico, ofreciendo soluciones innovadoras en odontología regenerativa. Objetivo: Determinar el diseño óptimo de un implante mandibular personalizado para la reconstrucción de un defecto óseo de tamaño crítico mediante análisis in silico. Metodología: Este estudio se centró en la identificación de proteínas osteogénicas mediante análisis in silico utilizando la plataforma STRING, explorando redes funcionales y asociaciones entre factores de crecimiento osteogénicos y el secretoma de las células madre dentales (hDPSCs). Se aplicaron criterios de inclusión y exclusión para seleccionar las proteínas más relevantes, identificando aquellas sobreexpresadas o subexpresadas en hDPSCs. Con base en los resultados, se diseñó un implante mandibular personalizado utilizando los softwares Nemofab y Geomagic, partiendo de imágenes obtenidas de una tomografía computarizada (TC) del paciente. Estas imágenes fueron importadas al software CAD para modelar el implante con precisión, seguido por manufactura asistida por computadora (CAM) para su producción. Finalmente, se empleó realidad aumentada para simular la colocación del implante en un entorno virtual que replicó la anatomía específica del paciente, permitiendo una evaluación prequirúrgica detallada y ajustes precisos. Este enfoque busca optimizar la regeneración ósea y proporcionar soluciones innovadoras en odontología regenerativa. Resultados: El análisis in silico demostró que las hDPSCs tienen un potencial osteogénico superior, consolidándose como una opción prometedora para la regeneración ósea en defectos críticos. Además, la incorporación de proteínas morfogenéticas óseas (BMP-2) aceleró significativamente los procesos de osificación, promoviendo la formación de nuevo tejido. La integración de estas herramientas avanzadas mejoró la visualización y planificación quirúrgica, incrementando la precisión y seguridad del procedimiento. La exitosa aplicación en un caso clínico real valida la aplicabilidad práctica del proyecto, con impacto directo en la salud del paciente. Conclusiones: Este análisis in sílico confirma que las hDPSCs representan una alternativa efectiva para la regeneración ósea en defectos críticos. La interacción entre las hDPSCs y BMP-2 potencia los procesos de osificación, estableciéndose como una estrategia innovadora en ingeniería tisular. El uso de tecnologías emergentes como inteligencia artificial y realidad virtual mejora la precisión quirúrgica, demostrando relevancia práctica en la planificación y ejecución de implantes personalizados. Además, esta investigación subraya la importancia de la colaboración multidisciplinaria y avanza la medicina regenerativa personalizada, proporcionando un modelo pedagógico para futuras investigaciones. En conjunto, ofrece soluciones novedosas en cirugía maxilofacial con un impacto significativo en la práctica clínica.
dc.description.abstractenglish	Background: Reconstruction of critical defects in the craniofacial complex presents significant challenges due to the absence of effective methods to optimize bone regeneration. Currently, a gap exists in the use of human dental stem cells (hDPSCs) combined with biocompatible scaffolds and biochemical signals. This study addresses these limitations through in silico analysis, offering innovative solutions in regenerative dentistry. Aim: To determine the optimal design of a customized mandibular implant for the reconstruction of a critical-size bone defect by in silico analysis. Methods: This study focused on the identification of osteogenic proteins by in silico analysis using the STRING platform, exploring functional networks and associations between osteogenic growth factors and the secretome of dental stem cells (hDPSCs). Inclusion and exclusion criteria were applied to select the most relevant proteins, identifying those over- or underexpressed in hDPSCs. Based on the results, a customized mandibular implant was designed using Nemofab and Geomagic software, starting from images obtained from a computed tomography (CT) scan of the patient. These images were imported into CAD software to accurately model the implant, followed by computer-aided manufacturing (CAM) for its production. Finally, augmented reality was used to simulate implant placement in a virtual environment that replicated the patient's specific anatomy, allowing for detailed pre-surgical evaluation and fine- tuning. This approach aims to optimize bone regeneration and provide innovative solutions in regenerative dentistry. Results: In silico analysis demonstrated that hDPSCs have superior osteogenic potential, consolidating them as a promising option for bone regeneration in critical defects. In addition, incorporating bone morphogenetic proteins (BMP-2) significantly accelerated the ossification processes, promoting the formation of new tissue. The integration of these advanced tools improved surgical visualization and planning, increasing the procedure's accuracy and safety. The successful application in a real clinical case validates the project's practical applicability, with a direct impact on patient health. Conclusions: This in silico analysis confirms that hDPSCs represent an effective alternative for bone regeneration in critical defects. The interaction between hDPSCs and BMP-2 enhances ossification processes, establishing itself as an innovative strategy in tissue engineering. Emerging technologies such as artificial intelligence and virtual reality improve surgical precision, demonstrating practical relevance in planning and executing customized implants. In addition, this research underscores the importance of multidisciplinary collaboration and advances personalized regenerative medicine, providing a pedagogical model for future research. Overall, it offers novel solutions in maxillofacial surgery with a significant impact on clinical practice.
dc.description.degreelevel	Pregrado	spa
dc.description.degreename	Odontólogo	spa
dc.description.sponsorship	Grupo de Investigación UNIECLO - Unidad de Epidemiología Clínica Oral.
dc.description.sponsorship	Grupo de Investigación UIBO - Unidad de Investigación Básica Oral.
dc.description.sponsorship	Grupo de Investigación UMIMC - Unidad de Manejo Integral de Malformaciones Craneofaciales
dc.format.mimetype	application/pdf
dc.identifier.instname	instname:Universidad El Bosque	spa
dc.identifier.reponame	reponame:Repositorio Institucional Universidad El Bosque	spa
dc.identifier.repourl	repourl:https://repositorio.unbosque.edu.co
dc.identifier.uri	https://hdl.handle.net/20.500.12495/13713
dc.language.iso	es
dc.publisher.faculty	Facultad de Odontología	spa
dc.publisher.grantor	Universidad El Bosque	spa
dc.publisher.program	Odontología	spa
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dc.rights	Atribución-NoComercial-CompartirIgual 4.0 Internacional
dc.rights.accessrights	https://purl.org/coar/access_right/c_abf2
dc.rights.accessrights	info:eu-repo/semantics/openAccess
dc.rights.local	Acceso abierto	spa
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subject	In Sílico
dc.subject	Células madre dentales
dc.subject	Impresión tridimensional
dc.subject	Implante hecho a la medida
dc.subject.keywords	In silico
dc.subject.keywords	Dental stem cells
dc.subject.keywords	Three-dimensional Impression
dc.subject.keywords	Custom Implant
dc.subject.nlm	WU 100
dc.title	Identificación de proteínas osteogénicas mediante análisis In Sílico para su aplicación en el diseño de un implante mandibular hecho a la medida
dc.title.translated	Identification of osteogenic proteins by In Silico analysis for application in the design of a custom-made mandibular implant
dc.type.coar	https://purl.org/coar/resource_type/c_7a1f
dc.type.coarversion	https://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.driver	info:eu-repo/semantics/bachelorThesis
dc.type.hasversion	info:eu-repo/semantics/acceptedVersion
dc.type.local	Tesis/Trabajo de grado - Monografía - Pregrado	spa