Decoding multimodal TBI markers for optimized recovery

Descripción del proyecto

Análisis de la recuperación tras un traumatismo craneoencefálico

Un traumatismo craneoencefálico (TCE) se produce cuando fuerzas mecánicas alteran la función cerebral y los procesos biológicos conexos. Los métodos actuales no permiten abordar la complejidad del TCE, lo que pone de relieve la necesidad de mejorar la integración de datos entre disciplinas. En el proyecto NeuroVitalizer, financiado por el Consejo Europeo de Investigación, se analizará la recuperación tras un TCE de leve a moderado utilizando un marco que incorpora la estimulación eléctrica en modelos «in vitro». Se examinará la morfología celular, la actividad eléctrica y la expresión de proteínas mediante fusión de datos asistida por inteligencia artificial para identificar patrones en los procesos de recuperación. El equipo del proyecto analizará la relación entre la actividad de los astrocitos y la salud neuronal, los protocolos óptimos de estimulación eléctrica y los biomarcadores tempranos para la predicción de la recuperación, abordando así el TCE desde múltiples perspectivas.

Objetivo

Traumatic brain injury (TBI) occurs when mechanical forces shake the brain and disrupt normal brain function, affecting biological processes like cellular, molecular, and electrical functions. These processes are highly interconnected, making it difficult to fully understand TBI recovery with traditional single-discipline methods. Current approaches often fail to address the complexity of TBI even in mild to moderate cases, creating an urgent need for new methods to overcome existing limits in data collection, integration, and interpretation across multiple subdisciplines.
In this project, I will set up a new framework for a comprehensive and systematic analysis of recovery processes post-trauma and the effect of electrical stimulation (ES) in in vitro models for mild to moderate TBI, which allows for a detailed examination in a controlled environment. Our experimental workflow will integrate insights on cellular morphology and structure from microscopy images, electrical activity, and network synchronization from multi-electrode array recordings, protein expression changes from immunostaining, and cell viability and stress markers found in the cell medium. Calcium imaging will provide insights into ionic homeostasis maintenance. An AI-driven data fusion approach will facilitate the analysis of these multimodal datasets revealing hidden patterns and relationships that traditional approaches cannot uncover.
Specifically, we want to address questions such as
• How do astrocyte protein expression and neuronal electrical activity relate to repair after TBI?
• To what extent can ES prevent neuronal death, and what are the best stimulation protocols? When should we start the treatment?
• Are there early biomarkers that can predict recovery success or delays?
This project introduces a cutting-edge method by integrating a multimodal data fusion setup and AI-based synthesis to tackle TBI recovery from multiple angles, capturing the complexity that standard approaches miss.