Análisis de la interacción ligando-receptor restringido por conectoma para comprender la comunicación de la red cerebral

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Zongchang Du^1,2,3, Congying Chu^2,3, Weiyang Shi^2,3

¹School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.

Nature communications

|September 1, 2025

Resumen

Este estudio introduce el análisis de la interacción ligando-receptor con conectoma restringido (CLRIA), un nuevo método para mapear las redes de comunicación del cerebro mediante la integración de datos estructurales y moleculares. CLRIA revela los patrones de comunicación del cerebro que decodifican las transiciones de estado del cerebro.

Área de la Ciencia:

La neurociencia
Biología computacional
Biología de sistemas

Sus antecedentes:

La resonancia magnética por difusión y la transcriptómica ofrecen visiones separadas de la comunicación cerebral.
Integrar la conectividad estructural y la señalización molecular para el análisis de la red cerebral es un desafío.

Objetivo del estudio:

Desarrollar un método que integre la resonancia magnética por difusión y los datos transcriptómicos para el análisis de la red de comunicación cerebral.
Inferir las redes de comunicación mediadas por la interacción ligando-receptor utilizando un nuevo enfoque computacional.

Principales métodos:

Desarrolló CLRIA (análisis de interacción ligando-receptor con restricción de conectoma) enmarcando la comunicación cerebral como un problema de transporte óptimo.
Acoplamiento de expresión ligando-receptor incorporado limitado por los costos de conectividad estructural.
Utilizó un algoritmo de minimización de mayoría de bloque para la optimización.

Principales resultados:

CLRIA deduce representaciones de bajo rango de las redes de comunicación del cerebro.
Validación de la precisión y la eficiencia computacional de CLRIA en datos simulados y publicados.
Los patrones derivados de CLRIA decodifican las transiciones del estado cerebral y evalúan las estrategias de comunicación.

Conclusiones:

CLRIA es una herramienta valiosa para diseccionar la comunicación compleja del cerebro.
Este método permite un enfoque unificado para comprender la dinámica de las redes cerebrales.
CLRIA hace avanzar la integración de datos multimodales en la investigación en neurociencias.

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