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Skin Diseases and Disorders01:23

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Skin is the first line of defense and encounters a variety of microbes. Some pathogenic strains are often the cause of a broad range of infections of the skin and other body systems. These conditions can affect people of all ages and may have different causes, including genetic factors, infections, autoimmune reactions, environmental factors, and lifestyle choices.
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Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
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Lysosomes are the site for the degradation of macromolecules and biological polymers released during membrane trafficking events such as secretory, endocytic, autophagic, and phagocytic pathways. The membrane-enclosed area of the lysosome, called the lumen, contains hydrolytic enzymes active in an acidic environment. These acid hydrolases are functional at a pH between 4.5 and 5 and are involved in cellular processes such as cell signaling, energy metabolism, restoration of the plasma membrane,...
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Updated: Dec 30, 2025

Assessment and Communication for People with Disorders of Consciousness
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Interfaces cerebro-ordenador crónicamente estables y de alta resolución para la decodificación del motor en tiempo

Erda Zhou1,2, Xiner Wang1,2, Jizhi Liang1,2

  • 12020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|September 6, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio introduce una interfaz cerebro-computadora (BCI) de micro-electrocorticografía de alta densidad (μECoG) para una decodificación motora estable en tiempo real. Este BCI flexible ofrece un rendimiento mejorado y una invasividad reducida para pacientes con trastornos neurológicos.

Palabras clave:
Interfaces cerebro-ordenadorSistemas microelectromecánicos flexibles y conformesMicro-electrocorticografía de alta resolución, descodificación del motor en tiempo real

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Área de la Ciencia:

  • La neurociencia
  • Ingeniería biomédica
  • Dispositivos médicos

Sus antecedentes:

  • Las interfaces cerebro-ordenador (BCI) son cruciales para restaurar la comunicación y las funciones motoras en personas con trastornos neurológicos.
  • Los BCI convencionales de electrocorticografía (ECoG) se enfrentan a limitaciones en la resolución espacial y el tamaño del dispositivo.
  • Se necesitan conjuntos de electrodos de alta densidad para mejorar la precisión de la decodificación de la actividad cerebral.

Objetivo del estudio:

  • Desarrollar y evaluar un sistema BCI de microelectrocorticografía (μECoG) flexible y de alta resolución.
  • Evaluar la estabilidad crónica y las capacidades de decodificación del motor en tiempo real del BCI μECoG.
  • Demostrar el potencial de la tecnología μECoG para superar las limitaciones de los BCI convencionales de ECoG.

Principales métodos:

  • Se utilizó la fabricación micro-nano para crear una matriz de electrodos μECoG flexible y de alta densidad con un aumento de 64 veces en la densidad de los electrodos.
  • Se realizó un experimento in vivo de 203 días para evaluar la estabilidad y el rendimiento crónicos.
  • Implementa algoritmos de decodificación del motor en tiempo real para tareas como el control del juego y el cursor.

Principales resultados:

  • El BCI μECoG demostró un rendimiento crónicamente estable durante 203 días.
  • Logró la decodificación del motor en tiempo real, permitiendo el control del juego en 7 minutos de entrenamiento.
  • Alcanzó un pico de velocidad de bits de 4,15 bits por segundo (BPS) para el control del cursor, comparable a las BCI intracorticales de EEG sin invasión.

Conclusiones:

  • Los BCI μECoG de alta resolución ofrecen una mayor especificidad espacial para mejorar el rendimiento de decodificación.
  • La matriz μECoG flexible y de alta densidad avanza significativamente la tecnología BCI, reduciendo el tamaño y la invasividad del dispositivo.
  • Este μECoG BCI representa un avance en la viabilidad clínica para interfaces cerebro-computadora flexibles y de alto rendimiento.