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Neural interfacing devices interact with the central nervous system to alleviate functional deficits arising from disease or injury. This often entails the use of invasive microelectrode implants that elicit inflammatory responses from glial cells and leads to loss of device function. Previous work focused on improving implant biocompatibility by modifying electrode composition; here, we investigated the direct effects of electrical stimulation on glial cells at the electrode interface. A high-throughput system that assesses primary glial cell response to biphasic stimulation waveforms at 0 mA, 0.15 mA, and 1.5 mA was developed and optimized. Primary mixed glial cell cultures were generated from heterozygous CX3CR-1 mice, electrically stimulated for 4 h/day over 3 days using 75 μm platinum-iridium microelectrodes, and biomarker immunofluorescence was measured. Electrodes were then imaged on a scanning electron microscope to assess sustained electrode damage. Fluorescence and electron microscopy analyses suggest varying degrees of localized responses for each biomarker assayed (Hoescht, EGFP, GFAP, and IL-1β), a result that expands on comparable models. This system allows for the comparison of a breadth of electrical stimulation parameters, and opens another avenue through which neural interfacing device developers can improve biocompatibility and longevity of electrodes in tissue.
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http://dx.doi.org/10.3389/fbioe.2024.1351087 | DOI Listing |
J Neurosci Methods
September 2025
Department of Computer Science and Engineering, IIT (ISM) Dhanbad, Dhanbad, 826004, Jharkhand, India. Electronic address:
Background: Interpretation of motor imagery (MI) in brain-computer interface (BCI) applications is largely driven by the use of electroencephalography (EEG) signals. However, precise classification in stroke patients remains challenging due to variability, non-stationarity, and abnormal EEG patterns.
New Methods: To address these challenges, an integrated architecture is proposed, combining multi-domain feature extraction with evolutionary optimization for enhanced EEG-based MI classification.
Biomed Phys Eng Express
September 2025
Southwest Jiaotong University School of Mechanical Engineering, No. 111, North Section 1, Second Ring Road, Jinniu District, Chengdu, Chengdu, Sichuan, 610031, CHINA.
Total hip arthroplasty (THA) is the standard surgical treatment for end-stage hip osteoarthritis, with its success dependent on precise preoperative planning, which, in turn, relies on accurate three-dimensional segmentation and reconstruction of the periarticular bone of the hip joint. However, patients with hip osteoarthritis often exhibit pathological characteristics, such as joint space narrowing, femoroacetabular impingement, osteophyte formation, and joint deformity. These changes present significant challenges for traditional manual or semi-automatic segmentation methods.
View Article and Find Full Text PDFACS Sens
September 2025
College of Chemistry, Beijing Normal University, Beijing 100875, China.
Dopamine (DA) signaling is essential for neurodevelopment and is particularly sensitive to disruption during adolescence. Protein restriction (PR) can impair DA dynamics, yet mechanistic insights remain limited due to challenges in real-time neurochemical sensing. Here, we present aptCFE, a robust implantable aptamer-based sensor fabricated via a reagent-free, 3 min electrochemical conjugation (E-conjugation) using amine-quinone chemistry.
View Article and Find Full Text PDFSci Adv
September 2025
School of Electrical and Electronic Engineering, Yonsei University, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.
Brain-computer interfaces (BCIs) enable direct communication between the brain and computers. However, their long-term functionality remains limited due to signal degradation caused by acute insertion trauma, chronic foreign body reaction (FBR), and biofouling at the device-tissue interface. To address these challenges, we introduce a multifunctional surface modification strategy called targeting-specific interaction and blocking nonspecific adhesion (TAB) coating for flexible fiber, achieving a synergistic integration of mechanical compliance and biochemical stability.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
September 2025
Recognizing hand gestures from surface electromyography (sEMG) signals is crucial for neural interfaces and human-machine interaction. However, developing subject-generic models remains challenging due to substantial inter-subject variability. Complicating matters further, the muscle groups driving gestures with varying degrees of freedom (DoFs) often overlap, producing highly convoluted feature distributions across subjects and DoFs.
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