The ability to seamlessly merge electronic devices with biological systems at the cellular length scale is an exciting prospect for exploring new fundamental cell biology and in designing next-generation therapeutic devices. Semiconductor nanowires are well suited for achieving this goal because of their intrinsic size and wide range of possible configurations. However, current studies have focused primarily on delivering substrate-bound nanowire devices through mechanical abrasion or electroporation, with these bulkier substrates negating many of the inherent benefits of using nanoscale materials. To improve on this, an important next step is learning how to distribute these devices in a drug-like fashion, where cells can naturally uptake and incorporate these electronic components, allowing for truly noninvasive device integration. We show that silicon nanowires (SiNWs) can potentially be used as such a system, demonstrating that label-free SiNWs can be internalized in multiple cell lines (96% uptake rate), undergoing an active "burst-like" transport process. Our results show that, rather than through exogenous manipulation, SiNWs are internalized primarily through an endogenous phagocytosis pathway, allowing cellular integration of these materials. To study this behavior, we have developed a robust set of methodologies for quantitatively examining high-aspect ratio nanowire-cell interactions in a time-dependent manner on both single-cell and ensemble levels. This approach represents one of the first dynamic studies of semiconductor nanowire internalization and offers valuable insight into designing devices for biomolecule delivery, intracellular sensing, and photoresponsive therapies.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5161427 | PMC |
http://dx.doi.org/10.1126/sciadv.1601039 | DOI Listing |
Small Methods
January 2025
School of Electrical and Electronic Engineering Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
Silicon nanowires (Si NWs) have attracted considerable interest owing to their distinctive properties, which render them promising candidates for a wide range of advanced applications in electronics, photonics, energy storage, and sensing. However, challenges in achieving large-scale production, high uniformity, and shape control limit their practical use. This study presents a novel fabrication approach combining nanoimprint lithography, nanotransfer printing, and metal-assisted chemical etching to produce highly uniform and shape-controlled Si NW arrays.
View Article and Find Full Text PDFPLoS One
January 2025
College of Physics and Electronic Engineering, Hainan Normal University, HaiKou, China.
We have successfully prepared a significant number of nanowires from non-toxic silicon sources. Compared to the SiO silicon source used in most other articles, our preparation method is much safer. It provides a simple and harmless new preparation method for the preparation of silicon nanowires.
View Article and Find Full Text PDFACS Appl Bio Mater
January 2025
Graduate School of Science and Technology, Gunma University, 1-5-1 Tenjin-Cho, Kiryu, Gunma 376-8515, Japan.
Rapid and sensitive detection of virus-related antigens and antibodies is crucial for controlling sudden seasonal epidemics and monitoring neutralizing antibody levels after vaccination. However, conventional detection methods still face challenges related to compatibility with rapid, highly sensitive, and compact detection apparatus. In this work, we developed a Si nanowire (SiNW)-based field-effect biosensor by precisely controlling the process conditions to achieve the required electrical properties via complementary metal-oxide-semiconductor (CMOS)-compatible nanofabrication processes.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Computer Science, Faculty of Sciences and Humanities Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia.
Impedance-based biosensing has emerged as a critical technology for high-sensitivity biomolecular detection, yet traditional approaches often rely on bulky, costly impedance analyzers, limiting their portability and usability in point-of-care applications. Addressing these limitations, this paper proposes an advanced biosensing system integrating a Silicon Nanowire Field-Effect Transistor (SiNW-FET) biosensor with a high-gain amplification circuit and a 1D Convolutional Neural Network (CNN) implemented on FPGA hardware. This attempt combines SiNW-FET biosensing technology with FPGA-implemented deep learning noise reduction, creating a compact system capable of real-time viral detection with minimal computational latency.
View Article and Find Full Text PDFSensors (Basel)
December 2024
CNRS, LAAS, 7 Avenue du Colonel Roche, F-31400 Toulouse, France.
The development of ion-sensitive field-effect transistor (ISFET) sensors based on silicon nanowires (SiNW) has recently seen significant progress, due to their many advantages such as compact size, low cost, robustness and real-time portability. However, little work has been done to predict the performance of SiNW-ISFET sensors. The present study focuses on predicting the performance of the silicon nanowire (SiNW)-based ISFET sensor using four machine learning techniques, namely multilayer perceptron (MLP), nonlinear regression (NLR), support vector regression (SVR) and extra tree regression (ETR).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!