Nanowire biosensors for label-free, real-time, ultrasensitive protein detection.
ABSTRACT Sensitive and quantitative analysis of proteins is central to disease diagnosis, drug screening, and proteomic studies. Among recent research advances exploiting new nanomaterials for biomolecule analysis, silicon nanowires (SiNWs), which are configured as field-effect transistors (FETs), have emerged as one of the most promising and powerful platforms for label-free, real-time, and highly sensitive electrical detection of proteins as well as many other biological species. Here, we describe a detailed protocol for realizing SiNW biosensors for protein detection that includes SiNW synthesis, FET device fabrication, surface receptor functionalization, and electrical sensing measurements. Moreover, incorporating both p-type and n-type SiNWs in the same sensor array provides a unique means of internal control for sensing signal verification.
- SourceAvailable from: Marco Crescentini[Show abstract] [Hide abstract]
ABSTRACT: Current sensing readout is one of the most frequent techniques used in biosensing due to the charge-transfer phenomena occurring at solid-liquid interfaces. The development of novel nanodevices for biosensing determines new challenges for electronic interface design based on current sensing, especially when compact and efficient arrays need to be organized, such as in recent trends of rapid label-free electronic detection of DNA synthesis. This paper will review the basic noise limitations of current sensing interfaces with particular emphasis on integrated CMOS technology. Starting from the basic theory, the paper presents, investigates and compares charge-sensitive amplifier architectures used in both continuous-time and discrete-time approaches, along with their design trade-offs involving noise floor, sensitivity to stray capacitance and bandwidth. The ultimate goal of this review is providing analog designers with helpful design rules and analytical tools. Also, in order to present a comprehensive overview of the state-of-the-art, the most relevant papers recently appeared in the literature about this topic are discussed and compared.IEEE Transactions on Biomedical Circuits and Systems 04/2014; 8(2):278-92. · 3.15 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Cancer is a major threat to public health and is still one of the leading causes of death worldwide. Cancer biomarkers are extremely important in the process of early detection of cancer, diagnosis, judgment of the curative effect and the prognosis. They also play an important role in mechanistic research into carcinogenesis. Detection methods based on cancer biomarkers for the determination of cancer can directly affect the diagnosis and treatment. Therefore, the development of highly sensitive and selective approaches for the detection of cancer biomarkers is critical. Micro- and nanoparticles play an important role in the clinical detection of cancer biomarkers. In this review, we provide an overview of the commonly used clinical detection methods for cancer biomarkers, such as enzyme-linked immunosorbent assay, chemiluminescence, electrochemiluminescence, as well as their technical characteristics. Additionally, various applications of recent advances in microparticles and nanoparticles in the clinical detection of cancer biomarkers are also reviewed.Analytical methods 01/2013; 5(21):5862. · 1.94 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: DNA sequencing has revolutionized biological and medical research, and is poised to have a similar impact in medicine. This tool is just one of a number of developments in our capability to identify, quantitate and functionally characterize the components of the biological networks keeping us healthy or making us sick, but in many respects it has played the leading role in this process. The new technologies do, however, also provide a bridge between genotype and phenotype, both in man and model (as well as all other) organisms, revolutionize the identification of elements involved in a multitude of human diseases or other phenotypes, and generate a wealth of medically relevant information on every single person, as the basis of a truly personalized medicine of the future.F1000prime reports. 09/2013; 5:34.