A simple and highly sensitive electrochemical DNA sensor based on a ferrocene-functionalized polypyrrole has been prepared on a microelectrode array substrate for a multi-DNA detection chip format. A copolymer formed with 1-(phthalimidylbutanoate)-1'-(N-(3-butylpyrrole)butanamide)ferrocene (Py-Fe-NHP) and pyrrole was electrocopolymerized on the gold surface of both macroelectrode and biochip formats. DNA probes bearing an amino group were covalently grafted by substitution of NHP groups and the hybridization reaction was followed by monitoring the redox signal of the ferrocenyl group acting as the probe. The integration of the polymers into chip format produces high-density arrays of individually addressable oligonucleotide microelectrodes. Results show that reducing the size of the electrodes from a macroelectrode to the chip format allows a variation of the nucleation and the growth process during electropolymerization of modified pyrrole monomers. These modifications enable an increase in the sensitivity and selectivity of DNA hybridization.
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http://dx.doi.org/10.1016/j.talanta.2010.02.017 | DOI Listing |
Nanomaterials (Basel)
December 2024
Personalized Medicine Centre, Almazov National Medical Research Centre, Akkuratova Str. 2, 197341 St. Petersburg, Russia.
This study addresses issues in developing spatially controlled magnetic fields for particle guidance, synthesizing biocompatible and chemically stable MNPs and enhancing their specificity to pathological cells through chemical modifications, developing personalized adjustments, and highlighting the potential of tumor-on-a-chip systems, which can simulate tissue environments and assess drug efficacy and dosage in a controlled setting. The research focused on two MNP types, uncoated magnetite nanoparticles (mMNPs) and carboxymethyl dextran coated superparamagnetic nanoparticles (CD-SPIONs), and evaluated their transport properties in microfluidic systems and porous media. The original uncoated mMNPs of bimodal size distribution and the narrow size distribution of the fractions (23 nm and 106 nm by radii) were demonstrated to agglomerate in magnetically driven microfluidic flow, forming a stable stationary web consisting of magnetic fibers within 30 min.
View Article and Find Full Text PDFNAR Genom Bioinform
December 2024
Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Emile St, Omaha, NE 68198, USA.
Chromatin contact maps are often shown as 2D heatmaps and visually compared to 1D genomic data by simple juxtaposition. While common, this strategy is imprecise, placing the onus on the reader to align features with each other. To remedy this, we developed HiCrayon, an interactive tool that facilitates the integration of 3D chromatin organization maps and 1D datasets.
View Article and Find Full Text PDFACS Nano
December 2024
School of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
The simultaneous detection of proteins and microRNA (miRNA) at the single extracellular vesicle (EV) level shows great promise for precise disease profiling, owing to the heterogeneity and scarcity of tumor-derived EVs. However, a highly reliable method for multiple-target analysis of single EVs remains to be developed. In this study, a igital ual CRISPR-Cas-powered ingle V valuation () system was proposed to enable the concurrent detection of surface protein and inner miRNA of EVs at the single-molecule level.
View Article and Find Full Text PDFAnal Chim Acta
January 2025
Center of Genomics, Helmy Institute, Zewail City of Science and Technology, Sheikh Zayed Dist, 12588, Giza, Egypt; Pathology and Molecular Genomics Unit of Medical Ain Shams Research Institute (MASRI), Faculty of Medicine, Ain Shams University. Cairo, 11591, Cairo, Egypt; Biochemistry Department, Faculty of Pharmacy, Misr University for Science and Technology, 12566, Giza, Egypt. Electronic address:
ACS Sens
November 2024
Brazilian Nanotechnology National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas, São Paulo 13083-970, Brazil.
Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of drug candidates remains a significant barrier to developing medicines. In this way, ultradense electrochemical chips are combined with machine learning (ML) to enable high-throughput, user-friendly, and accurate determination of the viability of 2D tumor cells (breast and colorectal) aiming at drug susceptibility assays.
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