Application of nanomaterials to arrays for infectious disease diagnosis

Preparation of diamond-based AuNP-modified nanocomposites with elevated catalytic performances

Diamond@graphene oxide@gold nanoparticle (D@GO@AuNP) nanocomposite materials with excellent catalytic activity and high recyclability were prepared, demonstrating potential applications as a composite catalytic material.

Immunodiagnostics and immunosensor design (IUPAC Technical Report)

This work compiles information on the principles of diagnostic immunochemical methods and the recent advances in this field. It presents an overview of modern techniques for the production of diagnostic antibodies, their modification with the aim of improving their diagnostic potency, the different types of immunochemical detection systems, and the increasing diagnostic applications for human health that include specific disease markers, individualized diagnosis of cancer subtypes, therapeutic and addictive drugs, food residues, and environmental contaminants. A special focus lies in novel developments of immunosensor techniques, promising approaches to miniaturized detection units and the associated microfluidic systems. The trends towards high-throughput systems, multiplexed analysis, and miniaturization of the diagnostic tools are discussed. It is also made evident that progress in the last few years has largely relied on novel chemical approaches.

The on-bead digestion of protein corona on nanoparticles by trypsin immobilized on the magnetic nanoparticle

Proteins interacting with nanoparticles would form the protein coronas on the surface of nanoparticles in biological systems, which would critically impact the biological identities of nanoparticles and/or result in the physiological and pathological consequences. The enzymatic digestion of protein corona was the primary step to achieve the identification of protein components of the protein corona for the bottom-up proteomic approaches. In this study, the investigation on the tryptic digestion of protein corona by the immobilized trypsin on a magnetic nanoparticle was carried out for the first time. As a comparison with the usual overnight long-time digestion and the severe self-digestion of free trypsin, the on-bead digestion of protein corona by the immobilized trypsin could be accomplished within 1h, along with the significantly reduced self-digestion of trypsin and the improved reproducibility on the identification of proteins by the mass spectrometry-based proteomic approach. It showed that the number of identified bovine serum (BS) proteins on the commercial Fe3O4 nanoparticles was increased by 13% for the immobilized trypsin with 1h digestion as compared to that of using free trypsin with even overnight digestion. In addition, the on-bead digestion of using the immobilized trypsin was further applied on the identification of human plasma protein corona on the commercial Fe3O4 nanoparticles, which leads the efficient digestion of the human plasma proteins and the identification of 149 human plasma proteins corresponding to putative critical pathways and biological processes.

Artificial Intelligence in Numerical Modeling of Silver Nanoparticles Prepared in Montmorillonite Interlayer Space

Artificial neural network (ANN) models have the capacity to eliminate the need for expensive experimental investigation in various areas of manufacturing processes, including the casting methods. An understanding of the interrelationships between input variables is essential for interpreting the sensitivity data and optimizing the design parameters. Silver nanoparticles (Ag-NPs) have attracted considerable attention for chemical, physical, and medical applications due to their exceptional properties. The nanocrystal silver was synthesized into an interlamellar space of montmorillonite by using the chemical reduction technique. The method has an advantage of size control which is essential in nanometals synthesis. Silver nanoparticles with nanosize and devoid of aggregation are favorable for several properties. In this investigation, the accuracy of artificial neural network training algorithm was applied in studying the effects of different parameters on the particles, including the AgNO3concentration, reaction temperature, UV-visible wavelength, and montmorillonite (MMT) d-spacing on the prediction of size of silver nanoparticles. Analysis of the variance showed that the AgNO3concentration and temperature were the most significant factors affecting the size of silver nanoparticles. Using the best performing artificial neural network, the optimum conditions predicted were a concentration of AgNO3of 1.0 (M), MMT d-spacing of 1.27 nm, reaction temperature of 27°C, and wavelength of 397.50 nm.

Green biosynthesis of silver nanoparticles using Callicarpa maingayi stem bark extraction

Different biological methods are gaining recognition for the production of silver nanoparticles (Ag-NPs) due to their multiple applications. The use of plants in the green synthesis of nanoparticles emerges as a cost effective and eco-friendly approach. In this study the green biosynthesis of silver nanoparticles using Callicarpa maingayi stem bark extract has been reported. Characterizations of nanoparticles were done using different methods, which include; ultraviolet-visible spectroscopy (UV-Vis), powder X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray fluorescence (EDXF) spectrometry, zeta potential measurements and Fourier transform infrared (FT-IR) spectroscopy. UV-visible spectrum of the aqueous medium containing silver nanoparticles showed absorption peak at around 456 nm. The TEM study showed that mean diameter and standard deviation for the formation of silver nanoparticles were 12.40 ± 3.27 nm. The XRD study showed that the particles are crystalline in nature, with a face centered cubic (fcc) structure. The most needed outcome of this work will be the development of value added products from Callicarpa maingayi for biomedical and nanotechnology based industries.