Monolithic DNApatite: An Elastic Apatite with Sub-Nanometer Scale Organo-Inorganic Structures.

Hydroxyapatite (HA) exhibits outstanding biocompatibility, bioactivity, osteoconductivity, and natural anti-inflammatory properties. Pure HA, ion-doped HA, and HA-polymer composites are investigated, but critical limitations such as brittleness remain; numerous efforts are being made to address them. Herein, the novel self-crystallization of a polymeric single-stranded deoxyribonucleic acid (ssDNA) without additional phosphate ions for synthesizing deoxyribonucleic apatite (DNApatite) is presented. The synthesized DNApatite, DNA1Ca2.2(PO4)1.3OH2.1, has a repetitive dual phase of inorganic HA crystals and amorphous organic ssDNA at the sub-nm scale, forming nanorods. Its mechanical properties, including toughness and elasticity, are significantly enhanced compared with those of HA nanorod, with a Young's modulus similar to that of natural bone.

Chain-like One-Dimensional Assembly of Mesoporous Silica Nanoparticles: An Approach To Improve Hydrogel Adhesion.

Mesoporous silica nanoparticles (MSNPs) are well known for their adhesive properties with hydrogels and living tissues. However, achieving direct contact between the silica nanoparticle surface and the adherend necessitates the removal of capping agents, which can lead to severe aggregation when exposed to wet surfaces. This aggregation is ineffective for simultaneously bridging the two adherends, resulting in a reduced adhesive strength. In this study, we designed and synthesized mesoporous silica nanochains (MSNCs) to enhance the interactions with hydrogels by promoting the formation of coarser structures with increased nanopore exposure. Chain-like one-dimensional assemblies in the MSNCs were generated by depleting the capping ligand, cetyltrimethylammonium bromide, from the surface of the MSNPs. To quantify the porous areas of the MSNCs, we analyzed scanning electron microscopy (SEM) images using an in-house SEM image analysis algorithm. Additionally, we conducted a comparative assessment of the adhesion energies of MSNCs and MSNPs on a poly(dimethylacrylamide) hydrogel using a universal testing machine. The MSNCs exhibited a maximum adhesion energy of 13.7 ± 0.7 J/m2 at 3 wt %, surpassing that of MSNPs (10.9 ± 0.3 J/m2) at 2 wt %. Moreover, the unique stacking structure of the MSNCs enabled them to maintain an adhesion energy of 13.4 ± 1.0 J/m2 at a high concentration of 9 wt %, whereas the adhesion energy of MSNPs decreased to 8.2 ± 0.4 J/m2. This underscores their potential as superior hydrogel adhesives in challenging wet tissue-like environments.

On-chip selection of adenosine aptamer using graphene oxide-coated magnetic nanoparticles.

Systematic evolution of ligands by exponential enrichment (SELEX) is a method that is generally used for developing aptamers, which have arisen the promising alternatives for antibodies. However, conventional SELEX methods have limitations, such as a limited selection of target molecules, time-consuming and complex fabrication processes, and labor-intensive processes, which result in low selection yields. Here, we used (i) graphene oxide (GO)-coated magnetic nanoparticles in the selection process for separation and label-free detection and (ii) a multilayered microfluidic device manufactured using a three-dimensionally printed mold that is equipped with automated control valves to achieve precise fluid flows. The developed on-chip aptamer selection device and GO-coated magnetic nanoparticles were used to screen aptamer candidates for adenosine in eight cycles of the selection process within approximately 2 h for each cycle. Based on results from isothermal titration calorimetry, an aptamer with a dissociation constant of 18.6 ± 1.5 µM was selected. Therefore, the on-chip platform based on GO-coated magnetic nanoparticles provides a novel label-free screening technology for biosensors and micro/nanobiotechnology for achieving high-quality aptamers.

Statistical Characterization of the Morphologies of Nanoparticles through Machine Learning Based Electron Microscopy Image Analysis.

Although transmission electron microscopy (TEM) may be one of the most efficient techniques available for studying the morphological characteristics of nanoparticles, analyzing them quantitatively in a statistical manner is exceedingly difficult. Herein, we report a method for mass-throughput analysis of the morphologies of nanoparticles by applying a genetic algorithm to an image analysis technique. The proposed method enables the analysis of over 150,000 nanoparticles with a high precision of 99.75% and a low false discovery rate of 0.25%. Furthermore, we clustered nanoparticles with similar morphological shapes into several groups for diverse statistical analyses. We determined that at least 1,500 nanoparticles are necessary to represent the total population of nanoparticles at a 95% credible interval. In addition, the number of TEM measurements and the average number of nanoparticles in each TEM image should be considered to ensure a satisfactory representation of nanoparticles using TEM images. Moreover, the statistical distribution of polydisperse nanoparticles plays a key role in accurately estimating their optical properties. We expect this method to become a powerful tool and aid in expanding nanoparticle-related research into the statistical domain for use in big data analysis.

Revealing the Presence of a Symbolic Sequence Representing Multiple Nucleotides Based on K-Means Clustering of Oligonucleotides.

In biological systems, a few sequence differences diversify the hybridization profile of nucleotides and enable the quantitative control of cellular metabolism in a cooperative manner. In this respect, the information required for a better understanding may not be in each nucleotide sequence, but representative information contained among them. Existing methodologies for nucleotide sequence design have been optimized to track the function of the genetic molecule and predict interaction with others. However, there has been no attempt to extract new sequence information to represent their inheritance function. Here, we tried to conceptually reveal the presence of a representative sequence from groups of nucleotides. The combined application of the K-means clustering algorithm and the social network analysis theorem enabled the effective calculation of the representative sequence. First, a "common sequence" is made that has the highest hybridization property to analog sequences. Next, the sequence complementary to the common sequence is designated as a 'representative sequence'. Based on this, we obtained a representative sequence from multiple analog sequences that are 8⁻10-bases long. Their hybridization was empirically tested, which confirmed that the common sequence had the highest hybridization tendency, and the representative sequence better alignment with the analogs compared to a mere complementary.

From a precursor to an etchant: spontaneous inversion of the role of Au(iii) chloride for one-pot synthesis of smooth and spherical gold nanoparticles.

We report the inversion of the role of Au(iii) chloride, from a gold precursor to an etchant, for the synthesis of smooth and spherical AuNPs with nanoscale size tunability in a one-pot-system. Inversion of the role of Au(iii) chloride was achieved by regulating the ratio between the reducing agent and Au(iii) chloride.

Systematic study of interdependent relationship on gold nanorod synthesis assisted by electron microscopy image analysis.

Here, we systematically investigated the independent, multiple, and synergic effects of three major components, namely, ascorbic acid (AA), seed, and silver ions (Ag+), on the characteristics of gold nanorods (GNRs), i.e., longitudinal localized surface plasmon resonance (LSPR) peak position, shape, size, and monodispersity. To quantitatively assess the shape and dimensions of GNRs, we used an automated transmission electron microscopy image analysis method using a MATLAB-based code developed in-house and the concept of solidity, which is the ratio between the area of a GNR and the area of its convex hull. The solidity of a straight GNR is close to 1, while it decreases for both dumbbell- and dogbone-shaped GNRs. We found that the LSPR peak position, shape, and monodispersity of the GNRs all altered simultaneously with changes in the amounts of individual components. For example, as the amount of AA increased, both the LSPR peak and solidity decreased, while the polydispersity increased. In contrast, as the amount of seeds increased, both the LSPR and solidity increased, while the monodispersity improved. More importantly, we found that the influence of each component can actually change depending on the composition of the GNR growth solution. For instance, the LSPR peak position red-shifted as the amount of AA increased when the seed content was low, whereas it blue-shifted when the seed content was high.