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.

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.

Oxidation of DJ-1-dependent cell transformation through direct binding of DJ-1 to PTEN.

DJ-1 is an oncogene and also a causative gene for a familial form of Parkinson's disease. DJ-1 has multiple functions, including anti-oxidative stress reaction and cysteine 106 (C106) of DJ-1 is an essential amino acid for DJ-1 to exert its function. While increased expression and secretion of DJ-1 into serum in patients with various cancers and regulation of p53 and PTEN by DJ-1 have been reported, the molecular mechanism underlying oncogenicity of DJ-1 is poorly understood. Here, we analyzed the function of DJ-1 in the PI3'K signaling pathway under an oxidative stress condition, focusing on the interaction of DJ-1 with PTEN. We found that both wild-type (wt) and C106S-DJ-1, a substitution mutant of DJ-1, directly bound to PTEN and inhibited PTEN phosphatase activity but that C106S-DJ-1 more strongly inhibited the activity than did wt-DJ-1. When NIH3T3 cells were treated with H2O2, oxidation of C106 of wt-DJ-1 occurred, accompanied by increased binding of wt-DJ-1 to PTEN, decreased PTEN activity and increased phosphorylation of AKT. C106S-DJ-1 transformed cells more strongly than did wt-DJ-1 and the transforming activity of DJ-1 was enhanced by H2O2 treatment of cells in which increased binding of DJ-1 to PTEN and decreased PTEN activity were observed. Furthermore, TOF-MS analysis of the oxidative status of C106 suggested that DJ-1 activity requires the presence of the reduced form of C106, which accounts for >50% of the total form. These results suggest that the oxidative status of DJ-1 regulates PTEN activity, leading to cell proliferation and transformation.

DJ-1 binds to mitochondrial complex I and maintains its activity.

Parkinson's disease (PD) is caused by neuronal cell death, and oxidative stress and mitochondrial dysfunction are thought to be responsible for onset of PD. DJ-1, a causative gene product of a familial form of Parkinson's disease, PARK7, plays roles in transcriptional regulation and anti-oxidative stress. The possible mitochondrial function of DJ-1 has been proposed, but its exact function remains unclear. In this study, we found that DJ-1 directly bound to NDUFA4 and ND1, nuclear and mitochondrial DNA-encoding subunits of mitochondrial complex I, respectively, and was colocalized with complex I and that complex I activity was reduced in DJ-1-knockdown NIH3T3 and HEK293 cells. These findings suggest that DJ-1 is an integral mitochondrial protein and that DJ-1 plays a role in maintenance of mitochondrial complex I activity.

Kaempferol derivatives prevent oxidative stress-induced cell death in a DJ-1-dependent manner.

DJ-1, a causative gene product of a familial form of Parkinson's disease (PD), PARK7, plays a role in anti-oxidative stress, and loss of its function is thought to result in the onset of PD. Superfluous oxidation of cysteine at amino acid 106 (C106) of DJ-1 renders DJ-1 inactive, and such oxidized DJ-1 was observed in patients with the sporadic form of PD. In this study, we examined the relationship between DJ-1 and compounds extracted from traditional Chinese medicines possessing anti-oxidant activity. Of the 12 compounds tested, 5 were found to specifically bind to the C106 region by using a quartz crystal microbalance. Although 4 compounds prevented rat PC12 and primary neuronal cells from undergoing H2O2-induced cell death, the protective activity of 2 compounds, kaempferol 3-O-beta-rutinoside and 6-hydroxykaempferol 3,6-di-O-beta-D-glucoside, was diminished in cells transfected with siRNA targeting DJ-1, indicating DJ-1-dependent reaction of these compounds. Furthermore, these compounds reduced the level of reactive oxygen species and restored tyrosine hydroxylase activity that had been induced and compromised, respectively, by treatment of cells with H2O2. The results suggest that these compounds are useful lead compounds for PD therapy.