Highly Bright Silica-Coated InP/ZnS Quantum Dot-Embedded Silica Nanoparticles as Biocompatible Nanoprobes.

Quantum dots (QDs) have outstanding optical properties such as strong fluorescence, excellent photostability, broad absorption spectra, and narrow emission bands, which make them useful for bioimaging. However, cadmium (Cd)-based QDs, which have been widely studied, have potential toxicity problems. Cd-free QDs have also been studied, but their weak photoluminescence (PL) intensity makes their practical use in bioimaging challenging. In this study, Cd-free QD nanoprobes for bioimaging were fabricated by densely embedding multiple indium phosphide/zinc sulfide (InP/ZnS) QDs onto silica templates and coating them with a silica shell. The fabricated silica-coated InP/ZnS QD-embedded silica nanoparticles (SiO2@InP QDs@SiO2 NPs) exhibited hydrophilic properties because of the surface silica shell. The quantum yield (QY), maximum emission peak wavelength, and full-width half-maximum (FWHM) of the final fabricated SiO2@InP QDs@SiO2 NPs were 6.61%, 527.01 nm, and 44.62 nm, respectively. Moreover, the brightness of the particles could be easily controlled by adjusting the amount of InP/ZnS QDs in the SiO2@InP QDs@SiO2 NPs. When SiO2@InP QDs@SiO2 NPs were administered to tumor syngeneic mice, the fluorescence signal was prominently detected in the tumor because of the preferential distribution of the SiO2@InP QDs@SiO2 NPs, demonstrating their applicability in bioimaging with NPs. Thus, SiO2@InP QDs@SiO2 NPs have the potential to successfully replace Cd-based QDs as highly bright and biocompatible fluorescent nanoprobes.

Au-Ag assembled on silica nanoprobes for visual semiquantitative detection of prostate-specific antigen.

BACKGROUND: Blood prostate-specific antigen (PSA) levels are widely used as diagnostic biomarkers for prostate cancer. Lateral-flow immunoassay (LFIA)-based PSA detection can overcome the limitations associated with other methods. LFIAbased PSA detection in clinical samples enables prognosis and early diagnosis owing to the use of high-performance signal reporters. RESULTS: Here, a semiquantitative LFIA platform for PSA detection in blood was developed using Au-Ag nanoparticles (NPs) assembled on silica NPs (SiO2@Au-Ag NPs) that served as signal reporters. Synthesized SiO2@Au-Ag NPs exhibited a high absorbance at a wide wavelength range (400-800 nm), with a high scattering on nitrocellulose membrane test strips. In LFIA, the color intensity of the test line on the test strip differed depending on the PSA concentration (0.30-10.00 ng/mL), and bands for the test line on the test strip could be used as a standard. When clinical samples were assessed using this LFIA, a visual test line with particular color intensity observed on the test strip enabled the early diagnosis and prognosis of patients with prostate cancer based on PSA detection. In addition, the relative standard deviation of reproducibility was 1.41%, indicating high reproducibility, and the signal reporter showed good stability for 10 days. CONCLUSION: These characteristics of the signal reporter demonstrated the reliability of the LFIA platform for PSA detection, suggesting potential applications in clinical sample analysis.

Silver-Assembled Silica Nanoparticles in Lateral Flow Immunoassay for Visual Inspection of Prostate-Specific Antigen.

Prostate-specific antigen (PSA) is the best-known biomarker for early diagnosis of prostate cancer. For prostate cancer in particular, the threshold level of PSA <4.0 ng/mL in clinical samples is an important indicator. Quick and easy visual detection of the PSA level greatly helps in early detection and treatment of prostate cancer and reducing mortality. In this study, we developed optimized silica-coated silver-assembled silica nanoparticles (SiO2@Ag@SiO2 NPs) that were applied to a visual lateral flow immunoassay (LFIA) platform for PSA detection. During synthesis, the ratio of silica NPs to silver nitrate changed, and as the synthesized NPs exhibited distinct UV spectra and colors, most optimized SiO2@Ag@SiO2 NPs showed the potential for early prostate cancer diagnosis. The PSA detection limit of our LFIA platform was 1.1 ng/mL. By applying each SiO2@Ag@SiO2 NP to the visual LFIA platform, optimized SiO2@Ag@SiO2 NPs were selected in the test strip, and clinical samples from prostate cancer patients were successfully detected as the boundaries of non-specific binding were clearly seen and the level of PSA was <4 ng/mL, thus providing an avenue for quick prostate cancer diagnosis and early treatment.

Facile Histamine Detection by Surface-Enhanced Raman Scattering using SiO2@Au@Ag Alloy Nanoparticles.

Histamine intoxication associated with seafood consumption represents a global health problem. The consumption of high concentrations of histamine can cause illnesses ranging from light symptoms, such as a prickling sensation, to death. In this study, gold-silver alloy-embedded silica (SiO2@Au@Ag) nanoparticles were created to detect histamine using surface-enhanced Raman scattering (SERS). The optimal histamine SERS signal was measured following incubation with 125 µg/mL of SiO2@Au@Ag for 2 h, with a material-to-histamine solution volume ratio of 1:5 and a phosphate-buffered saline-Tween 20 (PBS-T) solvent at pH 7. The SERS intensity of the histamine increased proportionally with the increase in histamine concentration in the range 0.1-0.8 mM, with a limit of detection of 3.698 ppm. Our findings demonstrate the applicability of SERS using nanomaterials for histamine detection. In addition, this study demonstrates that nanoalloys could have a broad application in the future.

DegPack: a web package using a non-parametric and information theoretic algorithm to identify differentially expressed genes in multiclass RNA-seq samples.

Gene expression in the whole cell can be routinely measured by microarray technologies or recently by using sequencing technologies. Using these technologies, identifying differentially expressed genes (DEGs) among multiple phenotypes is the very first step to understand difference between phenotypes. Thus many methods for detecting DEGs between two groups have been developed. For example, T-test and relative entropy are used for detecting difference between two probability distributions. When more than two phenotypes are considered, these methods are not applicable and other methods such as ANOVA F-test and Kruskal-Wallis are used for finding DEGs in the multiclass data. However, ANOVA F-test assumes a normal distribution and it is not designed to identify DEGs where genes are expressed distinctively in each of phenotypes. Kruskal-Wallis method, a non-parametric method, is more robust but sensitive to outliers. In this paper, we propose a non-parametric and information theoretical approach for identifying DEGs. Our method identified DEGs effectively and it is shown less sensitive to outliers in two data sets: a three-class drought resistant rice data set and a three-class breast cancer data set. In extensive experiments with simulated and real data, our method was shown to outperform existing tools in terms of accuracy of characterizing phenotypes using DEGs. A web service is implemented at http://biohealth.snu.ac.kr/software/degpack for the analysis of multi-class data and it includes SAMseq and PoissonSeq methods in addition to the method described in this paper.

GeneclusterViz: a tool for conserved gene cluster visualization, exploration and analysis.

MOTIVATION: Gene clusters are arrangements of functionally related genes on a chromosome. In bacteria, it is expected that evolutionary pressures would conserve these arrangements due to the functional advantages they provide. Visualization of conserved gene clusters across multiple genomes provides key insights into their evolutionary histories. Therefore, a software tool that enables visualization and functional analyses of gene clusters would be a great asset to the biological research community. RESULTS: We have developed GeneclusterViz, a Java-based tool that allows for the visualization, exploration and downstream analyses of conserved gene clusters across multiple genomes. GeneclusterViz combines an easy-to-use exploration interface for gene clusters with a host of other analysis features such as multiple sequence alignments, phylogenetic analyses and integration with the KEGG pathway database. AVAILABILITY: http://biohealth.snu.ac.kr/GeneclusterViz/; http://microbial.informatics.indiana.edu/GeneclusterViz/

Silica Encapsulation of Hydrophobic Optical NP-Embedded Silica Particles with Trimethoxy(2-Phenylethyl)silane.

Nanoparticles (NP) with optical properties embedded silica particles have been widely used in various fields because of their unique properties. The surfaces of optical NPs have been modified with various organic ligands to maintain their unique optical properties and colloidal stability. Among the surface modification methods, silica encapsulation of optical NPs is widely used to enhance their biocompatibility and stability. However, in the case of NPs with hydrophobic ligands on the surface, the ligands that determine the optical properties of the NPs may detach from the NPs, thereby changing the optical properties during silica encapsulation. Herein, we report a generally applicable silica encapsulation method using trimethoxy(2-phenylethyl)silane (TMPS) for non-hydrophilic optical NPs, such as quantum dots (QDs) and gold NPs. This silica encapsulation method was applied to fabricate multiple silica-encapsulated QD-embedded silica NPs (SiO2@QD@SiO2 NPs; QD2) and multiple silica-encapsulated gold NP-embedded silica NPs labeled with 2-naphthalene thiol (SiO2@Au2-NT@SiO2). The fabricated silica-encapsulated NPs exhibited optical properties without significant changes in the quantum yield or Raman signal intensity.

Enabling 100C Fast-Charging Bulk Bi Anodes for Na-Ion Batteries.

It is challenging to develop alloying anodes with ultrafast charging and large energy storage using bulk anode materials because of the difficulty of carrier-ion diffusion and fragmentation of the active electrode material. Herein, a rational strategy is reported to design bulk Bi anodes for Na-ion batteries that feature ultrafast charging, long cyclability, and large energy storage without using expensive nanomaterials and surface modifications. It is found that bulk Bi particles gradually transform into a porous nanostructure during cycling in a glyme-based electrolyte, whereas the resultant structure stores Na ions by forming phases with high Na diffusivity. These features allow the anodes to exhibit unprecedented electrochemical properties; the developed Na-Bi half-cell delivers 379 mA h g-1 (97% of that measured at 1C) at 7.7 A g-1 (20C) during 3500 cycles. It also retained 94% and 93% of the capacity measured at 1C even at extremely fast-charging rates of 80C and 100C, respectively. The structural origins of the measured properties are verified by experiments and first-principles calculations. The findings of this study not only broaden understanding of the underlying mechanisms of fast-charging anodes, but also provide basic guidelines for searching battery anodes that simultaneously exhibit high capacities, fast kinetics, and long cycling stabilities.

Multi-Quantum Dots-Embedded Silica-Encapsulated Nanoparticle-Based Lateral Flow Assay for Highly Sensitive Exosome Detection.

Exosomes are attracting attention as new biomarkers for monitoring the diagnosis and prognosis of certain diseases. Colorimetric-based lateral-flow assays have been previously used to detect exosomes, but these have the disadvantage of a high limit of detection. Here, we introduce a new technique to improve exosome detection. In our approach, highly bright multi-quantum dots embedded in silica-encapsulated nanoparticles (M-QD-SNs), which have uniform size and are brighter than single quantum dots, were applied to the lateral flow immunoassay method to sensitively detect exosomes. Anti-CD63 antibodies were introduced on the surface of the M-QD-SNs, and a lateral flow immunoassay with the M-QD-SNs was conducted to detect human foreskin fibroblast (HFF) exosomes. Exosome samples included a wide range of concentrations from 100 to 1000 exosomes/µL, and the detection limit of our newly designed system was 117.94 exosome/µL, which was 11 times lower than the previously reported limits. Additionally, exosomes were selectively detected relative to the negative controls, liposomes, and newborn calf serum, confirming that this method prevented non-specific binding. Thus, our study demonstrates that highly sensitive and quantitative exosome detection can be conducted quickly and accurately by using lateral immunochromatographic analysis with M-QD-SNs.

Lateral Flow Immunoassay with Quantum-Dot-Embedded Silica Nanoparticles for Prostate-Specific Antigen Detection.

Prostate cancer can be detected early by testing the presence of prostate-specific antigen (PSA) in the blood. Lateral flow immunoassay (LFIA) has been used because it is cost effective and easy to use and also has a rapid sample-to-answer process. Quantum dots (QDs) with very bright fluorescence have been previously used to improve the detection sensitivity of LFIAs. In the current study, a highly sensitive LFIA kit was devised using QD-embedded silica nanoparticles. In the present study, only a smartphone and a computer software program, ImageJ, were used, because the developed system had high sensitivity by using very bright nanoprobes. The limit of PSA detection of the developed LFIA system was 0.138 ng/mL. The area under the curve of this system was calculated as 0.852. The system did not show any false-negative result when 47 human serum samples were analyzed; it only detected PSA and did not detect alpha-fetoprotein and newborn calf serum in the samples. Additionally, fluorescence was maintained on the strip for 10 d after the test. With its high sensitivity and convenience, the devised LFIA kit can be used for the diagnosis of prostate cancer.

Silica-Coated Magnetic Iron Oxide Nanoparticles Grafted onto Graphene Oxide for Protein Isolation.

In this study, silica-coated magnetic iron oxide nanoparticles (MNPs@SiO2) were covalently conjugated onto graphene oxide (GO/MNP@SiO2) for protein isolation. First, MNPs were precisely coated with a silica layer on the surface by using the reverse microemulsion method, followed by incubation with 3-glycidyloxypropyltrimethoxysilane (GPTS) to produce the GPTS-functionalized MNPs@SiO2 (GPTS-coated MNPs@SiO2) that display epoxy groups on the surface. The silica shell on the MNPs was optimized at 300 µL of Igepal®CO-520, 5 mg of MNP, 100 µL of TEOS, 100 µL of NH4OH and 3% of 3-glycidyloxypropyltrimethoxysilane (GPTS). Simultaneously, polyethyleneimine (PEI) was covalently conjugated to GO to enhance the stability of GO in aqueous solutions and create the reaction sites with epoxy groups on the surface of GPTS-coated MNP@SiO2. The ratio of PEI grafted GO and GPTS-coated MNP@SiO2 (GO/MNP ratio) was investigated to produce GO/MNPs@SiO2 with highly saturated magnetization without aggregation. As a result, the GO/MNP ratio of 5 was the best condition to produce the GO/MNP@SiO2 with 9.53 emu/g of saturation superparamagnetization at a magnetic field of 2.0 (T). Finally, the GO/MNPs@SiO2 were used to separate bovine serum albumin (BSA) to investigate its protein isolation ability. The quantity of BSA adsorbed onto 1 mg of GO/MNP@SiO2 increased sharply over time to reach 628 ± 9.3 µg/mg after 15 min, which was 3.5-fold-higher than that of GPTS-coated MNP@SiO2. This result suggests that the GO/MNP@SiO2 nanostructure can be used for protein isolation.

Genome-wide analysis and modeling of DNA methylation susceptibility in 30 breast cancer cell lines by using CpG flanking sequences.

DNA methylation is an epigenetic modification of DNA that adds a methyl group to cytosine. Aberrant DNA methylation in the CpG context is frequently observed in cancer cells and it is known that aberrant DNA methylation silences tumor repressor genes. However, the mechanism of DNA methylation is not well understood. A widely accepted hypothesis is that DNA methylation does not randomly occur and may be controlled by some instructive mechanisms. In this paper, we conducted an extensive study on this important question by using proprietary sequencing data from methyl-binding domain protein (MBD)-Cap ChIP sequencing experiments for 30 breast cancer cell lines. The goal of our study is to investigate difference in nucleotide composition around CpG sites, where high levels of methylation are observed, and use the information for modeling DNA methylation susceptibility. First, we observed that DNA methylation is not uniform in the whole-genome region and also that the character composition of CpG flanking sequences are significantly different between hyper- and hypo-methylated groups. In an in-depth study, we used information theoretic approaches such as entropy and relative entropy to delineate character composition features and found enrichment of A (Adenine) and T (Thymine) in specific positions around hyper-methylated sites. As the methylation level is increased, A, T proportions in specific positions around hypermethylated sites are increased while A, T proportions in other positions around hypermethylated sites are decreased. Second, we built predictive models for methylation susceptibility by using characters flanking CpG sites as features and hyper-/hypo-methylation status as class. Third, we constructed predictive models using a log odds score of two profiles from DNA sequences surrounding CpG sites of hyper- and hypo-methylated groups. This analysis showed that distribution of profile scores of hyper-/hypo-methylated sites sequences is quite distinct. Our genome-wide CpG methylation study shows that nucleotides around CpG sites caries information for cytosine methylation. This is consistent with the seminal work on the instructive evidence of DNA methylation by Keshet et al. (Nature Genetics, 38(2), 149-153 2006). Our study is on the full genome scale and used the sequencing data, thus our study is significantly different in terms of resolution of data and analysis methods used for the study by Keshet et al.