Effect of Dentin Desensitizer Containing Novel Bioactive Glass on the Permeability of Dentin.

The objective of this study was to evaluate the effect of novel bioactive glass (BAG)-containing desensitizers on the permeability of dentin. Experimental dentin desensitizers containing 3 wt% BAG with or without acidic functional monomers (10-MDP or 4-META) were prepared. A commercial desensitizer, Seal & Protect (SNP), was used as a control. To evaluate the permeability of dentin, real-time dentinal fluid flow (DFF) rates were measured at four different time points (demineralized, immediately after desensitizer application, after two weeks in simulated body fluid (SBF), and post-ultrasonication). The DFF reduction rate (ΔDFF) was also calculated. The surface changes were analyzed using field emission scanning electron microscopy (FE-SEM). Raman spectroscopy was performed to analyze chemical changes on the dentin surface. The ΔDFF of the desensitizers containing BAG, BAG with 10-MDP, and BAG with 4-META significantly increased after two weeks of SBF storage and post-ultrasonication compared to the SNP at each time point (p < 0.05). Multiple precipitates were observed on the surfaces of the three BAG-containing desensitizers. Raman spectroscopy revealed hydroxyapatite (HAp) peaks on the dentin surfaces treated with the three BAG-containing desensitizers. Novel BAG-containing dentin desensitizers can reduce the DFF rate about 70.84 to 77.09% in the aspect of reduction of DFF through the HAp precipitations after two weeks of SBF storage.

Adiponectin-targeted SERS immunoassay biosensing platform for early detection of gestational diabetes mellitus.

The anisotropic gold nanotriangles (AuNTs) were synthesized by a fast seedless growth process. The high-yield monodispersed AuNT colloids were obtained through a purification process based on depletion-induced interactions. AuNTs were modulated with a localized surface plasmon resonance (LSPR) peak of 638 nm wavelength coherent with the Raman excitation light. However, from finite element computation results, the AuNT clusters showed better performance for the 785 nm laser source due to a red shift in their LSPR properties, hence it was selected for the surface-enhanced Raman scattering (SERS) immunoassay. A self-assembly strategy using a thiol group and ON-OFF strategy in the heat map was performed to ensure the stability of SERS immunoassay platform. The sandwich SERS immunoassay biosensor platform for adiponectin detection demonstrated a wide assay range (10-15-10-6 g/mL), good reliability (R2 = 0.994, clinically relevant range), femto-scale limit of detection (3.0 × 10-16 g/mL), and excellent selectivity without interference from other biomarkers. This showed the possibility of effectively detecting adiponectin levels in the biofluids of pregnant women. Therefore, our technology is the first to quantitatively detect adiponectin based on SERS technology for early detection of gestational diabetes mellitus and has the potential to be used as a clinical biosensor capable of diagnosing various obstetric diseases during early pregnancy.

An excitation wavelength-optimized, stable SERS biosensing nanoplatform for analyzing adenoviral and AstraZeneca COVID-19 vaccination efficacy status using tear samples of vaccinated individuals.

We introduce a label-free surface-enhanced Raman scattering (SERS) biosensing platform equipped with metallic nanostructures that can identify the efficacy of Oxford-AstraZeneca (AZD1222) vaccine in vaccinated individuals using non-invasive tear samples. We confirmed the hypothesis that the tears of people who receive the AZD1222 vaccine may be similar to those of adenovirus epidemic keratoconjunctivitis patients since the Oxford-AstraZeneca vaccine is derived from a replication-deficient ChAdOx1 vector of chimpanzee adenovirus. Additionally, we confirmed the potential of the three markers for estimating the vaccination status via analyzing the signals emanating from antibodies or immunoglobulin G by-product using our label-free, SERS biosensing technique with a high reproducibility (<3% relative standard deviation), femtomole-scale limit of detection (1 × 10-14 M), and high SERS response of >108. Therefore, our label-free SERS biosensing nanoplatforms with long-term storage and robust stability will enable rapid and robust monitoring of the vaccine presence in vaccinated individuals.

Effect of Novel Bioactive Glass-Containing Dentin Adhesive on the Permeability of Demineralized Dentin.

This study aimed to evaluate the effect of a novel bioactive glass (BAG)-containing dentin adhesive on the permeability of demineralized dentin. Bioactive glass (85% SiO2, 15% CaO) was fabricated using the sol-gel process, and two experimental dentin adhesives were prepared with 3 wt% silica (silica-containing dentin adhesive; SCA) or BAG (BAG-containing dentin adhesive; BCA). Micro-tensile bond strength (µTBS) test, fracture mode analysis, field-emission scanning electron microscopy (FE-SEM) analysis of adhesive and demineralized dentin, real-time dentinal fluid flow (DFF) rate measurement, and Raman confocal microscopy were performed to compare SCA and BCA. There was no difference in µTBS between the SCA and BCA (p > 0.05). Multiple precipitates were evident on the surface of the BCA, and partial occlusion of dentinal tubules was observed in FE-SEM of BCA-approximated dentin. The DFF rate was reduced by 50.10% after BCA approximation and increased by 6.54% after SCA approximation. Raman confocal spectroscopy revealed an increased intensity of the hydroxyapatite (HA) peak on the dentin surface after BCA application. The novel BAG-containing dentin adhesive showed the potential of both reducing dentin permeability and dentin remineralization.

Label-free breast cancer detection using fiber probe-based Raman spectrochemical biomarker-dominated profiles extracted from a mixture analysis algorithm.

We report the development of a label-free, simple, and high efficiency breast cancer detection platform with multimodal biomarker analytic algorithms on a portable 785 nm Raman setup with an endoscopic Raman-lensed fiber optic probe. We propose a multimodal biomarker extraction algorithm (PCMA) implemented by combining a multivariate statistics principal component analysis (PCA) algorithm and a multivariate curve resolution-alternating least squares (MCR-ALS) computational model for extraction of the biomarker information hidden in Raman spectrochemical data. We show that the six Raman spectrochemical peaks at 1009, 1270, 1305/1443, 1658, and 1750 cm-1 assigned to phenylalanine, amide III in proteins, CH2 deformation in lipids, amide I in proteins, and carbonyl, respectively, can be used as a biomarker for breast cancer diagnosis using the biomarker-dominated PCMA spectrochemical spectra of breast tissues. From 20 human breast tissues, the PCMA-linear discriminant analysis (PCMA-LDA) identification method achieved high classification performance with a sensitivity and specificity >99% along with an improvement of approximately 4.5% compared to the performance without the PCMA mixture analysis algorithm. Our label-free breast cancer detection method has the potential for clinical application to diagnose breast cancer in real-time during surgery.

Wavelength-dependent label-free identification of isolated nontuberculous mycobacteria using surface-enhanced Raman spectroscopy.

We investigated the effect of Raman excitation wavelengths on the surface-enhanced Raman spectroscopy (SERS)-based identification of isolated nontuberculous mycobacteria (NTM). The SERS spectra with 3 commonly used excitation wavelengths, 532, 638, and 785 nm, were compared across 6 representative NTM species that primarily cause human NTM infections in Korea and the United States; these species were identified. The statistical differences among NTM SERS spectra at each Raman excitation wavelength were verified using 1-way analysis of variance, and the 6 NTM species were identified using principal components-linear discriminant analysis with leave-one-out cross validation. The identification accuracies with aromatic amino acid biomarkers were 99.3%, 91.3%, and 90.7% for 532, 638, and 785 nm, respectively. We believe that the proposed SERS protocol with aromatic amino acid biomarkers at the 532-nm Raman excitation wavelength will enable fast and accurate identification of NTM compared to previous identification methods.

Label-Free Surface-Enhanced Raman Spectroscopy Biosensor for On-Site Breast Cancer Detection Using Human Tears.

Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.