Surface-enhanced Raman scattering detection of lysophosphatidic acid

Coordination-assembled phosphorescent microstructure from RTP HOF and Eu3+-doping ZGO:Mn phosphors for cancer biomarker amplification detection and information encryption

The ultra-long room temperature phosphorescent hydrogen-bonded organic framework (RTP HOF) materials can achieve long afterglow via ligand hydrogen bond interaction and water implement to suppress the non-radiative decays by matrices rigidification, and its electron donor conjugated structure is first developed as a phosphorescent quencher. The Eu3+/Mn2+ co-doped Zn2GeO4 phosphors (ZGO:Mn, Eu) with abundant metal sites and enhanced phosphorescence were synthesized as response factors and electron acceptors, combined with RTP HOFs to form microstructures featuring multi-color modulation, as an high-level anti-counterfeiting platform and lysophosphatidic acid (LPA) detection unit. LPA is an ideal plasma biomarker for early diagnosis of ovarian and other gynecologic cancers. This detection strategy relies on the differential coordination substitution to restore ZGO:Mn, Eu phosphorescence through synergistic coordination of LPA and the hydrophobic assistance of LPA, and dual functional groups identification of LPA achieve specific detection at the nanomolar level. The anti-counterfeiting platform can fetch specific information by controlling the afterglow distinction and excited light from ZGO:Mn, Eu and RTP HOF. This study not only provides a typical case of the preparation of two phosphors with heterogeneous optical properties, but also expands the application field of combined phosphors as intelligent luminescent materials.

Spectroscopic evaluation of carcinogenesis in endometrial cancer

Carcinogenesis is a multifaceted process of cancer formation. The transformation of normal cells into cancerous ones may be difficult to determine at a very early stage. Therefore, methods enabling identification of initial changes caused by cancer require novel approaches. Although physical spectroscopic methods such as FT-Raman and Fourier Transform InfraRed (FTIR) are used to detect chemical changes in cancer tissues, their potential has not been investigated with respect to carcinogenesis. The study aimed to evaluate the usefulness of FT-Raman and FTIR spectroscopy as diagnostic methods of endometrial cancer carcinogenesis. The results indicated development of endometrial cancer was accompanied with chemical changes in nucleic acid, amide I and lipids in Raman spectra. FTIR spectra showed that tissues with development of carcinogenesis were characterized by changes in carbohydrates and amides vibrations. Principal component analysis and hierarchical cluster analysis of Raman spectra demonstrated similarity of tissues with cancer cells and lesions considered precursor of cancer (complex atypical hyperplasia), however they differed from the control samples. Pearson correlation test showed correlation between cancer and complex atypical hyperplasia tissues and between non-cancerous tissue samples. The results of the study indicate that Raman spectroscopy is more effective in assessing the development of carcinogenesis in endometrial cancer than FTIR.

Analysis and Classification of Hepatitis Infections Using Raman Spectroscopy and Multiscale Convolutional Neural Networks

Hepatitis infections represent a major health concern worldwide. Numerous computer-aided approaches have been devised for the early detection of hepatitis. In this study, we propose a method for the analysis and classification of cases of hepatitis-B virus ( HBV), hepatitis-C virus (HCV), and healthy subjects using Raman spectroscopy and a multiscale convolutional neural network (MSCNN). In particular, serum samples of HBV-infected patients (435 cases), HCV-infected patients (374 cases), and healthy persons (499 cases) are analyzed via Raman spectroscopy. The differences between Raman peaks in the measured serum spectra indicate specific biomolecular differences among the three classes. The dimensionality of the spectral data is reduced through principal component analysis. Subsequently, features are extracted, and then feature normalization is applied. Next, the extracted features are used to train different classifiers, namely MSCNN, a single-scale convolutional neural network, and other traditional classifiers. Among these classifiers, the MSCNN model achieved the best outcomes with a precision of 98.89%, sensitivity of 97.44%, specificity of 94.54%, and accuracy of 94.92%. Overall, the results demonstrate that Raman spectral analysis and MSCNN can be effectively utilized for rapid screening of hepatitis B and C cases.

Recent advances in nanomaterial-based biosensors for the detection of exosomes

Exosomes are a type of extracellular vesicle actively secreted by almost all eukaryotic cells. They are ideal candidates for reliable next-generation biomarkers in the early diagnosis and therapeutic response evaluation of cancer. Thus, the quantification of exosomes is crucial in facilitating clinical research and application. Compared with traditional materials, nanomaterials have better optical, magnetic, electrical, and catalytic properties due to their small size, high specific surface area, and variable structure. The incorporation of nanomaterials into sensing systems is an attractive approach towards improving sensitivity and can provide improved sensor selectivity and stability. In this paper, we summarize the progress in nanomaterial-based exosome detection methods, including electrochemical biosensors, photoelectrochemical biosensors, colorimetric biosensors, fluorescence biosensors, chemiluminescence biosensors, electrochemiluminescence biosensors, surface plasmon resonance biosensors, and surface-enhanced Raman spectroscopy biosensors. Moreover, future research directions and challenges in exosome detection methods are discussed. We hope that this article will offer an overview of nanomaterial-based exosome detection techniques and open new avenues in disease research.Graphical abstract.

Dually Crosslinked Supramolecular Hydrogel for Cancer Biomarker Sensing

Lysophosphatidic acid (LPA) as the biomarker of early stage ovarian cancer is essentially difficult to detect due to lack of target spots. A dually crosslinked supramolecular hydrogel (DCSH) was developed to achieve sensing of LPA, which acts as a competitive guest molecule triggering the responsive crosslinking of the DCSH. Through this strategy, the surface plasmon resonance combined with optical waveguide spectroscopy could be used to quantitatively detect LPA with a responsive range covering physiological conditions (in pure form as well as mimicking LPA plasma solution) with high selectivity and sensitivity. LPA efficiently immerses into the host molecule β-cyclodextrin (β-CD) up to a 1:2 ratio by the competitive interaction mechanism, confirmed by one-dimensional nuclear overhauser effect spectroscopy (1D NOESY), high-resolution mass spectrometry (HRMS), isothermal titration calorimetry (ITC), and computational simulation. Our method opens a new strategy to detect biomarkers without target spots and provides a platform for surface plasmon resonance (SPR)-based sensors measuring small molecules.

Simultaneous FTIR and Raman Spectroscopy in Endometrial Atypical Hyperplasia and Cancer

Currently, endometrial carcinoma (EC) is the most common genital cancer in high-income countries. Some types of endometrial hyperplasia (EH) may be progressing to this malignancy. The diagnosis of EC and EH is based on time consuming histopathology evaluation, which is subjective and causes discrepancies in reassessment. Therefore, there is a need to create methods of objective evaluation allowing the diagnosis of early changes. The study aimed to simultaneously asses Fourier Transform Infrared (FTIR) and Raman spectroscopy combined with multidimensional analysis to identify the tissues of endometrial cancer, atypical hyperplasia and the normal control group, and differentiate them. The results of FTIR and Raman spectroscopy revealed quantitative and qualitative changes in the nucleic acid and protein in the groups of cancer and atypical hyperplasia, in comparison with the control group. Changes in the lipid region were also observed in Raman spectra. Pearson correlation coefficient demonstrated a statistically significant correlation between Raman spectra for the cancer and atypical hyperplasia groups (0.747, p < 0.05) and for atypical hyperplasia and the controls (0.507, p < 0.05), while FTIR spectra demonstrated a statistically significant positive correlation for the same group as in Raman data and for the control and cancer groups (0.966, p < 0.05). To summarize, the method of spectroscopy enables differentiation of atypical hyperplasia and endometrial cancer tissues from the physiological endometrial tissue.

Application of Raman spectroscopy in the detection of hepatitis B virus infection

OBJECTIVE

Detection of hepatitis B virus (HBV) using Raman spectroscopy.

METHODS

Raman spectroscopy was used to examine the serum samples of 500 patients with HBV and 500 non-HBV persons. First, the adaptive iterative weighted penalty least squares method (airPLS) was used to deduct the fluorescence background in Raman spectra. Then, a principal component analysis (PCA) was used to extract the processed Raman spectra, and a support vector machine (SVM) was used for modeling and prediction. The particle swarm optimization (PSO) algorithm was selected to optimize the parameters of the SVM instead of a traditional grid search. Finally, 600 serum samples were detected by Raman spectroscopy, and the results wereverified using a double-blind method.

RESULTS

In the Raman spectra, the non-HBV human Raman peaks at 509, 957, 1002, 1153, 1260, 1512, 1648 and 2305 cm^-1 were different from those of patients with HBV. The reported accuracy, sensitivity and specificity of the HBV serum model established using airPLS-PCA-PSO-SVM was 93.1%, 100% and 88%, respectively. The two groups were verified by a double-blind method. In the first group sensitivity was 87%, specificity was 92%, and the KAPPA value was 0.79; in the second group sensitivity was 80%, specificity was 79%, and the KAPPA value was 0.59.

CONCLUSION

This preliminary study shows that serum Raman spectroscopy combined with the airPLS-PCA-PSO-SVM model can be used for hepatitis B virus detection.

Exosome Classification by Pattern Analysis of Surface-Enhanced Raman Spectroscopy Data for Lung Cancer Diagnosis

Owing to the role of exosome as a cargo for intercellular communication, especially in cancer metastasis, the evidence has been consistently accumulated that exosomes can be used as a noninvasive indicator of cancer. Consequently, several studies applying exosome have been proposed for cancer diagnostic methods such as ELISA assay. However, it has been still challenging to get reliable results due to the requirement of a labeling process and high concentration of exosome. Here, we demonstrate a label-free and highly sensitive classification method of exosome by combining surface-enhanced Raman scattering (SERS) and statistical pattern analysis. Unlike the conventional method to read different peak positions and amplitudes of a spectrum, whole SERS spectra of exosomes were analyzed by principal component analysis (PCA). By employing this pattern analysis, lung cancer cell derived exosomes were clearly distinguished from normal cell derived exosomes by 95.3% sensitivity and 97.3% specificity. Moreover, by analyzing the PCA result, we could suggest that this difference was induced by 11 different points in SERS signals from lung cancer cell derived exosomes. This result paved the way for new real-time diagnosis and classification of lung cancer by using exosome as a cancer marker.

Near-Infrared Fluorogenic Probes with Polarity-Sensitive Emission for in Vivo Imaging of an Ovarian Cancer Biomarker

Lysophosphatidic acid (LPA, cutoff values ≥ 1.5 μM) is an effective biomarker for early stage ovarian cancer. The development of selective probes for LPA detection is therefore critical for early clinical diagnosis. Although current methods have been developed for the detection of LPA in solution, they cannot be used for tracking LPA in vivo. Here, we report a near-infrared (NIR) fluorescent probe that can selectively respond to LPA based on polarity-sensitive emission at a very low detection limit of 0.5 μM in situ. This probe exhibits a marked increase of fluorescence at 720 nm upon binding to LPA, allowing the direct visualization of LPA in vitro and in vivo without interference from other biomolecules. Moreover, the probe containing two arginine-glycine-aspartic acid units can be efficiently taken up by cancer cells based on an αvβ3 integrin receptor targeting mechanism. It also exhibits excellent biocompatibility and high pH stability in live cells and in vivo. Confocal laser scanning microscopy and flow cytometric imaging of SKOV-3 cells have confirmed that our probe can be used to image LPA in live cells. In particular, its NIR turn-on fluorescence can be used to effectively monitor LPA imaging in a SKOV-3 tumor-bearing mouse model. Our probe may pave the way for the detection of cancer-related biomarkers and even for early stage cancer diagnosis.

Silver nanopartical over AuFON substrate for enhanced raman readout and their application in pesticide monitoring

Surface-enhanced Raman detection of thiram is demonstrated by using Ag-nanoparticles (Ag NPs) on Au film over nanosphere (AuFON) substrate as the hybrid substrate. The SERS signal of the Ag NPs attached to solid supports is studied. The close coupling together of thousands of Ag NPs on AuFON leads to the generation of hot spots for SERS. The Ag NPs on AuFON can be applied to detect rhodamine-6G (R6G) with the detection limitation of 10⁻¹¹ M and the pesticide thiram in acetone with a detection limit of as low as 0.24 ppm, which is much lower than the maximal residue limit (MRL) of 7 ppm in fruit prescribed by the U.S. Environmental Protection Agency (EPA). The hybrid substrates are shown to be highly sensitive for the detection of thriam, which produce highly enhanced Raman signals with good uniformity and reproducibility due to having plenty of hot spots on its surface.

Intracellular SERS nanoprobes for distinction of different neuronal cell types

Distinction between closely related and morphologically similar cells is difficult by conventional methods especially without labeling. Using nuclear-targeted gold nanoparticles (AuNPs) as intracellular probes we demonstrate the ability to distinguish between progenitor and differentiated cell types in a human neuroblastoma cell line using surface-enhanced Raman spectroscopy (SERS). SERS spectra from the whole cell area as well as only the nucleus were analyzed using principal component analysis that allowed unambiguous distinction of the different cell types. SERS spectra from the nuclear region showed the developments during cellular differentiation by identifying an increase in DNA/RNA ratio and proteins transcribed. Our approach using nuclear-targeted AuNPs and SERS imaging provides label-free and noninvasive characterization that can play a vital role in identifying cell types in biomedical stem cell research.

Full range characterization of the Raman spectra of organs in a murine model

Raman spectroscopy is a minimally-invasive optical technique with great potential for in vivo cancer detection and disease diagnosis. However, there is no systematic study of the Raman spectra from different organs to date. We measured and characterized the Raman spectra eighteen naïve mouse organs in a broad frequency range of 700 to 3100 cm⁻¹. The peaks of generic proteins and lipids appeared in Raman spectra of all organs. Some organs like bone, teeth, brain and lung had unique Raman peaks. The autofluorescence was strong in liver, spleen, heart, and kidney. These results suggest that organ specific Raman probe design and specific data processing strategies are required in order to get the most useful information.

Emerging nanoproteomics approaches for disease biomarker detection: a current perspective

Availability of genome sequence of human and different pathogens has advanced proteomics research for various clinical applications. One of the prime goals of proteomics is identification and characterization of biomarkers for cancer and other fatal human diseases to aid an early diagnosis and monitor disease progression. However, rapid detection of low abundance biomarkers from the complex biological samples under clinically relevant conditions is extremely difficult, and it requires the development of ultrasensitive, robust and high-throughput technological platform. In order to overcome several technical limitations associated with sensitivity, dynamic range, detection time and multiplexing, proteomics has started integrating several emerging disciplines such as nanotechnology, which has led to the development of a novel analytical platform known as 'nanoproteomics'. Among the diverse classes of nanomaterials, the quantum dots, gold nanoparticles, carbon nanotubes and silicon nanowires are the most promising candidates for diagnostic applications. Nanoproteomics offers several advantages such as ultralow detection, short assay time, high-throughput capability and low sample consumption. In this article, we have discussed the application of nanoproteomics for biomarker discovery in various diseases with special emphasis on various types of cancer. Furthermore, we have discussed the prospects, merits and limitations of nanoproteomics.

Surface-enhanced Raman scattering biomedical applications of plasmonic colloidal particles

This review article presents a general view of the recent progress in the fast developing area of surface-enhanced Raman scattering spectroscopy as an analytical tool for the detection and identification of molecular species in very small concentrations, with a particular focus on potential applications in the biomedical area. We start with a brief overview of the relevant concepts related to the choice of plasmonic nanostructures for the design of suitable substrates, their implementation into more complex materials that allow generalization of the method and detection of a wide variety of (bio)molecules and the strategies that can be used for both direct and indirect sensing. In relation to indirect sensing, we devote the final section to a description of SERS-encoded particles, which have found wide application in biomedicine (among other fields), since they are expected to face challenges such as multiplexing and high-throughput screening.

Surface-enhanced Raman scattering of rat tissues

Surface-enhanced Raman scattering (SERS) is proven to be a powerful tool for investigation of biological structures. In this study, tissues obtained from different rat organs are examined using SERS. The tissue samples are crushed with a pestle after sudden freezing in liquid nitrogen and mixed with a concentrated colloidal silver nanoparticle suspension. The reproducibility of SERS spectra acquired from several tissue samples from different organs is demonstrated. The collected spectra are comparatively evaluated based on the physiological function of the organ from which the tissue is obtained. The spectra from the tissues show significant differences and indicate that they can be used for tissue characterization and differentiation. The identification of the origins of the bands on the spectra is also attempted. This study suggests that SERS can be used to monitor the changes at the molecular level during metabolic changes in an organ or tissue as a result of a disease or another cause.

Gold nanoparticles: interesting optical properties and recent applications in cancer diagnostics and therapy

Recent years have seen tremendous progress in the design and study of nanomaterials geared towards biological and biomedical applications, most notable among these being the noble metal nanoparticles. In this review, we outline the surface-plasmon resonance-enhanced optical properties of colloidal gold nanoparticles directed towards recent biomedical applications with an emphasis on cancer diagnostics and therapeutics. Methods of molecular-specific diagnostics/detection of cancer, including strongly enhanced surface plasmon resonance light-scattering, surface-enhanced emission of gold nanorods and surface-enhanced Raman scattering, are described. We also discuss the plasmonic photothermal therapy of cancer achieved by using the strongly enhanced surface-plasmon resonance absorption of gold nanospheres and nanorods.

An optofluidic device for surface enhanced Raman spectroscopy

We have developed an optofluidic device that improves the sensitivity of surface enhanced Raman spectroscopy (SERS) when compared to other SERS approaches. This device has a pinched and step microchannel-nanochannel junction that can trap and assemble nanoparticles/target molecules into optically enhanced SERS active clusters by using capillary force. These SERS active clusters provide an electromagnetic enhancement factor of approximately 10(8). In addition, due to the continuous capillary flow that can transport nanoparticles/target molecules into the junction sites, the numbers of nanoparticles/target molecules and SERS active sites are increased. As a result, the detection limit of SERS for adenine molecules was better than 10 pM.

Effects of chromophore orientation and molecule conformation on surface-enhanced Raman scattering studied with alkanoic acids and colloidal silver nanoparticles

Experimental studies have been carried out to gain a better understanding of the effects of chromophore orientation and molecular conformation on surface-enhanced Raman scattering (SERS) based on metal nanostructures. A series of alkanoic acids that contain a phenyl ring separated by methylene groups from the carboxylic acid, including phenylacetic acid, 3-phenylpropionic acid, 4-phenylbutyric acid, 5-phenylvaleric acid, and 6-phenylhexanoic acid, was investigated as model molecules with colloidal silver nanoparticles as SERS substrates. As the number of methylene groups increases, the molecules display an interesting zigzag intensity pattern of the phenyl ring bending mode around 1000 cm(-1) as well as a trend of appearance and disappearance of either the degenerate ring breathing mode or C[Double Bond]O vibrational mode near 1585 and 1630 cm(-1), respectively. Molecules containing an odd number of methylene units display a higher ring bending intensity and degenerate ring breathing mode and are suggested to have a trans conformation on the particle surface. Molecules with an even number of methylene units show a C[Double Bond]O vibrational mode and weaker ring bending in their SERS spectra and are suggested to have a gauche conformation on the silver nanoparticle surface. The different conformation is attributed to the varying interactions of the carboxylic group or the phenyl ring pi electrons with the silver surface. The SERS intensity was found to change little as the length between the phenyl ring and the carboxylic group was increased by adding CH(2) spacers. This is possibly because the effective distance between the phenyl ring and the silver surface does not change much with increasing number of CH(2) spacers as a result of changes in molecular conformation and variations in the phenyl ring orientation with CH(2) addition. The insight gained from this study is important for understanding SERS of complex molecules for which chromophore orientation and molecular conformation must be taken into careful consideration.