Antibody-based SERS diagnostics of fhit protein without label

Surface-enhanced Raman scattering (SERS) is a particularly promising technique that has the potential to perform highly selective and sensitive in situ measurements of antibody-antigen reactions. This work describes the use of silver (Ag) colloids for immunoassay-based SERS detection of the fragile histidine triad (Fhit) protein. Alterations in Fhit protein expression have been associated with several human cancers, and, thus, the detection of Fhit protein is important because it can potentially be used as a cancer diagnostic biomarker, for both cancer detection and therapy.     

Photonics of human saliva: potential optical methods for the screening of abnormal health conditions and infections

Human saliva can be treated as a pool of biological markers able to reflect on the state of personal health. Recent years have witnessed an increase in the use of optical devices for the analysis of body fluids. Several groups have carried out studies investigating the potential of saliva as a non-invasive and reliable clinical specimen for use in medical diagnostics. This brief review aims to highlight the optical technologies, mainly surface plasmon resonance (SPR), Raman, and Fourier transform infrared (FTIR) spectroscopy, which are being used for the probing of saliva for diverse biomedical applications. Advances in bio photonics offer the promise of unambiguous, objective and fast detection of abnormal health conditions and viral infections (such as COVID-19) from the analysis of saliva.     

Surface-enhanced Raman scattering integrating with machine learning for green tea storage time identification

The rapid and accurate identification of complex samples still remains a great challenge, especially for those with similar compositions. In this work, we report an integration strategy consisting of surface-enhanced Raman scattering (SERS) and machine learning to discriminate complex and similar analytes, in this case green tea products with different storage times. Surface-functionalized Ag nanoparticles (NPs) were used as a SERS substrate to reveal the changes in the sensory components of green tea with variable storage time. Principal components analysis (PCA)-based support vector machine (SVM) classification was used to extract the key spectral features and identify green tea with different storage times. The results showed that such an integration strategy achieved high predictive accuracy on time tag discrimination for green tea. The multiclass SVM classifier successfully recognized green tea with different storage times at a prediction accuracy of 95.9%, sensitivity of 96.6%, and specificity of 98.8%. Therefore, this work illustrates that the SERS-based PCA-SVM platform might be a facile and reliable tool for the identification of complex matrices with subtle differentiations.     

Raman microprobe spectroscopy: A new tool for biofouling diagnostics

Raman vibrational spectra were obtained from crystalline amino acids and acid molecules adsorbed at the surfaces of silver electrodes in aqueous solutions. Results revealed that aromatic acids such as phenylalanine adsorbed via their aromatic ring while bases such as alanine were coordinated by their amine functional groups. Sulphur containing acids (cysteine and cystine) were found to bond through their sulphur groups. In all cases, adsorption increased towards the point of zero charge of silver, as would be expected for uncharged species. Similar experiments carried out on α‐amylase solutions showed that the enzyme molecule changes its coordination to the silver surface as a function of electrode potential, indicating that C‐S, C‐N, and aromatic ring functional groups are all present on the outer surface of the enzyme structure.     

Aligned Silver Nanoparticles on Rippled Silicon Templates Exhibiting Anisotropic Plasmon Absorption

Aligned silver nanoparticles, grown by combining two simple bottom-up techniques, are reported. Physical vapor-deposited silver adatoms are shown to form nanoparticles preferentially in the valleys of rippled silicon templates prepared by low-energy ion bombardment. A 35-nm ripple periodicity produced highly aligned structures with a 0.21 eV polarization-dependent shift in the plasmon resonance peak. The speed and simplicity of the method is viable for cost-effective, large-scale production of mesoscale aligned nanostructures with adjustable periodicity.     

Silver-based surface enhanced Raman spectroscopy devices for detection of organophosphorus pesticides traces

The detection of traces of substances by surface-sensitive techniques such as surface enhanced Raman spectroscopy (SERS) explores the interaction of adsorbed molecules on plasmonic surfaces to improve the limit of detection of analytes. This article is an overview about recent development in SERS substrates applied in the detection of organophosphorus pesticides on plasmonic surfaces (arrays of metal nanoparticles). The morphology, roughness, chemical functionalization degree, and aggregation level of plasmonic centers are some of the critical parameters to be controlled in the optimization of SERS signal from specific analytes.     

A Filter-based Surface Enhanced Raman Spectroscopic Assay for Rapid Detection of Chemical Contaminants

We demonstrate a method to fabricate highly sensitive surface-enhanced Raman spectroscopic (SERS) substrates using a filter syringe system that can be applied to the detection of various chemical contaminants. Silver nanoparticles (Ag NPs) are synthesized via reduction of silver nitrate by sodium citrate. Then the NPs are aggregated by sodium chloride to form nanoclusters that could be trapped in the pores of the filter membrane. A syringe is connected to the filter holder, with a filter membrane inside. By loading the nanoclusters into the syringe and passing through the membrane, the liquid goes through the membrane but not the nanoclusters, forming a SERS-active membrane. When testing the analyte, the liquid sample is loaded into the syringe and flowed through the Ag NPs coated membrane. The analyte binds and concentrates on the Ag NPs coated membrane. Then the membrane is detached from the filter holder, air dried and measured by a Raman instrument. Here we present the study of the volume effect of Ag NPs and sample on the detection sensitivity as well as the detection of 10 ppb ferbam and 1 ppm ampicillin using the developed assay.     

Reflective FT-NIR and SERS studies of HER-II breast cancer biomarker using plasmonic-active nanostructured thin film immobilized oriented antibody

We describe the fabrication of plasmonic-active nanostructured thin film substrate as a label-free surface-enhanced Raman scattering (SERS)-based biosensor immobilized covalently with monoclonal HER-II antibody (mAb) to detect overexpressed HER-II as a biomarker in breast cancer serum (BCS). Oriented conjugation of mAb via hydrazone linkage to provide higher mAb accessibility was characterized by UV-vis and reflective Fourier transform near-infrared (FT-NIR) spectroscopic techniques. The interaction of BCS with mAb was studied by FT-NIR and nonresonant SERS at 637 nm. The results showed detection of glycoprotein content at different laser powers including a rise in amino acid and glycan content with varying results at higher power. With nonresonant SERS we observed nonlinear behavior of peak intensity. Analysis of variance was implemented to determine the effect of laser power which was found not to be a contributing factor. However, at the nanoscale, factors including the heating effect and aggregation of molecules can contribute to the nonlinearity of peak intensity.     

Nanoplasmonic sensor for foodborne pathogens detection. Towards development of ISO‐SERS methodology for taxonomic affiliation of Campylobacter spp.

According to EU summary report on zoonoses, zoonotic agents and food‐borne outbreaks in 2017, Campylobacter was the most commonly reported gastrointestinal bacterial pathogen in humans in the EU. Unfortunately, the standard methods for the detection of thermotolerant Campylobacter spp. in foods are time‐consuming. Additionally, the qualified staff is obligatory. For this reason, new methods of pathogens detection are needed. The present work demonstrates that surface‐enhanced Raman scattering (SERS) is a reliable and fast method for detection of Campylobacter spp. in food samples. The proposed method combines the SERS measurements performed on an Ag/Si substrate with two initial steps of the ISO standard procedure. Finally, the principal component analysis (PCA) allows for statistical classification of the studied bacteria. By applying the proposed ISO‐SERS‐PCA method in the case of Campylobacter bacteria the total detection time may be reduced from 7 to 8 days required by ISO method to 3 to 4 days in the case of SERS‐based approach.     

Label‐free diagnosis for colorectal cancer through coffee ring‐assisted surface‐enhanced Raman spectroscopy on blood serum

Surface‐enhanced Raman spectroscopy (SERS) is garnering considerable attention for the swift diagnosis of pathogens and abnormal biological status, that is, cancers. In this work, a simple, fast and inexpensive optical sensing platform is developed by the design of SERS sampling and data analysis. The pretreatment of spectral measurement employed gold nanoparticle colloid mixing with the serum from patients with colorectal cancer (CRC). The droplet of particle‐serum mixture formed coffee‐ring‐like region at the rim, providing strong and stable SERS profiles. The obtained spectra from cancer patients and healthy volunteers were analyzed by unsupervised principal component analysis (PCA) and supervised machine learning model, such as support‐vector machine (SVM), respectively. The results demonstrate that the SVM model provides the superior performance in the classification of CRC diagnosis compared with PCA. In addition, the values of carcinoembryonic antigen from the blood samples were compiled with the corresponding SERS spectra for SVM calculation, yielding improved prediction results.