Silver Nanoparticle Films Obtained by Convective Self-Assembly for Surface-Enhanced Raman Spectroscopy Analyses of the Pesticides Thiabendazole and Endosulfan.

Pesticides pose a great threat to human health and their rapid detection has become an urgent public safety issue engaging the scientific community to search for fast and reliable detection techniques. In this context, Surface Enhanced Raman Spectroscopy (SERS) has emerged as a valuable detection and analysis tool due to its high sensitivity and selectivity, proving its suitability for the food industry and environmental monitoring applications. Here, we report on the fabrication of colloidal silver nanoparticle (AgNP) films by convective self-assembly (CSA) on solid planar substrate and their use for the SERS analyses of two types of pesticides, the fungicide thiabendazole (TBZ) and the insecticide α-endosulfan (α-ES). Electron microscopy shows that these nanoparticle films are dense, highly compact, and uniform across several mm2 areas. The SERS efficiency of the fabricated AgNP films is evaluated using a well-known Raman probe, p-aminothiophenol, for multiple excitation laser lines (532 nm, 633 nm, and 785 nm). The films exhibit the largest SERS enhancement factors for 785 nm excitation, reaching values larger than 105. Thiabendazole could be readily adsorbed on the AgNPs without any sample surface functionalization and detected down to 10-6 M, reaching the sub-ppm range. Endosulfan, a challenging analyte with poor affinity to metal surfaces, was captured near the metal surface by using self-assembled alkane thiol monolayers (hexanethiol and octanethiol), as demonstrated by the thorough vibrational band analysis, and supported by density functional theory (DFT) calculations. In addition, principal component analysis (PCA) based on SERS spectra offers significant leverage in discrimination of the molecules anchored onto the metallic nanostructured surface. This present study demonstrates the utility of self-assembled colloidal nanoparticle films as SERS substrates for a broad range of analytes (para-aminothiophenol, thiabendazole, α-endosulfan, and alkanethiols) and contributes to the development of SERS-based sensors for pesticides detection, identification and monitoring.

Raman spectroscopy in oral cavity and oropharyngeal cancer: a systematic review.

Due to the high incidence of head and neck cancer and under-diagnosis in the early stages, non-invasive and highly accurate diagnostic tests are required for cancer detection. Recent advances in Raman spectroscopy techniques have yielded promising sensitivity and specificity results in the evaluation of cancer. The aim of this study was to investigate the potential value of Raman spectroscopy in oral cavity and oropharyngeal cancer diagnosis based on currently available scientific papers. A search of the PubMed database was performed using a specific strategy and according to the PRISMA guidelines. Raman spectroscopy achieved a maximum accuracy of 98% in cancer detection, while accuracy was 97.24% for tumour grading evaluation, 95% for cancer treatment assessment, and 77% for the detection of cancer recurrence. Moreover, early-stage cancer can be identified by Raman spectroscopy investigation of liquid biopsy samples. An in vivo technique with direct mucosa examination by fibre-optic Raman spectroscopy obtained a maximum accuracy of 94% in cancer diagnosis. The most prominent markers of the presence of malignancy were an increase in Raman signal intensity for proteins, nucleic acids, and water and a decrease for lipids. These cancer discriminants were detected in both fingerprint and high wavenumber regions. In conclusion, Raman spectroscopy is a promising tool for oral cavity and oropharyngeal cancer screening.

Rapid and noninvasive diagnosis of oral and oropharyngeal cancer based on micro-Raman and FT-IR spectra of saliva.

Fast, sensitive, and noninvasive techniques are needed for better health care management, particularly when traditional biopsies could be replaced with appropriate analyses of body fluids, such as saliva. Here is presented a proof-of-concept study, which aims to test a recently developed saliva samples preparation method, for oral and oropharyngeal cancer diagnosis, using micro-Raman and Fourier transform infrared (FT-IR) spectroscopic techniques. The detected biomarker bands and the cancer classification rates are compared and discussed. Saliva samples were collected from healthy donors and pathologically confirmed oral and oropharyngeal cancer patients. Principal components analysis (PCA) and principal components analysis-linear discriminant analysis (PCA-LDA) chemometric methods were applied to build discrimination models for the test and control groups. Based on the differences between salivary spectra of healthy and cancer patients, several biomarker bands were identified. Noteworthy, a significant vibrational biomarker band at 2064 cm-1, assigned to thiocyanate, was observed in both the FT-IR and Raman data-set. Other cancer characteristic Raman bands were 754 cm-1 (tryptophan), 530 and 927 cm-1 (lysozyme), 1001 cm-1 (phenylalanine), while the FT-IR biomarker band was located at 1075 cm-1 (phosphodiester bonds stretching in DNA, RNA). The oral and oropharyngeal cancer was classified with an accuracy of 90% based on the micro-Raman data and 82% based on the FT-IR data set, respectively. The study showed that oral and oropharyngeal cancer can be differentiated from control saliva samples based on their respective micro-Raman and FT-IR spectral signatures, due to the biomolecular modifications induced by the disease.