Rapid diagnosis of COVID-19 using FT-IR ATR spectroscopy and machine learning.

Early diagnosis of COVID-19 in suspected patients is essential for contagion control and damage reduction strategies. We investigated the applicability of attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy associated with machine learning in oropharyngeal swab suspension fluid to predict COVID-19 positive samples. The study included samples of 243 patients from two Brazilian States. Samples were transported by using different viral transport mediums (liquid 1 or 2). Clinical COVID-19 diagnosis was performed by the RT-PCR. We built a classification model based on partial least squares (PLS) associated with cosine k-nearest neighbours (KNN). Our analysis led to 84% and 87% sensitivity, 66% and 64% specificity, and 76.9% and 78.4% accuracy for samples of liquids 1 and 2, respectively. Based on this proof-of-concept study, we believe this method could offer a simple, label-free, cost-effective solution for high-throughput screening of suspect patients for COVID-19 in health care centres and emergency departments.

Diagnosis of Systemic Diseases Using Infrared Spectroscopy: Detection of Iron Overload in Plasma-Preliminary Study.

Despite the important role of iron in cellular homeostasis, iron overload (IO) is associated with systemic and tissue deposits which damage several organs. In order to reduce the impact caused by IO, invasive diagnosis exams (e.g., biopsies) and minimally invasive methods were developed including computed tomography and magnetic resonance imaging. However, current diagnostic methods are still time-consuming and expensive. A cost-effective solution is using Fourier-transform infrared spectroscopy (FTIR) for real-time and molecular-sensitive biofluid analysis during conventional laboratory exams. In this study, we performed the first evaluation of the accuracy of FTIR for IO diagnosis. The study was performed by collecting FTIR spectra of plasma samples of five rats intravenously injected with iron-dextran and five control rats. We developed a classification model based on principal component analysis and supervised methods including J48, random forest, multilayer perceptron, and radial basis function network. We achieved 100% accuracy for the classification of the IO status and provided a list of possible biomolecules related to the vibrational modes detected. In this preliminary study, we give a first step towards real-time diagnosis for acute IO or intoxication. Furthermore, we have expanded the literature knowledge regarding the pathophysiological changes induced by iron overload.

New insights of Raman spectroscopy for oral clinical applications.

Oral injuries are currently diagnosed by histopathological analysis of biopsy, which is an invasive procedure and does not give immediate results. On the other hand, the Raman spectroscopy technique is a real-time and minimally invasive analytical tool with a notable diagnostic capability. At the current stage, researchers are widely aware of the diagnostic potential of the technique and how it is considered promising for providing biochemical information in real time and without damaging the tissue. The problem originates from a lack of relevant studies and clinical trials that could show the actual use of Raman spectroscopy to help patients. Our goal here is to narrow the relationship between physicists, chemists, engineers, computer scientists, and the medical community, and in fact discuss the potential of Raman spectroscopy as a novel clinical analysis method. In the present study, we focused on the use of Raman spectroscopy as a daily clinical practice. In this context, additional studies and in vivo tests should be performed with the same approach as a real application. We want to show the scientific and industrial community what is really necessary for this, starting from a clinical point of view. Using our previous experience publishing different oral pathologies and types of samples, we also aim to discuss the current state and potential of Raman spectroscopy and what is required to implement Raman spectroscopy for oral clinical applications.

Human papillomavirus detection using PCR and ATR-FTIR for cervical cancer screening.

The human papillomavirus (HPV) genital infection is considered one of the most common sexually transmitted diseases worldwide, and has been associated with cervical cancer. The objective of this study was to investigate the efficacy of the diagnostic methods: polymerase chain reaction (PCR) and Fourier transform infrared (FTIR) equipped with an ATR (Attenuated Total Reflectance) unit (Pike Tech) spectroscopy, to diagnose HPV infection in women undergoing gynecological examination. Seventeen patients (41.46%) of the 41 patients analyzed were diagnosed with exophytic/condyloma acuminate lesions by clinical analysis, 29 patients (70.7%) (G1 group) of the 41 patients, showed positive result for HPV cell injury by oncotic colpocitology and 12 patients (29.3%) (G2 group), presented negative result for cellular lesion and absence of clinical HPV lesion. Four samples were obtained per patient, which were submitted oncotic colpocitology analysis (Papanicolau staining, two samples), PCR (one sample) and ATR-FTIR analysis (one sample). L1 gene was amplified by PCR technique with specific GP5+/GP6+ and MY09/MY11 primers. PCR results were uniformly positive for presence of HPV in all analyzed samples. Multivariate analysis of ATR-FTIR spectra suggests no significant biochemical changes between groups and no clustering formed, concurring with results of PCR. This study suggests that PCR and ATR-FTIR are highly sensitive technique for HPV detection.

Molecular model for hydrated biological tissues.

A density-functional microscopic model for soft tissues (STmod) is presented. The model was based on a prototype molecular structure from experimentally resolved type I collagen peptide residues and water clusters treated in periodic boundary conditions. We obtained the optimized geometry, binding and coupling energies, dipole moments, and vibrational frequencies. The results concerning the stability of the confined water clusters, the water-water, and water-collagen interactions were successfully correlated to some important experimental trends of normal and inflammatory tissues.

Spectral region optimization for Raman-based optical biopsy of inflammatory lesions.

OBJECTIVE: The biochemical alterations between inflammatory fibrous hyperplasia (IFH) and normal tissues of buccal mucosa were probed by using the FT-Raman spectroscopy technique. The aim was to find the minimal set of Raman bands that would furnish the best discrimination. BACKGROUND: Raman-based optical biopsy is a widely recognized potential technique for noninvasive real-time diagnosis. However, few studies had been devoted to the discrimination of very common subtle or early pathologic states as inflammatory processes that are always present on, for example, cancer lesion borders. METHODS: Seventy spectra of IFH from 14 patients were compared with 30 spectra of normal tissues from six patients. The statistical analysis was performed with principal components analysis and soft independent modeling class analogy cross-validated, leave-one-out methods. RESULTS: Bands close to 574, 1,100, 1,250 to 1,350, and 1,500 cm(-1) (mainly amino acids and collagen bands) showed the main intragroup variations that are due to the acanthosis process in the IFH epithelium. The 1,200 (C-C aromatic/DNA), 1,350 (CH(2) bending/collagen 1), and 1,730 cm(-1) (collagen III) regions presented the main intergroup variations. This finding was interpreted as originating in an extracellular matrix-degeneration process occurring in the inflammatory tissues. The statistical analysis results indicated that the best discrimination capability (sensitivity of 95% and specificity of 100%) was found by using the 530-580 cm(-1) spectral region. CONCLUSIONS: The existence of this narrow spectral window enabling normal and inflammatory diagnosis also had useful implications for an in vivo dispersive Raman setup for clinical applications.