Determination of sialic acid levels by using surface-enhanced Raman spectroscopy in periodontitis and gingivitis

The prognostic prediction of periodontal non-surgery therapy in periodontitis patients based on surface-enhanced Raman measurements of pre-treatment saliva

Periodontitis is one of the most prevalent dental diseases, and the patients with periodontitis often suffer from refractory periodontitis or recurrence of disease due to improper or inadequate treatment. In clinical practice, the early and accurate assessment of post-treatment prognosis in periodontitis patients is always very important in order to implement timely interventions. In this study, a pre-treatment saliva SERS based prognostic protocol was explored to predict the prognosis of periodontal non-surgery therapy in periodontitis patients. According to the biomolecular analysis, significant differences in the levels of ascorbic acid, uric acid and glutathione are observed between good prognosis group and poor prognosis group, which are expected to serve as potential prognostic markers. Furthermore, high accuracy, sensitivity and specificity can also be achieved by using the proposed prognostic model. The excellent performance of the proposed method has demonstrated its potential for fast, accurate, and non-invasive prognostic prediction of periodontal non-surgery therapy in periodontitis patients, even at the time before implementing treatment, thus is expected to benefit timely and rational guidance on clinical interventions.

Raman Spectroscopy: A Potential Diagnostic Tool for Oral Diseases

Oral diseases impose a major health burden worldwide and have a profound effect on general health. Dental caries, periodontal diseases, and oral cancers are the most common oral health conditions. Their occurrence and development are related to oral microbes, and effective measures for their prevention and the promotion of oral health are urgently needed. Raman spectroscopy detects molecular vibration information by collecting inelastic scattering light, allowing a “fingerprint” of a sample to be acquired. It provides the advantages of rapid, sensitive, accurate, and minimally invasive detection as well as minimal interference from water in the “fingerprint region.” Owing to these characteristics, Raman spectroscopy has been used in medical detection in various fields to assist diagnosis and evaluate prognosis, such as detecting and differentiating between bacteria or between neoplastic and normal brain tissues. Many oral diseases are related to oral microbial dysbiosis, and their lesions differ from normal tissues in essential components. The colonization of keystone pathogens, such as Porphyromonas gingivalis, resulting in microbial dysbiosis in subgingival plaque, is the main cause of periodontitis. Moreover, the components in gingival crevicular fluid, such as infiltrating inflammatory cells and tissue degradation products, are markedly different between individuals with and without periodontitis. Regarding dental caries, the compositions of decayed teeth are transformed, accompanied by an increase in acid-producing bacteria. In oral cancers, the compositions and structures of lesions and normal tissues are different. Thus, the changes in bacteria and the components of saliva and tissue can be used in examinations as special markers for these oral diseases, and Raman spectroscopy has been acknowledged as a promising measure for detecting these markers. This review summarizes and discusses key research and remaining problems in this area. Based on this, suggestions for further study are proposed.

Spectroscopic molecular-fingerprint profiling of saliva

Saliva analysis has been gaining interest as a potential non-invasive source of disease indicative biomarkers due to being a complex biofluid correlating with blood-based constituents on a molecular level. For saliva to cement its usage for analytical applications, it is paramount to gain underpinning molecular knowledge and establish a 'baseline' of the salivary composition in healthy individuals as well as characterize how these factors are impacting its performance as potential analytical biofluid. Here, we have systematically studied the molecular spectral fingerprint of saliva, including the changes associated with gender, age, and time. Via hybrid artificial neural network algorithms and Raman spectroscopy, we have developed a non-destructive molecular profiling approach enabling the assessment of salivary spectral changes yielding the determination of gender and age of the biofluid source. Our classification algorithm successfully identified the gender and age from saliva with high classification accuracy. Discernible spectral molecular 'barcodes' were subsequently constructed for each class and found to primarily stem from amino acid, protein, and lipid changes in saliva. This unique combination of Raman spectroscopy and advanced machine learning techniques lays the platform for a variety of applications in forensics and biosensing.

[Raman spectroscopy and its application in different areas of medicine]

The aim of the review is to learn about the areas of application of the Raman spectroscopy in medicine, particularly in dentistry. The method is widely used in biology, medicine, pharmacy, forensic science, gemology, food industry and other industries. The main advantages of Raman spectroscopy are no need for sample preparation and small amounts of the object of study, as well as the ability to contactlessly obtain unique information about the conformation and microenvironment of living cell molecules. The disadvantages are high costs of the equipment that are compensated with the long-term use by having no costs for additional reagents. The combinatorial scattering is used in dermatology, as it is a high-accuracy automated method of visualization and diagnostics of both benign growths as pigmented nevus, seborrheic keratosis, and malignant neoplasms as melanoma and basal cell carcinoma. This method is an analytical tool for diagnosing various diseases, making the direct measurements in hard and liquid media easier, does not require special treatment of samples and is not sensitive to absorption bands. The Raman spectroscopy use in dentistry allows diagnosing and comparative analysis of the changes of hard tissues of teeth and mucous membrane of the mouth, which improves security and rationalization of treatment and further prevention of complications before and after making different operations.

SP, N. M, Barik AK, Pai KM, Unnikrishnan VK, George SD, Kartha VB, Chidangil S. 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.

New insights into hidradenitis suppurativa diagnosis via salivary infrared biosignatures: A pilot study

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease which can lead to a prolonged physical disability. HS diagnosis is exclusively clinical with the absence of biomarkers. Our study aims at assessing the HS-diagnostic potential of infrared spectroscopy from saliva, as a biofluid reflecting the body's pathophysiological state. Infrared spectra from 127 patients (57 HS and 70 non-HS) were processed by multivariate methods: principal component analysis coupled with Kruskal-Wallis or Mann-Whitney tests to identify discriminant spectral wavenumbers and linear discriminant analysis to evaluate the performances of HS-diagnostic approach. Infrared features, mainly in the 1300 cm^-1 -1600 cm^-1 region, were identified as discriminant for HS and prediction models revealed diagnostic performances of about 80%. Tobacco and obesity, two main HS risk factors, do not seem to alter the infrared diagnosis. This pilot study shows the potential of salivary "liquid biopsy" associated to vibrational spectroscopy to develop a personalized medical approach for HS patients' management.

Asthma and COVID-19: a systematic review

Background

Severe coronavirus disease-19 (COVID-19) presents with progressive dyspnea, which results from acute lung inflammatory edema leading to hypoxia. As with other infectious diseases that affect the respiratory tract, asthma has been cited as a potential risk factor for severe COVID-19. However, conflicting results have been published over the last few months and the putative association between these two diseases is still unproven.

Methods

Here, we systematically reviewed all reports on COVID-19 published since its emergence in December 2019 to June 30, 2020, looking into the description of asthma as a premorbid condition, which could indicate its potential involvement in disease progression.

Results

We found 372 articles describing the underlying diseases of 161,271 patients diagnosed with COVID-19. Asthma was reported as a premorbid condition in only 2623 patients accounting for 1.6% of all patients.

Conclusions

As the global prevalence of asthma is 4.4%, we conclude that either asthma is not a premorbid condition that contributes to the development of COVID-19 or clinicians and researchers are not accurately describing the premorbidities in COVID-19 patients.

Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature

Saliva is a biofluid that can be considered as a “mirror” reflecting our body’s health status. Vibrational spectroscopy, Raman and infrared, can provide a detailed salivary fingerprint that can be used for disease biomarker discovery. We propose a systematic literature review based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to evaluate the potential of vibrational spectroscopy to diagnose oral and general diseases using saliva as a biological specimen. Literature searches were recently conducted in May 2020 through MEDLINE-PubMed and Scopus databases, without date limitation. Finally, over a period of 10 years, 18 publications were included reporting on 10 diseases (three oral and seven general diseases), with very high diagnostic performance rates in terms of sensitivity, specificity, and accuracy. Thirteen articles were related to six different cancers of the following anatomical sites: mouth, nasopharynx, lung, esophagus, stomach, and breast. The other diseases investigated and included in this review were periodontitis, Sjögren’s syndrome, diabetes, and myocardial infarction. Moreover, most articles focused on Raman spectroscopy (n = 16/18) and more specifically surface-enhanced Raman spectroscopy (n = 12/18). Interestingly, vibrational spectroscopy appears promising as a rapid, label-free, and non-invasive diagnostic salivary biometric tool. Furthermore, it could be adapted to investigate subclinical diseases—even if developmental studies are required.

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning

This review summarizes recent progress made using Raman spectroscopy and machine learning for potential universal medical diagnostic applications.