HPLC-LED-Induced Fluorescence Analysis of Tear Fluids: An Objective Method for Primary Open Angle Glaucoma Diagnosis.

PURPOSE: The study showcased the application of the lab-assembled HPLC-LED-IF system to analyze proteins in tear fluid samples collected from individuals diagnosed with primary open-angle glaucoma (POAG). METHODS: Clinical application of the said technique was evaluated by recording chromatograms of tear fluid samples from control and POAG subjects and by analyzing the protein profile using multivariate analysis. The data analysis methods involved are principal component analysis (PCA), Match/No-Match, and artificial neural network (ANN) based binary classification for disease diagnosis. RESULTS: Mahalanobis distance and spectral residual values calculated using a standard calibration set of clinically confirmed POAG samples for the Match/No-Match test gave 86.9% sensitivity and 81.8% specificity. ANN with leaving one out procedure has given 87.1% sensitivity and 81.8% specificity. CONCLUSION: The results of the study revealed that the utilization of a 278 nm LED excitation in the HPLC system offers good sensitivity for detecting proteins at low concentrations allowing to obtain reliable protein profiles for the diagnosis of POAG.

Protein profile pattern analysis: A multifarious, in vitro diagnosis technique for universal screening.

Universal health care is attracting increased attention nowadays, because of the large increase in population all over the world, and a similar increase in life expectancy, leading to an increase in the incidence of non-communicable (various cancers, coronary diseases, neurological and old-age-related diseases) and communicable diseases/pandemics like SARS-COVID 19. This has led to an immediate need for a healthcare technology that should be cost-effective and accessible to all. A technology being considered as a possible one at present is liquid biopsy, which looks for markers in readily available samples like body fluids which can be accessed non- or minimally- invasive manner. Two approaches are being tried now towards this objective. The first involves the identification of suitable, specific markers for each condition, using established methods like various Mass Spectroscopy techniques (Surface-Enhanced Laser Desorption/Ionization Mass Spectroscopy (SELDI-MS), Matrix-Assisted Laser Desorption/Ionization (MALDI-MS), etc., immunoassays (Enzyme-Linked Immunoassay (ELISA), Proximity Extension Assays, etc.) and separation methods like 2-Dimensional Polyacrylamide Gel Electrophoresis (2-D PAGE), Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Capillary Electrophoresis (CE), etc. In the second approach, no attempt is made the identification of specific markers; rather an efficient separation method like High-Performance Liquid Chromatography/ Ultra-High-Performance Liquid Chromatography (HPLC/UPLC) is used to separate the protein markers, and a profile of the protein pattern is recorded, which is analysed by Artificial Intelligence (AI)/Machine Learning (MI) methods to derive characteristic patterns and use them for identifying the disease condition. The present report gives a summary of the current status of these two approaches and compares the two in the use of their suitability for universal healthcare.

Correction: Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome.

[This corrects the article DOI: 10.1039/D3RA04389D.].

Protein profile analysis of tear fluid with hyphenated HPLC-UV LED-induced fluorescence detection for the diagnosis of dry eye syndrome.

Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4% sensitivity and 87.8% specificity. ANN with the leaving one out procedure has given 91.6% sensitivity and 93.9% specificity.

Serum protein profile study of myocardial infarction using a LED induced fluorescence based HPLC system.

Cardiovascular diseases (CVDs) are the major health conditions for high mortality and morbidity in humans. Delay in the diagnosis of CVDs effect patients long and short-term health condition. In -house assembled UV-light emitting diode (LED) based fluorescence detector for high -performance liquid chromatography (HPLC) (HPLC-LED-IF) system is used to record serum chromatograms of three categories of samples namely, before medicated- myocardial infarction (B-MI), after medicated- MI (A-MI), and normal. The sensitivity and performance of HPLC-LED-IF system is estimated using commercial serum proteins. Statistical analysis tools like, descriptive statistics, principal component analysis (PCA), and Match/ No Match test were applied to visualize the variation in three groups of samples. Statistical analysis of the protein profile data showed fairly good discrimination among the three categories. The receiver operating characteristic (ROC) curve also supported the reliability of the method to diagnose MI.

Cardiovascular biomarkers in body fluids: progress and prospects in optical sensors.

Cardiovascular diseases (CVD) are the major causative factors for high mortality and morbidity in developing and developed nations. The biomarker detection plays a crucial role in the early diagnosis of several non-infectious and life-threatening diseases like CVD and many cancers, which in turn will help in more successful therapy, reducing the mortality rate. Biomarkers have diagnostic, prognostic and therapeutic significances. The search for novel biomarkers using proteomics, bio-sensing, micro-fluidics, and spectroscopic techniques with good sensitivity and specificity for CVD is progressing rapidly at present, in addition to the use of gold standard biomarkers like troponin. This review is dealing with the current progress and prospects in biomarker research for the diagnosis of cardiovascular diseases. Expert opinion. Fast diagnosis of cardiovascular diseases (CVDs) can help to provide rapid medical intervention, which can affect the patient's short and long-term health. Identification and detection of proper biomarkers for early diagnosis are crucial for successful therapy and prognosis of CVDs. The present review discusses the analysis of clinical samples such as whole blood, blood serum, and other body fluids using techniques like high-performance liquid chromatography-LASER/LED-induced fluorescence, Raman spectroscopy, mainly, optical methods, combined with nanotechnology and micro-fluidic technologies, to probe patterns of multiple markers (marker signatures) as compared to conventional techniques.

Human tear fluid analysis for clinical applications: progress and prospects.

Introduction: Human blood and saliva are increasingly under investigation for the detection of biomarkers for early diagnosis of non-communicable (e.g.cancers) and communicable diseases like COVID-19. Exploring the potential application of human tears, an easily accessible body fluid, for the diagnosis of various diseases is the need of the hour.Areas covered: This review deals with a comprehensive account of applications of tear analysis using different techniques, their comparison and overall progress achieved till now. The techniques used for tear fluid analysis are HPLC/UPLC/SDS-PAGE, CE, etc., together with ELISA, Mass Spectrometry, etc. But, with advances in instrumentation and data processing methods, it has become easy to couple the various separation methods with highly sensitive optical techniques for the analysis of body fluids.Expert opinion: Tear analysis can provide valuable information about the health condition of the eyes since it contains several molecular constituents, and their relative concentrations may alter under abnormal conditions. Tear analysis has the advantage that it is totally non-invasive. This study recommends tear fluid as a reliable clinical sample to be probed by highly sensitive optical techniques to diagnose different health conditions, with special emphasis on eye diseases.

A review on human body fluids for the diagnosis of viral infections: scope for rapid detection of COVID-19.

Introduction: The unprecedented outbreaks of corona virus disease of 2019 (COVID-19) have highlighted the necessity of readily available, reliable, precise, and faster techniques for its detection. Nasopharyngeal swab has been the gold standard for the diagnosis of COVID-19. However, it is not an ideal screening procedure for massive screening as it implicates the patient's stay in the hospital or at home until diagnosis, thus causing crowding of the specimen at the diagnostic centers. Present study deal with the exploration of potential application of different body fluids using certain highly objective techniques (Optical and e-Nose) for faster detection of molecular markers thereby diagnosing viral infections.Areas covered: This report presents an evaluation of different body fluids, and their advantages for the rapid detection of COVID-19, coupled with highly sensitive optical techniques for the detection of molecular biomarkers.Expert opinion: Tears, saliva, and breath samples can provide valuable information about viral infections. Our brief review strongly recommends the application of saliva/tears and exhaled breath as clinical samples using technics such as high-performance liquid chromatography-laser-induced fluorescence, photoacoustic spectroscopy, and e-Nose, respectively, for the fast diagnosis of viral infections.