1H-NMR-based urine metabolomics of prostate cancer and benign prostatic hyperplasia.

Background: Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are prevalent conditions affecting a significant portion of the male population, particularly with advancing age. Traditional diagnostic methods, such as digital rectal examination (DRE) and prostate-specific antigen (PSA) tests, have limitations in specificity and sensitivity, leading to potential overdiagnosis and unnecessary biopsies. Significance: This study explores the effectiveness of 1H NMR urine metabolomics in distinguishing PCa from BPH and in differentiating various PCa grades, presenting a non-invasive diagnostic alternative with the potential to enhance early detection and patient-specific treatment strategies. Results: The study demonstrated the capability of 1H NMR urine metabolomics in detecting distinct metabolic profiles between PCa and BPH, as well as among different Gleason grade groups. Notably, this method surpassed the PSA test in distinguishing PCa from BPH. Untargeted metabolomics analysis also revealed several metabolites with varying relative concentrations between PCa and BPH cases, suggesting potential biomarkers for these conditions.

Analysis of urine using electronic tongue towards non-invasive cancer diagnosis.

Electronic tongues (e-tongues) have been broadly employed in monitoring the quality of food, beverage, cosmetics, and pharmaceutical products, and in diagnosis of diseases, as the e-tongues can discriminate samples of high complexity, reduce interference of the matrix, offer rapid response. Compared to other analytical approaches using expensive and complex instrumentation as well as required sample preparation, the e-tongue is non-destructive, miniaturizable and on-site method with little or no preparation of samples. Even though e-tongues are successfully commercialized, their application in cancer diagnosis from urine samples is underestimated. In this review, we would like to highlight the various analytical techniques such as Raman spectroscopy, infrared spectroscopy, fluorescence spectroscopy, and electrochemical methods (potentiometry and voltammetry) used as e-tongues for urine analysis towards non-invasive cancer diagnosis. Besides, different machine learning approaches, for instance, supervised and unsupervised learning algorithms are introduced to analyze extracted chemical data. Finally, capabilities of e-tongues in distinguishing between patients diagnosed with cancer and healthy controls are highlighted.

A review on conjugated polymer-based electronic tongues.

Electronic tongues (e-tongues) are analytical technologies that mimic the biological tongues which are non-specific, low-selective, and cross-sensitive taste systems. The e-tongues consist of an array of sensors, being able to produce electrical signals that correspond to particular chemical compositions of a sample solution. The performance and efficiency of e-tongues have been optimized for many years via the development of novel materials and technologies. Various conjugated polymers (CPs) have been used in e-tongues over the past decades thanks to their fascinating electrical properties and wide-ranging chemistries. In most studies, CPs such as polypyrrole (PPy), polyaniline (PANI), polythiophene (PT), and poly(3,4-ethylenedioxythiophene) (PEDOT), have drawn considerable interest in e-tongues because of their controllable electrical properties, relatively facile and cost-effective preparation, and good environmental stability that can significantly enhance their versatility, compared to other types of e-tongues. This review article reports major conjugated polymer-based e-tongues (CPETs) that have been studied with these aforementioned CPs over the last two decades.