Characterization and diagnosis of cancer by native fluorescence spectroscopy of human urine

Photonic sensor based on surface imprinted polymers for enhanced point-of-care diagnosis of bacterial urinary tract infections

Effective bacterial detection is crucial for health diagnostics, particularly for the detection of pathogenic species like Escherichia coli (E. coli), which is responsible for up to 90% of urinary tract infections (UTIs), is especially crucial. Current detection methods are time-consuming, often delaying diagnosis and treatment. This study introduces an innovative approach for rapid E. coli detection using porous silicon (PSi) substrates combined with Surface Imprinted Polymers (SIPs) for photoluminescence-based (PL-based) E. coli detection. The PSi/SIP substrates offer high sensitivity, selectivity, and a low limit of detection (LOD) without the need for natural recognition elements. These substrates, fabricated via metal-assisted chemical etching (MACE) and PDMS-based E. coli imprinting, demonstrate reliable repeatability and a fast detection. Real-time detection experiments in phosphate-buffered saline (PBS) and urine showed consistent stair-like quenching of the PL signal with increasing E. coli concentrations, achieving theoretical LODs of approximately 13 ± 2 CFU/mL in PBS and 17 ± 3 CFU/mL in urine. The substrates exhibited excellent selectivity, differentiating E. coli from other species such as Cronobacter sakazakii (C. sakazakii) and Listeria monocytogenes. The high sensitivity and reproducibility of PSi/SIP substrates, along with the ease of use and rapid detection capabilities of the resulting sensor, highlight the potential of this novel platform for point-of-care (PoC) applications in clinical diagnostics.

Non-Invasive Endometrial Cancer Screening through Urinary Fluorescent Metabolome Profile Monitoring and Machine Learning Algorithms

Endometrial cancer is becoming increasingly common, highlighting the need for improved diagnostic methods that are both effective and non-invasive. This study investigates the use of urinary fluorescence spectroscopy as a potential diagnostic tool for endometrial cancer. Urine samples were collected from endometrial cancer patients (n = 77), patients with benign uterine tumors (n = 23), and control gynecological patients attending regular checkups or follow-ups (n = 96). These samples were analyzed using synchronous fluorescence spectroscopy to measure the total fluorescent metabolome profile, and specific fluorescence ratios were created to differentiate between control, benign, and malignant samples. These spectral markers demonstrated potential clinical applicability with AUC as high as 80%. Partial Least Squares Discriminant Analysis (PLS-DA) was employed to reduce data dimensionality and enhance class separation. Additionally, machine learning models, including Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD), were utilized to distinguish between controls and endometrial cancer patients. PLS-DA achieved an overall accuracy of 79% and an AUC of 90%. These promising results indicate that urinary fluorescence spectroscopy, combined with advanced machine learning models, has the potential to revolutionize endometrial cancer diagnostics, offering a rapid, accurate, and non-invasive alternative to current methods.

Influence of vitamins and food on the fluorescence spectrum of human urine

OBJECTIVES

Fluorescence spectroscopy of human urine is a method with the potential to gain importance as a diagnostic tool in the medical field, e.g., for measuring Coproporphyrin III (CPIII) as an indicator of cancer and acute types of porphyria. Food can change human urine's color, which could influence the urine fluorescence spectrum and the detection of CPIII in urine. To determine if there is a noticeable influence on the urine fluorescence spectrum or on the detection of CPIII in urine, 16 vitamin supplements, and three food items were tested. Such investigation may also prevent false interpretation of measured data.

METHODS

Urine samples were collected before and after (overnight, ca. 8 h) intake of each test substance. Samples were investigated by fluorescence spectrum analysis. At excitation wavelengths from 300 to 500 nm and emission wavelengths from 400 to 700 nm excitation-emission-matrices were measured. Data obtained from urine before intake were compared to the data from overnight urine. Furthermore, the investigation of any interference with the CPIII concentration was performed at an excitation wavelength of 407 ± 3 nm and emission wavelengths of 490-800 nm.

RESULTS

Only vitamin B2, but none of the other tested substances, showed noticeable influence on the urine fluorescence spectrum. None of the tested substances showed noticeable interference with the recovery rate of CPIII.

CONCLUSIONS

The correct interpretation of measured data by fluorescence spectroscopy is possible with the exception if vitamin B2 supplementation was performed; thus, the consumption of vitamin B2 supplements before fluorescence testing of the patient's urine should be avoided and/or must be requested. CPIII concentrations could reliably be measured in all cases.

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.

Urine fluorescence spectroscopy combined with machine learning for screening of hepatocellular carcinoma and liver cirrhosis

In this paper, we investigated the possibility of using urine fluorescence spectroscopy and machine learning method to identify hepatocellular carcinoma (HCC) and liver cirrhosis from healthy people. Urine fluorescence spectra of HCC (n = 62), liver cirrhosis (n = 65) and normal people (n = 60) were recorded at 405 nm excitation using a Fluorescent scan multimode reader. The normalized fluorescence spectra revealed endogenous metabolites differences associated with the disease, mainly the abnormal metabolism of porphyrin derivatives and bilirubin in the urine of patients with HCC and liver cirrhosis compared to normal people. The Support vector machine (SVM) algorithm was used to differentiate the urine fluorescence spectra of the HCC, liver cirrhosis and normal groups, and its overall diagnostic accuracy was 83.42%, the sensitivity for HCC and liver cirrhosis were 93.55% and 73.85%, and the specificity for HCC and liver cirrhosis were 88.00% and 89.34%, respectively. This exploratory work shown that the combination of urine fluorescence spectroscopy and SVM algorithm has great potential for the noninvasive screening of HCC and liver cirrhosis.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Strong Dependence between Tryptophan-Related Fluorescence of Urine and Malignant Melanoma

Urine autofluorescence at 295 nm is significantly higher in patients with malignant melanoma at each clinical stage compared to the healthy group. The largest difference is in the early-stages and without metastases. With increasing stage, the autofluorescence at 295 nm decreases. There is also a significant negative correlation between autofluorescence and Clark classification. Based on our results, it is assumed that the way malignant melanoma grows also affects urinary autofluorescence.

Fluorescence photo-bleaching of urine and its applicability in oral cancer diagnosis

Photo-stability of urine is of crucial importance for the applicability of fluorescence spectroscopy of urine samples for diagnosis of cancer. We report the results of a detailed study on fluorescence photo-bleaching of human urine samples. We also present the results of a preliminary investigation on evaluation of the applicability of photo-bleaching characteristics of urine for discriminating patients with oral cancer from healthy volunteers. The time-lapse fluorescence induced by continuous shining of 405 nm radiation from a diode laser was recorded from the urine samples obtained from 18 patients with oral cancer as well as from 22 healthy volunteers with history of no known major illness in the past two months. The integrated fluorescence intensity (ΣI), calculated for each spectrum, was found to decrease with time till a point after which no further decrease was observed. Further, while significant differences were observed in the spectra of cancerous patients and healthy volunteers, these differences were found to be varying with time till the intensities of the observed fluorescence spectra corresponding to the two categories of urine samples became stable. The curve, generated by plotting ΣI vs. time, was found to be best fitted (R² > 0.95) with a double-exponential decay function. The photo-bleaching constants, obtained from curve-fitting, were found to have statistically significant differences corresponding to the urine samples of cancerous patients and healthy volunteers. A classification algorithm developed based on nearest-mean classifier (NMC) and applied on the photo-bleaching constants in leave-one-subject-out cross-validation mode was found to provide a sensitivity and specificity of up to ∼ 86% in discriminating the two categories of urine samples.

High wavenumber Raman spectroscopy in the characterization of urinary metabolites of normal subjects, oral premalignant and malignant patients

Urine has emerged as one of the diagnostically potential bio fluids, as it has many metabolites. As the concentration and the physiochemical properties of the urinary metabolites may vary under pathological transformation, Raman spectroscopic characterization of urine has been exploited as a significant tool in identifying several diseased conditions, including cancers. In the present study, an attempt was made to study the high wavenumber (HWVN) Raman spectroscopic characterization of urine samples of normal subjects, oral premalignant and malignant patients. It is concluded that the urinary metabolites flavoproteins, tryptophan and phenylalanine are responsible for the observed spectral variations between the normal and abnormal groups. Principal component analysis-based linear discriminant analysis was carried out to verify the diagnostic potentiality of the present technique. The discriminant analysis performed across normal and oral premalignant subjects classifies 95.6% of the original and 94.9% of the cross-validated grouped cases correctly. In the second analysis performed across normal and oral malignant groups, the accuracy of the original and cross-validated grouped cases was 96.4% and 92.1% respectively. Similarly, the third analysis performed across three groups, normal, oral premalignant and malignant groups, classifies 93.3% and 91.2% of the original and cross-validated grouped cases correctly.

An in vitro diagnosis of oral premalignant lesion using time-resolved fluorescence spectroscopy under UV excitation-a pilot study

In spite of rapid advancement in cancer treatment, early diagnosis of cancer and medicable precursors are still the finest approach towards the assurance of patient lives and enhancement in the quality of their life. In this regard, the present study deals with the time-resolved fluorescence spectroscopy of normal and premalignant oral tissues under UV excitations (280nm and 310nm). The decay kinetics at 350nm emission of normal tissues exhibit higher fluorescence lifetime than that of premalignant tissues and subsequent statistical analysis shows that the data were statistically significant. Further, the decay kinetics at 450nm emission for normal and premalignant oral tissues was obtained. Subsequently, statistical analysis revealed that except fast component, rest of the component lifetimes and fractional amplitudes were not statistically significant. An attempt has also been made to explore the better statistical tool to discriminate premalignant tissues from normal ones at 350nm emission. Among stepwise linear discriminant analysis (SLDA) and receiver operator characteristics (ROC), the former discriminates premalignant from normal tissues with 86.7% specificity and 93.3% sensitivity. Hence, fluorescence lifetime spectroscopy at 350nm emission opens a new avenue for early detection of oral cancer.

Autofluorescence signatures for classifying lung cells during epithelial mesenchymal transition

Morphological ​and autofluorescence (blue, green, red) ​patterns in lung normal cells during EMT progression.

Recent advances in optical diagnosis of oral cancers: Review and future perspectives

Optical diagnosis techniques offer several advantages over traditional approaches, including objectivity, speed, and cost, and these label-free, noninvasive methods have the potential to change the future workflow of cancer management. The oral cavity is particularly accessible and, thus, such methods may serve as alternate/adjunct tools to traditional methods. Recently, in vivo human clinical studies have been initiated with a view to clinical translation of such technologies. A comprehensive review of optical methods in oral cancer diagnosis is presented. After an introduction to the epidemiology and etiological factors associated with oral cancers currently used, diagnostic methods and their limitations are presented. A thorough review of fluorescence, infrared absorption, and Raman spectroscopic methods in oral cancer diagnosis is presented. The applicability of minimally invasive methods based on serum/saliva is also discussed. The review concludes with a discussion on future demands and scope of developments from a clinical point of view. © 2015 Wiley Periodicals, Inc. Head Neck 38: E2403-E2411, 2016.

Early diagnosis of colorectal cancer in rats with DMH induced carcinogenesis by means of urine autofluorescence analysis

Cancer is one of the most highlighted topics of current research. Early detection of this disease allows more effective therapy, hence higher chance of cure. Application of fluorescence spectral techniques into oncological diagnostic is one of the potential alternatives. Chemically induced carcinogenesis in rats is widely used model for exploration of various aspects of colorectal cancer. This study shows value of discriminate analysis of urine fluorescent fingerprint between healthy control group of rats and those with dimethylhydrazine induced early lesions of colorectal cancer. Using fluorescence spectroscopy, significant difference (P < 0.05) between both of group was achieved.