Feasibility of Voltage-Applied SERS Measurement of Bile Juice as an Effective Analytical Scheme to Enhance Discrimination between Gall Bladder (GB) Polyp and GB Cancer

Rapid diagnosis and recurrence prediction of choledocholithiasis disease using raw bile with machine learning assisted SERS

Surface-enhanced Raman spectroscopy (SERS) analysis based on body fluids has been widely applied in disease diagnose. Choledocholithiasis is a widespread and often recurrent digestive system disease, with limited data on factors predicting its formation and reappearance. Bile contains many components that could provide valuable diagnostic information; however, the current diagnosis of biliary disease by SERS focuses on detecting specific component in the bile, overlooking the complex interplay and correlations among multiple factors that could be crucial for accurate diagnosis. This work directly obtained multi-component SERS spectral information of raw bile from 46 patients. Characteristic information was extracted from bile SERS spectra using Principal Component Analysis (PCA), revealing variations in the content of characteristic components associated with different choledocholithiasis types and their recurrence frequency. Pearson correlation analysis was also introduced to reveal the interactions of primary active substances pertinent to choledocholithiasis diagnosis. The efficacy of PCA and Support Vector Machine (SVM) models in classifying stone types, presented an accuracy of 99.2 %. Furthermore, the interaction patterns among SERS characteristic components in choledocholithiasis recurrence frequency were revealed, and with the support of SVM, the prediction for different recurrence rates reached an accuracy of 95.2 %. Overall, this work demonstrates that integrating SERS with machine learning can support disease diagnosis and the interpretation of correlations among multiple components, facilitating elucidating the disease mechanisms.

Label-free surface-enhanced Raman spectroscopy of serum with machine-learning algorithms for gallbladder cancer diagnosis

Gallbladder cancer (GBC) is a rare but frequently fatal biliary tract malignancy that is typically only discovered when it is already advanced. In the search of an efficient diagnosis method. Therefore, in this study, we investigated a novel technique for the quick and non-invasive diagnosis of GBC based on serum surface-enhanced Raman spectroscopy (SERS). SERS spectra of serum from 41 patients with GBC and 72 normal subjects were recorded. Principal component analysis-linear discriminant analysis (PCA-LDA), and PCA-support vector machine (PCA-SVM), Linear SVM and Gaussian radial basis function-SVM (RBF-SVM) algorithms were used to establish the classification models, respectively. When the Linear SVM was used, the overall diagnostic accuracy for classifying the two groups could achieve 97.1%, and when RBF-SVM was used, the diagnostic sensitivity of GBC was 100%. The results demonstrated that SERS in combination with a machine learning algorithm is a promising candidate to be one of the diagnostic tools for GBC in the future.

Biomedical Photonics Methods in Solving Diagnostic Tasks

Modern photonics methods are considered in relation to solving a number of diagnostic problems in practical medicine. The basic principles of the application of optical noninvasive diagnostic methods are described and examples are given: laser Doppler flowmetry, digital diaphanoscopy, Raman spectroscopy, spectrophotometry, time-resolved fluorescence spectroscopy, and video capillaroscopy. The advantages and prospects of using photonics methods in clinical practice, making it possible to detect various pathological conditions of biological tissues, including those at the early stages of diseases, are demonstrated.

Surface plasmon-enhanced fluorescence and surface-enhanced Raman scattering dual-readout chip constructed with silver nanowires: Label-free clinical detection of direct-bilirubin

It has been found that the direct/total bilirubin ratio (D/T-BIL) is related to the survival rate of COVID-19 pneumonia. The presence of an excessive amount of bilirubin in human blood also causes liver and neurological damage, leading to death. Therefore, upon considering the adverse impact of the presence of excessive bilirubin in human blood, it has become highly imperative to detect bilirubin in a fast and label-free manner. Herein, we designed and constructed a random-crossed-woodpile nanostructure from silver nanowires to form a 3-dimensional plasmonic hotspot-rich (3D-PHS) nanostructure and successfully used it to detect direct bilirubin (D-BIL) in human blood in a label-free manner. The 3D-PHS nanochip provides rich spatial hot spots that are simultaneously responsive to SERS and SPEF effects and consequently, successfully used to measure and characterize D-BIL with a detection limit of ∼10 nM, requiring only 10μL of human serum for rapid screening, which is the first time D-BIL has been detected in a clinically relevant range. This demonstrates a simple, label-free, pretreatment-free potential biosensing technology that can be used in health care units, and further, in the efficient detection of point-of-care testing with a portable spectrometer.

Spectroscopic investigation of faeces with surface-enhanced Raman scattering: a case study with coeliac patients on gluten-free diet

Surface-enhanced Raman scattering (SERS) spectra of faecal samples can be obtained by adding AuNP to their methanol extracts according to the reported protocol, and display bands that are due to bilirubin-like species but also to xanthine and hypoxanthine, two metabolic products secreted by gut bacteria. A total of 27 faecal samples from three different groups, i.e. coeliac patients (n = 9), coeliac patients on gluten-free diet (n = 10) and a control group (n = 8), were characterized with both SERS spectroscopy and 16S rRNA sequencing analysis. Significant differences are present between SERS spectra of coeliac patients and those on gluten-free diet, with a marked increase in the relative intensity of both xanthine and hypoxanthine for the latter. Interestingly, these differences do not correlate with bacterial composition as derived from 16S rRNA sequencing.

Raman, Infrared and Brillouin Spectroscopies of Biofluids for Medical Diagnostics and for Detection of Biomarkers

This review surveys Infrared, Raman/SERS and Brillouin spectroscopies for medical diagnostics and detection of biomarkers in biofluids, that include urine, blood, saliva and other biofluids. These optical sensing techniques are non-contact, noninvasive and relatively rapid, accurate, label-free and affordable. However, those techniques still have to overcome some challenges to be widely adopted in routine clinical diagnostics. This review summarizes and provides insights on recent advancements in research within the field of vibrational spectroscopy for medical diagnostics and its use in detection of many health conditions such as kidney injury, cancers, cardiovascular and infectious diseases. The six comprehensive tables in the review and four tables in supplementary information summarize a few dozen experimental papers in terms of such analytical parameters as limit of detection, range, diagnostic sensitivity and specificity, and other figures of merits. Critical comparison between SERS and FTIR methods of analysis reveals that on average the reported sensitivity for biomarkers in biofluids for SERS vs FTIR is about 103 to 105 times higher, since LOD SERS are lower than LOD FTIR by about this factor. High sensitivity gives SERS an edge in detection of many biomarkers present in biofluids at low concentration (nM and sub nM), which can be particularly advantageous for example in early diagnostics of cancer or viral infections.HighlightsRaman, Infrared spectroscopies use low volume of biofluidic samples, little sample preparation, fast time of analysis and relatively inexpensive instrumentation.Applications of SERS may be a bit more complicated than applications of FTIR (e.g., limited shelf life for nanoparticles and substrates, etc.), but this can be generously compensated by much higher (by several order of magnitude) sensitivity in comparison to FTIR.High sensitivity makes SERS a noninvasive analytical method of choice for detection, quantification and diagnostics of many health conditions, metabolites, and drugs, particularly in diagnostics of cancer, including diagnostics of its early stages.FTIR, particularly ATR-FTIR can be a method of choice for efficient sensing of many biomarkers, present in urine, blood and other biofluids at sufficiently high concentrations (mM and even a few µM)Brillouin scattering spectroscopy detecting visco-elastic properties of probed liquid medium, may also find application in clinical analysis of some biofluids, such as cerebrospinal fluid and urine.

Feasibility of discrimination of gall bladder (GB) stone and GB polyp using voltage-applied SERS measurement of bile juice samples in conjunction with two-trace two-dimensional (2T2D) correlation analysis

Voltage-applied SERS measurement of bile juice in conjunction with two-trace two-dimensional (2T2D) correlation analysis was demonstrated as a potential tool to enhance discrimination of gall bladder (GB) stone and GB polyp. When SERS spectra of the aqueous phases extracted from raw bile juice samples were measured with applying external voltage from -300 to +300 mV (100 mV intervals), subsequent spectral variations of the adsorbed components (bilirubin-containing compounds) on the SERS substrate were minute, and discrimination of the two GB diseases in a principal component score domain was difficult. Therefore, 2T2D correlation analysis, effectively identifying asynchronous (dissimilar) spectral behaviors in the voltage-induced SERS spectra, was used to improve the discrimination. When two spectra of a sample collected with application of +100 and +300 mV were adopted, the features of subsequent 2T2D slice spectra were characteristic, and discrimination of GB stone and GB polyp substantially improved. External voltage application and recognition of the voltage-induced spectral features by 2T2D correlation analysis were key factors for the improvement. Since the demonstrated method relied on only a few SERS-active compounds, infrared (IR) spectroscopy featuring all the present components in the samples was also evaluated for comparison. However, the IR-based discrimination was inferior because the metabolite compositions in the samples between the GB diseases were not noticeably different.