SERS sensing for cancer biomarker: Approaches and directions

Ligand-Driven Annular-Epitaxial Growth of CuS-Au Heterostructures as Trinity Plasmonic Nanozyme for Multimode Diagnosis of Pathogenic Bacteria

This study presents a novel method to control the site-selective growth of Au nanostars on CuS nanodisc substrate, it indicates that the surfactant ligands play a key role in the architecture control, only CTAC and homologous series with appropriate affinity to CuS can direct the annular-epitaxial growth of Au nanoparticles on the CuS, which demonstrates superior peroxidase (POD)-mimic and SERS activity. Mechanistic studies indicate that plasmon-enhanced catalytic and SERS activity can be attributed to the spatially separated CuS-Au heterostructure, which supports the light-triggered hot electron-hole pairs production and localized surface plasmon resonance hotspots. For practical biosensing, the CuS-Au heterostructures assembled lateral flow assay (LFA) was used for SERS/catalytic colorimetric/photothermal three-mode detection of Streptococcus pneumoniae and Klebsiella pneumoniae, with visually colorimetric mode at 103 CFU/mL and quantitative SERS/photothermal modes at 2-102 CFU/mL within 15 min, 15 clinical samples were used to validate the assay, the result was 100% concordant to the results of quantitative real-time PCR. This study provides a unique avenue to controllably produce plasmon-enhanced nanozyme, which can provide multi-mode signals for LFA application and meet the requirements of different scenarios.

Highly Accurate and Robust Early Stage Detection of Cholangiocarcinoma Using Near-Lossless SERS Signal Processing with Machine Learning and 2D CNN for Point-of-care Mobile Application

INTRODUCTION

Cholangiocarcinoma (CCA), a malignancy of the bile ducts, presents a significant health burden with a notably high prevalence in Northeast Thailand, where its incidence ratio is 85 per 100,000 population per year. The prognosis for CCA patients remains poor, particularly for proximal tumors, with a dismal 5-year survival rate of just 10%. The challenge in managing CCA is exacerbated by its typically late detection, contributing to a high mortality rate. Current screening methods, such as ultrasound, are insufficient, as many CCA patients do not exhibit prior symptoms or detectable liver fluke (Opisthorchis viverrini : OV) infections, underscoring the urgent need for alternative early detection methods.

METHODS

In this study, we introduce a novel approach utilizing surface-enhanced Raman spectroscopy (SERS) combined with near-lossless signal compression via discrete wavelet transform (DWT) together with 2D CNN for the first time. Hamster serums of different stages were collected as the data set. DWT was employed for feature extraction, enabling the capture of the entire SERS spectrum, unlike traditional methods like PCA and LDA, which focus only on specific peaks. These features were used to train a 2D convolutional neural network (2D CNN), which is particularly robust against translation, rotation, and scaling, thus effectively addressing the SERS peak shifting issues. We validated our approach using gold-standard histology, and notably, our method could detect CCA at an early stage. The ability to identify CCA at the early stage significantly improves the chances of successful intervention and patient outcomes.

RESULTS AND CONCLUSION

Our results demonstrate that our method, combining SERS with extremely compact wavelet feature extraction and 2D CNN, outperformed other approaches (PCA + SVM, PCA + 1D CNN, PCA + 2D CNN, LDA + SVM, and DWT + 1D CNN), achieving performance of 95.1% accuracy, 95.08% sensitivity, 98.4% specificity, and an area under the curve (AUC) of 95%. The trained model was further deployed on a server and mobile application interface, paving the way for future field experiments in rural areas and home-use potential point-of-care services.

Application of Surface-Enhanced Raman Spectroscopy in Head and Neck Cancer Diagnosis

Surface-enhanced Raman spectroscopy (SERS) has emerged as a crucial analytical tool in the field of oncology, particularly presenting significant challenges for the diagnosis and treatment of head and neck cancer. This Review provides an overview of the current status and prospects of SERS applications, highlighting their profound impact on molecular biology-level diagnosis, tissue-level identification, HNC therapeutic monitoring, and integration with emerging technologies. The application of SERS for single-molecule assays such as epidermal growth factor receptors and PD-1/PD-L1, gene expression analysis, and tumor microenvironment characterization is also explored. This Review showcases the innovative applications of SERS in liquid biopsies such as high-throughput lateral flow analysis for ctDNA quantification and salivary diagnostics, which can offer rapid and highly sensitive assays suitable for immediate detection. At the tissue level, SERS enables cancer cell visualization and intraoperative tumor margin identification, enhancing surgical precision and decision-making. The role of SERS in radiotherapy, chemotherapy, and targeted therapy is examined along with its use in real-time pharmacokinetic studies to monitor treatment response. Furthermore, this Review delves into the synergistic relationship between SERS and artificial intelligence, encompassing machine learning and deep learning algorithms, marking the dawn of a new era in precision oncology. The integration of SERS with genomics, metabolomics, transcriptomics, proteomics, and single-cell omics at the multiomics level will revolutionize our comprehension and management of HNC. This Review offers an overview of the transformative impacts of SERS and examines future directions as well as challenges in this dynamic research field.

Rapid determination of malachite green in fish by surface-enhanced Raman spectroscopy combined with MIL-100 (Fe)

Surface-enhanced Raman spectroscopy (SERS) was combined with stoichiometric analysis to synthesize a AuNPs@MIL-100 (Fe) SERS substrate. This high-performance, and low-cost metal-organic framework-based SERS nano sensor is capable of detecting malachite green (MG) residues in fish. The minimum detectable  concentration of MG in standard solutions is 0.1 μg/L, while in fish samples, the detection range spanned from 0.003-0.088 μg/kg. The partial least squares regression (PLSR) and support vector machine regression (SVR) were applied to model the SERS data, enhancing both the precision and reliability of the detection. The results show that compared with the traditional linear regression and PLSR models, the prediction accuracy of the SVR model is an  improvement with higher stability. MG standard solutions and three fish samples can  be analysed directly or after simple extraction. This method can be used to detect trace harmful substances in different aquatic products.

Porous Nanoframe Based Plasmonic Structure With High-Density Hotspots for the Quantitative Detection of Gaseous Benzaldehyde

Owing to its high sensitivity, surface-enhanced Raman scattering (SERS) has immense potential for the identification of lung cancer from the variation in volatile biomarkers in the exhaled gas. However, two prevailing factors limit the application of SERS: 1) the adsorption of target molecules into SERS hotspots and 2) the detection specificity in multiple interference environments. To improve the density of the SERS hotspots, 3D Au@Ag-Au particles are prepared in a porous nanoframes (PPFs) based plasmonic structure, which facilitated a richer local electromagnetic field distribution among the Au nanocubic (NC) cores, Au-Ag porous nanoframes, and Au nanoparticles, thereby promoting the adsorption probability of gaseous aldehydes into the hotspots. L-cysteines (l-Cys)-modified 3D Au@Ag-Au PPFs are proposed as a benzaldehyde (BA) gas detection carrier to accurately detect biomarkers in complex exhaled gases and eliminate interference from other components. Unlike the conventional use of 4-aminothiophenol as a linker molecule, the novel L-Cys-modified SERS substrate is sensitive toward the aldehyde molecules and immune to other volatile organic compounds (ethanol, cyclohexane, toluene, etc.). Furthermore, a medical mask consisting of this SERS substrate is designed to realize intelligent detection of gaseous BA concentrations assisted by a machine learning algorithm.

Surface-Enhanced Raman Spectroscopy for Nitrite Detection

Nitrite is an important chemical intermediate in the nitrogen cycle and is ubiquitously present in environmental and biological systems as a metabolite or additive in the agricultural and food industries. However, nitrite can also be toxic in excessive concentrations. As such, the development of quick, sensitive, and portable assays for its measurement is desirable. In this review, we summarize the working principles and applications of surface-enhanced Raman spectroscopy (SERS) as a rapid, portable, and ultrasensitive method for nitrite detection and showcase its applicability in various water, food, and biological samples. The challenges and opportunities for future developments are also discussed.

Plasmonics-enhanced spikey nanorattle-based biosensor for direct SERS detection of mRNA cancer biomarkers

We present a plasmonics-enhanced spikey nanorattle-based biosensor for direct surface-enhanced Raman scattering (SERS) detection of mRNA cancer biomarkers. Early detection of cancers such as head and neck squamous cell carcinoma (HNSCC) is critical for improving patient outcomes in regions with limited access to traditional diagnostic methods. Our method targets Keratin 14 (KRT14), a promising diagnostic mRNA biomarker for HNSCC, using a sandwich hybridization approach with magnetic beads and SERS spikey nanorattles (SpNR). We synthesized SpNR with a core-gap-shell structure to enhance SERS signals, achieving a limit of detection of 90 femtomolar. A pilot study using clinical samples demonstrated the efficacy of our biosensor in distinguishing between tissue with positive or negative diagnosis for HNSCC, highlighting its potential for rapid and sensitive cancer diagnostics in low-resource settings. This plasmonic assay offers a promising avenue for portable and high-specificity detection of nucleic acid biomarkers, with implications for early cancer detection and improved patient care, especially in middle and low-resource settings.

Streamlined Flow Synthesis of Plasmonic Nanoparticles and SERS Detection of Uremic Toxins with Trace-Level Liquid Volumes in a Microchamber

Rapid detection of uremic toxins is crucial due to their severe health risks, including oxidative stress, inflammation, neurotoxicity, cardiovascular complications, and progression of chronic kidney disease. Surface-enhanced Raman spectroscopy (SERS) may provide sensitive, fast, and clinical-grade real-time monitoring of these toxins, enabling effective management with timely dialysis treatments. This study introduces a 3D-printed microchamber that integrates the fabrication of plasmonic metal nanoparticles for the in-flow detection of biological toxins and pharmaceutical drugs using SERS, making it ideal for on-site diagnostics in clinical settings. The microchamber supports quantitative and highly reproducible detection with liquid volumes under 100 μL, which is crucial for trace-level biomarker detection and minimizing cross-contamination. It employs a tunable solvent exchange method for the in situ synthesis of silver nanoparticles (AgNPs) on flexible PDMS or rigid Si wafer substrates, avoiding costly nanofabrication techniques. Ultralow detection limits were achieved for two model compounds and three pharmaceutical drugs: 10-11 M for rhodamine 6G, 10-7 M for adenine, and 10-6 M for the pharmaceutical drugs. A total of 13 biological toxins, including three neurotransmitters, one neuromodulator, five amino acids, two polyamines, and two urea cycle metabolites, were detected with quantitative limits ranging from 10-3 to 10-6 M, all below permissible levels and aligning with physiological conditions. SERS detection within microchambers facilitates rapid on-site analysis, proving ideal for personalized health monitoring, point-of-care diagnostics, and environmental pollution assessment.

Synergistic SERS enhancement of NiCo-LDHs microurchins and silver nanoparticles for ultra-sensitive and reusable detection of thiabendazole

Two-dimensional layered semiconductor materials as a distinctive class of materials are comprehensively explored for widespread applications due to narrow bandgap, controllable morphology, and tunable metal cation composition. Herein, we constructed a sensing platform of surface enhanced Raman spectroscopy (SERS) by combination of nickel‑cobalt layered double hydroxide (NiCo-LDH) microurchins and plasmonic silver nanoparticles (Ag NPs) for fungicide detection of thiabendazole (TBZ). The NiCo-LDHs/Ag-NPs microcomposites consist of NiCo-LDHs microurchins having a large number of nanoneedles deposited with photoreduced Ag NPs. The SERS platform with NiCo-LDHs/Ag-NPs shows an excellent SERS performance for TBZ detection, including an ultra-low detection limit of 1.49 × 10-11 M, a sublime enhancement factor of 1.71 × 109, high uniformity, good reproducibility, and long-term storage stability. The ultrahigh SERS activity of NiCo-LDH/Ag-NPs can be attributed to strong electromagnetic enhancement in the nanoscale gaps between Ag NPs, massive charge transfer through large-area NiCo-LDH/Ag-NPs interfaces, and the synergistic action of electromagnetic and charge transfer mechanisms. Besides, the unique morphology of NiCo-LDHs/Ag-NPs microcomposite provides a broad surface area for adsorption of TBZ molecules for further Raman signal enhancement. The practicability of the proposed SERS platform is confirmed by detecting TBZ in the real samples of apple juice and river water. The exceptional self-cleaning capability of the NiCo-LDHs/Ag-NPs microcomposite with an retention rate of 81.97 % even after the fifth degradation cycle underscores its impressive sustainable reusability and cost-effectiveness. The findings in this work lay the foundation for the development of high-performance SERS platforms to ensure food safety and environmental protection.

Advancing cerumen analysis: exploring innovative vibrational spectroscopy techniques with respect to their potential as new point-of-care diagnostic tools

Cerumen, commonly known as earwax, is a complex mixture composed of secretions from ceruminous glands. These secretions are heterogeneous mixtures mainly composed of lipids and proteins. Despite its prevalence, the potential diagnostic value of cerumen remains largely unexplored. Here, we present an in-depth analysis of cerumen utilizing well-known vibrational approaches such as conventional Raman spectroscopy or surface-enhanced Raman spectroscopy (SERS) together with advanced vibrational spectroscopy techniques such as coherent Raman scattering (CRS), i.e. broadband coherent anti-Stokes Raman scattering (CARS) or stimulated Raman scattering (SRS), as well as optical photothermal infrared (OPTIR) spectroscopy. Through the integration of these vibrational spectroscopic methods, lipids and proteins can be identified as the main components of cerumen; however, they contribute to the final spectral information to various extents depending on the vibrational detection scheme applied. The inherently weak Raman signal could be enhanced by linear (SERS) and non-linear (CRS) processes, resulting in efficient acquisition of fingerprint information and allowing for the detection of marker modes, which cannot be addressed by conventional Raman spectroscopy. OPTIR spectroscopy provides complementary information to Raman spectroscopy, however, without the contribution of a fluorescence background. Our findings underscore the utility of these cutting-edge techniques in unveiling the intricate molecular landscape of cerumen, paving the way for novel point-of-care diagnostic methodologies and therapeutic interventions.

Tunable Nanoislands Decorated Tapered Optical Fibers Reveal Concurrent Contributions in Through-Fiber SERS Detection

Creating plasmonic nanoparticles on a tapered optical fiber (TF) tip enables a remote surface-enhanced Raman scattering (SERS) sensing probe, ideal for challenging sampling scenarios like biological tissues, site-specific cells, on-site environmental monitoring, and deep brain structures. However, nanoparticle patterns fabricated from current bottom-up methods are mostly random, making geometry control difficult. Uneven statistical distribution, clustering, and multilayer deposition introduce uncertainty in correlating device performance with morphology. Ultimately, this limits the design of the best-performance remote SERS sensing probe. Here we employ a tunable solid-state dewetting method to create densely packed monolayer Au nanoislands with varied geometric parameters in direct contact with the silica TF surface. These patterns exhibit analyzable nanoparticle sizes, densities, and uniform distribution across the entire taper surface, enabling a systematic investigation of particle size, density, and analyte effects on the SERS performance of the through-fiber detection system. The study is focused on the SERS response of a widely employed benchmark molecule, rhodamine 6G (R6G), and serotonin, a highly relevant neurotransmitter for the neuroscience field. The numerical simulations and limit of detection (LOD) experiments on R6G show that the increase of the total near-field enhancement volume promotes the SERS sensitivity of the probe. However, we observed a different behavior for serotonin linked to its interaction with the nanoparticle's surface. The obtained LOD is as low as 10-7 M, a value not achieved so far in a through-fiber detection scheme. Therefore, our work offers a strategy to design nanoparticle-based remote SERS sensing probes and provides new clues to discover and understand intricate plasmonic-driven chemical reactions.

Sensing with Molecularly Imprinted Membranes on Two-Dimensional Solid-Supported Substrates

Molecularly imprinted membranes (MIMs) have been a focal research interest since 1990, representing a breakthrough in the integration of target molecules into membrane structures for cutting-edge sensing applications. This paper traces the developmental history of MIMs, elucidating the diverse methodologies employed in their preparation and characterization on two-dimensional solid-supported substrates. We then explore the principles and diverse applications of MIMs, particularly in the context of emerging technologies encompassing electrochemistry, surface-enhanced Raman scattering (SERS), surface plasmon resonance (SPR), and the quartz crystal microbalance (QCM). Furthermore, we shed light on the unique features of ion-sensitive field-effect transistor (ISFET) biosensors that rely on MIMs, with the notable advancements and challenges of point-of-care biochemical sensors highlighted. By providing a comprehensive overview of the latest innovations and future trajectories, this paper aims to inspire further exploration and progress in the field of MIM-driven sensing technologies.

Evaluating the accuracy of Raman spectroscopy in differentiating leukemia patients from healthy individuals: A systematic review and meta-analysis

PURPOSE

To assess the accuracy of Raman spectroscopy in distinguishing between patients with leukemia and healthy individuals.

METHOD

PubMed, Embase, Web of Science, Cochrane Library, and CNKI databases were searched for relevant articles published from inception of the respective database to November 1, 2023. The pooled sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR), were calculated along with their corresponding 95 % confidence intervals (CI). A summary comprehensive receiver operating characteristic curve (SROC) was constructed and the area under the curve (AUC) was calculated. The degree of heterogeneity was tested and analyzed.

RESULTS

Fifteen groups of original studies from 13 articles were included. The pooled SEN and SPE were 0.93 (95 % CI, [0.92 -0.93]) and 0.91(95 % CI, [0.90-0.92]), respectively. The DOR was 613.01 (95 %CI, [270.79-1387.75]), and the AUC was 0.99. The Deeks' funnel plot asymmetry test indicated no significant publication bias among the included studies (bias coefficient, 40.80; P = 0.13 < 0.10). The meta-regression analysis findings indicated that the observed heterogeneity could be attributed to variations in sample categories and Raman spectroscopy techniques.

CONCLUSION

We confirmed that Raman spectroscopy has good accuracy in differentiating patients with leukemia from healthy individuals, and may become a means of leukemia screening in clinical practice. In the case of analysis based on live cells using surface-enhanced Raman spectroscopy (SERS) improved diagnostic efficacy was observed.

Photonics-powered augmented reality skin electronics for proactive healthcare: multifaceted opportunities

Rapid technological advancements have created opportunities for new solutions in various industries, including healthcare. One exciting new direction in this field of innovation is the combination of skin-based technologies and augmented reality (AR). These dermatological devices allow for the continuous and non-invasive measurement of vital signs and biomarkers, enabling the real-time diagnosis of anomalies, which have applications in telemedicine, oncology, dermatology, and early diagnostics. Despite its many potential benefits, there is a substantial information vacuum regarding using flexible photonics in conjunction with augmented reality for medical purposes. This review explores the current state of dermal augmented reality and flexible optics in skin-conforming sensing platforms by examining the obstacles faced thus far, including technical hurdles, demanding clinical validation standards, and problems with user acceptance. Our main areas of interest are skills, chiroptical properties, and health platform applications, such as optogenetic pixels, spectroscopic imagers, and optical biosensors. My skin-enhanced spherical dichroism and powerful spherically polarized light enable thorough physical inspection with these augmented reality devices: diabetic tracking, skin cancer diagnosis, and cardiovascular illness: preventative medicine, namely blood pressure screening. We demonstrate how to accomplish early prevention using case studies and emergency detection. Finally, it addresses real-world obstacles that hinder fully realizing these materials' extraordinary potential in advancing proactive and preventative personalized medicine, including technical constraints, clinical validation gaps, and barriers to widespread adoption.