Label-free imaging techniques are powerful tools for characterizing biomolecular interactions, offering important advantages over traditional fluorescence-based imaging methods. Among these approaches, surface plasmon resonance imaging (SPRi) has emerged as a particularly versatile and enabling platform owing to its simple experimental configuration, rapid data acquisition, and high imaging sensitivity. A related variant, surface plasmon resonance microscopy (SPRM), further extends the capabilities of SPR-based sensing by providing enhanced spatial resolution and expanded sensing depth, allowing interrogation of interactions at the single-particle and single-event level. The combined versatility of SPRi and SPRM has supported a wide range of applications, including molecular recognition, quantitative interaction analysis, extracellular vesicle detection, and nanobubble characterization. More recently, the integration of machine-learning approaches into both instrumental development and postacquisition data analysis has significantly enhanced the ability of SPR-based imaging techniques to address complex sample environments, enabling multiplexed, high-throughput, and information-rich measurements. This review provides a comprehensive overview of recent advances in SPRi and SPRM, with a particular emphasis on innovative methodological developments and emerging applications within the broader SPR research landscape. Key topics include advances in optical configuration, machine-learning-assisted analysis, nanoparticle and nanoscale object characterization, and the development of sensing platforms for biomarker assessment.

PurposeThis paper aims to improve the refractive index sensor performance for analytes with large refractive index by adopting the technology of microstructured fiber (MF) and surface plasmon resonance (SPR).Design/methodology/approachThe structure adopts an MF with a hexagonal lattice cladding structure composed of all-circular air holes, and three defect regions are introduced. The liquid analyte that needs to be tested is filled in the defect area. The surface plasmon polarition mode is generated and coupled with the core mode, thus forming a refractive index sensing channel. When the resonance conditions are satisfied, the resonance wavelength will be changed with the refractive index of the liquid analyte. All parameters that may affect the performance of the sensor are numerical simulated, and the structure is optimized through a large number of calculations.FindingsThe results demonstrate that the maximum dynamic sensitivity (SR) can reach to 24,260 nm/RIU, and the average sensitivity (SR-AV) can reach to 18,046 nm/RIU when the refractive index range is from 1.42 to 1.47. Besides, the sensitivity linearity (R2) is approximately 0.965, and its resolution is 4.1 x 10-6 RIU. The comparison with some literature results shown that the proposed sensor has certain advantages over the sensors reported in these literatures.Originality/valueThis work proposed an SPR-based refractive index sensor with a simple MF structure. It has a certain reference significance for the design and optimization of SPR-based MF sensors. Moreover, owing to its simple structure, high refractive index sensitivity and linear sensing performance, this sensor will play an important role in the detection of high refractive index liquid analytes.

Ultrasensitive detection of multiple diseases markers is of great importance in improving diagnostic accuracy, precision, and efficiency. A versatile Au nanozyme Raman probe strategy was employed to develop an ultrasensitive multiplex surface-enhanced Raman scattering (SERS) immunosensor using encoded silica photonic crystal beads (SPCBs). The efficient Au nanozyme Raman probe strategy was constructed using a robust Au nanozyme with high dual enzyme-like activity and SERS activity. On the one hand, Au nanozyme tags with oxidase-like activity can catalyze the oxidation of Raman-inactive 3,3' ,5,5' tetramethylbenzidine (TMB) to Raman-active oxidized TMB (ox-TMB) in the presence of O2 . On the other hand, Au nanozyme tags with peroxidase-like activity can catalyze Raman-inactive TMB to Ramanactive ox-TMB in the presence of H2 O2 . This dual catalysis action results in many Raman-active reporter molecules (ox-TMB) enabling highly sensitive detection. Meanwhile, the Au nanozyme as an extraordinary SERS substrate further enhances the detection signals of these Raman reporter molecules. Using reflection peaks of different SPCBs to encode tumor markers, an ultrasensitive multiplex SERS immunosensor was developed for detection of carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP), which exhibited wide linear ranges of 0.0 01-10 0 ng/mL for CEA and 0.01-10 0 0 ng/mL for AFP, accompanied by low detection limits of 0.66 pg/mL for CEA and 9.5 pg/mL for AFP, respectively. This work demonstrates a universal and promising nanozyme Raman probe strategy to develop ultrasensitive multiplex SERS immunosensors for precise clinical diagnosis of disease. (c) 2025 Published by Elsevier B.V. on behalf of Chinese Chemical Society and Institute of Materia Medica, Chinese Academy of Medical Sciences.

Curvature-sensitive proteins play important roles in cellular physiology. To study their interaction properties, reliable platforms of curved membrane mimics are key but current systems are limited by the requirement for fluorescent labels, which can modify membrane conformation and activity, leading to obscured description of interaction behavior as compared to native conditions. We report here the construction and application of a robust and tunable curved membrane interface for label-free surface plasmon resonance (SPR) based probing of the interactions with bridging integrator 1 (BIN1), a BAR-domain containing protein that has been linked to cancer and autoimmune diseases. The curvature was tuned with varying vesicle size, and surface charge was controlled by doping different content of ganglioside GM1. A twentyfold enhancement of BIN1 response was observed on 50-nm vesicles as compared to the flat SLB. Replacement of GM1 with neutral GA1 or reducing GM1 content from 1 % to 0.1 % in vesicles led to much lower response signal, suggesting the preference of negatively charged membranes in BIN1 binding. To demonstrate the application in complex media and for biomarker monitoring, we measured BIN1 in spiked urine samples, which showed excellent results. Small loss in signal was observed as compared to that in PBS buffer, which have been attributed to ionic compounds present in the urine sample that interfere with BIN1-membrane interactions. This work shows that the vesicle-based curved membrane proves to be an effective platform for investigating membrane-curvature sensing proteins and their biophysical interactions, and for quantifying protein markers in biological matrices by SPR.

Fundamental studies of uncommon plasmonic materials expand their potential applications in nanoplasmonics. In this work, nanometers thin films of indium, a plasmonic yet rarely explored metal, were characterized for its surface plasmon polariton (SPP) properties and the performance in surface plasmon resonance (SPR) sensing and surface-enhanced Raman spectroscopy (SERS). Direct deposition of indium films on glass slides exhibited coalescence of discrete particles and generated no SPR response due to gaps disrupting SPP propagation. Addition of a 2-nm Cr base layer reduced the particle size and produced a resonance dip under the Kretschmann configuration. SPR sensing with a 2/40 nm Cr/In film was demonstrated for the first time and compared to the standard 2/50 nm Cr/Au film, revealing a sensitivity approximately 77% that of the gold film. The optical properties of the passivating In2O3 layer are investigated through analogous RF magnetron sputtered In2O3 films to allow for improved computational modeling and optimization of the substrates for plasmonic applications. Low extinction coefficient (k) at typical SPR wavelengths (~650 nm) found for the oxide layer indicates minimal effects on SPR response. However, finite-difference time-domain (FDTD) simulations revealed that the presence of the oxide layer resulted in a >50% increase in the SERS enhancement in the UV range, while exhibiting little effect with incident light in the visible range. This work provides insights into the plasmonic properties of thin indium films for optical sensing applications and highlights the critical role of the oxide layer in wavelength-specific performance.

In this work, we report the plasmonic properties of aluminum films as substrate materials for multiple analytical platforms, including surface plasmon resonance (SPR) and MALDI-MS. The intrinsic optical sensitivity was characterized with ionic polymer coatings, lipid vesicles, and medically relevant biomarkers. In SPR imaging mode, the aluminum film allowed for the sensitive quantification of kinetic differences of binding interactions between the ionic polymer and biomarker peptides of CXCL8 and CXCL10. The binding was found to be correlated to the charge densities of the biomarkers and the polymer coating, and the use of an artificial urine matrix could alter the association behavior. The e-beam fabricated Al film was also shown to be effective for enriching phosphorylated peptides from milk proteins for mass spectrometric profiling. The surface-assisted ionization process was further investigated by comparing MALDI spectra of biomarkers obtained on conventional stainless steel plates, Au films, and Al films. Results indicate that aluminum films have m/z intensity values significantly higher than those on a steel plate and Au film, suggesting the electronic and plasmonic properties of aluminum thin films, especially those under UV conditions, may lead to an improved performance in MALDI signals. We believe that Al thin films have great potential as substrates for developing bioanalytical methods and can have vast benefits for the future study of biophysical interactions.

Alpha-synuclein is a presynaptic neuronal protein that is genetically and neuropathologically linked to Parkinson’s disease (PD), playing a critical role in the development of neurodegenerative disorders through its tendency to self-aggregate. However, its membrane-binding dynamics, especially in response to membrane curvature, remain poorly understood. Herein, we report the development and application of a tunable, curved membrane system built on an optical sensor platform for surface plasmon resonance (SPR) characterization of the protein-membrane interactions of alpha synuclein. Vesicles of varied size, lipid compositions, and charges were immobilized at the interface, enabling precise control of the interface with properties relevant to the effects on binding characteristics. Incorporation of cholesterol, sphingomyelin, and ganglioside (GM1) allowed the investigation of protein binding in a more biologically relevant membrane environment. Finally, the impact of a disaggregation agent on alpha synuclein binding was characterized to understand the disruption process. Our results demonstrate the capability of the optical biosensing system for studying complex protein-membrane interactions and facilitating the understanding of curvature-sensitive binding by alpha-synuclein.

Morphological changes of cancer cells are often used as an important indicator within efficiency studies of anticancer drugs. Morphological cell analysis on cell size and shape distribution is typically performed using microscopic methods, which are time consuming and require skilled personnel. Recently, more advanced image processing and pattern recognition have enabled identification and quantitative analysis of the cell’s abnormality and classification in an automated way. However, these methods usually involve multiple staining steps. In addition to computational complexity, the processes greatly compromise real-time applications of the system. Therefore, a non-invasive, real-time method allowing for assessment of living cells’ reactions to a death inducer is very much needed. Here, we present an SPR biosensor that measures the changes in cancer cells’ size and detachment, relating the cell confluency with the changes of the refractive index on the cell-substrate interface. As a proof-of-concept, we chose HeLa cell and hydrogen peroxide (H2O2) induced apoptosis as the model system to study the morphological changes of the cell. The results show that the SPR response to cell apoptosis agreed with the cellular morphological changes observed via microscopy. Interestingly, we observed simultaneous apoptosis and necrosis at high H2O2 concentrations. This simultaneous occurrence was verified using a mathematical model which incorporated other important factors such as cell thickness and intercellular refractive index. This model helped resolve the disagreement between SPR signal and cell confluency at high H2O2 concentrations. Our results show the potential of SPR as a label free and real time monitoring method for morphological changes and surface detachment of cancer cells. This method can be fully expanded to other cell-based sensing applications.

Clinically relevant matrices such as human blood and serum can cause substantial interference in biosensing measurements, severely compromising the effectiveness of the sensors. We report the characterization of a positively charged lipid membrane that has demonstrated unique features to suppress the nonspecific signal for antifouling effects by using SPR, fluorescence recovery after photobleaching (FRAP), and MALDI-TOF-MS. The ethylphosphocholine (EPC) lipid membrane proved to be exceptionally effective at reducing irreversible interactions from human serum on a Protein A surface. The membrane formation conditions and their effects on membrane fluidity and mobility were characterized for understanding the antifouling functions when various capture molecules were immobilized. Specifically, EPC lipid membranes on a Protein A substrate appear to exhibit a strong interaction, likely through the electrostatic effect with the negatively charged proteins that resulted in a stable hydration layer. The strong interaction also limited lipid mobility, contributing to a robust, protective interface that remained undamaged in undiluted serum. Tailoring a surface with antifouling lipid membranes allows for a range of biosensing applications in highly complex biological media.

3-Dimensional (3D) printing technology has greatly facilitated the recent advancements in science and engineering that benefit many aspects of scientific investigation, with examples including disease diagnostics, dentistry, aerospace, and fundamental research. For analytical chemistry, many advancements can be directly linked to achievements associated with 3D printing of optics, flow systems, mechanical/structural components, and parts related to detection/measurement, which before the advent of 3D printing were limited by complicated, cumbersome, expensive, and material-limited production. More importantly, the totality of these advances has made the possibility of 3D printing the majority of an analytical system an achievable reality. In this review, we highlight the recent achievements and advancements reported in literature that will facilitate the development of the next-generation analytical instrumentation through the use of 3D printing technology. A great deal of attention is given to those in the context of bioanalytical platforms and novel biosensing strategies. Limited by space, we will explicitly focus the discussion on the following areas: improvement/utilization of new printing materials, methods towards higher resolution, fabrication and production of optical components, novel microfluidic flow systems, and printed structural components for instrumentation.

Surface plasmon resonance (SPR) proves to be one of the most effective methods of label-free detection and has been integral for the study of biomolecular interactions and the development of biosensors. This trend delves into the latest SPR research and progress built upon the Kretschmann configuration, a pivotal platform, and highlights three key developments that have enhanced the capabilities of the technique. We will first cover a range of explorations of novel plasmonic materials that have shaped SPR performance. Innovative signal transduction and collection, which leverages traditional materials and emerging alternatives, will then be discussed. Finally, the evolving landscape of data analysis, including the integration of machine learning algorithms to navigate complex SPR datasets, will be reviewed. We will also discuss the implementation of these improvements that have enabled new biosensing functions. These advancements not only pave the way for enhanced biosensing in general but also open new avenues for the technique to play a more significant role in research concerning human health.

Abstract Lipidomic profiling has been linked to the detection of cancers as dysregulation of lipid metabolism is closely associated with many disease states. Current work on chip‐based profiling has been limited and is largely hindered by issues associated with the chip's sophisticated fabrication processes. We report here the design and fabrication of a highly efficient microfluidic mixer/extractor by using three‐dimensional (3D) printing technology for on‐chip cell lysis/enrichment for lipidomic profiling with matrix‐assisted laser desorption/ionization mass spectrometry (MALDI‐MS). The platform consists of a micropillar mixer for flow‐through lysis and an on‐chip reservoir to separate phases where the lipid‐enriched layer was collected for subsequent MS analysis. The mass transfer between the two phases was simulated by a computational fluid dynamics study, and the efficiency in cell lysis in different extraction solvent systems was characterized by fluorescence microscopy. Results showed increased performance in extraction with the micropillar mixer as compared with the standard Bligh‐Dyer method. For lipid profiling of C. reinhardtii cells by MALDI‐MS, over 65 lipid species from the monogalactosyldiacylglycerol, digalactosyldiacylglycerol, diacylglyceryltrimethylhomo‐Ser, and triacylglycerol lipid families have been identified. The effect of organic solvents on extraction and lipid profiles was also investigated, and the results indicated that the extractant formula has a diverse impact on the collection of certain types of lipid species, presenting useful guidance for the system to be applied to targeted enrichment of lipids with specific cells. The microfluidic chips by the 3D printing technique reported here offer new platforms potentially for clinical lipidomics and can provide a novel avenue in disease diagnosis.

A majority of biomimetic membranes used for current biophysical studies rely on planar structures such as supported lipid bilayer (SLB) and self-assembled monolayers (SAMs). While they have facilitated key information collection, the lack of curvature makes these models less effective for the investigation of curvature-dependent protein binding. Here, we report the development and characterization of curved membrane mimics on a solid substrate with tunable curvature and ease in incorporation of cellular membrane components for the study of protein-membrane interactions. The curved membranes were generated with an underlayer lipid membrane composed of DGS-Ni-NTA and POPC lipids on the substrate, followed by the attachment of histidine-tagged cholera toxin (his-CT) as a capture layer. Lipid vesicles containing different compositions of gangliosides, including GA(1), GM(1), GT(1b), and GQ(1b), were anchored to the capture layer, providing fixation of the curved membranes with intact structures. Characterization of the curved membrane was accomplished with surface plasmon resonance (SPR), fluorescence recovery after photobleaching (FRAP), and nano-tracking analysis (NTA). Further optimization of the interface was achieved through principal component analysis (PCA) to understand the effect of ganglioside type, percentage, and vesicle dimensions on their interactions with proteins. In addition, Monte Carlo simulations were employed to predict the distribution of the gangliosides and interaction patterns with single point and multipoint binding models. This work provides a reliable approach to generate robust, component-tuning, and curved membranes for investigating protein interactions more pertinently than what a traditional planar membrane offers.

A Surface Plasmon Resonance (SPR) biosensor based on an inhibition immunoassay was developed for the detection of diclofenac (DCF) in aqueous solution. Due to the small size of DCF, an hapten-protein conjugate was produced by coupling DCF to bovine serum albumin (BSA). DCF-BSA conjugate formation was confirmed via MALDI-TOF mass spectrometry. The resulting conjugate was immobilized onto the surface of a sensor fabricated via e-beam deposition of a 2 nm chromium adhesion layer followed by a 50 nm gold layer onto precleaned BK7 glass slides. Immobilization onto the nano thin gold surface was accomplished by covalent amide linkage through a self-assembled monolayer. Samples were composed of a mixture of antibody at a fixed concentration and DCF at different known concentrations in deionized water, causing the inhibition of anti-DCF on the sensor. The DCF-BSA was obtained with a ratio of 3 DCF molecules per BSA. A calibration curve was performed using concentrations between 2 and 32 μg L−1. The curve was fitted using the Boltzmann equation, reaching a limit of detection (LOD) of 3.15 μg L−1 and limit of quantification (LOQ) of 10.52 μg L−1, the inter-day precision was calculated and an RSD value of 1.96% was obtained; and analysis time of 10 min. The developed biosensor is a preliminary approach to the detection of DCF in environmental water samples, and the first SPR biosensor developed for DCF detection using a hapten-protein conjugate.

Monoclonal antibodies to oxytocin (OT) and vasopressin (VP) revealed some positively staining stromal cells in the subcapsular cortex and in the medulla of the human thymus. We further demonstrated that these cells are a subset of epithelial endocrine cells and also contain immunoreactive interleukin-1 together with the neuropeptides. In addition, the thymic cells stained by monoclonal antibodies directed to the cyclic part of oxytocin or vasopressin also contained some immunoreactive neurophysins. These data support the concept of intrathymic synthesis of neurohypophyseal-like peptides fitting the hypothalamic model. However, we observed that, contrary to the situation in the brain, OT- and VP-like peptides colocalized in the same thymic cells. Furthermore, one monoclonal antibody, specific for the tail part of oxytocin, did not label thymic cells. Therefore, thymic neuropeptide(s) could be related to, but distinct from, authentic OT and VP. These observations suggest some molecular differences between hypothalamic and thymic oxytocin biosynthetic pathways which need to be further investigated.

The correct detection and quantification of pollutants in water is key to regulating their presence in the environment. Biosensors offer several advantages, such as minimal sample preparation, short measurement times, high specificity and sensibility and low detection limits. The purpose of this review is to explore the different types of optical biosensors, focusing on their biological elements and their principle of operation, as well as recent applications in the detection of pollutants in water. According to our literature review, 33% of the publications used fluorescence-based biosensors, followed by surface plasmon resonance (SPR) with 28%. So far, SPR biosensors have achieved the best results in terms of detection limits. Although less common (22%), interferometers and resonators (4%) are also highly promising due to the low detection limits that can be reached using these techniques. In terms of biological recognition elements, 43% of the published works focused on antibodies due to their high affinity and stability, although they could be replaced with molecularly imprinted polymers. This review offers a unique compilation of the most recent work in the specific area of optical biosensing for water monitoring, focusing on both the biological element and the transducer used, as well as the type of target contaminant. Recent technological advances are discussed.

Herein, a "two-in-one" Ag@Au core-shell nanozyme probe inducing double-signal amplification has been developed to significantly elevate the sensitivity of SPR sensors via sandwich immunoassay. The Ag@Au core-shell nanozyme with intrinsic peroxide-like activity was demonstrated to catalyze a polymerization reaction leading to formation of polyaniline, allowing further improvement of detection performance of SPR immunosensor. The method demonstrated here offers a universal strategy for enhanced SPR detection and further expands the application of nanozymes.

A 3D printed microfluidic device with a micropillar mixer for onchip cell lysis and separation demonstrated with the algae cells. The enriched lipids are loaded onto a microarray for lipidomic profiling by MALDI-MS to reveal cytotoxicity effect and for disease diagnosis.

Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS)-based lipid profiling is a powerful method to study the cytotoxicity of chemical exposure to microorganisms at the single cell level. We report here a combined approach of machine learning (ML) and microchip-based MALDI-time of flight (TOF) mass spectrometry to investigate the cytotoxic effect of herbicides on algae through single cell lipid profiling. Algal species Selenastrum capricornutum was chosen as the target system, and its exposure to different doses of common chemical herbicides and the resulting cytotoxic behaviors under various stress conditions were characterized. A lipid library for S. capricornutum has been established with 63 identified lipids that include glycosyldiacylglycerols and triacylglycerols. We demonstrated that major alternations occurred for lipids with functional groups of digalactosyldiacylglycerol (DGDG), triacylglycerol (TAG), and monogalactosyldiacylglycerol (MGDG). DGDG was shown to decrease upon exposure to herbicides of norflurazon and atrazine, while some MGDG and TAG lipids would increase for norflurazon. Compared to other algae, S. capricornutum was more strongly impacted by norflurazon than atrazine while the latter was observed to have a greater effect on C. reinhardtii. Machine learning algorithms have been applied to improve the classification of herbicide impact and help identify lipid species affected by the chemical exposure. A total of 69 machine learning models were trained and tested for the identification of ideal algorithms in the classification process, in which flexible discriminant analysis and support vector machine model were found to be the most accurate and consistent. The ML algorithms accurately differentiated herbicide impact and have identified cytotoxic differences that were previously hidden. The results suggest that herbicides express toxicity among different algae likely on the basis of metabolic differences. The ML-assisted method proves to be highly effective and can provide an advanced technological platform for probing cytotoxicity for bacterial species and in metabolic pathway analysis.

SBECD (Captisol (R)) with an average degree of substitution of 6.5 sulfobutylether functional groups (SBE = 6.5), is a solubility enhancer for remdesivir (RDV) and a major component in Veklury, which was approved by FDA for the treatment of patients with COVID-19 over 12 years old and weighing over 40 kg who require hospitalization. SBECD is cleared mainly by renal filtration, thus, potential accumulation of SBECD in the human body is a concern for patients dosed with Veklury with compromised renal function. An LC-MS/MS method was developed and validated for specific, accurate, and precise determination of SBECD concentrations in human plasma. In this method, the hexa-substituted species, SBE6, was selected for SBECD quantification, and the mass transition from its dicharged molecular ion [(M-2H)/2]2-, Molecular (parent) Ion (Q1)/Molecular (parent) Ion (Q3) of m/z 974.7/974.7, was selected for quantitative analysis of SBECD. Captisol-G (SBE-gamma-CD, SBE = 3) was chosen as the internal standard. With 25 mu L of formic-acid-treated sample and with a calibration range of 10.0-1000 mu g/mL, the method was validated with respect to pre-established criteria based on regulatory guidelines and was applied to determine SBECD levels in plasma samples collected from pediatric patients during RDV clinical studies.