In this study, a nanoscale surface plasmon resonance (SPR) sensor was developed to determine the ovarian cancer marker carbohydrate antigen (CA) 125 level in serum utilizing the molecular imprinting method. For this, CA 125-imprinted poly(2-hydroxyethyl methacrylate-N-methacryloyl-(L)-tryptophan methyl ester) (p(HEMA-MATrp)) nanoparticles (NPs) were synthesized and used to coat the SPR gold chip surface. Additionally, non-imprinted p(HEMA-MATrp) nanoparticles were prepared as a control. SEM imaging, FTIR-ATR and Zeta Sizer analysis were performed for the characterization of the synthesized NPs, and the nanoscale chip surface was also characterized using BET, ellipsometry and contact angle measurements. The capability of the developed nanoscale sensor system was evaluated using the CA 125 biomarker in the concentration range of 0.1–10 U mL⁻¹. Ultrasensitive CA 125 glycoprotein detection was achieved with a low limit of detection value of 0.01 U mL⁻¹. The Langmuir adsorption model was found to be the best-suited model for expounding the interaction between the CA 125-imprinted p(HEMA-MATrp) NP chip and the CA 125 glycoprotein. In order to study the selectivity of the sensor, CA 125, human serum albumin and lysozyme were applied to the system. The highest response was obtained for CA 125. Additionally, real-sample studies were performed using artificial serum. The results showed that the developed sensor system was very effective in determining CA 125 levels even in complex media. The nanoscale chip was reused five times to detect CA 125 without any significant reduction in binding capacity, and the chip was stable for over five months. These results indicated that a precise detection method with high sensitivity, selectivity, and reliability in order to determine the level of CA 125 ovarian cancer biomarker in serum was successfully developed.

Viral infections can pose a major threat to public health by causing serious illness, leading to pandemics, and burdening healthcare systems. The global spread of such infections causes disruptions to every aspect of life including business, education, and social life. Fast and accurate diagnosis of viral infections has significant implications for saving lives, preventing the spread of the diseases, and minimizing social and economic damages. Polymerase chain reaction (PCR)-based techniques are commonly used to detect viruses in the clinic. However, PCR has several drawbacks, as highlighted during the recent COVID-19 pandemic, such as long processing times and the requirement for sophisticated laboratory instruments. Therefore, there is an urgent need for fast and accurate techniques for virus detection. For this purpose, a variety of biosensor systems are being developed to provide rapid, sensitive, and high-throughput viral diagnostic platforms, enabling quick diagnosis and efficient control of the virus’s spread. Optical devices, in particular, are of great interest due to their advantages such as high sensitivity and direct readout. The current review discusses solid-phase optical sensing techniques for virus detection, including fluorescence-based sensors, surface plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), optical resonators, and interferometry-based platforms. Then, we focus on an interferometric biosensor developed by our group, the single-particle interferometric reflectance imaging sensor (SP-IRIS), which has the capability to visualize single nanoparticles, to demonstrate its application for digital virus detection.

Pathogenic microorganisms and viruses can easily transfer from one host to another and cause disease in humans. The determination of these pathogens in a time- and cost-effective way is an extreme challenge for researchers. Rapid and label-free detection of pathogenic microorganisms and viruses is critical in ensuring rapid and appropriate treatment. Sensor technologies have shown considerable advancements in viral diagnostics, demonstrating their great potential for being fast and sensitive detection platforms. In this review, we present a summary of the use of an interferometric reflectance imaging sensor (IRIS) for the detection of microorganisms. We highlight low magnification modality of IRIS as an ensemble biomolecular mass measurement technique and high magnification modality for the digital detection of individual nanoparticles and viruses. We discuss the two different modalities of IRIS and their applications in the sensitive detection of microorganisms and viruses.

Wet Age-related macular degeneration (AMD) is the leading cause of vision loss in industrialized nations, often resulting in blindness. Biologics, therapeutic agents derived from biological sources, have been effective in AMD, albeit at a high cost. Due to the high cost of AMD treatment, it is critical to determine the binding affinity of biologics to ensure their efficacy and make quantitative comparisons between different drugs. This study evaluates the in vitro VEGF binding affinity of two drugs used for treating wet AMD, monoclonal antibody-based bevacizumab and fusion protein-based aflibercept, performing quantitative binding measurements on an Interferometric Reflectance Imaging Sensor (IRIS) system. Both biologics can inhibit Vascular Endothelial Growth Factor (VEGF). For comparison, the therapeutic molecules were immobilized on to the same support in a microarray format, and their real-time binding interactions with recombinant human VEGF (rhVEGF) were measured using an IRIS. The results indicated that aflibercept exhibited a higher binding affinity to VEGF than bevacizumab, consistent with previous studies using ELISA and SPR. The IRIS system’s innovative and cost-effective features, such as silicon-based semiconductor chips for enhanced signal detection and multiplexed analysis capability, offer new prospects in sensor technologies. These attributes make IRISs a promising tool for future applications in the development of therapeutic agents, specifically biologics.