Extended Kalman Filtering Projection Method to Reduce the 3σ Noise Value of Optical Biosensors

AI integration into wavelength-based SPR biosensing: Advancements in spectroscopic analysis and detection

BACKGROUND

In recent years, employing deep learning methods in the biosensing area has significantly reduced data analysis time and enhanced data interpretation and prediction accuracy. In some SPR fields, research teams have further enhanced detection capabilities using deep learning techniques. However, the application of deep learning to spectroscopic surface plasmon resonance (SPR) biosensors has not been reported. This study addresses the integration of AI methods to improve the signal-to-noise ratio (SNR) and detection accuracy of wavelength-based portable SPR biosensors.

RESULTS

We designed a deep neural network integrated with the spectral subtraction method to extract SPR responses from the proposed portable SPR biosensor. Using difference spectra as the model input, our AI model provided superior noise reduction and enhanced detection capabilities, outperforming traditional spectral feature extraction methods like dip or centroid positioning. Our study achieved a significantly amplified SNR and improved detection resolution to an impressive 10-7 RIU level. In addition, we employ Shapley Additive Explanations (SHAP) analysis to determine which parts of the input the AI model considers most important when extracting SPR response, thereby increasing the interpretability and transparency of the AI model. The results indicate that the wavelength regions considered most important by our proposed AI model are very close to the full width at half maximum (FWHM) range. This region is also recognized by traditional theory as having a significant impact on the sensitivity of SPR sensing.

SIGNIFICANCE

Integrating AI into wavelength-based portable SPR biosensing represents a significant advancement in on-site detection technologies, driving potential applications across various monitoring scenarios. Our findings highlight the AI model's effectiveness in reducing noise and enhancing detection accuracy, particularly in measurements involving low-concentration analytes. This innovation holds great promise for fields that demand real-time, high-precision, on-site detection, such as biomedical diagnostics, environmental monitoring, and biochemical analysis, setting the stage for transformative shifts in these critical areas.

A Review on Perception of Binding Kinetics in Affinity Biosensors: Challenges and Opportunities

There are challenges associated with design and development of affinity biosensors due to the complicated multiphysics nature of the system. Understanding the binding interaction between target molecules and immobilized receptors and its kinetics is a crucial step to develop robust and reliable biosensor technologies. Evaluation of binding kinetics in biosensors becomes more important and challenging for clinical samples with a complex matrix. Despite drastic advancements in biosensor technologies, having a practical perception of the binding kinetics has remained a critical bottleneck due to limited fundamental understanding. This Review aims to provide a comprehensive discussion on concepts and advances developed so far for the perception of binding kinetics in affinity biosensors. Here, modeling approaches and measurement techniques are presented to characterize the binding interactions in biosensor technologies, while the effect of fouling and secondary factors in the binding interactions will be discussed in the concept of kinetics. This Review will investigate the existing research gaps and potential opportunities in the perception of binding kinetics and challenges to develop robust and reliable biosensors.

On the reproducibility of electron-beam lithographic fabrication of photonic nanostructures

Photonic nanostructures such as gratings and ring resonators have become ubiquitous building blocks in Photonics. For example, they are used in filters, they resonantly enhance signals and act as grating couplers. Much research effort is invested in using such structures to create novel functionalities, which often employs electron-beam lithography. An intrinsic issue in this field is the ability to accurately achieve a specific operating wavelength, especially for resonant systems, because nanometer-scale variations in feature size may easily detune the device. Here, we examine some of the key fabrication steps and show how to improve the reproducibility of fabricating wavelength scale photonic nanostructures. We use guided mode resonance grating sensors as our exemplar and find that the exposure condition and the development process significantly affect the consistency of the resonance wavelength, amplitude, and sensitivity of the sensor. By having careful control over these factors, we can achieve consistent performance for all the sensors studied, with less than 10% variation in their resonance behaviors. These investigations provide useful guidelines for fabricating nanostructures more reliably and to achieve a higher success rate in exploratory experiments.

Quantum Plexcitonic Sensing

While fundamental to quantum sensing, quantum state control has been traditionally limited to extreme conditions. This restricts the impact of the practical implementation of quantum sensing on a broad range of physical measurements. Plexcitons, however, provide a promising path under ambient conditions toward quantum state control and thus quantum sensing, owing to their origin from strong plasmon-exciton coupling. Herein, we harness plexcitons to demonstrate quantum plexcitonic sensing by strongly coupling excitonic particles to a plasmonic hyperbolic metasurface. As compared to classical sensing in the weak-coupling regime, our model of quantum plexcitonic sensing performs at a level that is ∼40 times more sensitive. Noise-modulated sensitivity studies reinforce the quantum advantage over classical sensing, featuring better sensitivity, smaller sensitivity uncertainty, and higher resilience against optical noise. The successful demonstration of quantum plexcitonic sensing opens the door for a variety of physical, chemical, and biological measurements by leveraging strongly coupled plasmon-exciton systems.

Intensity-Based Camera Setup for Refractometric and Biomolecular Sensing with a Photonic Crystal Microfluidic Chip

Label-free sensing is a promising approach for point-of-care testing devices. Among optical transducers, photonic crystal slabs (PCSs) have positioned themselves as an inexpensive yet versatile platform for label-free biosensing. A spectral resonance shift is observed upon biomolecular binding to the functionalized surface. Commonly, a PCS is read out by a spectrometer. Alternatively, the spectral shift may be translated into an intensity change by tailoring the system response. Intensity-based camera setups (IBCS) are of interest as they mitigate the need for postprocessing, enable spatial sampling, and have moderate hardware requirements. However, they exhibit modest performance compared with spectrometric approaches. Here, we show an increase of the sensitivity and limit of detection (LOD) of an IBCS by employing a sharp-edged cut-off filter to optimize the system response. We report an increase of the LOD from (7.1 ± 1.3) × 10^-4 RIU to (3.2 ± 0.7) × 10^-5 RIU. We discuss the influence of the region of interest (ROI) size on the achievable LOD. We fabricated a biochip by combining a microfluidic and a PCS and demonstrated autonomous transport. We analyzed the performance via refractive index steps and the biosensing ability via diluted glutathione S-transferase (GST) antibodies (1:250). In addition, we illustrate the speed of detection and demonstrate the advantage of the additional spatial information by detecting streptavidin (2.9 µg/mL). Finally, we present the detection of immunoglobulin G (IgG) from whole blood as a possible basis for point-of-care devices.

Label-free multiplex sensing from buffer and immunoglobulin G sensing from whole blood with photonic crystal slabs using angle-tuning of an optical interference filter

Direct detection of biomarkers from unpurified whole blood has been a challenge for label-free detection platforms, such as photonic crystal slabs (PCS). A wide range of measurement concepts for PCS exist, but exhibit technical limitations, which render them unsuitable for label-free biosensing with unfiltered whole blood. In this work, we single out the requirements for a label-free point-of-care setup based on PCS and present a wavelength selecting concept by angle tuning of an optical interference filter, which fulfills these requirements. We investigate the limit of detection (LOD) for bulk refractive index changes and obtain a value of 3.4 E-4 refractive index units (RIU). We demonstrate label-free multiplex detection for different types of immobilization entities, including aptamers, antigens, and simple proteins. For this multiplex setup we detect thrombin at a concentration of 6.3 µg/ml, antibodies of glutathione S-transferase (GST) diluted by a factor of 250, and streptavidin at a concentration of 33 µg/ml. In a first proof of principle experiment, we demonstrate the ability to detect immunoglobulins G (IgG) from unfiltered whole blood. These experiments are conducted directly in the hospital without temperature control of the photonic crystal transducer surface or the blood sample. We set the detected concentration levels into a medical frame of reference and point out possible applications.

CRISPR/Cas Precisely Regulated DNA-Templated Silver Nanocluster Fluorescence Sensor for Meat Adulteration Detection

Meat adulteration can cause consumer fraud, food allergies, and religious issues. Rapid and sensitive detection methods are urgently demanded to supervise meat authenticity. Herein, a clustered regularly interspaced short palindromic repeats (CRISPR)/Cas precisely regulated DNA-templated silver nanocluster (DNA-AgNC) sensor was ingeniously designed to detect meat adulteration. Specific sequence recognition of CRISPR/Cas12a allowed accurate identification of target DNA. The emerging label-free fluorescent probes, DNA-AgNCs, a class of promising fluorophores in biochemical analysis with attractive photostability and remarkably enhanced fluorescence properties, were first introduced as the substrates of CRISPR/Cas12a system, allowing a sensitive output of amplified signals through the precise regulation of the unique target DNA-activated trans-cleavage activity of Cas12a. Based on this specific recognition, efficient signal transduction of CRISPR/Cas12a, and the outstanding fluorescence properties of DNA-AgNCs, the proposed strategy achieved a satisfactory linear range from 10 pM to 1 μM with a limit of detection (LOD) as low as 1.9 pM, which can achieve sensitive detection of meat adulteration.

Metasurface-enhanced mid-infrared spectroscopy in the liquid phase

Vibrational spectroscopy is an important tool in chemical and biological analysis. A key issue when applying vibrational spectroscopy to dilute liquid samples is the inherently low sensitivity caused by short interaction lengths and small extinction coefficients, combined with low target molecule concentrations. Here, we introduce a novel type of surface-enhanced infrared absorption spectroscopy based on the resonance of a dielectric metasurface. We demonstrate that the method is suitable for probing vibrational bands of dilute analytes with a range of spectral linewidths. We observe that the absorption signal is enhanced by 1-2 orders of magnitude and show that this enhancement leads to a lower limit of detection compared to attenuated total reflection (ATR). Overall, the technique provides an important addition to the spectroscopist's toolkit especially for probing dilute samples.

Time-Resolved Thickness and Shape-Change Quantification using a Dual-Band Nanoplasmonic Ruler with Sub-Nanometer Resolution

Time-resolved measurements of changes in the size and shape of nanobiological objects and layers are crucial to understand their properties and optimize their performance. Optical sensing is particularly attractive with high throughput and sensitivity, and label-free operation. However, most state-of-the-art solutions require intricate modeling or multiparameter measurements to disentangle conformational or thickness changes of biomolecular layers from complex interfacial refractive index variations. Here, we present a dual-band nanoplasmonic ruler comprising mixed arrays of plasmonic nanoparticles with spectrally separated resonance peaks. As electrodynamic simulations and model experiments show, the ruler enables real-time simultaneous measurements of thickness and refractive index variations in uniform and heterogeneous layers with sub-nanometer resolution. Additionally, nanostructure shape changes can be tracked, as demonstrated by quantifying the degree of lipid vesicle deformation at the critical coverage prior to rupture and supported lipid bilayer formation. In a broader context, the presented nanofabrication approach constitutes a generic route for multimodal nanoplasmonic optical sensing.

Inverse designed plasmonic metasurface with parts per billion optical hydrogen detection

Plasmonic sensors rely on optical resonances in metal nanoparticles and are typically limited by their broad spectral features. This constraint is particularly taxing for optical hydrogen sensors, in which hydrogen is absorbed inside optically-lossy Pd nanostructures and for which state-of-the-art detection limits are only at the low parts-per-million (ppm) range. Here, we overcome this limitation by inversely designing a plasmonic metasurface based on a periodic array of Pd nanoparticles. Guided by a particle swarm optimization algorithm, we numerically identify and experimentally demonstrate a sensor with an optimal balance between a narrow spectral linewidth and a large field enhancement inside the nanoparticles, enabling a measured hydrogen detection limit of 250 parts-per-billion (ppb). Our work significantly improves current plasmonic hydrogen sensor capabilities and, in a broader context, highlights the power of inverse design of plasmonic metasurfaces for ultrasensitive optical (gas) detection.

Plasmonic hydrogen sensors have limited sensitivity due to broad spectral features. Here, the authors use a particle swarm optimization algorithm to inversely design a plasmonic metasurface based on a periodic array of Pd nanoparticles, and demonstrate hydrogen detection limit of 250 ppb.

Beyond Q: The Importance of the Resonance Amplitude for Photonic Sensors

Resonant photonic sensors are enjoying much attention based on the worldwide drive toward personalized healthcare diagnostics and the need to better monitor the environment. Recent developments exploiting novel concepts such as metasurfaces, bound states in the continuum, and topological sensing have added to the interest in this topic. The drive toward increasingly higher quality (Q)-factors, combined with the requirement for low costs, makes it critical to understand the impact of realistic limitations such as losses on photonic sensors. Traditionally, it is assumed that the reduction in the Q-factor sufficiently accounts for the presence of loss. Here, we highlight that this assumption is overly simplistic, and we show that losses have a stronger impact on the resonance amplitude than on the Q-factor. We note that the effect of the resonance amplitude has been largely ignored in the literature, and there is no physical model clearly describing the relationship between the limit of detection (LOD), Q-factor, and resonance amplitude. We have, therefore, developed a novel, ab initio analytical model, where we derive the complete figure of merit for resonant photonic sensors and determine their LOD. In addition to highlighting the importance of the optical losses and the resonance amplitude, we show that, counter-intuitively, optimization of the LOD is not achieved by maximization of the Q-factor but by counterbalancing the Q-factor and amplitude. We validate the model experimentally, put it into context, and show that it is essential for applying novel sensing concepts in realistic scenarios.

Single-Molecule Identification of the Conformations of Human C-Reactive Protein and Its Aptamer Complex with Solid-State Nanopores

Human C-reactive protein (CRP) is an established inflammatory biomarker and was proved to be potentially relevant to disease pathology and cancer progression. A large body of methodologies have been reported for CRP analysis, including electrochemical/optical biosensors, aptamer, or antibody-based detection. Although the detection limit is rather low until pg/uL, most of which are time-consuming and relatively expensive, and few of them provided CRP single-molecule information. This work demonstrated the nanopore-based approach for the characterization of CRP conformation under versatile conditions. With an optimized pore of 14 nm in diameter, we achieved the detection limit as low as 0.3 ng/μL, voltage polarity significantly influences the electro-osmotic force and CRP translocation behavior, and the pentameric conformation of CRP may dissociate into pro-inflammatory CRP isoforms and monomeric CRP at bias potential above 300 mV. CRP tends to translocate through nanopores faster along with the increase in pH values, due to more surface charge on both CRP and pore inner wall and stronger electro-osmotic force. The CRP could specifically bind with its aptamer of different concentrations to form complexes, and the complexes exhibited distinguishable nanopore translocation behavior compared with CRP alone. The variation of the molar ratio of aptamer significantly influences the orientation of CRP translocation. The plasma test under physiological conditions displayed the ability of the nanopore system on the CRP identification with a concentration of 3 ng/μL.

SARS-CoV-2 Tests: Bridging the Gap between Laboratory Sensors and Clinical Applications

This review covers emerging biosensors for SARS-CoV-2 detection together with a review of the biochemical and clinical assays that are in use in hospitals and clinical laboratories. We discuss the gap in bridging the current practice of testing laboratories with nucleic acid amplification methods, and the robustness of assays the laboratories seek, and what emerging SARS-CoV-2 sensors have currently addressed in the literature. Together with the established nucleic acid and biochemical tests, we review emerging technology and antibody tests to determine the effectiveness of vaccines on individuals.