Broadband polarimetric glucose determination in protein containing media using characteristic optical rotatory dispersion

Extracting Superficial Scattering by Q-Sensing Technique

Optical properties determine how light interacts with biological tissues. The current methods for measuring these optical properties are influenced by both deep and superficial skin layers. Polarization-based methods have been proposed in order to determine the influence of deep layer scattering. Polarized light allows for the separation of ballistic photons from diffuse ones, enhancing image contrast and resolution while providing additional tissue information. The Q-sensing technique captures co-polarizedI ∥ $$ \left({I}_{\parallel}\right) $$ and cross-polarizedI ⊥ $$ \left({I}_{\perp}\right) $$ signals, making it possible to isolate the superficial scattering. However, the random structure of tissues leads to rapid depolarization of the polarized light. Detecting where the light becomes depolarized aids in sensing abnormalities within the tissues. Hence, this research focuses on identifying where depolarization occurs within the tissue. Tissue-mimicking phantoms, simulating the optical properties of biological tissues, are created to measure depolarization at various thicknesses. Experimental findings are validated with a Monte Carlo simulation, modeling polarized light behavior through the polydisperse tissue (as the tissue scatterers are heterogeneous in size). Additionally, the research demonstrates how polarized light can extract the optical properties of the medium.

An automatic glucose monitoring system based on periplasmic binding proteins for online bioprocess monitoring

Glucose is one of the most vital nutrients in all living organisms, so its monitoring is critical in healthcare and bioprocessing. Enzymatic sensors are more popular as a technology solution to meet the requirement. However, periplasmic binding proteins have been investigated extensively for their high sensitivity, enabling microdialysis sampling to replace existing complex and expensive glucose monitoring solutions based on enzymatic sensors. The binding proteins are used as optical biosensors by introducing an environment-sensitive fluorophore to the protein. The biosensor's construction, characterization, and potential application are well studied, but a complete glucose monitoring system based on it is yet to be reported. This work documents the development of the first glucose sensor prototype based on glucose binding protein (GBP) for automatic and continuous glucose measurements. The development includes immobilizing the protein into reusable chips and a low-cost solution for non-invasive glucose sampling in bioprocesses using microdialysis sampling technique. A program was written in LabVIEW to accompany the prototype for the complete automation of measurement. The sampling technique allowed glucose measurements of a few micromolar to 260 mM glucose levels. A thorough analysis of the sampling mode and the device's performance was conducted. The reported measurement accuracy was 81.78%, with an RSD of 1.83%. The prototype was also used in online glucose monitoring of E. coli cell culture. The mode of glucose sensing can be expanded to the measurement of other analytes by switching the binding proteins.

Atom-based optical polarization modulator

In this work, we employ 87Rb atoms as rotation media to manipulate the polarization of optical fields in both magnetic and magnetic-free environments. Employing the nonlinear magneto-optical rotation mechanism, we achieve a state-of-the-art magneto-optical rotation coefficient of 1.74×108 rad⋅T-1⋅m-1 which is four orders of magnitude higher than commonly employed materials. Additionally, in a magnetic-free environment, we achieve all-optical cross-polarization modulation between the pump and probe light via Rb atoms. The nonlinear magneto-optical rotation configuration introduces inventive techniques for a new type of magneto-optical modulator while the all-optical configuration paves the way for exploring photonic integrated circuit (PIC) devices free from disruptions caused by electrical or magnetic crosstalk.

Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians

Diabetes Mellitus incidence and its negative outcomes have dramatically increased worldwide and are expected to further increase in the future due to a combination of environmental and social factors. Several methods of measuring glucose concentration in various body compartments have been described in the literature over the years. Continuous advances in technology open the road to novel measuring methods and innovative measurement sites. The aim of this comprehensive review is to report all the methods and products for non-invasive glucose measurement described in the literature over the past five years that have been tested on both human subjects/samples and tissue models. A literature review was performed in the MDPI database, with 243 articles reviewed and 124 included in a narrative summary. Different comparisons of techniques focused on the mechanism of action, measurement site, and machine learning application, outlining the main advantages and disadvantages described/expected so far. This review represents a comprehensive guide for clinicians and industrial designers to sum the most recent results in non-invasive glucose sensing techniques' research and production to aid the progress in this promising field.

Method for determination of optical rotatory dispersion curve by using a polarization axis finder

We report a new, to the best of our knowledge, measurement method of optical rotatory dispersion (ORD) based on a polarization axis finder (PAF) and digital image processing. The collimated quasi-monochromatic light is output by a monochromator and passes through a polarizer and the chiral samples, and a PAF is employed to modulate the light beam spatially to form an "hourglass" intensity pattern, which is utilized to determine the polarization direction of linearly polarized light. After being recorded by a digital camera, the modulated patterns with and without samples are analyzed by our specially designed digital image processing program to calculate the optical rotation (OR) angle of the chiral substance at a certain wavelength, and the ORD curve can be obtained by fitting a series of OR angles with different wavelengths. The ORD curves of two standard quartz plates with opposite chirality and a glucose solution with different concentrations are measured experimentally, and the fitted coefficients and measurement results agree well with their theoretical values, which indicates that the presented method is an effective and accurate way to determine the ORD of chiral substances conveniently.

In vitro glucose concentration measurement by a reusable enzymatic glucose sensor and a highly stable circular heterodyne polarimeter

A reliable glucose concentration measurement system was proposed that consisted of a circular heterodyne polarimeter and a reusable enzymatic sensor. The circular heterodyne polarimeter was constructed using a highly stable circular heterodyne light source and a compact alignment-free apparatus that provided phase stability of less than 1° within 20 min. The reusable enzymatic glucose sensor can be reused more than 100 times and retain 90% of its initial performance under optimum storage conditions within a month. The proposed method can be used to determine glucose concentrations in aqueous solutions and human serum. The optimum resolution of the proposed method was approximately 0.88 mg/dl for the glucose solution and 0.68 mg/dl for the serum-based sample.

Dual-Retarder Mueller Polarimetry System for Extraction of Optical Properties of Serum Albumin Protein Media

A dual liquid-crystal variable retarder Mueller polarimetry system incorporating a gold-based surface plasmon resonance prism coupler was proposed for extracting the optical properties of serum albumin protein media in the reflectance configuration. The feasibility of the proposed system was demonstrated by measuring the circular dichroism and circular birefringence properties of glucose tissue phantom solutions with different albumin concentrations. The results showed that the circular dichroism increased with albumin concentration, while the optical rotation angle increased with glucose concentration. Both properties reduced over time as a result of the protein glycation effect, which led to a gradual reduction in the glucose content of the sample.

Review of optical sensing and manipulation of chiral molecules and nanostructures with the focus on plasmonic enhancements [Invited]

Chiral molecules are ubiquitous in nature; many important synthetic chemicals and drugs are chiral. Detecting chiral molecules and separating the enantiomers is difficult because their physiochemical properties can be very similar. Here we review the optical approaches that are emerging for detecting and manipulating chiral molecules and chiral nanostructures. Our review focuses on the methods that have used plasmonics to enhance the chiroptical response. We also review the fabrication and assembly of (dynamic) chiral plasmonic nanosystems in this context.

Polarimetric Measurements of Surface Chirality Based on Linear and Nonlinear Light Scattering

A molecule, molecular aggregate, or protein that cannot be superimposed on its mirror image presents chirality. Most living systems are organized by chiral building blocks, such as amino acids, peptides, and carbohydrates, and any change in their molecular structure (i.e., handedness or helicity) alters the biochemical and pharmacological functions of the molecules, many of which take place at surfaces. Therefore, studying surface chirogenesis at the nanoscale is fundamentally important and derives various applications. For example, since proteins contain highly ordered secondary structures, the intrinsic chirality can be served as a signature to measure the dynamics of protein adsorption and protein conformational changes at biological surfaces. Furthermore, a better understanding of chiral recognition and separation at bio-nanointerfaces is helpful to standardize chiral drugs and monitor the synthesis of adsorbents with high precision. Thus, exploring the changes in surface chirality with polarized excitations would provide structural and biochemical information of the adsorbed molecules, which has led to the development of label-free and noninvasive measurement tools based on linear and nonlinear optical effects. In this review, the principles and selected applications of linear and nonlinear optical methods for quantifying surface chirality are introduced and compared, aiming to conceptualize new ideas to address critical issues in surface biochemistry.

Non-Invasive Glucose Monitoring Using Optical Sensor and Machine Learning Techniques for Diabetes Applications

Diabetes is a major public health challenge affecting more than 451 million people. Physiological and experimental factors influence the accuracy of non-invasive glucose monitoring, and these need to be overcome before replacing the finger prick method. Also, the suitable employment of machine learning techniques can significantly improve the accuracy of glucose predictions. One aim of this study is to use light sources with multiple wavelengths to enhance the sensitivity and selectivity of glucose detection in an aqueous solution. Multiple wavelength measurements have the potential to compensate for errors associated with inter- and intra-individual differences in blood and tissue components. In this study, the transmission measurements of a custom built optical sensor are examined using 18 different wavelengths between 410 and 940 nm. Results show a high correlation value (0.98) between glucose concentration and transmission intensity for four wavelengths (485, 645, 860 and 940 nm). Five machine learning methods are investigated for glucose predictions. When regression methods are used, 9% of glucose predictions fall outside the correct range (normal, hypoglycemic or hyperglycemic). The prediction accuracy is improved by applying classification methods on sets of data arranged into 21 classes. Data within each class corresponds to a discrete 10 mg/dL glucose range. Classification based models outperform regression, and among them, the support vector machine is the most successful with F1-score of 99%. Additionally, Clarke error grid shows that 99.75% of glucose readings fall within the clinically acceptable zones. This is an important step towards critical diagnosis during an emergency patient situation.