Selection of appropriate protein assay method for a paper microfluidics platform

Expedient measurement of total protein in human serum and plasma via the biuret method using fiber optic probe for patient samples and certified reference materials

The biuret method is currently recognized as a reference measurement procedure for serum/plasma total protein by the Joint Committee for Traceability in Laboratory Medicine (JCTLM). However, as the reaction involved in this method is highly time-dependent, to ensure identical measurement conditions for calibrator and samples for high accuracy, a fast and simple measurement procedure is critical to ensure the precision and trueness of this method. We measured serum/plasma total protein using a Cary 60 spectrophotometer coupled with a fiber optic probe, which was faster and simpler than the conventional cuvette method. The biuret method utilizing alkaline solutions of copper sulfate and potassium sodium tartrate was added to the sample and calibrator (NIST SRM 927e) incubated for 1 h before measurement. A panel of samples consisting of pooled human serum, single donor serum, and certified reference materials (CRMs) from three sources were measured for method validation. Sixteen native patient samples were measured using the newly developed biuret method and compared against clinical analyzers. Additionally, the results of three cycles of a local External Quality Assessment (EQA) Programme submitted by participating clinical laboratories were compared against the biuret method. Our biuret method using fiber optic probe demonstrated good precision with within-day relative standard deviation (RSD) of 0.04 to 0.23% and between-day RSD of 0.58%. The deviations between the obtained values and the certified values for all three CRMs ranged from -0.38 to 1.60%, indicating good method trueness. The routine methods using clinical analyzers were also found to agree well with the developed biuret method using fiber optic probe for EQA samples and native patient samples. The biuret method using a fiber optic probe represented a convenient and reliable way of measuring serum total protein. It also demonstrated excellent precision and trueness using CRMs and patient samples, which made the method a simpler candidate reference method for serum protein measurement.

Mathematical processing of RGB data in microfluidic paper-based analytical devices

Microfluidic paper-based analytical devices often are combined with scanners as detectors. In this work, different scanning options offered by scanners: resolution, scanning mode, exposure to radiation, colour restoration, and saving format were tested. Moreover, different attempts to mathematical data treatment based on intensities of three channels-Red, Green and Blue, were studied. All measurements presented in this article were conducted for a model dye-bromothymol blue and a model analyte-zinc(II) ion (complexed with xylenol orange in a paper matrix). The article summarizes the scanning options and possibilities of mathematical calculations. Nevertheless, it is suggested that the best option is to use the prior prepared calculation file to paste obtained intensities and compare all presented in this article (and the most frequently used) equations to process intensities and decide which one should be used in the particular analysis.

Paper microzone assay embedded on a 3D printed support for colorimetric quantification of proteins in different biological and food samples

This study describes the development of a paper microzone colorimetric assay embedded on a 3D printed support for quantifying total protein content in different biological matrices and foods. The aim was to develop an accurate and reliable method, ensuring at the same time the possibility of customizability, facility of use, wide applicability, and reduced analysis for both time and costs. The device consists of a 3D printed thermoplastic polyurethane support housing the detection substrate (GF/F glass microfiber). The bromophenol blue (BPB) assay was optimized in this substrate to quantify total protein content. The analytical performance, assessed through image analysis, indicated that the hue factor of the HSV colour space represents the best analytical signal (r² > 0.98%). The optimized assay ensures a sufficiently low limit of detection (0.05 mg mL^-1), and an accuracy between 92% and 95%. The bioanalytical feasibility was demonstrated through total protein concentration measurement in different biological matrices (bee venom and mouse brain tissue), and foods (soya milk, cow's milk and protein supplements). The obtained values showed a strong agreement with those derived from a standard spectrophotometric analysis. Overall, the paper microzone BPB assay may represent an important contribution to protein quantification technology and could significantly impact many areas, such as quality control analysis and pre-clinical laboratory analysis.

Fluorescence turn-on detection of human serum albumin based on the assembly of gold nanoclusters and bromocresol green

As the most abundant protein in plasma, human serum albumin plays a vital role in physiological processes, such as maintaining blood osmotic pressure and carrying small-molecule ligands. Since the content of albumin in the human serum can reflect the status of liver and renal function, albumin quantitation is significant in clinical diagnosis. In this work, fluorescence turn-on detection of human serum albumin (HSA) had been performed based on the assembly of gold nanoclusters and bromocresol green. Gold nanoclusters (AuNCs) capped by reduced glutathione (GSH) were assembled with bromocresol green (BCG), and the assembly was used as a fluorescent probe for HSA. After BCG assembling, the fluorescence of gold nanoclusters was nearly quenched. In acidic solution, HSA can selectively bind to BCG on the assembly and recover the fluorescence of the solution. Based on this turn-on fluorescence, ratiometric HSA quantification was realized. Under optimal conditions, HSA detection by the probe possessed a good linear relationship in the range of 0.40-22.50 mg·mL^-1, and the detection limit was 0.27 ± 0.04 mg·mL^-1 (3σ, n = 3). Common coexisting components in serum and blood proteins did not interfere with the detection of HSA. This method has the advantages of easy manipulation and high sensitivity, and the fluorescent response is insensitive to reaction time.

Machine Learning-Based Analytical Systems: Food Forensics

Despite a large amount of money being spent on both food analyses and control measures, various food-borne illnesses associated with pathogens, toxins, pesticides, adulterants, colorants, and other contaminants pose a serious threat to human health, and thus food safety draws considerable attention in the modern pace of the world. The presence of various biogenic amines in processed food have been frequently considered as the primary quality parameter in order to check food freshness and spoilage of protein-rich food. Various conventional detection methods for detecting hazardous analytes including microscopy, nucleic acid, and immunoassay-based techniques have been employed; however, recently, array-based sensing strategies are becoming popular for the development of a highly accurate and precise analytical method. Array-based sensing is majorly facilitated by the advancements in multivariate analytical techniques as well as machine learning-based approaches. These techniques allow one to solve the typical problem associated with the interpretation of the complex response patterns generated in array-based strategies. Consequently, the machine learning-based neural networks enable the fast, robust, and accurate detection of analytes using sensor arrays. Thus, for commercial applications, most of the focus has shifted toward the development of analytical methods based on electrical and chemical sensor arrays. Therefore, herein, we briefly highlight and review the recently reported array-based sensor systems supported by machine learning and multivariate analytics to monitor food safety and quality in the field of food forensics.

Excessive iodine in iodized household salt in Nepal

Iodine is an essential trace element required for the regulation of physiological processes involving the thyroid gland. However, inadequate and excessive intake of iodine are responsible for health problems, such as iodine deficiency disorders, hypothyroidism, hyperthyroidism, thyroiditis, thyroid papillary cancer, and thyrotoxicosis. The Universal Salt Iodization (USI) program has become successful in providing supplemental iodine at the population level globally. Packaging quality, fortification level, and transportation and storage conditions of iodized salt determine the availability of iodine. Previous studies have reported severe health issues caused by excessive iodine intake after the implementation of the USI program. To understand the levels of iodine, we collected 2117 household salt samples from seven districts of Nepal and tested them for iodine content; among them, 98.1% were iodized. Overall median concentration of iodine was 53.9 ppm (range: 43.5-61.4 ppm). The majority (67.2%) of samples had iodine in the range of 45-75 ppm. Approximately 0.9% of samples had inadequate, 13.3% contained adequate, and 83.9% had excessive iodine than the World Health Organization-recommended value. Iodine content varied among the sampling districts and seasons, to some extent. Our study confirmed that iodized salt is widely used in Nepal and is excessively iodized. Excessive intake of iodine through iodized salt requires further attention by policy makers. The iodine level may need adjustment to address the health impact.

Handmade Paper as a Paper Analytical Device for Determining the Quality of an Antidiabetic Drug

Paper analytical devices (PADs) are a class of low-cost, portable, and easy-to-use platform for several analytical tests in clinical diagnostics, environmental pollution monitoring, and food and drug safety screening. These devices are primarily made from cellulosic paper. Considering the importance of eco-friendly and local or distributed manufacturing of devices realized during the COVID-19 pandemic, we systematically studied the potential of handmade Nepali paper to be used in fabricating PADs in this work. We characterized five different handmade papers made from locally available plant fibers using an eco-friendly method and used them to fabricate PADs for determining the drug quality. The thickness, grammage, and apparent density of the paper samples ranged from 198.6 to 314.8 μm, 49.1 to 117.8 g/m2, and 0.23 to 0.43 g/cm3, respectively. The moisture content, water filtration, and wicking speed ranged from 5.8 to 7.1%, 35.7 to 156.7, and 0.062 to 0.124 mms-1, respectively. Furthermore, the water contact angle and porosity ranged from 76.6 to 112.1° and 79 to 83%, respectively. The best paper sample (P5) was chosen to fabricate PADs for the determination of metformin, an antidiabetic drug. The metformin assay on PADs followed a linear range from 0.0625 to 0.5 mg/mL. The assay had a limit of detection and limit of quantitation of 0.05 and 0.18 mg/mL, respectively. The average amount of metformin concentration in samples collected from local pharmacies (n = 20) was 465.6 ± 15.1 mg/tablet. When compared with the spectrophotometric method, PAD assay correctly predicted the concentration of 90% samples. The PAD assay on handmade paper may provide a low-cost and easy-to-use system for screening the quality of drugs and other point-of-need applications.

Opto-Microfluidic Integration of the Bradford Protein Assay in Lithium Niobate Lab-on-a-Chip

This paper deals with the quantification of proteins by implementing the Bradford protein assay method in a portable opto-microfluidic platform for protein concentrations lower than 1.4 mg/mL. Absorbance is measured by way of optical waveguides integrated to a cross-junction microfluidic circuit on a single lithium niobate substrate. A new protocol is proposed to perform the protein quantification based on the high correlation of the light absorbance at 595 nm, as commonly used in the Bradford method, with the one achieved at 633 nm with a cheap commercially available diode laser. This protocol demonstrates the possibility to quantify proteins by using nL volumes, 1000 times less than the standard technique such as paper-analytical devices. Moreover, it shows a limit of quantification of at least 0.12 mg/mL, which is four times lower than the last literature, as well as a better accuracy (98%). The protein quantification is obtained either by using one single microfluidic droplet as well by performing statistical analysis over ensembles of several thousands of droplets in less than 1 min. The proposed methodology presents the further advantage that the protein solutions can be reused for other investigations and the same pertains to the opto-microfluidic platform.

Machine-Learning-Assisted Analysis of Colorimetric Assays on Paper Analytical Devices

Paper-based analytical devices (PADs) employing colorimetric detection and smartphone images have gained wider acceptance in a variety of measurement applications. PADs are primarily meant to be used in field settings where assay and imaging conditions greatly vary, resulting in less accurate results. Recently, machine-learning (ML)-assisted models have been used in image analysis. We evaluated a combination of four ML models-logistic regression, support vector machine (SVM), random forest, and artificial neural network (ANN)-as well as three image color spaces, RGB, HSV, and LAB, for their ability to accurately predict analyte concentrations. We used images of PADs taken at varying lighting conditions, with different cameras and users for food color and enzyme inhibition assays to create training and test datasets. The prediction accuracy was higher for food color than enzyme inhibition assays in most of the ML models and color space combinations. All models better predicted coarse-level classifications than fine-grained concentration classes. ML models using the sample color along with a reference color increased the models' ability to predict the result in which the reference color may have partially factored out the variation in ambient assay and imaging conditions. The best concentration class prediction accuracy obtained for food color was 0.966 when using the ANN model and LAB color space. The accuracy for enzyme inhibition assay was 0.908 when using the SVM model and LAB color space. Appropriate models and color space combinations can be useful to analyze large numbers of samples on PADs as a powerful low-cost quick field-testing tool.

Smartphone-Assisted Protein to Creatinine Ratio Determination on a Single Paper-Based Analytical Device

Proteinuria is a condition in which an excessive amount of protein is excreted in urine. It is, among others, an indicator of kidney disease or risk of cardiovascular disease. Rapid and reliable diagnosis and monitoring of proteinuria is of great importance for both patients and their physicians. For that reason, a paper-based sensor for proteinuria diagnosis was designed, optimized, and validated utilizing smartphone-assisted signal acquisition. In the first step, a few commonly employed protein assays were optimized and compared in terms of analytical performance on paper matrix. The tetrabromophenol blue method was selected as the one providing a sufficiently low limit of detection (39 mg·L-1) on the one hand and appropriate long-term stability (up to 3 months) on the other hand. The optimized assay was employed for protein-to-creatinine ratio (PCR) determination on a single paper-based sensor. For both analytes the linear ranges were within the clinically relevant range. The analytical usefulness of the developed sensors was demonstrated by a PCR recovery study in artificial urine. The obtained PCR recoveries were from ca. 80 to 150%.

Rapid electrochemical-biosensor microchip platform for determination of microalbuminuria in CKD patients

An electrochemical-biosensor (EC-biosensor) microchip consisting of screen-printed electrodes and a double-layer reagent paper detection zone impregnated with amaranth is proposed for the rapid determination of microalbuminuria (MAU) in human urine samples. Under the action of an applied deposition potential, the amaranth is adsorbed on the electrode surface and the subsequent reaction between the modified surface and the MAU content in the urine sample prompts the formation of an inert layer on the electrode surface. The inert layer impedes the transfer of electrons and hence produces a drop in the response peak current, from which the MAU concentration can then be determined. The measurement results obtained for seven artificial urine samples with known MAU concentrations in the range of 0.1-40 mg/dL show that the measured response peak current is related to the MAU concentration with a determination coefficient of R² = 0.991 in the low concentration range of 0.1-10 mg/dL and R² = 0.996 in the high concentration range of 10-40 mg/dL. Furthermore, the detection results obtained for 82 actual chronic kidney disease (CKD) patients show an excellent agreement (R² = 0.988) with the hospital analysis results. Overall, the results confirm that the proposed detection platform provides a convenient and reliable approach for performing sensitive point-of-care testing (POCT) of the MAU content in human urine samples.

Sorting Technology for Circulating Tumor Cells Based on Microfluidics

Circulating tumor cells (CTCs) carry reliable clinical information for the diagnosis and treatment of cancer that is a malignant disease with a high mortality rate. However, the amount of CTCs in the blood is quite low. To obtain credible clinical information, an efficient method of extracting CTCs is necessary. Microfluidic technology has proven its effectiveness on CTCs separation in recent years. Here, we present a comprehensive review of CTC sorting methods based on microfluidics. Specifically, we introduce four different microfluidic sorting methods of CTCs and compare their advantages and disadvantages. Finally, we summarize the analysis of CTCs based on microfluidics and present a prospective view of future research.