Soy sauce, a dark-colored seasoning, is added to enhance the sensory properties of foods. Soy sauce can be consumed as a condiment or added during the preparation of food. There are 3 types of soy sauce: fermented, acid-hydrolyzed vegetable protein (acid- HVP), and mixtures of these. 3-Chloropropane-1,2-diol (3-MCPD) is a heat-produced contaminants formed during the preparation of soy sauce and was found to be a by-product of acid-HVP-produced soy sauce in 1978. 3-MCPD has been reported to be carcinogenic, nephrotoxic, and reproductively toxic in laboratory animal testing and has been registered as a chemosterilant for rodent control. 3-MCPD is classified as a possible carcinogenic compound, and the maximum tolerated limit in food has been established at both national and international levels. The purpose of this review is to provide an overview on the detection of 3-MCPD in soy sauce, its toxic effects, and the potential methods to reduce its concentration, especially during the production of acid-HVP soy sauce. The methods of quantification are also critically reviewed with a focus on efficiency, suitability, and challenges encountered in analysis.
INTRODUCTION: Malnutrition is common in cancer patients. Generally, it is believed that the resting energy expenditure (REE) is elevated in cancer patients and this contributes to the development of malnutrition. Thus, to be able to assess the REE is important in planning adequate nutrition support.
METHODS: A cross-sectional study was carried out to assess the REE in patients with solid tumour (n=25), leukemia (n=25) and healthy subjects (n=50) by using the indirect calorimetry method under standard conditions.
RESULTS: There was no significant difference between the measured REE among patients with solid tumour, leukemia and the control group (p=0.534). By contrast, there was a significant difference between the REE/kg FFM in solid tumour patients compared to the leukemia group and the healthy subjects, (p=0.049 and p=0.002). The REE derived from the Harris Benedict Equation was found to be significantly higher than the measured REE. The stress factor for patients with solid tumour was 1.35 and that for leukemia patients was 1.36.
CONCLUSION: The REE/kg FFM in the cancer patients undergoing anticancer therapy appeared to be higher than expected compared to healthy subjects. The Harris Benedict Equation (HBE) was found to over-estimate the REE of cancer patients in the study. As the total energy expenditure (TEE) is estimated by multiplying the REE with the stress factor and physical activity factor, the overestimated REE from HBE will further increase the risk of overfeeding in this population.
Guanine (G), adenine (A), thymine (T), and cytosine (C) are the four basic constituents of DNA. Studies on DNA composition have focused especially on DNA damage and genotoxicity. However, the development of a rapid, simple, and multiplex method for the simultaneous measurement of the four DNA bases remains a challenge. In this study, we describe a graphite-based nanocomposite electrode (Au-rGO/MWCNT/graphite) that uses a simple electro-co-deposition approach. We successfully applied the developed sensor for multiplex detection of G, A, T, and C, using square-wave voltammetry. The sensor was tested using real animal and plant DNA samples in which the hydrolysis of T and C could be achieved with 8 mol L-1 of acid. The electrochemical sensor exhibited excellent sensitivity (G = 178.8 nA/μg mL-1, A = 92.9 nA/μg mL-1, T = 1.4 nA/μg mL-1, and C = 15.1 9 nA/μg mL-1), low limit of detection (G, A = 0.5 μg mL-1; T, C = 1.0 μg mL-1), and high selectivity in the presence of common interfering factors from biological matrixes. The reliability of the established method was assessed by method validation and comparison with the ultraperformance liquid chromatography technique, and a correlation of 103.7% was achieved.
Unpredictable natural disasters, disease outbreaks, climate change, pollution, and war constantly threaten food crop production. Smart and precision farming encourages using information or data obtained by using advanced technology (sensors, AI, and IoT) to improve decision-making in agriculture and achieve high productivity. For instance, weather prediction, nutrient information, pollutant assessment, and pathogen determination can be made with the help of new analytical and bioanalytical methods, demonstrating the potential for societal impact such as environmental, agricultural, and food science. As a rising technology, biosensors can be a potential tool to promote smart and precision farming in developing and underdeveloped countries. This review emphasizes the role of on-field, in vivo, and wearable biosensors in smart and precision farming, especially those biosensing systems that have proven with suitably complex and analytically challenging samples. The development of various agricultural biosensors in the past five years that fulfill market requirements such as portability, low cost, long-term stability, user-friendliness, rapidity, and on-site monitoring will be reviewed. The challenges and prospects for developing IoT and AI-integrated biosensors to increase crop yield and advance sustainable agriculture will be discussed. Using biosensors in smart and precision farming would ensure food security and revenue for farming communities.
Food contamination is a serious concern because of a high level of chemicals in food causes severe health issues. Safeguarding the public from the risk of adulterated foods has become a challenging mission. Chloropropanols are of importance to food safety and food security because they are common chemical food contaminants and believed to be carcinogenic to humans. In chemical sensing, chloropropanols are challenging analytes owing to the lacking diversity of functional groups and difficulty in targeting the hydroxyl group in aqueous environments. Moreover, because of their small molecular size, the compositions of chloropropanols remain challenging for achieving chromatographic determination. Herein, to simulate human smell and taste sensations, serum albumins, which are protein-based receptors, were introduced as low-selective receptors for differential sensing. Utilizing serum albumins, a fluorophore (PRODAN), and an additive (ascorbic acid), a differential-based optical biosensor array was developed to detect and differentiate chloropropanols. By integrating the sensor array with linear discriminant analysis (LDA), four chloropropanols were effectively differentiated based on their isomerism properties and the number of the hydroxyl groups, even at ultra-low concentration (5 nM). This concentration is far below the maximum tolerable level of 0.18 μM for chloropropanols. The sensing array was then employed for chloropropanols differentiation and quantification in the complex mixtures (e.g., synthetic soy and dark soy sauces). Leave-one-out cross-validation (LOOCV) analysis demonstrated 100% accurate classification for all tests. These results signify our differential sensing array as a practical and powerful tool to speedily identify, differentiate, and even quantify chloropropanols in food matrices.
Oil and grease content in wastewater is used as an environmental monitoring parameter in the oil and gas industry to prevent serious pollution. Conventional oil and grease laboratory testing is time-consuming and necessitates the use of a hazardous chemical solvent, resulting in non-real-time test data and unnecessary chemical waste. On-site or real-time analysis can enable monitoring of oil and grease in wastewater before discharge to the environment from an operating plant, allowing immediate action to be taken to mitigate environmental impact before contamination spirals out of control. Bioluminescent whole-cell biosensors have been reported to have high sensitivity and selectivity in environmental samples, but only for a few traces of organic compounds such as polycyclic aromatics and naphthalene, allowing for faster analysis times. However, no evaluation of biosensor application for oil and grease (a mixture of hydrocarbons) detection in wastewater, which is critical in the oil and gas industry, has been published to date. Herein, the advantages, disadvantages, challenges, and limitations of using a whole-cell bioluminescent biosensor technology to measure oil and grease content in wastewater are carefully reviewed. This review attempts to bridge the knowledge gap between conventional laboratory methods and biosensor technology in terms of analytical challenges, identifying areas for improvement as well as real-world applications for oil and grease content detection in wastewater.
Butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), and tert-butylhydroquinone (TBHQ) are synthetic antioxidants used in the food industry. Herein, we describe the development of a novel graphite nanocomposite-based electrochemical sensor for the multiplex detection and measurement of BHA, BHT, and TBHQ levels in complex food samples using a linear sweep voltammetry technique. Moreover, our newly established analytical method exhibited good sensitivity, limit of detection, limit of quantitation, and selectivity. The accuracy and reliability of analytical results were challenged by method validation and comparison with the results of the liquid chromatography method, where a linear correlation of more than 0.99 was achieved. The addition of sodium dodecyl sulfate as supporting additive further enhanced the LSV response (anodic peak current, Ipa) of BHA and BHT by 2- and 20-times, respectively.
Clinicians, working in the health-care diagnostic systems of developing countries, currently face the challenges of rising costs, increased number of patient visits, and limited resources. A significant trend is using low-cost substrates to develop microfluidic devices for diagnostic purposes. Various fabrication techniques, materials, and detection methods have been explored to develop these devices. Microfluidic paper-based analytical devices (μPADs) have gained attention for sensing multiplex analytes, confirming diagnostic test results, rapid sample analysis, and reducing the volume of samples and analytical reagents. μPADs, which can provide accurate and reliable direct measurement without sample pretreatment, can reduce patient medical burden and yield rapid test results, aiding physicians in choosing appropriate treatment. The objectives of this review are to provide an overview of the strategies used for developing paper-based sensors with enhanced analytical performances and to discuss the current challenges, limitations, advantages, disadvantages, and future prospects of paper-based microfluidic platforms in clinical diagnostics. μPADs, with validated and justified analytical performances, can potentially improve the quality of life by providing inexpensive, rapid, portable, biodegradable, and reliable diagnostics.
The objective of this study was to evaluate the effects ofNi(II) and Cr(VI) individually and in combination on the simultaneous removal of chemical oxygen demand (COD), nitrogen and metals under a sequencing batch reactor (SBR) operation. Three identical laboratory-scale SBRs were operated with FILL, REACT, SETTLE, DRAW and IDLE periods in a ratio of 1:12:1:2:8 for a cycle time of 24 h until the steady state was achieved. Nickel(II) at increasing concentrations up to 35 mg/L was added to one of the reactors; Cr(VI) at increasing concentrations up to 25 mg/L was added to a second reactor; while a combination of Ni(II) and Cr(VI) in equal concentrations up to 10 mg/L was added to a third reactor. The results demonstrate that both Ni(II) and Cr(VI) exerted a more pronounced inhibitory effect on the removal of ammonia nitrogen (AN) than on COD removal. Synergistic and antagonistic inhibitory effects on the rates of COD and AN removal, respectively, were observed for the 50% Ni(II) and 50% Cr(VI) (w/w) mixture in the concentration range between 10 and 20 mg/L. The simultaneous presence of 50% Ni(II) and 50% Cr(VI) at a concentration of 20 mg/L resulted in system failure.
This paper reports the application of hexamethyldisilazane-trimethylsilyl trifluoromethanesulfonate (HMDS-TMSOTf) for the simultaneous silylation of 3-monochloro-1,2-propanediol (3-MCPD) and 1,3-dicholoropropanol (1,3-DCP) in solid and liquid food samples. 3-MCPD and 1,3-DCP are chloropropanols that have been established as Group 2B carcinogens in clinical testing. They can be found in heat-processed food, especially when an extended high-temperature treatment is required. However, the current AOAC detection method is time-consuming and expensive. Thus, HMDS-TMSOTf was used in this study to provide a safer, and cost-effective alternative to the HFBI method. Three important steps are involved in the quantification of 3-MCPD and 1,3-DCP: extraction, derivatization and quantification. The optimization of the derivatization process, which involved focusing on the catalyst volume, derivatization temperature, and derivatization time was performed based on the findings obtained from both the Box-Behnken modeling and a real experimental set up. With the optimized conditions, the newly developed method was used for actual food sample quantification and the results were compared with those obtained via the standard AOAC method. The developed method required less samples and reagents but it could be used to achieve lower limits of quantification (0.0043mgL(-1) for 1,3-DCP and 0.0011mgL(-1) for 3-MCPD) and detection (0.0028mgL(-1) for 1,3-DCP and 0.0008mgL(-1) for 3-MCPD). All the detected concentrations are below the maximum tolerable limit of 0.02mgL(-1). The percentage of recovery obtained from food sample analysis was between 83% and 96%. The new procedure was validated with the AOAC method and showed a comparable performance. The HMDS-TMSOTf derivatization strategy is capable of simultaneously derivatizing 1,3-DCP and 3-MCPD at room temperature, and it also serves as a rapid, sensitive, and accurate analytical method for food samples analysis.
The early detection of acute myocardial infarction (AMI) upon the onset of chest pain symptoms is crucial for patient survival. However, this detection is challenging, particularly without a persistent elevation of ST-segment reflected in an electrocardiogram or in blood tests. A majority of the available point-of-care testing devices allow accurate and rapid diagnosis of AMI. However, AMI diagnosis is reliable only at intermediate and later stages, with myocardial injury (> 6 h) and MI, based on the expression of specific cardiac biomarkers including troponin I or T (cTnI or cTnT), creatine kinase-MB (CK-MB), and myoglobin. Diagnosis at the early myocardial ischemia stage is not possible. To overcome this limitation, a sensitive and rapid microfluidic paper-based device (µPAD) was developed for the simultaneous detection of multiple cardiac biomarkers for the early and late diagnosis of AMI. The glycogen phosphorylase isoenzyme BB (GPBB) was detected during early (within first 4 h) ischemic myocardial injury. On the same µPAD platform, detection of prolonged elevation of levels of cTnT and CK-MB, which are only produced 6 h after the onset of chest pain in human serum, was possible. Sandwich immunoassay performed on the µPAD achieved reproducibility (RSD approximately 10% and intra-and inter-day precision (CV 10-20%, 99th percentile), as well as consistently stable test results for 28 days, with strong correlation (r2= 0.962), using the standard Siemens Centaur XPT Immunoassay system. The present findings indicate the potential of the µPAD platform as a point-of-care device for the early diagnosis and prognosis of AMI.
Cardiovascular disease (CVD) is the leading cause of death worldwide and is a global health issue. Traditionally, statistical models are used commonly in the risk prediction and assessment of CVD. However, the adoption of artificial intelligent (AI) approach is rapidly taking hold in the current era of technology to evaluate patient risks and predict the outcome of CVD. In this review, we outline various conventional risk scores and prediction models and do a comparison with the AI approach. The strengths and limitations of both conventional and AI approaches are discussed. Besides that, biomarker discovery related to CVD are also elucidated as the biomarkers can be used in the risk stratification as well as early detection of the disease. Moreover, problems and challenges involved in current CVD studies are explored. Lastly, future prospects of CVD risk prediction and assessment in the multi-modality of big data integrative approaches are proposed.
Graphite material is abundantly available from recyclable sources. It possesses a good electrical conductance property, which makes it an attractive material as a working electrode. However, due to a high activation overpotential it has limited applications as compared to other solid metal electrodes. In this present work, we obtained a graphite rod from a used battery, and carried out electrochemical improvements by electro-deposition with gold nanoparticles (AuNPs). The heterogeneous electron transfer rate and electron transfer resistance of the fabricated electrode were improved. The electrode overpotential has shown improvement by 50 mV, and the effective surface area has increased by 2 fold. To determine the practicability of the AuNPs/graphite electrode, we used the electrode in the analysis of myricetin. A square-wave voltammetry was used in the analysis, and the detection response increased by 2.5 fold, which suggested an improvement in the electrode sensitivity.
A sensitive biosensor capable of detecting trace concentrations of several cancer biomarkers in clinical samples is critical for early detection of cancer because different cancer biomarkers may be expressed at different stages of cancer. Previous multiplex studies using microarrays or color-coded beads had limited multiplex detection in a single well, and difficulty in optimizing and unifying the incubation parameters for all tests made in different wells had posed challenges to small sample size and lengthened assay time. Herein, we proposed a novel approach to achieve multiplex analysis on a single three-dimensional porous calcium alginate bead. Because of the high surface area to volume ratio of the calcium alginate immuno-bead, the sensitivity and linear dynamic range of the as-proposed multiplex analysis method are significantly improved. Based on the direct sandwich immunoassay principle, dual-capturing antibodies were encapsulated into a single 3D porous calcium alginate bead as a proof-of-concept for multiplexity detection of serum-HER2 and serum-CA125 breast cancer biomarkers. High sensitivity was attained, with LODs of 0.004 ng mL-1 for serum HER2, and 0.005 U mL-1 for serum CA125, both of which are below the clinical cutoff values, enabling for early breast cancer diagnosis. Stability tests revealed that the 3D immuno-beads were stable at 4 °C and room temperature (25 °C) for at least 14 days. Most importantly, the results obtained using the developed system were in good agreement with those obtained using standard methods while analyzing real clinical samples. In addition, the analysis required only approximately 30 min, which was much less time than typical ELISA techniques. When endogenous interferences were introduced, no cross-reactivity was observed. We anticipate this approach to be potentially used in the multiplex assays and biosensors.
The sharp increase in incidence of dengue infection has necessitated the development of methods for the rapid diagnosis of this deadly disease. Here we report the design and development of a reliable, sensitive, and specific optical immunosensor for the detection of the dengue nonstructural protein 1 (NS1) biomarker in clinical samples obtained during early stages of infection. The present optical NS1 immunosensor comprises a biosensing surface consisting of specific monoclonal NS1 antibody for immunofluorescence-based NS1 antigen determination using fluorescein isothiocyanate (FITC) conjugated to IgG antibody. The linear range of the optical immunosensor was from 15-500ngmL-1, with coefficient of determination (R2) of 0.92, high reproducibility (the relative standard deviation obtained was 2%), good stability for 21days at 4°C, and low detection limit (LOD) at 15ngmL-1. Furthermore, the optical immunosensor was capable of detecting NS1 analytes in plasma specimens from patients infected with the dengue virus, with low cross-reaction with plasma specimens containing the Japanese encephalitis virus (JEV) and Zika virus. No studies have been performed on the reproducibility and cross-reactivity regarding NS1 specificity, which is thus a limitation for optical NS1 immunosensors. In contrast, the present study addressed these limitations carefully where these two important experiments were conducted to showcase the robustness of our newly developed optical-based fluorescence immunosensor, which can be practically used for direct NS1 determination in any untreated clinical sample.
Type 2 diabetes mellitus (T2DM) is a pressing health issue that threatens global health and the productivity of populations worldwide. Despite its long-recognized role in diabetes management, glycated hemoglobin (HbA1c) only received WHO endorsement as a T2DM diagnostic tool in 2011. Although conventional plasma-specific tests have long been utilized to diagnose T2DM, the public should be informed that plasma-specific tests are not markedly better than HbA1c tests, particularly in terms of variability and convenience for diagnosing diabetes. In the midst of the debates associated with establishing HbA1c as the preeminent diabetes diagnostic tool, unceasing efforts to standardize HbA1c tests have played an integral part in achieving more efficient communication from laboratory to clinical practice and thus better diabetes care. This review discusses the current status of HbA1c tests in the diagnosis, prevention, treatment and management of T2DM across the globe, focusing on increasing the recognition of glycated hemoglobin variants with effective utilization of different HbA1c methods, updating the current status of HbA1c standardization programs, tapping into the potential of POC analyzers to establish a cost-effective HbA1c test for diabetes care, and inspiring the advancement of HbA1c biosensors for future clinical usage.
We describe a gold nanoparticle-based sandwich immunoassay for the dual detection and measurement of hemoglobin A1c (HbA1c) and total hemoglobin in the whole blood (without pretreatment) in a single step for personalized medicine. The optimized antibody-functionalized gold nanoparticles immunoreact simultaneously with HbA1c and total hemoglobin to form a sandwich at distinctive test lines to transduce visible signals. The applicability of this method as a personal management tool was demonstrated by establishing a calibration curve to relate % HbA1c, a useful value for type 2 diabetes management, to the signal ratio of captured HbA1c to all other forms of hemoglobin. The platform showed excellent selectivity (100%) toward HbA1c at distinctive test lines when challenged with HbA0, glycated HbA0 and HbA2. The reproducibility of the measurement was good (6.02%) owing to the dual measurement of HbA1c and total hemoglobin. A blood sample stability test revealed that the quantitative measurement of % HbA1c was consistent and no false-positive results were detected. Also, this method distinguished the blood sample with elevated HbF from the normal samples and the variants. The findings of this study highlight the potential of a lateral flow immunosensor as a simple, inexpensive, consistent, and convenient strategy for the dual measurement of HbA1c and total Hb to provide useful % HbA1c values for better on-site diabetes care.
Cardiovascular disease is a major global health issue. In particular, acute myocardial infarction (AMI) requires urgent attention and early diagnosis. The use of point-of-care diagnostics has resulted in the improved management of cardiovascular disease, but a major drawback is that the performance of POC devices does not rival that of central laboratory tests. Recently, many studies and advances have been made in the field of surface-enhanced Raman scattering (SERS), including the development of POC biosensors that utilize this detection method. Here, we present a review of the strengths and limitations of these emerging SERS-based biosensors for AMI diagnosis. The ability of SERS to multiplex sensing against existing POC detection methods are compared and discussed. Furthermore, SERS calibration-free methods that have recently been explored to minimize the inconvenience and eliminate the limitations caused by the limited linear range and interassay differences found in the calibration curves are outlined. In addition, the incorporation of artificial intelligence (AI) in SERS techniques to promote multivariate analysis and enhance diagnostic accuracy are discussed. The future prospects for SERS-based POC devices that include wearable POC SERS devices toward predictive, personalized medicine following the Fourth Industrial Revolution are proposed.
Recently, surface enhanced Raman scattering (SERS) has attracted much attention in medical diagnosis applications owing to better detection sensitivity and lower limit of detection (LOD) than colorimetric detection. In this paper, a novel calibration-free SERS-based μPAD with multi-reaction zones for simultaneous quantitative detection of multiple cardiac biomarkers - GPBB, CK-MB and cTnT for early diagnosis and prognosis of acute myocardial infarction (AMI) are presented. Three distinct Raman probes were synthesised, subsequently conjugated with respective detecting antibodies and used as SERS nanotags for cardiac biomarker detection. Using a conventional calibration curve, quantitative simultaneous measurement of multiple cardiac biomarkers on SERS-based μPAD was performed based on the characteristic Raman spectral features of each reporter used in different nanotags. However, a calibration free point-of-care testing device is required for fast screening to rule-in and rule-out AMI patients. Partial least squares predictive models were developed and incorporated into the immunosensing system, to accurately quantify the three unknown cardiac biomarkers levels in serum based on the previously obtained Raman spectral data. This method allows absolute quantitative measurement when conventional calibration curve fails to provide accurate estimation of cardiac biomarkers, especially at low and high concentration ranges. Under an optimised condition, the LOD of our SERS-based μPAD was identified at 8, 10, and 1 pg mL-1, for GPBB, CK-MB and cTnT, respectively, which is well below the clinical cutoff values. Therefore, this proof-of-concept technique shows significant potential for highly sensitive quantitative detection of multiplex cardiac biomarkers in human serum to expedite medical decisions for enhanced patient care.