Mathematical Modelling of Biosensing Platforms Applied for Environmental Monitoring

In recent years, mathematical modelling has known an overwhelming integration in different scientific fields. In general, modelling is used to obtain new insights and achieve more quantitative and qualitative information about systems by programming language, manipulating matrices, creating algorithms and tracing functions and data. Researchers have been inspired by these techniques to explore several methods to solve many problems with high precision. In this direction, simulation and modelling have been employed for the development of sensitive and selective detection tools in different fields including environmental control. Emerging pollutants such as pesticides, heavy metals and pharmaceuticals are contaminating water resources, thus threatening wildlife. As a consequence, various biosensors using modelling have been reported in the literature for efficient environmental monitoring. In this review paper, the recent biosensors inspired by modelling and applied for environmental monitoring will be overviewed. Moreover, the level of success and the analytical performances of each modelling-biosensor will be discussed. Finally, current challenges in this field will be highlighted.

Online specific recognition of mycotoxins using aptamer-grafted ionic affinity monolith with mixed-mode mechanism

Herein, a facile and practical aptamer-grafted ionic affinity monolith with mixed-mode mechanism was explored as a versatile platform for online specific recognition of polar and non-polar mycotoxins. The mixed-mode mechanism including molecular affinity adsorption (between aptamers and targets), hydrophilic interaction and ionic interaction (between stationary phase and targets) were adopted and provided a better flexibility in adjusting separation selectivity to reduce nonspecific adsorption with respect to the single mode. Preparation and characterization of aptamer-based affinity monoliths were investigated, The characterization of pore size distribution, Brunauer-Emmett-Teller (BET) surface area and the specificity and cross-reaction were also evaluated. As a result, the hydrophilic nature and negative charge on affinity monolith were obtained. Multiple interactions including aptamer affinity binding, hydrophilic interaction (HI) and ion exchange (IE) could be adopted for online selective extraction. Specific recognitions of polar ochratoxin A (OTA), non-polar zearalenone (ZEN) and aflatoxin B1 (AFB1) was fulfilled with LODs as 0.03, 0.05 and 0.05 μg/L, respectively. Applied to real cereals, good recoveries of the fortified OTA, AFB1 and ZEN were achieved as 92.6 ± 1.3% ~ 95.6 ± 1.3% (n=3), 93.9 ± 2.3% ~ 98.2 ± 3.4% (n=3) and 92.7 ± 2.0% ~ 96.9 ± 3.5% (n=3) in corn, wheat and rice, respectively. The results displayed that Apt-MCs with hydrophilic and ionic interaction mixed-mode mechanism were efficient enough and competent for the online recognition of mycotoxins in cereals.

Implementation of chemometrics in quality evaluation of food and beverages

Conventional methods for food quality evaluation based on chemical or microbiological analysis followed by traditional univariate statistics such as ANOVA are considered insufficient for some purposes. More sophisticated instrumental methods including spectroscopy and chromatography, in combination with multivariate analysis-chemometrics, can be used to determine food authenticity, identify adulterations or mislabeling and determine food safety. The purpose of this review is to present the current state of knowledge on the use of chemometric tools for evaluating quality of food products of animal and plant origin and beverages. The article describes applications of several multivariate techniques in food and beverages research, showing their role in adulteration detection, authentication, quality control, differentiation of samples and comparing their classification and prediction ability.