Investigation on the ability of heteroatom-doped graphene for biorecognition

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple cross-reactive sensors to identify specific targets via pattern recognition. When the sensor arrays are fabricated with nanomaterials, the binding affinity of analytes to the sensors and the response of sensor arrays can be remarkably enhanced, thereby making the detection process more rapid, sensitive, and accurate. Data analysis is vital in converting the signals from sensor arrays into meaningful information regarding the analytes. As the sensor arrays can generate complex, high-dimensional data in response to analytes, they require the use of machine learning algorithms to reduce the dimensionality of the data to gain more reliable outcomes. Moreover, the advances in handheld smart devices have made it easier to read and analyze the sensor array signals, with the advantages of convenience, portability, and efficiency. While facing some challenges, the integration of artificial intelligence with nanosensor arrays holds promise for enhancing food safety monitoring.

Aptamer-based detection of fumonisin B1: A critical review

Mycotoxin contamination is a current issue affecting several crops and processed products worldwide. Among the diverse mycotoxin group, fumonisin B1 (FB1) has become a relevant compound because of its adverse effects in the food chain. Conventional analytical methods previously proposed to quantify FB1 comprise LC-MS, HPLC-FLD and ELISA, while novel approaches integrate different sensing platforms and fluorescently labelled agents in combination with antibodies. Nevertheless, such methods could be expensive, time-consuming and require experience. Aptamers (ssDNA) are promising alternatives to overcome some of the drawbacks of conventional analytical methods, their high affinity through specific aptamer-target binding has been exploited in various designs attaining favorable limits of detection (LOD). So far, two aptamers specific to FB1 have been reported, and their modified and shortened sequences have been explored for a successful target quantification. In this critical review spanning the last eight years, we have conducted a systematic comparison based on principal component analysis of the aptamer-based techniques for FB1, compared with chromatographic, immunological and other analytical methods. We have also conducted an in-silico prediction of the folded structure of both aptamers under their reported conditions. The potential of aptasensors for the future development of highly sensitive FB1 testing methods is emphasized.

Incorporation-limiting mechanisms during nitrogenation of monolayer graphene films in nitrogen flowing afterglows

Monolayer graphene films are exposed to the flowing afterglow of a low-pressure microwave nitrogen plasma, characterized by the absence of ion irradiation and significant populations of N atoms and N₂(A) metastables. Hyperspectral Raman imaging of graphene domains reveals damage generation with a progressive rise of the D/G and D/2D band ratios following subsequent plasma treatments. Plasma-induced damage is mostly zero-dimensional and the graphene state remains in the pre-amorphous regime. Over the range of experimental conditions investigated, damage formation increases with the fluence of energy provided by heterogenous surface recombination of N atoms and deexcitation of N₂(A) metastable species. In such conditions, X-ray photoelectron spectroscopy reveals that the nitrogen incorporation (either as pyridine, pyrrole, or quaternary moieties) does not simply increase with the fluence of plasma-generated N atoms but is also linked to the damage generation. Based on these findings, a surface reaction model for monolayer graphene nitrogenation is proposed. It is shown that the nitrogen incorporation is first limited by the plasma-induced formation of defect sites at low damage and then by the adsorption of nitrogen atoms at high damage.

Aptamer-Target-Gold Nanoparticle Conjugates for the Quantification of Fumonisin B1

Fumonisin B1 (FB1), a mycotoxin classified as group 2B hazard, is of high importance due to its abundance and occurrence in varied crops. Conventional methods for detection are sensitive and selective; however, they also convey disadvantages such as long assay times, expensive equipment and instrumentation, complex procedures, sample pretreatment and unfeasibility for on-site analysis. Therefore, there is a need for quick, simple and affordable quantification methods. On that note, aptamers (ssDNA) are a good alternative for designing specific and sensitive biosensing techniques. In this work, the assessment of the performance of two aptamers (40 and 96 nt) on the colorimetric quantification of FB1 was determined by conducting an aptamer-target incubation step, followed by the addition of gold nanoparticles (AuNPs) and NaCl. Although MgCl₂ and Tris-HCl were, respectively, essential for aptamer 96 and 40 nt, the latter was not specific for FB1. Alternatively, the formation of Aptamer (96 nt)-FB1-AuNP conjugates in MgCl₂ exhibited stabilization to NaCl-induced aggregation at increasing FB1 concentrations. The application of asymmetric flow field-flow fractionation (AF4) allowed their size separation and characterization by a multidetection system (UV-VIS, MALS and DLS online), with a reduction in the limit of detection from 0.002 µg/mL to 56 fg/mL.