Rapid and accurate electrochemical sensor for food allergen detection in complex foods

The Impact of Artificial Intelligence on Allergy Diagnosis and Treatment

PURPOSE OF REVIEW

Artificial intelligence (AI), be it neuronal networks, machine learning or deep learning, has numerous beneficial effects on healthcare systems; however, its potential applications and diagnostic capabilities for immunologic diseases have yet to be explored. Understanding AI systems can help healthcare workers better assimilate artificial intelligence into their practice and unravel its potential in diagnostics, clinical research, and disease management.

RECENT FINDINGS

We reviewed recent advancements in AI systems and their integration in healthcare systems, along with their potential benefits in the diagnosis and management of diseases. We explored machine learning as employed in allergy diagnosis and its learning patterns from patient datasets, as well as the possible advantages of using AI in the field of research related to allergic reactions and even remote monitoring. Considering the ethical challenges and privacy concerns raised by clinicians and patients with regard to integrating AI in healthcare, we explored the new guidelines adapted by regulatory bodies. Despite these challenges, AI appears to have been successfully incorporated into various healthcare systems and is providing patient-centered solutions while simultaneously assisting healthcare workers. Artificial intelligence offers new hope in the field of immunologic disease diagnosis, monitoring, and management and thus has the potential to revolutionize healthcare systems.

Review of Electrochemical Biosensors for Food Safety Detection

Food safety issues are directly related to people's quality of life, so there is a need to develop efficient and reliable food contaminants' detection devices to ensure the safety and quality of food. Electrochemical biosensors have the significant advantages of miniaturization, low cost, high sensitivity, high selectivity, rapid detection, and low detection limits using small amounts of samples, which are expected to enable on-site analysis of food products. In this paper, the latest electrochemical biosensors for the detection of biological contaminants, chemical contaminants, and genetically modified crops are reviewed based on the analytes of interest, electrode materials and modification methods, electrochemical methods, and detection limits. This review shows that electrochemical biosensors are poised to provide miniaturized, specific, selective, fast detection, and high-sensitivity sensor platforms for food safety.

Recent Advances in Electrochemical Sensing Strategies for Food Allergen Detection

Food allergy has been indicated as the most frequent adverse reaction to food ingredients over the past few years. Since the only way to avoid the occurrence of allergic phenomena is to eliminate allergenic foods, it is essential to have complete and accurate information on the components of foodstuff. In this framework, it is mandatory and crucial to provide fast, cost-effective, affordable, and reliable analysis methods for the screening of specific allergen content in food products. This review reports the research advancements concerning food allergen detection, involving electrochemical biosensors. It focuses on the sensing strategies evidencing different types of recognition elements such as antibodies, nucleic acids, and cells, among others, the nanomaterial role, the several electrochemical techniques involved and last, but not least, the ad hoc electrodic surface modification approaches. Moreover, a selection of the most recent electrochemical sensors for allergen detection are reported and critically analyzed in terms of the sensors’ analytical performances. Finally, advantages, limitations, and potentialities for practical applications of electrochemical biosensors for allergens are discussed.