Reusable Electronic Tongue Based on Transient Receptor Potential Vanilloid 1 Nanodisc-Conjugated Graphene Field-Effect Transistor for a Spiciness-Related Pain Evaluation

Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development

The food flavor science, traditionally reliant on experimental methods, is now entering a promising era with the help of artificial intelligence (AI). By integrating existing technologies with AI, researchers can explore and develop new flavor substances in a digital environment, saving time and resources. More and more research will use AI and big data to enhance product flavor, improve product quality, meet consumer needs, and drive the industry toward a smarter and more sustainable future. In this review, we elaborate on the mechanisms of flavor recognition and their potential impact on nutritional regulation. With the increase of data accumulation and the development of internet information technology, food flavor databases and food ingredient databases have made great progress. These databases provide detailed information on the nutritional content, flavor molecules, and chemical properties of various food compounds, providing valuable data support for the rapid evaluation of flavor components and the construction of screening technology. With the popularization of AI in various fields, the field of food flavor has also ushered in new development opportunities. This review explores the mechanisms of flavor recognition and the role of AI in enhancing food flavor analysis through high-throughput omics data and screening technologies. AI algorithms offer a pathway to scientifically improve product formulations, thereby enhancing flavor and customized meals. Furthermore, it discusses the safety challenges of integrating AI into the food flavor industry.

TRPA1 nanovesicle-conjugated receptonics for rapid biocide screening

Although biocides are important materials in modern society and help protect human health and the environment, increasing exposure to combined biocides can cause severe side effects in the human body, such as lung fibrosis. In this study, we developed a receptonics system to screen for biocides in combined household chemical products based on biocides. The system contains transient receptor potential ankyrin 1 (TRPA1) nanovesicles (NVs) to sense biocides based on pain receptors and a side-gated field-effect transistor (SGFET) using a single-layer graphene (SLG) micropattern channel. The binding affinities between the TRPA1 receptor and the various biocides were estimated by performing biosimulation and using a calcium ion (Ca2+) assay, and the sensitivity of the system was compared with that of TRPA1 NV receptonics systems. Based on the results of the TRPA1 NV receptonics system, the antagonistic and potentiation effects of combined biocides and household chemical products depended on the concentration. Finally, the TRPA1 NV receptonics system was applied to screen for biocides in real products, and its performance was successful. Based on these results, the TRPA1 NV receptonics system can be utilized to perform risk evaluations and identify biocides in a simple and rapid manner.

Synchronous Diagnosis of Respiratory Viruses Variants via Receptonics Based on Modeling Receptor-Ligand Dynamics

The transmission and pathogenesis of highly contagious fatal respiratory viruses are increasing, and the need for an on-site diagnostic platform has arisen as an issue worldwide. Furthermore, as the spread of respiratory viruses continues, different variants have become the dominant circulating strains. To prevent virus transmission, the development of highly sensitive and accurate on-site diagnostic assays is urgently needed. Herein, a facile diagnostic device is presented for multi-detection based on the results of detailed receptor-ligand dynamics simulations for the screening of various viral strains. The novel bioreceptor-treated electronics (receptonics) device consists of a multichannel graphene transistor and cell-entry receptors conjugated to N-heterocyclic carbene (NHC). An ultrasensitive multi-detection performance is achieved without the need for sample pretreatment, which will enable rapid diagnosis and prevent the spread of pathogens. This platform can be applied for the diagnosis of variants of concern in clinical respiratory virus samples and primate models. This multi-screening platform can be used to enhance surveillance and discriminate emerging virus variants before they become a severe threat to public health.

Recent advancements in the taste transduction mechanism, identification, and characterization of taste components

In the realm of human nutrition, the phenomenon known as taste refers to a distinctive sensation elicited by the consumption of food and various compounds within the oral cavity and on the tongue. Moreover, taste affects the overall comfort in the oral cavity, and is a fundamental attribute for the assessment of food items. Accordingly, clarifying the material basis of taste would be conducive to deepening the cognition of taste, investigating the mechanism of taste presentation, and accurately covering up unpleasant taste. In this paper, the basic biology and physiology of transduction of bitter, umami, sweet, sour, salty, astringent, as well as spicy tastes are reviewed. Furthermore, the detection process of taste components is summarized. Particularly, the applications, advantages, and distinctions of various isolation, identification, and evaluation methods are discussed in depth. In conclusion, the future of taste component detection is discussed.