FOCUS-DB: An Online Comprehensive Database on Food Additive Safety

Abstract

Processing and packaging food has greatly exaggerated the use of food additives in different types of food products. Safety assessment to determine the pharmacokinetic and toxicological properties of food additives is imperative and experimentally challenging. Several resources of food additives properties have been collated; however, information remains partial, scattered, and not readily accessible, particularly for food safety. To address the concern related to the potential health hazard of food additives, we have developed the Food-Additive-Consumption-Safety Database (FOCUS-DB). Presently, the database comprises 2885 food additives, distributed into 18 categories with 40,800 collected data points, 89,435 predicted data points, and 14,425 external links. The dynamic web interface of the FOCUS-DB resource enables a risk assessment of additives, their approval status in various regulatory authorities, physicochemical properties, acceptable daily intake, GHS signals, biological pathways, predicted pharmacokinetic parameters, and various toxicity endpoint values. FOCUS-DB supports the exploration of food additives; it is beneficial for both the regulatory authorities and industries to optimize the usage limits of the additives and formulations. This database is a promising tool that helps understand the relationship between food additives and toxicity, which could be used to develop a future food safety framework.

A Computational Approach for Respiratory Hazard Identification of Flavor Chemicals in Tobacco Products

“…In general, multiple chemical registry numbers for the same chemical and lack of registry number while reporting tobacco chemicals is a common problem. There is a need to develop consolidated data sets, such as the recent food additives database . In this study, data from multiple sources were curated and organized for information on the chemical structures, flavor and GHS classification, and use in tobacco products to build a large library of flavor chemicals.…”

“…There is a need to develop consolidated data sets, such as the recent food additives database. 53 In this study, data from multiple sources were curated and organized for information on the chemical structures, flavor and GHS classification, and use in tobacco products to build a large library of flavor chemicals. On the basis of publicly available data, only one-third of chemicals in this flavor library are currently reported in tobacco products.…”

CERM: Context-Aware Literature-Based Discovery via Sentiment Analysis

“…We then invite external data curators to assign the sentiment of selected entity pairs given their corresponding sentences. This labeling is done using the Amazon Mechanical Turk System 7 . Each entity pair and respective sentences are labeled by 3 different people as either positive, negative, or neutral.…”

“…Research on the first system has been extensively conducted, but research on the second is limited. In addition, research in this field often prioritizes the development of databases [7,18,23,25] that summarize existing relationships rather than adaptive systems that can learn and incorporate new information. Arguably, such a system is much needed given that research related to food science is still developing; thus, knowledge about the effects of compounds on diseases can change based on the latest studies.…”