Food Constituent and Food Metabolite Databases

2021 ◽  
pp. 2-18
Author(s):  
Aidin Foroutan ◽  
David S. Wishart
Keyword(s):  
Food Constituent

scholarly journals Deep learning improves prediction of drug–drug and drug–food interactions

2018 ◽  
Vol 115 (18) ◽  
pp. E4304-E4311 ◽  
Author(s):  
Jae Yong Ryu ◽  
Hyun Uk Kim ◽  
Sang Yup Lee
Keyword(s):  
Drug Interactions ◽  
Adverse Drug Events ◽  
Structural Information ◽  
Drug Prescription ◽  
Pharmacological Effects ◽  
Drug Candidates ◽  
Causal Mechanisms ◽  
Alternative Drug ◽  
Food Constituent ◽  
Approved Drugs

Drug interactions, including drug–drug interactions (DDIs) and drug–food constituent interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug events (ADEs), with causal mechanisms often unknown. Several computational methods have been developed to better understand drug interactions, especially for DDIs. However, these methods do not provide sufficient details beyond the chance of DDI occurrence, or require detailed drug information often unavailable for DDI prediction. Here, we report development of a computational framework DeepDDI that uses names of drug–drug or drug–food constituent pairs and their structural information as inputs to accurately generate 86 important DDI types as outputs of human-readable sentences. DeepDDI uses deep neural network with its optimized prediction performance and predicts 86 DDI types with a mean accuracy of 92.4% using the DrugBank gold standard DDI dataset covering 192,284 DDIs contributed by 191,878 drug pairs. DeepDDI is used to suggest potential causal mechanisms for the reported ADEs of 9,284 drug pairs, and also predict alternative drug candidates for 62,707 drug pairs having negative health effects. Furthermore, DeepDDI is applied to 3,288,157 drug–food constituent pairs (2,159 approved drugs and 1,523 well-characterized food constituents) to predict DFIs. The effects of 256 food constituents on pharmacological effects of interacting drugs and bioactivities of 149 food constituents are predicted. These results suggest that DeepDDI can provide important information on drug prescription and even dietary suggestions while taking certain drugs and also guidelines during drug development.

Food Constituent Estimation for Lifestyle Disease Prevention by Multi-Task CNN

2019 ◽  
Vol 33 (8) ◽  
pp. 732-746 ◽  
Author(s):  
Sulfayanti F. Situju ◽  
Hironori Takimoto ◽  
Suzuka Sato ◽  
Hitoshi Yamauchi ◽  
Akihiro Kanagawa ◽  
...  
Keyword(s):  
Disease Prevention ◽  
Food Constituent ◽  
Lifestyle Disease

scholarly journals THE VITAMIN B1 AND B2 G CONTENT OF LIVER EXTRACT AND BREWERS' YEAST CONCENTRATE

1934 ◽  
Vol 59 (3) ◽  
pp. 315-331 ◽  
Author(s):  
D. K. Miller ◽  
C. P. Rhoads
Keyword(s):  
Liver Extract ◽  
Vitamin B1 ◽  
Normal Growth ◽  
Similar Rate ◽  
Vitamin B2 ◽  
Experimental Conditions ◽  
Adequate Amount ◽  
Brewers Yeast ◽  
Food Constituent ◽  
Sufficient Vitamin

1. Liver extract powder, No. 343 Lilly, and the same material prepared for parenteral use, when administered daily by mouth in amounts derived from 2.5 gm. of fresh whole liver, to rats weighing from 40 to 50 gm., contain sufficient vitamin B1 to support normal growth, provided the animals receive in addition an adequate amount of vitamin B2 G. Moreover, liver extract in the forms mentioned, administered in the same amounts, does not contain sufficient vitamin B2 G to maintain normal growth of similar rate when all other necessary constituents of the diet are provided. 2. Liver extract (Lilly) in the form prepared for parenteral use, when administered daily by intraperitoneal injections, in amounts derived from 2.5 gm. of fresh whole liver, to rats under standard experimental conditions, does not contain sufficient vitamin B2 G to maintain normal growth. Furthermore, the amount of vitamin B1 present in liver extract in this form is not as effective in supporting normal growth when given by intraperitoneal injection as it is when given by mouth. 3. Vegex, when administered daily in amounts of 50, 150, and 250 mg. to rats of 40 to 50 gm. in weight contains sufficient vitamin B1 to maintain normal growth of the rats, provided the animals receive in addition an adequate amount of vitamin B2 G. However, vegex in the same amounts does not contain sufficient vitamin B2 G to support normal growth of similar rats when all other necessary constituents of the diet are provided. 4. These experiments indicate that the extrinsic, anti-anemic factor of Castle and the thermostable growth-promoting food constituent, commonly known as vitamin B2 G, are not identical.

scholarly journals Electrochemical Peptide-Based Sensors for Foodborne Pathogens Detection

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3200
Author(s):  
Mihaela Tertis ◽  
Oana Hosu ◽  
Bogdan Feier ◽  
Andreea Cernat ◽  
Anca Florea ◽  
...  
Keyword(s):  
Foodborne Pathogens ◽  
New Technologies ◽  
Food Samples ◽  
World Health ◽  
Chronic Patients ◽  
Food Research ◽  
Health Domains ◽  
Food Constituent ◽  
Recognition Elements ◽  
Health Organization

Food safety and quality control pose serious issues to food industry and public health domains, in general, with direct effects on consumers. Any physical, chemical, or biological unexpected or unidentified food constituent may exhibit harmful effects on people and animals from mild to severe reactions. According to the World Health Organization (WHO), unsafe foodstuffs are especially dangerous for infants, young children, elderly, and chronic patients. It is imperative to continuously develop new technologies to detect foodborne pathogens and contaminants in order to aid the strengthening of healthcare and economic systems. In recent years, peptide-based sensors gained much attention in the field of food research as an alternative to immuno-, apta-, or DNA-based sensors. This review presents an overview of the electrochemical biosensors using peptides as molecular bio-recognition elements published mainly in the last decade, highlighting their possible application for rapid, non-destructive, and in situ analysis of food samples. Comparison with peptide-based optical and piezoelectrical sensors in terms of analytical performance is presented. Methods of foodstuffs pretreatment are also discussed.

scholarly journals High throughput ‘omics’ approaches to assess the effects of phytochemicals in human health studies

2008 ◽  
Vol 99 (E-S1) ◽  
pp. ES127-ES134 ◽  
Author(s):  
Jaroslava Ovesná ◽  
Ondřej Slabý ◽  
Olivier Toussaint ◽  
Milan Kodíček ◽  
Petr Maršík ◽  
...  
Keyword(s):  
Human Health ◽  
High Throughput ◽  
Fruits And Vegetables ◽  
Expression Profiles ◽  
Future Technology ◽  
Whole Process ◽  
Large Numbers ◽  
Health Studies ◽  
Food Constituent ◽  
Experimental Approaches

Human health is affected by many factors. Diet and inherited genes play an important role. Food constituents, including secondary metabolites of fruits and vegetables, may interact directly with DNA via methylation and changes in expression profiles (mRNA, proteins) which results in metabolite content changes. Many studies have shown that food constituents may affect human health and the exact knowledge of genotypes and food constituent interactions with both genes and proteins may delay or prevent the onset of diseases. Many high throughput methods have been employed to get some insight into the whole process and several examples of successful research, namely in the field of genomics and transcriptomics, exist. Studies on epigenetics and RNome significance have been launched. Proteomics and metabolomics need to encompass large numbers of experiments and linked data. Due to the nature of the proteins, as well as due to the properties of various metabolites, experimental approaches require the use of comprehensive high throughput methods and a sufficiency of analysed tissue or body fluids. In this contribution, we describe the basic tools currently used in nutrigenomics studies and indicate the general requirements for future technology methodological routings.

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