1
|
Shi L, Jia W, Zhang R, Fan Z, Bian W, Mo H. High-throughput analysis of hazards in novel food based on the density functional theory and multimodal deep learning. Food Chem 2024; 442:138468. [PMID: 38266417 DOI: 10.1016/j.foodchem.2024.138468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 12/30/2023] [Accepted: 01/15/2024] [Indexed: 01/26/2024]
Abstract
The emergence of cultured meat presents the potential for personalized food additive manufacturing, offering a solution to address future food resource scarcity. Processing raw materials and products in synthetic food products poses challenges in identifying hazards, impacting the entire industrial chain during the industry's further evolution. It is crucial to examine the correlation of biological information at different levels and to reveal the temporal dynamics jointly. Proposed active prevention method includes four aspects: (i) Investigating the molecular-level mechanism underlying the binding and dissociation of hazards with proteins represents a novel approach to mitigate matrix effect. (ii) Identifying distinct fragments is a pivotal advancement toward developing a novel screening strategy for hazards throughout the food chain. (iii) Designing an artificial intelligence model-based approach to acquire multi-dimensional histology data also holds significant potential for various applications. (iv) Integrating multimodal data is a practical approach to enhance evaluation and feedback control accuracy.
Collapse
Affiliation(s)
- Lin Shi
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Wei Jia
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China; Shaanxi Testing Institute of Product Quality Supervision, Xi'an, Shaanxi 710048, China; Shaanxi Research Institute of Agricultural Products Processing Technology, Xi'an 710021, China; Shaanxi Sky Pet Biotechnology Co., Ltd, Xi'an 710075, China.
| | - Rong Zhang
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Zibian Fan
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Wenwen Bian
- Shaanxi Testing Institute of Product Quality Supervision, Xi'an, Shaanxi 710048, China
| | - Haizhen Mo
- School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China; Shaanxi Research Institute of Agricultural Products Processing Technology, Xi'an 710021, China.
| |
Collapse
|
2
|
Das M, Proshad R, Chandra K, Islam M, Abdullah Al M, Baroi A, Idris AM. Heavy metals contamination, receptor model-based sources identification, sources-specific ecological and health risks in road dust of a highly developed city. Environ Geochem Health 2023; 45:8633-8662. [PMID: 37682507 DOI: 10.1007/s10653-023-01736-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 08/16/2023] [Indexed: 09/09/2023]
Abstract
The present study quantified Ni, Cu, Cr, Pb, Cd, As, Zn, and Fe levels in road dust collected from a variety of sites in Tangail, Bangladesh. The goal of this study was to use a matrix factorization model to identify the specific origin of these components and to evaluate the ecological and health hazards associated with each potential origin. The inductively coupled plasma mass spectrometry was used to determine the concentrations of Cu, Ni, Cr, Pb, As, Zn, Cd, and Fe. The average concentrations of these elements were found to be 30.77 ± 8.80, 25.17 ± 6.78, 39.49 ± 12.53, 28.74 ± 7.84, 1.90 ± 0.79, 158.30 ± 28.25, 2.42 ± 0.69, and 18,185.53 ± 4215.61 mg/kg, respectively. Compared to the top continental crust, the mean values of Cu, Pb, Zn, and Cd were 1.09, 1.69, 2.36, and 26.88 times higher, respectively. According to the Nemerow integrated pollution index (NIPI), pollution load index (PLI), Nemerow integrated risk index (NIRI), and potential ecological risk (PER), 84%, 42%, 30%, and 16% of sampling areas, respectively, which possessed severe contamination. PMF model revealed that Cu (43%), Fe (69.3%), and Cd (69.2%) were mainly released from mixed sources, natural sources, and traffic emission, respectively. Traffic emission posed high and moderate risks for modified NIRI and potential ecological risks. The calculated PMF model-based health hazards indicated that the cancer risk value for traffic emission, natural, and mixed sources had been greater than (1.0E-04), indicating probable cancer risks and that traffic emission posed 38% risk to adult males where 37% for both adult females and children.
Collapse
Affiliation(s)
- Mukta Das
- Department of Zoology, Government Saadat College, Tangail, 1903, Bangladesh
| | - Ram Proshad
- Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, Sichuan, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Krishno Chandra
- Faculty of Agricultural Engineering and Technology, Sylhet Agricultural University, Sylhet, 3100, Bangladesh
| | - Maksudul Islam
- Department of Environmental Science, Patuakhali Science and Technology University, Dumki, Patuakhali, 8602, Bangladesh
| | - Mamun Abdullah Al
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Aquatic Eco-Health Group, Fujian Key Laboratory of Watershed Ecology, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Artho Baroi
- Department of Crop Botany, Bangladesh Agricultural University, Mymensingh, 2202, Bangladesh
| | - Abubakr M Idris
- Department of Chemistry, College of Science, King Khalid University, 62529, Abha, Saudi Arabia
- Research Center for Advanced Materials Science (RCAMS), King Khalid University, 62529, Abha, Saudi Arabia
| |
Collapse
|