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Aleixandre M, Prasetyawan D, Nakamoto T. Automatic scent creation by cheminformatics method. Sci Rep 2024; 14:31284. [PMID: 39733041 PMCID: PMC11682350 DOI: 10.1038/s41598-024-82654-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 12/06/2024] [Indexed: 12/30/2024] Open
Abstract
The sense of smell is fundamental for various aspects of human existence including the flavor perception, environmental awareness, and emotional impact. However, unlike other senses, it has not been digitized. Its digitalization faces challenges such as the lack of reliable odor sensing technology or the precise scent delivery through olfactory displays. Its subjective nature and context dependence add complexity to the process. Moreover, the method of converting odors to digital information remains unclear. This work focuses on one of the most challenging aspects of digital olfaction: automatic scent creation. We propose a method that automatically creates a desired odor profile with the addition of one specific odor descriptor. It is based on a deep neural network that predicts odor descriptors from the multidimensional sensing data, such as mass spectra and an odor reproduction technique using odor components. The results demonstrate that the proposed method can successfully create a scent with the desired odor profile and that its performance depends on the accuracy of the underlying odor predicting method. This opens up the possibility of automatic scent creation, allowing for the presentation of scents with specific odor profiles with an olfactory display.
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Affiliation(s)
- Manuel Aleixandre
- Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST), Institute of Integrated Research (IIR), Institute of Science Tokyo, 4259 Nagatsuta-cho, Midori, Yokohama, 226-8503, Kanagawa, Japan
| | - Dani Prasetyawan
- Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST), Institute of Integrated Research (IIR), Institute of Science Tokyo, 4259 Nagatsuta-cho, Midori, Yokohama, 226-8503, Kanagawa, Japan
| | - Takamichi Nakamoto
- Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST), Institute of Integrated Research (IIR), Institute of Science Tokyo, 4259 Nagatsuta-cho, Midori, Yokohama, 226-8503, Kanagawa, Japan.
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2
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Queiroz LP, Nogueira IBR, Ribeiro AM. Flavor Engineering: A comprehensive review of biological foundations, AI integration, industrial development, and socio-cultural dynamics. Food Res Int 2024; 196:115100. [PMID: 39614513 DOI: 10.1016/j.foodres.2024.115100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 09/11/2024] [Accepted: 09/12/2024] [Indexed: 12/01/2024]
Abstract
This state-of-the-art review comprehensively explores flavor development, spanning biological foundations, analytical methodologies, and the socio-cultural impact. It incorporates an industrial perspective and examines the role of artificial intelligence (AI) in flavor science. Initiating with the biological intricacies of flavor, the review delves into the interplay of taste, aroma, and texture rooted in sensory experiences. Advances in mathematical modeling and analytical techniques open avenues for interdisciplinary collaboration and technological innovation, addressing variations in flavor perception. The impact of flavor extends beyond gustatory experiences, influencing economics, society, nutrition, health, and technological innovation. This collective understanding deepens insight into the dynamic interplay between olfactory and flavor elements within cultural landscapes, emphasizing how sensory experiences are woven into human culture and heritage. The evolution of food flavor analysis, encompassing sensory analysis, instrumental analysis, a combination of both, and the integration of artificial intelligence techniques, signifies dynamic progression and, promising advancements in precision, efficiency, and innovation within the flavor industry. This comprehensive review involved analyzing key aspects within flavor engineering and related sectors. Articles and book chapters on these topics were collected using metadata analysis. The data for this analysis was extracted from major online databases, including Scopus, Web of Science, and ScienceDirect.
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Affiliation(s)
- L P Queiroz
- LSRE-LCM - Laboratory of Separation and Reaction Engineering - Laboratory of Catalysis and Materials, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto 4200-465, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto 4200-465, Portugal.
| | - I B R Nogueira
- Chemical Engineering Department, Norwegian University of Science and Technology, Sem Sælandsvei 4, Kjemiblokk 5, Trondheim 793101, Norway
| | - A M Ribeiro
- LSRE-LCM - Laboratory of Separation and Reaction Engineering - Laboratory of Catalysis and Materials, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto 4200-465, Portugal; ALiCE - Associate Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto 4200-465, Portugal
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3
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Zhan K, Kanj AB, Heinke L. Classification and Identification of Perfume Scents by an Enantioselective Colorimetric Sensor Array of Chiral Metal-Organic-Framework-Based Fabry-Pérot Films. Chemistry 2024; 30:e202400798. [PMID: 38623849 DOI: 10.1002/chem.202400798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 04/11/2024] [Accepted: 04/15/2024] [Indexed: 04/17/2024]
Abstract
Many odors, like perfumes, are complex mixtures of chiral and achiral molecules where the cost-efficient (enantio-)selective sensing represents a major technical challenge. Here, we present a colorimetric sensor array of surface-mounted metal-organic-framework (SURMOF) films in Fabry-Pérot (FP) cavities. The optical properties of the FP-SURMOF films with different chiral and achiral structures are affected by the (enantio-)selective adsorption of the analytes in the SURMOF pores, resulting in different responses to the analyte molecules. The read-out of the sensor array is performed by the digital camera of a common smartphone, where the RGB values are determined. By analyzing the sensor array data with simple machine learning algorithms, the analytes are discriminated. After demonstrating the enantioselective response for a pair of pure chiral odor molecules, we apply the sensor array to detect and discriminate a large number (16) of common commercial perfumes and eau de toilettes. While our untrained human nose is not able to discriminate all perfumes, the presented colorimetric sensor array can classify all perfumes with great classification accuracy. Moreover, the sensor array was used to identify unlabeled samples correctly. We foresee such an FP-chiral-SURMOF-based sensor array as a powerful approach toward inexpensive selective odors sensing applications.
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Affiliation(s)
- Kuo Zhan
- Institute of Functional Interfaces (IFG), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
- School of Physical Science and Engineering, Beijing Jiaotong University, 100044, Beijing, China
| | - Anemar Bruno Kanj
- Institute of Functional Interfaces (IFG), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
| | - Lars Heinke
- Institute of Functional Interfaces (IFG), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany
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Queiroz L, Rebello CM, Costa EA, Santana V, Rodrigues BCL, Rodrigues AE, Ribeiro AM, Nogueira IBR. Generating Flavor Molecules Using Scientific Machine Learning. ACS OMEGA 2023; 8:10875-10887. [PMID: 37008127 PMCID: PMC10061502 DOI: 10.1021/acsomega.2c07176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 03/03/2023] [Indexed: 06/19/2023]
Abstract
Flavor is an essential component in the development of numerous products in the market. The increasing consumption of processed and fast food and healthy packaged food has upraised the investment in new flavoring agents and consequently in molecules with flavoring properties. In this context, this work brings up a scientific machine learning (SciML) approach to address this product engineering need. SciML in computational chemistry has opened paths in the compound's property prediction without requiring synthesis. This work proposes a novel framework of deep generative models within this context to design new flavor molecules. Through the analysis and study of the molecules obtained from the generative model training, it was possible to conclude that even though the generative model designs the molecules through random sampling of actions, it can find molecules that are already used in the food industry, not necessarily as a flavoring agent, or in other industrial sectors. Hence, this corroborates the potential of the proposed methodology for the prospecting of molecules to be applied in the flavor industry.
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Affiliation(s)
- Luana
P. Queiroz
- LSRE-LCM-Laboratory
of Separation and Reaction Engineering-Laboratory of Catalysis and
Materials, Faculty of Engineering, University
of Porto, Rua Dr. Roberto
Frias, 4200-465 Porto, Portugal
- ALiCE-Associate
Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
| | - Carine M. Rebello
- Departamento
de Engenharia Química, Escola Politécnica (Polytechnic
Institute), Universidade Federal da Bahia, 40210-630 Salvador, Brazil
| | - Erbet A. Costa
- Departamento
de Engenharia Química, Escola Politécnica (Polytechnic
Institute), Universidade Federal da Bahia, 40210-630 Salvador, Brazil
| | - Vinícius
V. Santana
- LSRE-LCM-Laboratory
of Separation and Reaction Engineering-Laboratory of Catalysis and
Materials, Faculty of Engineering, University
of Porto, Rua Dr. Roberto
Frias, 4200-465 Porto, Portugal
- ALiCE-Associate
Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
| | - Bruno C. L. Rodrigues
- LSRE-LCM-Laboratory
of Separation and Reaction Engineering-Laboratory of Catalysis and
Materials, Faculty of Engineering, University
of Porto, Rua Dr. Roberto
Frias, 4200-465 Porto, Portugal
- ALiCE-Associate
Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
| | - Alírio E. Rodrigues
- LSRE-LCM-Laboratory
of Separation and Reaction Engineering-Laboratory of Catalysis and
Materials, Faculty of Engineering, University
of Porto, Rua Dr. Roberto
Frias, 4200-465 Porto, Portugal
- ALiCE-Associate
Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
| | - Ana M. Ribeiro
- LSRE-LCM-Laboratory
of Separation and Reaction Engineering-Laboratory of Catalysis and
Materials, Faculty of Engineering, University
of Porto, Rua Dr. Roberto
Frias, 4200-465 Porto, Portugal
- ALiCE-Associate
Laboratory in Chemical Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
| | - Idelfonso B. R. Nogueira
- Chemical
Engineering Department, Norwegian University
of Science and Technology, Sem Sælandsvei 4, Kjemiblokk 5, 7491 Trondheim, Norway
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Lee YJ, Lee S, Kim DM. Translational Detection of Indole by Complementary Cell-free Protein Synthesis Assay. Front Bioeng Biotechnol 2022; 10:900162. [PMID: 35646868 PMCID: PMC9136167 DOI: 10.3389/fbioe.2022.900162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 04/28/2022] [Indexed: 11/16/2022] Open
Abstract
The information encoded in a single copy of DNA is processed into a plethora of protein molecules via the cascade of transcription and translation. Thus, the molecular process of gene expression can be considered an efficient biological amplifier from the viewpoint of synthetic biology. Cell-free protein synthesis (CFPS) enables the implementation of this amplification module for in vitro analysis of important biomolecules and avoids many of the problems associated with whole cell-based approaches. Here, we developed a method to analyze indole by using a combination of enzymatic conversion of indole and amino acid-dependent CFPS. In this method, indole molecules in the assay sample are used to generate tryptophan, which is incorporated into signal-generating proteins in the subsequent cell-free synthesis reaction. The activity of cell-free synthesized proteins was successfully used to estimate the indole concentration in the assay sample. In principle, the developed method could be extended to analyses of other important bioactive compounds.
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Affiliation(s)
- You Jin Lee
- Department of Chemical Engineering and Applied Chemistry, Daejeon, Korea
| | - Soojin Lee
- Department of Microbiology and Molecular Biology, Chungnam National University, Daejeon, Korea
| | - Dong-Myung Kim
- Department of Chemical Engineering and Applied Chemistry, Daejeon, Korea
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Zioga E, Tøstesen M, Kjærulf Madsen S, Shetty R, Bang-Berthelsen CH. Bringing plant-based Cli-meat closer to original meat experience: insights in flavor. FUTURE FOODS 2022. [DOI: 10.1016/j.fufo.2022.100138] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
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Abstract
The fragrance field of perfumes has attracted considerable scientific, industrial, cultural, and civilizational interest. The marine odor is characterized by the specific smell of sea breeze, seashore, algae, and oyster, among others. Marine odor is a more recent fragrance and is considered as one of the green and modern fragrances. The smells reproducing the marine environment are described due to their content of Calone 1951 (7-methyl-2H-1,5-benzodioxepin-3(4H)-one), which is a synthetic compound. In addition to the synthetic group of benzodioxepanes, such as Calone 51 and its derivatives, three other groups of chemical compounds seem to represent the marine smell. The first group includes the polyunsaturated cyclic ((+)-Dictyopterene A) and acyclic (giffordene) hydrocarbons, acting as pheromones. The second group corresponds to polyunsaturated aldehydes, such as the (Z,Z)-3,6-nonadienal, (E,Z)-2,6-nonadienal, which are most likely derived from the degradation of polyunsaturated fatty acids. The third group is represented by small molecules such as sulfur compounds and halogenated phenols which are regarded as the main flavor compounds of many types of seafood. This review exposes, most notably, the knowledge state on the occurrence of marine ingredients in fragrance. We also provide a detailed discussion on several aspects of essential oils, which are the most natural ingredients from various marine sources used in fragrance and cosmetics, including synthetic and natural marine ingredients.
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