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Yan B, Jia Y, Zhang X, Zhang L, Guan W, Lu C. Aggregation-induced emission micelle-based sensing array for discrimination of long-chain fatty acids. Chem Commun (Camb) 2024. [PMID: 39073114 DOI: 10.1039/d4cc01801j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
A sensing array based on aggregation-induced emission micelles was proposed for efficient discrimination of three typical long-chain fatty acids (lauric, palmitic, and stearic acids) and their mixtures.
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Affiliation(s)
- Bingqian Yan
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 10029, China.
| | - Yunxiu Jia
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 10029, China.
| | - Xin Zhang
- Department of Chemistry, Capital Normal University, Beijing, 100048, China
| | - Lijuan Zhang
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 10029, China.
| | - Weijiang Guan
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 10029, China.
| | - Chao Lu
- State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 10029, China.
- Pingyuan Laboratory, College of Chemistry, Zhengzhou University, Zhengzhou, 450001, China
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Li M, Zhao Z, Zhang Y, Guo X, Zhang Y, Wang J, Liu Y, Yang L, Mou W, Zhang X, Gao H. Chemometrics combined with comprehensive two-dimensional gas chromatography-mass spectrometry for the identification of Baijiu vintage. Food Chem 2024; 444:138690. [PMID: 38354654 DOI: 10.1016/j.foodchem.2024.138690] [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: 11/03/2023] [Revised: 02/03/2024] [Accepted: 02/05/2024] [Indexed: 02/16/2024]
Abstract
The identification of baijiu vintage is crucial for quality assessment and economic value determination. However, its complex composition and multifaceted influences pose significant technical challenges, necessitating research into its aging mechanisms and the development of related identification methods. This study utilized Chemometrics in conjunction with GC × GC-TOFMS for Baijiu Vintage identification. Data compression achieved a reduction of over 1000-fold without compromising key information, enabling analysis on many samples and get their changing regular in a big matrix by MCR. Subsequently, MCR-ALS facilitated the extraction of physical and chemical meaningful information related to baijiu vintage. Key MCR principal components suitable for qualitative and quantitative assessments were selected using CARS-PLS. The regression model demonstrated errors of less than one year. Furthermore, a PLS-DA model provided 30 MCR principal components as potential markers. The research results provide technical support for baijiu vintage identification and lay the groundwork for studying the changing patterns of flavor compounds in baijiu.
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Affiliation(s)
- Miao Li
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Zhengyu Zhao
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Yusong Zhang
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Xinguang Guo
- China National Research Institute of Food & Fermentation Industries Co., Ltd, Beijing 100016, China
| | - Yu Zhang
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Jian Wang
- China National Research Institute of Food & Fermentation Industries Co., Ltd, Beijing 100016, China
| | - Yangqingxue Liu
- China National Research Institute of Food & Fermentation Industries Co., Ltd, Beijing 100016, China
| | - Lihua Yang
- Guangzhou Hexin Instrument Co. Ltd., Guangzhou 510535, China
| | - Wenlong Mou
- Department of Chemistry, Capital Normal University, Beijing 100048, China
| | - Xin Zhang
- Department of Chemistry, Capital Normal University, Beijing 100048, China.
| | - Hongbo Gao
- China National Research Institute of Food & Fermentation Industries Co., Ltd, Beijing 100016, China.
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Wu T, Liu P, Wu J, Jiang Y, Zhou N, Zhang Y, Xu Q, Zhang Y. Broiler Spaghetti Meat Abnormalities: Muscle Characteristics and Metabolomic Profiles. Animals (Basel) 2024; 14:1236. [PMID: 38672384 PMCID: PMC11047362 DOI: 10.3390/ani14081236] [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: 03/17/2024] [Revised: 04/17/2024] [Accepted: 04/18/2024] [Indexed: 04/28/2024] Open
Abstract
Spaghetti meat (SM) is a newly identified muscle abnormality that significantly affects modern broiler chickens, consequently exerting a substantial economic impact on the poultry industry worldwide. However, investigations into the meat quality and the underlying causative factors of SM in broilers remain limited. Therefore, this study was undertaken to systematically evaluate meat quality and muscle fiber characteristics of SM-affected meat. To elucidate the disparities between SM-affected and normal (NO) muscles in broiler chickens reared under identical conditions, we selected 18 SM-affected breast tissues and 18 NO breast tissues from 200 broiler chickens raised according to commercial standards under the same conditions for our study. The results showed that compared with the NO group, the muscle surface of the SM group lost integrity, similar to strip and paste. The brightness and yellowness values were significantly higher than those of the NO group. On the contrary, the shear force and protein were significantly lower in the SM group. Microscopic examination revealed that the muscle fibers in the SM group were lysed, necrotic, and separated from each other, with a large number of neutrophils diffusely distributed on the sarcolemma and endometrium. Thirty-five significantly different metabolites were observed in the breast muscles between both groups. Among them, the top differential metabolites-14,15-DiHETrE, isotretinoin, L-malic acid, and acetylcysteine-were mainly enriched in lipid metabolism and inflammatory pathways, including linoleic acid, arachidonic acid, phenylalanine, and histidine metabolism. Overall, these findings not only offer new insights into the meat quality and fiber traits of SM but also contribute to the understanding of potential mechanisms and nutritional regulators for SM myopathy.
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Affiliation(s)
- Teng Wu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
- Key Laboratory for Evaluation and Utilization of Livestock and Poultry Resources (Poultry), Ministry of Agriculture and Rural Affairs, Beijing 100176, China
| | - Pingping Liu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
| | - Jia Wu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
- Key Laboratory for Evaluation and Utilization of Livestock and Poultry Resources (Poultry), Ministry of Agriculture and Rural Affairs, Beijing 100176, China
| | - Youluan Jiang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
| | - Ning Zhou
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
| | - Yang Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
- Key Laboratory for Evaluation and Utilization of Livestock and Poultry Resources (Poultry), Ministry of Agriculture and Rural Affairs, Beijing 100176, China
| | - Qi Xu
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
- Key Laboratory for Evaluation and Utilization of Livestock and Poultry Resources (Poultry), Ministry of Agriculture and Rural Affairs, Beijing 100176, China
| | - Yu Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.W.); (P.L.); (J.W.); (Y.J.); (N.Z.); (Y.Z.); (Q.X.)
- Key Laboratory for Evaluation and Utilization of Livestock and Poultry Resources (Poultry), Ministry of Agriculture and Rural Affairs, Beijing 100176, China
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Vosough M, Salemi A, Rockel S, Schmidt TC. Enhanced efficiency of MS/MS all-ion fragmentation for non-targeted analysis of trace contaminants in surface water using multivariate curve resolution and data fusion. Anal Bioanal Chem 2024; 416:1165-1177. [PMID: 38206346 PMCID: PMC10850027 DOI: 10.1007/s00216-023-05102-x] [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: 09/22/2023] [Revised: 11/18/2023] [Accepted: 11/30/2023] [Indexed: 01/12/2024]
Abstract
Data-independent acquisition-all-ion fragmentation (DIA-AIF) mode of mass spectrometry can facilitate wide-scope non-target analysis of contaminants in surface water due to comprehensive spectral identification. However, because of the complexity of the resulting MS2 AIF spectra, identifying unknown pollutants remains a significant challenge, with a significant bottleneck in translating non-targeted chemical signatures into environmental impacts. The present study proposes to process fused MS1 and MS2 data sets obtained from LC-HRMS/MS measurements in non-targeted AIF workflows on surface water samples using multivariate curve resolution-alternating least squares (MCR-ALS). This enables straightforward assignment between precursor ions obtained from resolved MS1 spectra and their corresponding MS2 spectra. The method was evaluated for two sets of tap water and surface water contaminated with 14 target chemicals as a proof of concept. The data set of surface water samples consisting of 3506 MS1 and 2170 MS2 AIF mass spectral features was reduced to 81 components via a fused MS1-MS2 MCR model that describes at least 98.8% of the data. Each component summarizes the distinct chromatographic elution of components together with their corresponding MS1 and MS2 spectra. MS2 spectral similarity of more than 82% was obtained for most target chemicals. This highlights the potential of this method for unraveling the composition of MS/MS complex data in a water environment. Ultimately, the developed approach was applied to the retrospective non-target analysis of an independent set of surface water samples.
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Affiliation(s)
- Maryam Vosough
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany.
- Department of Clean Technologies, Chemistry and Chemical Engineering Research Center of Iran, P.O. Box 14335-186, Tehran, Iran.
| | - Amir Salemi
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany
| | - Sarah Rockel
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany
| | - Torsten C Schmidt
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany
- IWW Water Centre, Moritzstr. 26, Mülheim an der Ruhr, 45476, Germany
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