1
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Qu Y, Chen M, Wang Y, Qu L, Wang R, Liu H, Wang L, Nie Z. Rapid screening of infertility-associated gynecological conditions via ambient glow discharge mass spectrometry utilizing urine metabolic fingerprints. Talanta 2024; 274:125969. [PMID: 38608629 DOI: 10.1016/j.talanta.2024.125969] [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: 12/04/2023] [Revised: 02/29/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024]
Abstract
Infertility presents a widespread challenge for many families worldwide, often arising from various gynecological diseases (GDs) that hinder successful pregnancies. Current diagnostic methods for GDs have disadvantages such as low efficiency, high cost, misdiagnose, invasive injury and etc. This paper introduces a rapid, non-invasive, efficient, and straightforward analytical method that utilizes desorption, separation, and ionization mass spectrometry (DSI-MS) platform in conjunction with machine learning (ML) to detect urine metabolite fingerprints in patients with different GDs. We analyzed 257 samples from patients diagnosed with polycystic ovary syndrome (PCOS), premature ovarian insufficiency (POI), diminished ovarian reserve (DOR), endometriosis (EMS), recurrent pregnancy loss (RPL), recurrent implantation failure (RIF), and 87 samples from healthy control (HC) individuals. We identified metabolite differences and dysregulated pathways through dimensionality reduction methods, with the result of the discovery of 7 potential biomarkers for GDs diagnosis. The ML method effectively distinguished subtle differences in urine metabolite fingerprints. We anticipate that this innovative approach will offer a patient-friendly, rapid screening, and differentiation method for infertility-related GDs patients.
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Affiliation(s)
- Yijiao Qu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Ming Chen
- Centre of Reproductive Medicine, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, 518000, China; Department of Gynecology and Obstetrics, Guangxi University of Chinese Medicine, Nanning, 530200, China
| | - Yiran Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Liangliang Qu
- School of Life Sciences, Nanchang University, Nanchang, 330031, China
| | - Ruiyue Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Huihui Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Liping Wang
- Centre of Reproductive Medicine, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, 518000, China.
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100190, China.
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2
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Li S, Xiao Q, Sun J, Li Z, Zhang M, Tian Y, Zhang Z, Dong H, Jiao Y, Xu F, Zhang P. A new chemical derivatization reagent sulfonyl piperazinyl for the quantification of fatty acids using LC-MS/MS. Talanta 2024; 277:126378. [PMID: 38870757 DOI: 10.1016/j.talanta.2024.126378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 05/04/2024] [Accepted: 06/05/2024] [Indexed: 06/15/2024]
Abstract
In our previous study, a chemical derivatization reagent named 5-(dimethylamino) naphthalene-1-sulfonyl piperazine (Dns-PP) was developed to enhance the chromatographic retention and the mass spectrometric response of free fatty acids (FFAs) in reversed-phase liquid chromatography coupled with electrospray ionization-mass spectrometry (RPLC-ESI-MS). However, Dns-PP exhibited strong preferences for long-chain FFAs, with limited improvement for short- or medium-chain FFAs. In this study, a new series of labeling reagents targeting FFAs were designed, synthesized, and evaluated. Among these reagents, Tmt-PP (N2, N2, N4, N4-tetramethyl-6-(4-(piperazin-1-ylsulfonyl) phenyl)-1,3,5-triazine-2,4-diamine) exhibited the best MS response and was selected for further evaluations. We compared Tmt-PP with Dns-PP and four commonly used carboxyl labeling reagents from existing studies, demonstrating the advantages of Tmt-PP. Further comparisons between Tmt-PP and Dns-PP in measuring FFAs from biological samples revealed that Tmt-PP labeling enhanced the MS response for about 80 % (30/38) of the measured FFAs, particularly for short- and medium-chain FFAs. Moreover, Tmt-PP labeling significantly improved the chromatographic retention of short-chain FFAs. To ensure accurate quantification, we developed a stable isotope-labeled Tmt-PP (i.e., d12-Tmt-PP) to react with chemical standards and serve as one-to-one internal standards (IS). The method was validated for accuracy, precision, sensitivity, linearity, stability, extraction efficiency, as well as matrix effect. Overall, this study introduced a new chemical derivatization reagent Tmt-PP (d12-Tmt-PP), providing a sensitive and accurate option for quantifying FFAs in biological samples.
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Affiliation(s)
- Siqi Li
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Qinwen Xiao
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Jiarui Sun
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Zhaoqian Li
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Mengting Zhang
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Yuan Tian
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Zunjian Zhang
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Haijuan Dong
- The Public Laboratory Platform, China Pharmaceutical University, Nanjing, 210009, PR China
| | - Yu Jiao
- Department of Organic Chemistry, China Pharmaceutical University, Nanjing, 210009, PR China.
| | - Fengguo Xu
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China; School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing, 210009, PR China.
| | - Pei Zhang
- Key Laboratory of Drug Quality Control and Pharmacovigilance (Ministry of Education), State Key Laboratory of Natural Medicine, China Pharmaceutical University, Nanjing, 210009, PR China.
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3
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Wang Y, Wan L, Li Y, Qu Y, Qu L, Ma X, Yu Y, Wang X, Nie Z. Profiling of carbonyl metabolic fingerprints in urine of Graves' disease patients based on atmospheric ionization mass spectrometry. Talanta 2024; 277:126329. [PMID: 38815320 DOI: 10.1016/j.talanta.2024.126329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 05/22/2024] [Accepted: 05/25/2024] [Indexed: 06/01/2024]
Abstract
Graves' disease (GD) is considered among the organ autoimmune diseases and is somewhat linked to other autoimmune and secondary diseases. Commonly used detection methods rely on identifying characteristic clinical features and abnormal biochemical markers, but they have certain limitations and may be affected by patient medication. In this study, a desorption separation ionization (DSI) device coupled with a linear ion trap mass spectrometer is introduced for effective detection and screening of urine from GD patients. To enhance the sensitivity of MS analysis, derivatization reagent is utilized as a labeling method. The MS signal is used for metabolic profiling, through which differential metabolites and pathways are identified. Subsequently, processing the acquired spectra with a machine learning algorithm enables successful differentiation of GD patients and healthy individuals. This method is believed to provide versatile and powerful technical support for effective detection on the scene. Notably, this method offers the advantage of achieving early and rapid diagnosis of thyroid-related diseases.
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Affiliation(s)
- Yiran Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Li Wan
- Clinical Biobank, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Yuze Li
- State Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan, 750021, China
| | - Yijiao Qu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Liangliang Qu
- School of Life Sciences, Nanchang University, Nanchang, 330031, China
| | - Xiaobing Ma
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
| | - Yang Yu
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoxia Wang
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology, National Health Commission, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
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4
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Wang Y, Ma W, Qu Y, Jia K, Liu J, Li Y, Jiang L, Xiong C, Nie Z. Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19. Anal Chem 2024; 96:7360-7366. [PMID: 38697955 DOI: 10.1021/acs.analchem.4c00291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.
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Affiliation(s)
- Yiran Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenbo Ma
- State Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan 750021, China
| | - Yijiao Qu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ke Jia
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jianfeng Liu
- Department of Laboratory Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province 341000, China
- Ganzhou Key Laboratory of Neuroinflammation Research, Gannan Medical University, Ganzhou, Jiangxi Province 341000, China
| | - Yuze Li
- State Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan 750021, China
| | - Lixia Jiang
- Department of Laboratory Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province 341000, China
- Ganzhou Key Laboratory of Neuroinflammation Research, Gannan Medical University, Ganzhou, Jiangxi Province 341000, China
| | - Caiqiao Xiong
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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5
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Shi Q, Yu X, Sun S, Wu W, Shi W, Yu Q. Diverse thermal desorption combined with self-aspirating corona discharge ionization for direct mass spectrometry analysis of complex samples. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:2071-2076. [PMID: 38505988 DOI: 10.1039/d4ay00200h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
The thermal desorption (TD) technique is widely employed in modern mass spectrometry to facilitate the detection of non-volatile analytes. In this study, we developed a compact TD device based on a small resistance wire and coupled it with a self-aspirating corona discharge ionization (CDI) source to conduct direct MS analysis of various liquid and solid samples. Due to its small size and low heat capacity, the temperature of the TD module can be flexibly and rapidly modulated by controlling the power sequence. Multiple heating modes, including pulse heating (PH), isothermal heating, and step heating (SH), are realized and characterized, and then applied for the detection of different real samples. In particular, the PH mode is suitable for the simultaneous detection of multiple components in samples with relatively simple matrices, while the SH mode is capable of component separation. In addition, the sensitivity and quantitative capability of the TD-CDI system for DEP solutions were tested, showing acceptable stability with a relative standard deviation of about 6.7% and a detection limit of 0.088 ng. Overall, the developed TD-CDI system provides a simple, convenient, and versatile tool for direct mass spectrometry analysis of real samples.
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Affiliation(s)
- Qinhao Shi
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Xiaohua Yu
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Shuang Sun
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Weilong Wu
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Wenyan Shi
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
| | - Quan Yu
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
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6
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Zhai Y, Fu X, Xu W. Miniature mass spectrometers and their potential for clinical point-of-care analysis. MASS SPECTROMETRY REVIEWS 2023. [PMID: 37610153 DOI: 10.1002/mas.21867] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 08/04/2023] [Accepted: 08/11/2023] [Indexed: 08/24/2023]
Abstract
Mass spectrometry (MS) has become a powerful technique for clinical applications with high sensitivity and specificity. Different from conventional MS diagnosis in laboratory, point-of-care (POC) analyses in clinics require mass spectrometers and analytical procedures to be friendly for novice users and applicable for on-site clinical diagnosis. The recent decades have seen the progress in the development of miniature mass spectrometers, providing a promising solution for clinical POC applications. In this review, we report recent advances of miniature mass spectrometers and their exploration in clinical applications, mainly including the rapid analysis of illegal drugs, on-site monitoring of therapeutic drugs, and detection of biomarkers. With improved analytical performance, miniature mass spectrometers are also expected to apply to more and more clinical applications. Some promising POC analyses that can be performed by miniature mass spectrometers in the future are discussed. Lastly, we also provide our perspectives on the challenges in technical development of miniature mass spectrometers for clinical POC analysis.
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Affiliation(s)
- Yanbing Zhai
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Xinyan Fu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Wei Xu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
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7
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Li Z, Sun C, Jia K, Wang X, Han J, Chen J, Wang J, Liu H, Nie Z. Biofluid Metabolic Profiling for Lung Cancer Screening via Reactive Matrix-Assisted Laser Desorption Ionization Mass Spectrometry. Anal Chem 2023; 95:12062-12070. [PMID: 37534414 DOI: 10.1021/acs.analchem.3c02015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
Lung cancer (LC) has the highest mortality rate among various cancer diseases. Developing an early screening method for LC with high classification accuracy is essential. Herein, 2-hydrazinoquinoline (2-HQ) is utilized as a dual-mode reactive matrix for metabolic fingerprint analysis and LC screening via matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). Metabolites in both positive mode and negative mode can be detected using 2-HQ as the matrix, and derivative analysis of aldehyde and ketone compounds can be achieved simultaneously. Hundreds of serum and urine samples from LC patients and healthy volunteers were analyzed. Combined with machine learning, LC patients and healthy volunteers were successfully distinguished with a high area under the curve value (0.996 for blind serum samples and 0.938 for urine). The MS signal was identified for metabolic profiling, and dysregulated metabolites of the LC group were analyzed. The above results showed that this method has great potential for rapid screening of LC.
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Affiliation(s)
- Zhengzhou Li
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chen Sun
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Ke Jia
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiao Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Han
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Junyu Chen
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiyun Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Huihui Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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8
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Rankin‐Turner S, Sears P, Heaney LM. Applications of ambient ionization mass spectrometry in 2022: An annual review. ANALYTICAL SCIENCE ADVANCES 2023; 4:133-153. [PMID: 38716065 PMCID: PMC10989672 DOI: 10.1002/ansa.202300004] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 04/16/2023] [Accepted: 04/17/2023] [Indexed: 06/28/2024]
Abstract
The development of ambient ionization mass spectrometry (AIMS) has transformed analytical science, providing the means of performing rapid analysis of samples in their native state, both in and out of the laboratory. The capacity to eliminate sample preparation and pre-MS separation techniques, leading to true real-time analysis, has led to AIMS naturally gaining a broad interest across the scientific community. Since the introduction of the first AIMS techniques in the mid-2000s, the field has exploded with dozens of novel ion sources, an array of intriguing applications, and an evident growing interest across diverse areas of study. As the field continues to surge forward each year, ambient ionization techniques are increasingly becoming commonplace in laboratories around the world. This annual review provides an overview of AIMS techniques and applications throughout 2022, with a specific focus on some of the major fields of research, including forensic science, disease diagnostics, pharmaceuticals and food sciences. New techniques and methods are introduced, demonstrating the unwavering drive of the analytical community to further advance this exciting field and push the boundaries of what analytical chemistry can achieve.
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Affiliation(s)
- Stephanie Rankin‐Turner
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public HealthJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Patrick Sears
- School of Chemistry and Chemical EngineeringUniversity of SurreyGuildfordUK
| | - Liam M Heaney
- School of Sport, Exercise and Health SciencesLoughborough UniversityLoughboroughUK
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9
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Fan J, Wang X, Yu Y, Li Y, Nie Z. Screening of hepatocellular carcinoma via machine learning based on atmospheric pressure glow discharge mass spectrometry. Analyst 2023; 148:337-343. [PMID: 36515910 DOI: 10.1039/d2an01756c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a high mortality rate. The diagnosis of HCC is currently based on alpha-fetoprotein detection, imaging examinations, and liver biopsy, which are expensive or invasive. Here, we developed a cost-effective, time-saving, and painless method for the screening of HCC via machine learning based on atmospheric pressure glow discharge mass spectrometry (APGD-MS). Ninety urine samples from HCC patients and healthy control (HC) participants were analyzed. The relative quantification data were utilized to train machine learning models. Neural network was chosen as the best classifier with a classification accuracy of 94%. Besides, the levels of eleven urinary carbonyl metabolites were found to be significantly different between HCC and HC, including glycolic acid, pyroglutamic acid, acetic acid, etc. The possible reasons for the regulation were tentatively proposed. This method realizes the screening of HCC via potential urine metabolic biomarkers based on APGD-MS, bringing a hopeful point-of-care diagnosis of HCC in a patient-friendly manner.
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Affiliation(s)
- Jinghan Fan
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China. .,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiao Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China. .,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yile Yu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China. .,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuze Li
- State Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering, College of Chemistry and Chemical Engineering, Ningxia University, Yinchuan 750021, China.
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China. .,University of Chinese Academy of Sciences, Beijing 100049, China
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10
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Zhang M, Lai Z, Zhang R, Liu S, Tian H, Qiu Y, Li D, Zhou J, Li Z. Polyurea-Modified Magnetic Particles with Versatile Probes for Chemoselective Capture of Carbonyl Metabolites and Biomarker Discovery. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2023; 19:e2204734. [PMID: 36354199 DOI: 10.1002/smll.202204734] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 10/11/2022] [Indexed: 06/16/2023]
Abstract
Playing a great role in human physiologies and pathologies, carbonyl metabolites are intimately associated with a variety of diseases, though the effective analysis method of them remains a challenge. A hydrazide-terminated polyurea-modified magnetic particle (HPMP) with versatile probes is developed to address this issue. The capture ability of HPMPs for carbonyl metabolite is more than 1200 µmol g-1 , which is increased by 4 orders of magnitude via the introduction of polyurea. With a broad linear range of over 4 orders of magnitude, remarkably improved sensitivity, and limit of detection at attomole quantities, HPMPs are applied in relative quantification of more than 1500 carbonyl metabolites in 113 human serum samples with high throughput and high coverage. The combined indicators of these metabolites demonstrates a great diagnostic accuracy for distinguishing between health and disease subjects as well as differentiating the patients with benign lung disease and lung cancer. Combining powerful capture ability, low-cost preparation, and convenient operation, the HPMPs demonstrate extensive application in biomarker discovery and the detailed study of the biochemical landscape.
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Affiliation(s)
- Mo Zhang
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Zhizhen Lai
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Renjun Zhang
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Shuai Liu
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Hongtao Tian
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Yuming Qiu
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Dan Li
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Jiang Zhou
- Analytical Instrumentation Center, College of Chemistry and Molecular Engineering, Peking University, 292 Chengfu Road, Beijing, 100871, China
| | - Zhili Li
- Department of Biophysics and Structural Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
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11
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Wang Y, Li Y, Wang X, Yu D, Nie Z. Rapid detection and classification of hongmu by atmospheric pressure ionization mass spectrometry. Analyst 2022; 147:4857-4865. [DOI: 10.1039/d2an01169g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A schematic diagram of atmospheric pressure glow discharge mass spectrometry (APGD-MS) for hongmu detection.
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Affiliation(s)
- Yiran Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuze Li
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiao Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Dehua Yu
- Art and Design School, Beijing Institute of Technology, Beijing, 100081, China
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
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