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Chen J, Li Y, Chen J, Wang R, Lu M, Yu C. Miniature mass spectrometer-based point-of-care assay for quantification of metformin and sitagliptin in human blood and urine. Anal Bioanal Chem 2024; 416:3305-3312. [PMID: 38642098 DOI: 10.1007/s00216-024-05281-1] [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: 02/05/2024] [Revised: 03/12/2024] [Accepted: 03/25/2024] [Indexed: 04/22/2024]
Abstract
Metformin (MET) and sitagliptin (STG) are widely used as the first-line and long-term oral hypoglycemic agents for managing type 2 diabetes mellitus (T2DM). However, the current lack of convenient and rapid measurement methods poses a challenge for individualized management. This study developed a point-of-care (POC) assay method utilizing a miniature mass spectrometer, enabling rapid and accurate quantification of MET and STG concentrations in human blood and urine. By combining the miniature mass spectrometer with paper spray ionization, this method simplifies the process into three to four steps, requires minimal amounts of bodily fluids (50 μL of blood and 2 μL of urine), and is able to obtain quantification results within approximately 2 min. Stable isotope-labeled internal standards were employed to enhance the accuracy and stability of measurement. The MS/MS responses exhibited good linear relationship with concentration, with relative standard deviations (RSDs) below 25%. It has the potential to provide immediate treatment feedback and decision support for patients and healthcare professionals in clinical practice.
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Affiliation(s)
- Jingying Chen
- Central Hospital Affiliated to Shandong First Medical University, Jinan, 250000, Shandong Province, China
| | - Yaohan Li
- Central Hospital Affiliated to Shandong First Medical University, Jinan, 250000, Shandong Province, China
| | - Jingjing Chen
- Central Hospital Affiliated to Shandong First Medical University, Jinan, 250000, Shandong Province, China
| | - Ruimin Wang
- Central Hospital Affiliated to Shandong First Medical University, Jinan, 250000, Shandong Province, China
| | - Miaoshan Lu
- Central Hospital Affiliated to Shandong First Medical University, Jinan, 250000, Shandong Province, China
| | - Changbin Yu
- Central Hospital Affiliated to Shandong First Medical University, Jinan, 250000, Shandong Province, China.
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Wen Y, Xie Y, Wang C, Hua L, Zhang L, Chen P, Li H. Determination of the two-compartment model parameters of exhaled HCN by fast negative photoionization mass spectrometry. Talanta 2024; 271:125710. [PMID: 38295448 DOI: 10.1016/j.talanta.2024.125710] [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: 12/03/2023] [Revised: 01/18/2024] [Accepted: 01/22/2024] [Indexed: 02/02/2024]
Abstract
Breath exhaled hydrogen cyanide (HCN) has been identified to be associated with several respiratory diseases. Accurately distinguishing the concentration and release rate of different HCN sources is of great value in clinical research. However, there are still significant challenges due to the high adsorption and low concentration characteristics of exhaled HCN. In this study, a two-compartment kinetic model method based on negative photoionization mass spectrometry was developed to simultaneously determine the kinetic parameters including concentrations and release rates in the airways and alveoli. The influences of the sampling line diameter, length, and temperature on the response time of the sampling system were studied and optimized, achieving a response time of 0.2 s. The negative influence of oral cavity-released HCN was reduced by employing a strategy based on anatomical lung volume calculation. The calibration for HCN in the dynamic range of 0.5-100 ppbv and limit of detection (LOD) at 0.3 ppbv were achieved. Subsequently, the experiments of smoking, short-term passive smoking, and intake of bitter almonds were performed to examine the influences of endogenous and exogenous factors on the dynamic parameters of the model method. The results indicate that compared with steady-state concentration measurements, the kinetic parameters obtained using this model method can accurately and significantly reflect the changes in different HCN sources, highlighting its potential for HCN-related disease research.
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Affiliation(s)
- Yuxuan Wen
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, People's Republic of China; University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, People's Republic of China; Liaoning Key Laboratory for Mass Spectrometry Technology and Instrumentation, Dalian 116023, People's Republic of China; Dalian Key Laboratory for Online Analytical Instrumentation, 457 Zhongshan Road, Dalian, 116023, People's Republic of China
| | - Yuanyuan Xie
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, People's Republic of China; Liaoning Key Laboratory for Mass Spectrometry Technology and Instrumentation, Dalian 116023, People's Republic of China; Dalian Key Laboratory for Online Analytical Instrumentation, 457 Zhongshan Road, Dalian, 116023, People's Republic of China
| | - Chen Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, People's Republic of China; University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, People's Republic of China; Liaoning Key Laboratory for Mass Spectrometry Technology and Instrumentation, Dalian 116023, People's Republic of China; Dalian Key Laboratory for Online Analytical Instrumentation, 457 Zhongshan Road, Dalian, 116023, People's Republic of China
| | - Lei Hua
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, People's Republic of China; Liaoning Key Laboratory for Mass Spectrometry Technology and Instrumentation, Dalian 116023, People's Republic of China; Dalian Key Laboratory for Online Analytical Instrumentation, 457 Zhongshan Road, Dalian, 116023, People's Republic of China
| | - Lichuan Zhang
- Affiliated Zhongshan Hospital of Dalian University, Dalian, People's Republic of China
| | - Ping Chen
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, People's Republic of China; Liaoning Key Laboratory for Mass Spectrometry Technology and Instrumentation, Dalian 116023, People's Republic of China; Dalian Key Laboratory for Online Analytical Instrumentation, 457 Zhongshan Road, Dalian, 116023, People's Republic of China.
| | - Haiyang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian, 116023, People's Republic of China; Liaoning Key Laboratory for Mass Spectrometry Technology and Instrumentation, Dalian 116023, People's Republic of China; Dalian Key Laboratory for Online Analytical Instrumentation, 457 Zhongshan Road, Dalian, 116023, People's Republic of China.
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Fakhri E, Sultan MT, Manolescu A, Ingvarsson S, Svavarsson HG. Application of p and n-Type Silicon Nanowires as Human Respiratory Sensing Device. SENSORS (BASEL, SWITZERLAND) 2023; 23:9901. [PMID: 38139745 PMCID: PMC10748167 DOI: 10.3390/s23249901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/05/2023] [Accepted: 12/15/2023] [Indexed: 12/24/2023]
Abstract
Accurate and fast breath monitoring is of great importance for various healthcare applications, for example, medical diagnoses, studying sleep apnea, and early detection of physiological disorders. Devices meant for such applications tend to be uncomfortable for the subject (patient) and pricey. Therefore, there is a need for a cost-effective, lightweight, small-dimensional, and non-invasive device whose presence does not interfere with the observed signals. This paper reports on the fabrication of a highly sensitive human respiratory sensor based on silicon nanowires (SiNWs) fabricated by a top-down method of metal-assisted chemical-etching (MACE). Besides other important factors, reducing the final cost of the sensor is of paramount importance. One of the factors that increases the final price of the sensors is using gold (Au) electrodes. Herein, we investigate the sensor's response using aluminum (Al) electrodes as a cost-effective alternative, considering the fact that the electrode's work function is crucial in electronic device design, impacting device electronic properties and electron transport efficiency at the electrode-semiconductor interface. Therefore a comparison is made between SiNWs breath sensors made from both p-type and n-type silicon to investigate the effect of the dopant and electrode type on the SiNWs respiratory sensing functionality. A distinct directional variation was observed in the sample's response with Au and Al electrodes. Finally, performing a qualitative study revealed that the electrical resistance across the SiNWs renders greater sensitivity to breath than to dry air pressure. No definitive research demonstrating the mechanism behind these effects exists, thus prompting our study to investigate the underlying process.
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Affiliation(s)
- Elham Fakhri
- Department of Engineering, Reykjavik University, Menntavegur 1, 107 Reykjavik, Iceland; (M.T.S.); (A.M.)
| | - Muhammad Taha Sultan
- Department of Engineering, Reykjavik University, Menntavegur 1, 107 Reykjavik, Iceland; (M.T.S.); (A.M.)
| | - Andrei Manolescu
- Department of Engineering, Reykjavik University, Menntavegur 1, 107 Reykjavik, Iceland; (M.T.S.); (A.M.)
| | - Snorri Ingvarsson
- Science Institute, University of Iceland, Dunhaga 3, 107 Reykjavik, Iceland;
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Fu X, Hong J, Zhai Y, Liu K, Xu W. Deep Bottom-up Proteomics Enabled by the Integration of Liquid-Phase Ion Trap. Anal Chem 2023. [PMID: 37367992 DOI: 10.1021/acs.analchem.3c00532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023]
Abstract
In bottom-up proteomics, the complexity of the proteome requires advanced peptide separation and/or fractionation methods to acquire an in-depth understanding of protein profiles. Proposed earlier as a solution-phase ion manipulation device, liquid phase ion traps (LPITs) were used in front of mass spectrometers to accumulate target ions for improved detection sensitivity. In this work, an LPIT-reversed phase liquid chromatography-tandem mass spectrometry (LPIT-RPLC-MS/MS) platform was established for deep bottom-up proteomics. LPIT was used here as a robust and effective method for peptide fractionation, which also shows good reproducibility and sensitivity on both qualitative and quantitative levels. LPIT separates peptides based on their effective charges and hydrodynamic radii, which is orthogonal to that of RPLC. With excellent orthogonality, the integration of LPIT with RPLC-MS/MS could effectively increase the number of peptides and proteins being detected. When HeLa cells were analyzed, peptide and protein coverages were increased by ∼89.2% and 50.3%, respectively. With high efficiency and low cost, this LPIT-based peptide fraction method could potentially be used in routine deep bottom-up proteomics.
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Affiliation(s)
- Xinyan Fu
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Jie Hong
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Yanbing Zhai
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Kefu Liu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410083, China
| | - Wei Xu
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
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