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Zhao J, Quinto M, Zakia F, Li D. Microextraction of essential oils: A review. J Chromatogr A 2023; 1708:464357. [PMID: 37696126 DOI: 10.1016/j.chroma.2023.464357] [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: 06/01/2023] [Revised: 08/29/2023] [Accepted: 08/31/2023] [Indexed: 09/13/2023]
Abstract
Liquid phase microextraction (LPME) and solid phase microextraction (SPME) are popular extraction techniques for sample preparation due to their green and highly efficient single-step extraction efficiency. With the increasing attention to essential oils, their evaluation and analysis are significant in analytical sciences. In this review, starting from a brief description of the recent advances in the last decade, the attention has been focused on the up-to-date research works and applications based on liquid and solid phase microextraction for essential oil analyses. Particular attention has been given to the approaches using ionic liquids, eutectic solvents, gas flow assisted, and novel composite materials. In the end, the technological convergence of novel microextraction of essential oils in the future has been prospected.
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Affiliation(s)
- Jinhua Zhao
- Department of Chemistry, Analysis and Inspection Center, Yanbian University, Park Road 977, Yanji, Jilin, China
| | - Maurizio Quinto
- Department of Chemistry, Analysis and Inspection Center, Yanbian University, Park Road 977, Yanji, Jilin, China; Department of Agriculture, Food, Natural Resources and Engineering (DAFNE), University of Foggia, Via Napoli 25, Foggia 71122, Italy
| | - Fatima Zakia
- Department of Chemistry, Analysis and Inspection Center, Yanbian University, Park Road 977, Yanji, Jilin, China
| | - Donghao Li
- Department of Chemistry, Analysis and Inspection Center, Yanbian University, Park Road 977, Yanji, Jilin, China; Interdisciplinary Program of Biological Functional Molecules, College of Integration Science, Yanbian University, Park Road 977, Yanji, Jilin, China.
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Ye L, Zhang HM, Zhou BJ, Tang W, Zhou JL. Advancements in Analyzing Tumor Metabolites through Chemical Derivatization-Based Chromatography. J Chromatogr A 2023; 1706:464236. [PMID: 37506465 DOI: 10.1016/j.chroma.2023.464236] [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: 06/19/2023] [Revised: 07/19/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023]
Abstract
Understanding the metabolic abnormalities of tumors is crucial for early diagnosis, prognosis, and treatment. Accurate identification and quantification of metabolites in biological samples are essential to investigate the relationship between metabolite variations and tumor development. Common techniques like LC-MS and GC-MS face challenges in measuring aberrant metabolites in tumors due to their strong polarity, isomerism, or low ionization efficiency during MS detection. Chemical derivatization of metabolites offers an effective solution to overcome these challenges. This review focuses on the difficulties encountered in analyzing aberrant metabolites in tumors, the principles behind chemical derivatization methods, and the advancements in analyzing tumor metabolites using derivatization-based chromatography. It serves as a comprehensive reference for understanding the analysis and detection of tumor metabolites, particularly those that are highly polar and exhibit low ionization efficiency.
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Affiliation(s)
- Lu Ye
- School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines; Engineering Laboratory of Development and Application of Traditional Chinese Medicines; Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou 311121, China
| | - Hua-Min Zhang
- School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines; Engineering Laboratory of Development and Application of Traditional Chinese Medicines; Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou 311121, China
| | - Bing-Jun Zhou
- School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines; Engineering Laboratory of Development and Application of Traditional Chinese Medicines; Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou 311121, China
| | - Weiyang Tang
- School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines; Engineering Laboratory of Development and Application of Traditional Chinese Medicines; Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou 311121, China.
| | - Jian-Liang Zhou
- School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China; Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines; Engineering Laboratory of Development and Application of Traditional Chinese Medicines; Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, Hangzhou Normal University, Hangzhou 311121, China.
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Eremina OE, Kapitanova OO, Medved'ko AV, Zelenetskaya AS, Egorova BV, Shekhovtsova TN, Vatsadze SZ, Veselova IA. Plier Ligands for Trapping Neurotransmitters into Complexes for Sensitive Analysis by SERS Spectroscopy. BIOSENSORS 2023; 13:bios13010124. [PMID: 36671959 PMCID: PMC9856153 DOI: 10.3390/bios13010124] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 01/05/2023] [Accepted: 01/06/2023] [Indexed: 05/28/2023]
Abstract
Catecholamines-dopamine, noradrenaline and adrenaline are important biomarkers of neurotransmitter metabolism, indicating neuroendocrine tumors and neurodegenerative diseases. Surface-enhanced Raman spectroscopy (SERS) is a promising analytical technique with unprecedented multiplexing capabilities. However, not all important analytes exhibit strong SERS signals on stable and robust nanostructured substrates. In this work, we propose a novel indicator system based on the formation of mixed ligand complexes with bispidine-based bis-azole ligands which can serve as pliers to trap Cu(II) ions and stabilize its complexes with catecholamines. Four synthesized ligands with different functional groups: carboxyl, amino, benzyl, and methoxybenzyl, were applied for forming stable complexes to shift maximum absorbance of catecholamines from the ultraviolet region to 570-600 nm. A new absorbance band in the visible range resonates with the local surface plasmon resonance (LSPR) band of metal nanoparticles and most used laser wavelengths. This match allowed use of Molecular Immobilization and Resonant Raman Amplification by Complex-Loaded Enhancers (MIRRACLE) methodology to measure intense Raman signals on a nanostructured silver-based SERS-active substrate. The synthesized plier-like ligands fixed and stabilized catecholamine complexes with Cu(II) on the SERS sensor surface, which facilitated the determination of dopamine in a 3.2 × 10-12-1 × 10-8 M concentration range.
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Affiliation(s)
- Olga E. Eremina
- Chemistry Department, Moscow State University, Moscow 119991, Russia
| | | | - Alexei V. Medved'ko
- N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Moscow 119991, Russia
| | | | | | | | - Sergey Z. Vatsadze
- N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, Moscow 119991, Russia
| | - Irina A. Veselova
- Chemistry Department, Moscow State University, Moscow 119991, Russia
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Chen ZH, Chen ZY, Kang J, Chu XP, Fu R, Zhang JT, Qi YF, Chen JH, Lin JT, Jiang BY, Yang XN, Wu YL, Zhong WZ, Nie Q. Investigation on the incidence and risk factors of lung cancer among Chinese hospital employees. Thorac Cancer 2022; 13:2210-2222. [PMID: 35818719 PMCID: PMC9346177 DOI: 10.1111/1759-7714.14549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 06/05/2022] [Accepted: 06/07/2022] [Indexed: 11/08/2022] Open
Abstract
Objective In recent years, the lung cancer incidence has grown and the population is younger. We intend to find out the true detection rate of pulmonary nodules and the incidence of lung cancer in the population and search for the risk factors. Method Hospital employees ≥40 years old who underwent low‐dose computed tomography (CT) lung cancer screening from January 2019 to March 2022 were selected to record CT‐imaging characteristics, pathology, staging, and questionnaires to investigate past history, smoking history, diet, mental health, etc. PM2.5 and radiation intake in radiation‐related occupation received monitoring in hospital. Result The detection rate of suspicious pulmonary nodules was 9.1% (233/2552), and the incidence rate of lung cancer (including adenocarcinoma in situ) was 4.0% (103/2552). Morbidity among doctors, nurses, technicians, administers, and logistics was no difference (p = 0.184), but higher in women than in men (4.7% vs 2.4% p = 0.002). The invasiveness increased with age and CT density of nodules (p = 0.018). The relationship between lung cancer morbidity and PM2.5 was not clear (p = 0.543); and no lung cancer has been found in employees related ionizing radiation. Conclusion The high screening rate has brought about a high incidence of lung cancer. At present, the risk factor analysis of lung cancer based on small samples cannot find the direct cause. Most of the ground glass opacity (GGO)s detected by LDCT screening are indolent, but there are also rapidly progressive lung cancer. A predictive model to identify active and indolent GGO is necessary.
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Affiliation(s)
- Zi-Hao Chen
- School of Medicine, South China University of Technology, Guangzhou, China.,Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhi-Yong Chen
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jing Kang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Xiang-Peng Chu
- School of Medicine, South China University of Technology, Guangzhou, China.,Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Rui Fu
- School of Medicine, South China University of Technology, Guangzhou, China.,Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jia-Tao Zhang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.,The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Yi-Fan Qi
- School of Medicine, South China University of Technology, Guangzhou, China.,Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jing-Hua Chen
- 12th People's Hospital of Guangzhou, Guangzhou, China
| | - Jun-Tao Lin
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ben-Yuan Jiang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xue-Ning Yang
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yi-Long Wu
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Wen-Zhao Zhong
- School of Medicine, South China University of Technology, Guangzhou, China.,Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Qiang Nie
- School of Medicine, South China University of Technology, Guangzhou, China.,Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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