Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis

Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Pr...
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Autor*in:	Doudou Lou [verfasserIn] Keqing Shi [verfasserIn] Hui-Ping Li [verfasserIn] Qingfu Zhu [verfasserIn] Liang Hu [verfasserIn] Jiaxin Luo [verfasserIn] Rui Yang [verfasserIn] Fei Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery

Übergeordnetes Werk:	In: Journal of Nanobiotechnology - BMC, 2003, 20(2022), 1, Seite 10
Übergeordnetes Werk:	volume:20 ; year:2022 ; number:1 ; pages:10

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/s12951-022-01239-6

Katalog-ID:	DOAJ078726565

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520			\|a Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract
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allfields	10.1186/s12951-022-01239-6 doi (DE-627)DOAJ078726565 (DE-599)DOAJ780b230c15ff4053b268d67e29a7832b DE-627 ger DE-627 rakwb eng TP248.13-248.65 R855-855.5 Doudou Lou verfasserin aut Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery Biotechnology Medical technology Keqing Shi verfasserin aut Hui-Ping Li verfasserin aut Qingfu Zhu verfasserin aut Liang Hu verfasserin aut Jiaxin Luo verfasserin aut Rui Yang verfasserin aut Fei Liu verfasserin aut In Journal of Nanobiotechnology BMC, 2003 20(2022), 1, Seite 10 (DE-627)362770328 (DE-600)2100022-0 14773155 nnns volume:20 year:2022 number:1 pages:10 https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/article/780b230c15ff4053b268d67e29a7832b kostenfrei https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/toc/1477-3155 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2022 1 10
spelling	10.1186/s12951-022-01239-6 doi (DE-627)DOAJ078726565 (DE-599)DOAJ780b230c15ff4053b268d67e29a7832b DE-627 ger DE-627 rakwb eng TP248.13-248.65 R855-855.5 Doudou Lou verfasserin aut Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery Biotechnology Medical technology Keqing Shi verfasserin aut Hui-Ping Li verfasserin aut Qingfu Zhu verfasserin aut Liang Hu verfasserin aut Jiaxin Luo verfasserin aut Rui Yang verfasserin aut Fei Liu verfasserin aut In Journal of Nanobiotechnology BMC, 2003 20(2022), 1, Seite 10 (DE-627)362770328 (DE-600)2100022-0 14773155 nnns volume:20 year:2022 number:1 pages:10 https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/article/780b230c15ff4053b268d67e29a7832b kostenfrei https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/toc/1477-3155 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2022 1 10
allfields_unstemmed	10.1186/s12951-022-01239-6 doi (DE-627)DOAJ078726565 (DE-599)DOAJ780b230c15ff4053b268d67e29a7832b DE-627 ger DE-627 rakwb eng TP248.13-248.65 R855-855.5 Doudou Lou verfasserin aut Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery Biotechnology Medical technology Keqing Shi verfasserin aut Hui-Ping Li verfasserin aut Qingfu Zhu verfasserin aut Liang Hu verfasserin aut Jiaxin Luo verfasserin aut Rui Yang verfasserin aut Fei Liu verfasserin aut In Journal of Nanobiotechnology BMC, 2003 20(2022), 1, Seite 10 (DE-627)362770328 (DE-600)2100022-0 14773155 nnns volume:20 year:2022 number:1 pages:10 https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/article/780b230c15ff4053b268d67e29a7832b kostenfrei https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/toc/1477-3155 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2022 1 10
allfieldsGer	10.1186/s12951-022-01239-6 doi (DE-627)DOAJ078726565 (DE-599)DOAJ780b230c15ff4053b268d67e29a7832b DE-627 ger DE-627 rakwb eng TP248.13-248.65 R855-855.5 Doudou Lou verfasserin aut Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery Biotechnology Medical technology Keqing Shi verfasserin aut Hui-Ping Li verfasserin aut Qingfu Zhu verfasserin aut Liang Hu verfasserin aut Jiaxin Luo verfasserin aut Rui Yang verfasserin aut Fei Liu verfasserin aut In Journal of Nanobiotechnology BMC, 2003 20(2022), 1, Seite 10 (DE-627)362770328 (DE-600)2100022-0 14773155 nnns volume:20 year:2022 number:1 pages:10 https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/article/780b230c15ff4053b268d67e29a7832b kostenfrei https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/toc/1477-3155 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2022 1 10
allfieldsSound	10.1186/s12951-022-01239-6 doi (DE-627)DOAJ078726565 (DE-599)DOAJ780b230c15ff4053b268d67e29a7832b DE-627 ger DE-627 rakwb eng TP248.13-248.65 R855-855.5 Doudou Lou verfasserin aut Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery Biotechnology Medical technology Keqing Shi verfasserin aut Hui-Ping Li verfasserin aut Qingfu Zhu verfasserin aut Liang Hu verfasserin aut Jiaxin Luo verfasserin aut Rui Yang verfasserin aut Fei Liu verfasserin aut In Journal of Nanobiotechnology BMC, 2003 20(2022), 1, Seite 10 (DE-627)362770328 (DE-600)2100022-0 14773155 nnns volume:20 year:2022 number:1 pages:10 https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/article/780b230c15ff4053b268d67e29a7832b kostenfrei https://doi.org/10.1186/s12951-022-01239-6 kostenfrei https://doaj.org/toc/1477-3155 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2022 1 10
language	English
source	In Journal of Nanobiotechnology 20(2022), 1, Seite 10 volume:20 year:2022 number:1 pages:10
sourceStr	In Journal of Nanobiotechnology 20(2022), 1, Seite 10 volume:20 year:2022 number:1 pages:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery Biotechnology Medical technology
isfreeaccess_bool	true
container_title	Journal of Nanobiotechnology
authorswithroles_txt_mv	Doudou Lou @@aut@@ Keqing Shi @@aut@@ Hui-Ping Li @@aut@@ Qingfu Zhu @@aut@@ Liang Hu @@aut@@ Jiaxin Luo @@aut@@ Rui Yang @@aut@@ Fei Liu @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	362770328
id	DOAJ078726565
language_de	englisch
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callnumber-first	T - Technology
author	Doudou Lou
spellingShingle	Doudou Lou misc TP248.13-248.65 misc R855-855.5 misc Severe acute pancreatitis misc Early diagnosis misc Extracellular vesicles misc Metabolomics misc Biomarker discovery misc Biotechnology misc Medical technology Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis
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topic_title	TP248.13-248.65 R855-855.5 Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis Severe acute pancreatitis Early diagnosis Extracellular vesicles Metabolomics Biomarker discovery
topic	misc TP248.13-248.65 misc R855-855.5 misc Severe acute pancreatitis misc Early diagnosis misc Extracellular vesicles misc Metabolomics misc Biomarker discovery misc Biotechnology misc Medical technology
topic_unstemmed	misc TP248.13-248.65 misc R855-855.5 misc Severe acute pancreatitis misc Early diagnosis misc Extracellular vesicles misc Metabolomics misc Biomarker discovery misc Biotechnology misc Medical technology
topic_browse	misc TP248.13-248.65 misc R855-855.5 misc Severe acute pancreatitis misc Early diagnosis misc Extracellular vesicles misc Metabolomics misc Biomarker discovery misc Biotechnology misc Medical technology
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title	Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis
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title_full	Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis
author_sort	Doudou Lou
journal	Journal of Nanobiotechnology
journalStr	Journal of Nanobiotechnology
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author_browse	Doudou Lou Keqing Shi Hui-Ping Li Qingfu Zhu Liang Hu Jiaxin Luo Rui Yang Fei Liu
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title_sort	quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis
callnumber	TP248.13-248.65
title_auth	Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis
abstract	Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract
abstractGer	Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract
abstract_unstemmed	Abstract Background Severe acute pancreatitis (SAP) is the most common gastrointestinal disease and is associated with unpredictable seizures and high mortality rates. Despite improvements in the treatment of acute pancreatitis, the timely and accurate diagnosis of SAP remains highly challenging. Previous research has shown that extracellular vesicles (EVs) in the plasma have significant potential for the diagnosis of SAP since the pancreas can release EVs that carry pathological information into the peripheral blood in the very early stages of the disease. However, we know very little about the metabolites of EVs that might play a role in the diagnosis of SAP. Methods Here, we performed quantitative metabolomic analyses to investigate the metabolite profiles of EVs isolated from SAP plasma. We also determined the metabolic differences of EVs when compared between healthy controls, patients with SAP, and those with mild acute pancreatitis (MAP). Results A total of 313 metabolites were detected, mainly including organic acids, amino acids, fatty acids, and bile acids. The results showed that the metabolic composition of EVs derived from SAP and MAP was significantly different from those derived from healthy controls and identified specific differences between EVs derived from patients with SAP and MAP. On this basis, we identified four biomarkers from plasma EVs for SAP detection, including eicosatrienoic acid (C20:3), thiamine triphosphate, 2-Acetylfuran, and cis-Citral. The area under the curve (AUC) was greater than 0.95 for both discovery (n = 30) and validation (n = 70) sets. Conclusions Our data indicate that metabolic profiling analysis of plasma EVs and the screening of potential biomarkers are of significant potential for improving the early diagnosis and severity differentiation of acute pancreatitis. Graphical abstract
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title_short	Quantitative metabolic analysis of plasma extracellular vesicles for the diagnosis of severe acute pancreatitis
url	https://doi.org/10.1186/s12951-022-01239-6 https://doaj.org/article/780b230c15ff4053b268d67e29a7832b https://doaj.org/toc/1477-3155
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author2	Keqing Shi Hui-Ping Li Qingfu Zhu Liang Hu Jiaxin Luo Rui Yang Fei Liu
author2Str	Keqing Shi Hui-Ping Li Qingfu Zhu Liang Hu Jiaxin Luo Rui Yang Fei Liu
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up_date	2024-07-03T19:28:53.956Z
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