Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy
Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks ges...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cohn, Brad R. [verfasserIn] Joe, Bonnie N. [verfasserIn] Zhao, Shoujun [verfasserIn] Kornak, John [verfasserIn] Zhang, Vickie Y. [verfasserIn] Iman, Rahwa [verfasserIn] Kurhanewicz, John [verfasserIn] Vahidi, Kiarash [verfasserIn] Yu, Jingwei [verfasserIn] Caughey, Aaron B. [verfasserIn] Swanson, Mark G. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
Electronic reference to access in vivo concentrations (ERETIC) High-resolution magic angle spinning (HR-MAS) |
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| Übergeordnetes Werk: |
Enthalten in: Magnetic resonance materials in physics, biology and medicine - Heidelberg : Springer, 1993, 22(2009), 6 vom: 25. Sept. |
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| Übergeordnetes Werk: |
volume:22 ; year:2009 ; number:6 ; day:25 ; month:09 |
| Links: |
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| DOI / URN: |
10.1007/s10334-009-0184-0 |
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| Katalog-ID: |
SPR009481028 |
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| 100 | 1 | |a Cohn, Brad R. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy |
| 264 | 1 | |c 2009 | |
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| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. | ||
| 650 | 4 | |a Electronic reference to access in vivo concentrations (ERETIC) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Gestational age |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a High-resolution magic angle spinning (HR-MAS) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Spectroscopy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a High-resolution quantum estimation (HR-QUEST) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Human amniotic fluid |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Joe, Bonnie N. |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Shoujun |e verfasserin |4 aut | |
| 700 | 1 | |a Kornak, John |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Vickie Y. |e verfasserin |4 aut | |
| 700 | 1 | |a Iman, Rahwa |e verfasserin |4 aut | |
| 700 | 1 | |a Kurhanewicz, John |e verfasserin |4 aut | |
| 700 | 1 | |a Vahidi, Kiarash |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Jingwei |e verfasserin |4 aut | |
| 700 | 1 | |a Caughey, Aaron B. |e verfasserin |4 aut | |
| 700 | 1 | |a Swanson, Mark G. |e verfasserin |4 aut | |
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10.1007/s10334-009-0184-0 doi (DE-627)SPR009481028 (SPR)s10334-009-0184-0-e DE-627 ger DE-627 rakwb eng 610 570 530 ASE 610 ASE 33.07 bkl 35.25 bkl 44.64 bkl Cohn, Brad R. verfasserin aut Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. Electronic reference to access in vivo concentrations (ERETIC) (dpeaa)DE-He213 Gestational age (dpeaa)DE-He213 High-resolution magic angle spinning (HR-MAS) (dpeaa)DE-He213 Spectroscopy (dpeaa)DE-He213 High-resolution quantum estimation (HR-QUEST) (dpeaa)DE-He213 Human amniotic fluid (dpeaa)DE-He213 Joe, Bonnie N. verfasserin aut Zhao, Shoujun verfasserin aut Kornak, John verfasserin aut Zhang, Vickie Y. verfasserin aut Iman, Rahwa verfasserin aut Kurhanewicz, John verfasserin aut Vahidi, Kiarash verfasserin aut Yu, Jingwei verfasserin aut Caughey, Aaron B. verfasserin aut Swanson, Mark G. verfasserin aut Enthalten in Magnetic resonance materials in physics, biology and medicine Heidelberg : Springer, 1993 22(2009), 6 vom: 25. Sept. (DE-627)308449711 (DE-600)1502491-X 1352-8661 nnns volume:22 year:2009 number:6 day:25 month:09 https://dx.doi.org/10.1007/s10334-009-0184-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 33.07 ASE 35.25 ASE 44.64 ASE AR 22 2009 6 25 09 |
| spelling |
10.1007/s10334-009-0184-0 doi (DE-627)SPR009481028 (SPR)s10334-009-0184-0-e DE-627 ger DE-627 rakwb eng 610 570 530 ASE 610 ASE 33.07 bkl 35.25 bkl 44.64 bkl Cohn, Brad R. verfasserin aut Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. Electronic reference to access in vivo concentrations (ERETIC) (dpeaa)DE-He213 Gestational age (dpeaa)DE-He213 High-resolution magic angle spinning (HR-MAS) (dpeaa)DE-He213 Spectroscopy (dpeaa)DE-He213 High-resolution quantum estimation (HR-QUEST) (dpeaa)DE-He213 Human amniotic fluid (dpeaa)DE-He213 Joe, Bonnie N. verfasserin aut Zhao, Shoujun verfasserin aut Kornak, John verfasserin aut Zhang, Vickie Y. verfasserin aut Iman, Rahwa verfasserin aut Kurhanewicz, John verfasserin aut Vahidi, Kiarash verfasserin aut Yu, Jingwei verfasserin aut Caughey, Aaron B. verfasserin aut Swanson, Mark G. verfasserin aut Enthalten in Magnetic resonance materials in physics, biology and medicine Heidelberg : Springer, 1993 22(2009), 6 vom: 25. Sept. (DE-627)308449711 (DE-600)1502491-X 1352-8661 nnns volume:22 year:2009 number:6 day:25 month:09 https://dx.doi.org/10.1007/s10334-009-0184-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 33.07 ASE 35.25 ASE 44.64 ASE AR 22 2009 6 25 09 |
| allfields_unstemmed |
10.1007/s10334-009-0184-0 doi (DE-627)SPR009481028 (SPR)s10334-009-0184-0-e DE-627 ger DE-627 rakwb eng 610 570 530 ASE 610 ASE 33.07 bkl 35.25 bkl 44.64 bkl Cohn, Brad R. verfasserin aut Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. Electronic reference to access in vivo concentrations (ERETIC) (dpeaa)DE-He213 Gestational age (dpeaa)DE-He213 High-resolution magic angle spinning (HR-MAS) (dpeaa)DE-He213 Spectroscopy (dpeaa)DE-He213 High-resolution quantum estimation (HR-QUEST) (dpeaa)DE-He213 Human amniotic fluid (dpeaa)DE-He213 Joe, Bonnie N. verfasserin aut Zhao, Shoujun verfasserin aut Kornak, John verfasserin aut Zhang, Vickie Y. verfasserin aut Iman, Rahwa verfasserin aut Kurhanewicz, John verfasserin aut Vahidi, Kiarash verfasserin aut Yu, Jingwei verfasserin aut Caughey, Aaron B. verfasserin aut Swanson, Mark G. verfasserin aut Enthalten in Magnetic resonance materials in physics, biology and medicine Heidelberg : Springer, 1993 22(2009), 6 vom: 25. Sept. (DE-627)308449711 (DE-600)1502491-X 1352-8661 nnns volume:22 year:2009 number:6 day:25 month:09 https://dx.doi.org/10.1007/s10334-009-0184-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 33.07 ASE 35.25 ASE 44.64 ASE AR 22 2009 6 25 09 |
| allfieldsGer |
10.1007/s10334-009-0184-0 doi (DE-627)SPR009481028 (SPR)s10334-009-0184-0-e DE-627 ger DE-627 rakwb eng 610 570 530 ASE 610 ASE 33.07 bkl 35.25 bkl 44.64 bkl Cohn, Brad R. verfasserin aut Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. Electronic reference to access in vivo concentrations (ERETIC) (dpeaa)DE-He213 Gestational age (dpeaa)DE-He213 High-resolution magic angle spinning (HR-MAS) (dpeaa)DE-He213 Spectroscopy (dpeaa)DE-He213 High-resolution quantum estimation (HR-QUEST) (dpeaa)DE-He213 Human amniotic fluid (dpeaa)DE-He213 Joe, Bonnie N. verfasserin aut Zhao, Shoujun verfasserin aut Kornak, John verfasserin aut Zhang, Vickie Y. verfasserin aut Iman, Rahwa verfasserin aut Kurhanewicz, John verfasserin aut Vahidi, Kiarash verfasserin aut Yu, Jingwei verfasserin aut Caughey, Aaron B. verfasserin aut Swanson, Mark G. verfasserin aut Enthalten in Magnetic resonance materials in physics, biology and medicine Heidelberg : Springer, 1993 22(2009), 6 vom: 25. Sept. (DE-627)308449711 (DE-600)1502491-X 1352-8661 nnns volume:22 year:2009 number:6 day:25 month:09 https://dx.doi.org/10.1007/s10334-009-0184-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 33.07 ASE 35.25 ASE 44.64 ASE AR 22 2009 6 25 09 |
| allfieldsSound |
10.1007/s10334-009-0184-0 doi (DE-627)SPR009481028 (SPR)s10334-009-0184-0-e DE-627 ger DE-627 rakwb eng 610 570 530 ASE 610 ASE 33.07 bkl 35.25 bkl 44.64 bkl Cohn, Brad R. verfasserin aut Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. Electronic reference to access in vivo concentrations (ERETIC) (dpeaa)DE-He213 Gestational age (dpeaa)DE-He213 High-resolution magic angle spinning (HR-MAS) (dpeaa)DE-He213 Spectroscopy (dpeaa)DE-He213 High-resolution quantum estimation (HR-QUEST) (dpeaa)DE-He213 Human amniotic fluid (dpeaa)DE-He213 Joe, Bonnie N. verfasserin aut Zhao, Shoujun verfasserin aut Kornak, John verfasserin aut Zhang, Vickie Y. verfasserin aut Iman, Rahwa verfasserin aut Kurhanewicz, John verfasserin aut Vahidi, Kiarash verfasserin aut Yu, Jingwei verfasserin aut Caughey, Aaron B. verfasserin aut Swanson, Mark G. verfasserin aut Enthalten in Magnetic resonance materials in physics, biology and medicine Heidelberg : Springer, 1993 22(2009), 6 vom: 25. Sept. (DE-627)308449711 (DE-600)1502491-X 1352-8661 nnns volume:22 year:2009 number:6 day:25 month:09 https://dx.doi.org/10.1007/s10334-009-0184-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 33.07 ASE 35.25 ASE 44.64 ASE AR 22 2009 6 25 09 |
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Enthalten in Magnetic resonance materials in physics, biology and medicine 22(2009), 6 vom: 25. Sept. volume:22 year:2009 number:6 day:25 month:09 |
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Enthalten in Magnetic resonance materials in physics, biology and medicine 22(2009), 6 vom: 25. Sept. volume:22 year:2009 number:6 day:25 month:09 |
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Electronic reference to access in vivo concentrations (ERETIC) Gestational age High-resolution magic angle spinning (HR-MAS) Spectroscopy High-resolution quantum estimation (HR-QUEST) Human amniotic fluid |
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Magnetic resonance materials in physics, biology and medicine |
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Cohn, Brad R. @@aut@@ Joe, Bonnie N. @@aut@@ Zhao, Shoujun @@aut@@ Kornak, John @@aut@@ Zhang, Vickie Y. @@aut@@ Iman, Rahwa @@aut@@ Kurhanewicz, John @@aut@@ Vahidi, Kiarash @@aut@@ Yu, Jingwei @@aut@@ Caughey, Aaron B. @@aut@@ Swanson, Mark G. @@aut@@ |
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2009-09-25T00:00:00Z |
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Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. 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Cohn, Brad R. |
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Cohn, Brad R. ddc 610 bkl 33.07 bkl 35.25 bkl 44.64 misc Electronic reference to access in vivo concentrations (ERETIC) misc Gestational age misc High-resolution magic angle spinning (HR-MAS) misc Spectroscopy misc High-resolution quantum estimation (HR-QUEST) misc Human amniotic fluid Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy |
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610 570 530 ASE 610 ASE 33.07 bkl 35.25 bkl 44.64 bkl Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy Electronic reference to access in vivo concentrations (ERETIC) (dpeaa)DE-He213 Gestational age (dpeaa)DE-He213 High-resolution magic angle spinning (HR-MAS) (dpeaa)DE-He213 Spectroscopy (dpeaa)DE-He213 High-resolution quantum estimation (HR-QUEST) (dpeaa)DE-He213 Human amniotic fluid (dpeaa)DE-He213 |
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ddc 610 bkl 33.07 bkl 35.25 bkl 44.64 misc Electronic reference to access in vivo concentrations (ERETIC) misc Gestational age misc High-resolution magic angle spinning (HR-MAS) misc Spectroscopy misc High-resolution quantum estimation (HR-QUEST) misc Human amniotic fluid |
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ddc 610 bkl 33.07 bkl 35.25 bkl 44.64 misc Electronic reference to access in vivo concentrations (ERETIC) misc Gestational age misc High-resolution magic angle spinning (HR-MAS) misc Spectroscopy misc High-resolution quantum estimation (HR-QUEST) misc Human amniotic fluid |
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ddc 610 bkl 33.07 bkl 35.25 bkl 44.64 misc Electronic reference to access in vivo concentrations (ERETIC) misc Gestational age misc High-resolution magic angle spinning (HR-MAS) misc Spectroscopy misc High-resolution quantum estimation (HR-QUEST) misc Human amniotic fluid |
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Magnetic resonance materials in physics, biology and medicine |
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610 - Medicine & health 570 - Life sciences; biology 530 - Physics |
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Magnetic resonance materials in physics, biology and medicine |
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Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy |
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(DE-627)SPR009481028 (SPR)s10334-009-0184-0-e |
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Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy |
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Cohn, Brad R. |
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Magnetic resonance materials in physics, biology and medicine |
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Magnetic resonance materials in physics, biology and medicine |
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eng |
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600 - Technology 500 - Science |
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2009 |
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Cohn, Brad R. Joe, Bonnie N. Zhao, Shoujun Kornak, John Zhang, Vickie Y. Iman, Rahwa Kurhanewicz, John Vahidi, Kiarash Yu, Jingwei Caughey, Aaron B. Swanson, Mark G. |
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Elektronische Aufsätze |
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Cohn, Brad R. |
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10.1007/s10334-009-0184-0 |
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610 570 530 |
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verfasserin |
| title_sort |
quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1h hr-mas spectroscopy |
| title_auth |
Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy |
| abstract |
Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. |
| abstractGer |
Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. |
| abstract_unstemmed |
Object To establish and compare normative metabolite concentrations in 2nd and 3rd trimester human amniotic fluid samples in an effort to reveal metabolic biomarkers of fetal health and development. Materials and methods Twenty-one metabolite concentrations were compared between 2nd (15–27 weeks gestation, N = 23) and 3rd (29–39 weeks gestation, N = 27) trimester amniotic fluid samples using 1H high resolution magic angle spinning (HR-MAS) spectroscopy. Data were acquired using the electronic reference to access in vivo concentrations method and quantified using a modified semi-parametric quantum estimation algorithm modified for high-resolution ex vivo data. Results Sixteen of 21 metabolite concentrations differed significantly between 2nd and 3rd trimester groups. Betaine (0.00846±0.00206 mmol/kg vs. 0.0133±0.0058 mmol/kg, P < 0.002) and creatinine (0.0124±0.0058 mmol/kg vs. 0.247±0.011 mmol/kg, P < 0.001) concentrations increased significantly, while glucose (5.96±1.66 mmol/kg vs. 2.41±1.69 mmol/kg, P < 0.001), citrate (0.740±0.217 mmol/kg vs. 0.399±0.137 mmol/kg, P < 0.001), pyruvate (0.0659±0.0103 mmol/kg vs. 0.0299±0.286 mmol/kg, P < 0.001), and numerous amino acid (e.g. alanine, glutamate, isoleucine, leucine, lysine, and valine) concentrations decreased significantly with advancing gestation. A stepwise multiple linear regression model applied to 50 samples showed that gestational age can be accurately predicted using combinations of alanine, glucose and creatinine concentrations. Conclusion These results provide key normative data for 2nd and 3rd trimester amniotic fluid metabolite concentrations and provide the foundation for future development of magnetic resonance spectroscopy (MRS) biomarkers to evaluate fetal health and development. |
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6 |
| title_short |
Quantitative metabolic profiles of 2nd and 3rd trimester human amniotic fluid using 1H HR-MAS spectroscopy |
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https://dx.doi.org/10.1007/s10334-009-0184-0 |
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Joe, Bonnie N. Zhao, Shoujun Kornak, John Zhang, Vickie Y. Iman, Rahwa Kurhanewicz, John Vahidi, Kiarash Yu, Jingwei Caughey, Aaron B. Swanson, Mark G. |
| author2Str |
Joe, Bonnie N. Zhao, Shoujun Kornak, John Zhang, Vickie Y. Iman, Rahwa Kurhanewicz, John Vahidi, Kiarash Yu, Jingwei Caughey, Aaron B. Swanson, Mark G. |
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10.1007/s10334-009-0184-0 |
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2024-07-04T02:14:39.485Z |
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| score |
7.400365 |