Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues
Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relat...
Ausführliche Beschreibung
Autor*in: |
Stefania Casagrande [verfasserIn] Maciej Dzialo [verfasserIn] Lisa Trost [verfasserIn] Kasja Malkoc [verfasserIn] Edyta Teresa Sadowska [verfasserIn] Michaela Hau [verfasserIn] Barbara Pierce [verfasserIn] Scott McWilliams [verfasserIn] Ulf Bauchinger [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2023 |
---|
Schlagwörter: |
---|
Übergeordnetes Werk: |
In: iScience - Elsevier, 2019, 26(2023), 12, Seite 108321- |
---|---|
Übergeordnetes Werk: |
volume:26 ; year:2023 ; number:12 ; pages:108321- |
Links: |
---|
DOI / URN: |
10.1016/j.isci.2023.108321 |
---|
Katalog-ID: |
DOAJ099164035 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ099164035 | ||
003 | DE-627 | ||
005 | 20240414015444.0 | ||
007 | cr uuu---uuuuu | ||
008 | 240414s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.isci.2023.108321 |2 doi | |
035 | |a (DE-627)DOAJ099164035 | ||
035 | |a (DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 0 | |a Stefania Casagrande |e verfasserin |4 aut | |
245 | 1 | 0 | |a Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. | ||
650 | 4 | |a Ornithology | |
650 | 4 | |a Physiology | |
650 | 4 | |a Evolutionary biology | |
653 | 0 | |a Science | |
653 | 0 | |a Q | |
700 | 0 | |a Maciej Dzialo |e verfasserin |4 aut | |
700 | 0 | |a Lisa Trost |e verfasserin |4 aut | |
700 | 0 | |a Kasja Malkoc |e verfasserin |4 aut | |
700 | 0 | |a Edyta Teresa Sadowska |e verfasserin |4 aut | |
700 | 0 | |a Michaela Hau |e verfasserin |4 aut | |
700 | 0 | |a Barbara Pierce |e verfasserin |4 aut | |
700 | 0 | |a Scott McWilliams |e verfasserin |4 aut | |
700 | 0 | |a Ulf Bauchinger |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t iScience |d Elsevier, 2019 |g 26(2023), 12, Seite 108321- |w (DE-627)1019532106 |x 25890042 |7 nnns |
773 | 1 | 8 | |g volume:26 |g year:2023 |g number:12 |g pages:108321- |
856 | 4 | 0 | |u https://doi.org/10.1016/j.isci.2023.108321 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9 |z kostenfrei |
856 | 4 | 0 | |u http://www.sciencedirect.com/science/article/pii/S2589004223023982 |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/2589-0042 |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_31 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_171 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_370 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2001 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2005 | ||
912 | |a GBV_ILN_2006 | ||
912 | |a GBV_ILN_2007 | ||
912 | |a GBV_ILN_2008 | ||
912 | |a GBV_ILN_2009 | ||
912 | |a GBV_ILN_2010 | ||
912 | |a GBV_ILN_2011 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_2015 | ||
912 | |a GBV_ILN_2020 | ||
912 | |a GBV_ILN_2021 | ||
912 | |a GBV_ILN_2025 | ||
912 | |a GBV_ILN_2026 | ||
912 | |a GBV_ILN_2027 | ||
912 | |a GBV_ILN_2038 | ||
912 | |a GBV_ILN_2044 | ||
912 | |a GBV_ILN_2048 | ||
912 | |a GBV_ILN_2049 | ||
912 | |a GBV_ILN_2050 | ||
912 | |a GBV_ILN_2055 | ||
912 | |a GBV_ILN_2059 | ||
912 | |a GBV_ILN_2061 | ||
912 | |a GBV_ILN_2064 | ||
912 | |a GBV_ILN_2068 | ||
912 | |a GBV_ILN_2088 | ||
912 | |a GBV_ILN_2110 | ||
912 | |a GBV_ILN_2112 | ||
912 | |a GBV_ILN_2129 | ||
912 | |a GBV_ILN_2143 | ||
912 | |a GBV_ILN_2153 | ||
912 | |a GBV_ILN_2190 | ||
912 | |a GBV_ILN_2336 | ||
912 | |a GBV_ILN_2470 | ||
912 | |a GBV_ILN_2507 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4035 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4251 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4326 | ||
912 | |a GBV_ILN_4333 | ||
912 | |a GBV_ILN_4335 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4393 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 26 |j 2023 |e 12 |h 108321- |
author_variant |
s c sc m d md l t lt k m km e t s ets m h mh b p bp s m sm u b ub |
---|---|
matchkey_str |
article:25890042:2023----::iohnramtblsibodoeeibyrdcshlaiaeegn |
hierarchy_sort_str |
2023 |
publishDate |
2023 |
allfields |
10.1016/j.isci.2023.108321 doi (DE-627)DOAJ099164035 (DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9 DE-627 ger DE-627 rakwb eng Stefania Casagrande verfasserin aut Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. Ornithology Physiology Evolutionary biology Science Q Maciej Dzialo verfasserin aut Lisa Trost verfasserin aut Kasja Malkoc verfasserin aut Edyta Teresa Sadowska verfasserin aut Michaela Hau verfasserin aut Barbara Pierce verfasserin aut Scott McWilliams verfasserin aut Ulf Bauchinger verfasserin aut In iScience Elsevier, 2019 26(2023), 12, Seite 108321- (DE-627)1019532106 25890042 nnns volume:26 year:2023 number:12 pages:108321- https://doi.org/10.1016/j.isci.2023.108321 kostenfrei https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9 kostenfrei http://www.sciencedirect.com/science/article/pii/S2589004223023982 kostenfrei https://doaj.org/toc/2589-0042 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 26 2023 12 108321- |
spelling |
10.1016/j.isci.2023.108321 doi (DE-627)DOAJ099164035 (DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9 DE-627 ger DE-627 rakwb eng Stefania Casagrande verfasserin aut Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. Ornithology Physiology Evolutionary biology Science Q Maciej Dzialo verfasserin aut Lisa Trost verfasserin aut Kasja Malkoc verfasserin aut Edyta Teresa Sadowska verfasserin aut Michaela Hau verfasserin aut Barbara Pierce verfasserin aut Scott McWilliams verfasserin aut Ulf Bauchinger verfasserin aut In iScience Elsevier, 2019 26(2023), 12, Seite 108321- (DE-627)1019532106 25890042 nnns volume:26 year:2023 number:12 pages:108321- https://doi.org/10.1016/j.isci.2023.108321 kostenfrei https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9 kostenfrei http://www.sciencedirect.com/science/article/pii/S2589004223023982 kostenfrei https://doaj.org/toc/2589-0042 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 26 2023 12 108321- |
allfields_unstemmed |
10.1016/j.isci.2023.108321 doi (DE-627)DOAJ099164035 (DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9 DE-627 ger DE-627 rakwb eng Stefania Casagrande verfasserin aut Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. Ornithology Physiology Evolutionary biology Science Q Maciej Dzialo verfasserin aut Lisa Trost verfasserin aut Kasja Malkoc verfasserin aut Edyta Teresa Sadowska verfasserin aut Michaela Hau verfasserin aut Barbara Pierce verfasserin aut Scott McWilliams verfasserin aut Ulf Bauchinger verfasserin aut In iScience Elsevier, 2019 26(2023), 12, Seite 108321- (DE-627)1019532106 25890042 nnns volume:26 year:2023 number:12 pages:108321- https://doi.org/10.1016/j.isci.2023.108321 kostenfrei https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9 kostenfrei http://www.sciencedirect.com/science/article/pii/S2589004223023982 kostenfrei https://doaj.org/toc/2589-0042 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 26 2023 12 108321- |
allfieldsGer |
10.1016/j.isci.2023.108321 doi (DE-627)DOAJ099164035 (DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9 DE-627 ger DE-627 rakwb eng Stefania Casagrande verfasserin aut Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. Ornithology Physiology Evolutionary biology Science Q Maciej Dzialo verfasserin aut Lisa Trost verfasserin aut Kasja Malkoc verfasserin aut Edyta Teresa Sadowska verfasserin aut Michaela Hau verfasserin aut Barbara Pierce verfasserin aut Scott McWilliams verfasserin aut Ulf Bauchinger verfasserin aut In iScience Elsevier, 2019 26(2023), 12, Seite 108321- (DE-627)1019532106 25890042 nnns volume:26 year:2023 number:12 pages:108321- https://doi.org/10.1016/j.isci.2023.108321 kostenfrei https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9 kostenfrei http://www.sciencedirect.com/science/article/pii/S2589004223023982 kostenfrei https://doaj.org/toc/2589-0042 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 26 2023 12 108321- |
allfieldsSound |
10.1016/j.isci.2023.108321 doi (DE-627)DOAJ099164035 (DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9 DE-627 ger DE-627 rakwb eng Stefania Casagrande verfasserin aut Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. Ornithology Physiology Evolutionary biology Science Q Maciej Dzialo verfasserin aut Lisa Trost verfasserin aut Kasja Malkoc verfasserin aut Edyta Teresa Sadowska verfasserin aut Michaela Hau verfasserin aut Barbara Pierce verfasserin aut Scott McWilliams verfasserin aut Ulf Bauchinger verfasserin aut In iScience Elsevier, 2019 26(2023), 12, Seite 108321- (DE-627)1019532106 25890042 nnns volume:26 year:2023 number:12 pages:108321- https://doi.org/10.1016/j.isci.2023.108321 kostenfrei https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9 kostenfrei http://www.sciencedirect.com/science/article/pii/S2589004223023982 kostenfrei https://doaj.org/toc/2589-0042 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 26 2023 12 108321- |
language |
English |
source |
In iScience 26(2023), 12, Seite 108321- volume:26 year:2023 number:12 pages:108321- |
sourceStr |
In iScience 26(2023), 12, Seite 108321- volume:26 year:2023 number:12 pages:108321- |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Ornithology Physiology Evolutionary biology Science Q |
isfreeaccess_bool |
true |
container_title |
iScience |
authorswithroles_txt_mv |
Stefania Casagrande @@aut@@ Maciej Dzialo @@aut@@ Lisa Trost @@aut@@ Kasja Malkoc @@aut@@ Edyta Teresa Sadowska @@aut@@ Michaela Hau @@aut@@ Barbara Pierce @@aut@@ Scott McWilliams @@aut@@ Ulf Bauchinger @@aut@@ |
publishDateDaySort_date |
2023-01-01T00:00:00Z |
hierarchy_top_id |
1019532106 |
id |
DOAJ099164035 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ099164035</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414015444.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.isci.2023.108321</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ099164035</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Stefania Casagrande</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ornithology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Physiology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Evolutionary biology</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Science</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Q</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Maciej Dzialo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lisa Trost</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Kasja Malkoc</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Edyta Teresa Sadowska</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Michaela Hau</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Barbara Pierce</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Scott McWilliams</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ulf Bauchinger</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">iScience</subfield><subfield code="d">Elsevier, 2019</subfield><subfield code="g">26(2023), 12, Seite 108321-</subfield><subfield code="w">(DE-627)1019532106</subfield><subfield code="x">25890042</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:26</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:12</subfield><subfield code="g">pages:108321-</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.isci.2023.108321</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.sciencedirect.com/science/article/pii/S2589004223023982</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2589-0042</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">26</subfield><subfield code="j">2023</subfield><subfield code="e">12</subfield><subfield code="h">108321-</subfield></datafield></record></collection>
|
author |
Stefania Casagrande |
spellingShingle |
Stefania Casagrande misc Ornithology misc Physiology misc Evolutionary biology misc Science misc Q Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues |
authorStr |
Stefania Casagrande |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)1019532106 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut aut aut aut aut aut aut |
collection |
DOAJ |
remote_str |
true |
illustrated |
Not Illustrated |
issn |
25890042 |
topic_title |
Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues Ornithology Physiology Evolutionary biology |
topic |
misc Ornithology misc Physiology misc Evolutionary biology misc Science misc Q |
topic_unstemmed |
misc Ornithology misc Physiology misc Evolutionary biology misc Science misc Q |
topic_browse |
misc Ornithology misc Physiology misc Evolutionary biology misc Science misc Q |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
iScience |
hierarchy_parent_id |
1019532106 |
hierarchy_top_title |
iScience |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)1019532106 |
title |
Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues |
ctrlnum |
(DE-627)DOAJ099164035 (DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9 |
title_full |
Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues |
author_sort |
Stefania Casagrande |
journal |
iScience |
journalStr |
iScience |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2023 |
contenttype_str_mv |
txt |
container_start_page |
108321 |
author_browse |
Stefania Casagrande Maciej Dzialo Lisa Trost Kasja Malkoc Edyta Teresa Sadowska Michaela Hau Barbara Pierce Scott McWilliams Ulf Bauchinger |
container_volume |
26 |
format_se |
Elektronische Aufsätze |
author-letter |
Stefania Casagrande |
doi_str_mv |
10.1016/j.isci.2023.108321 |
author2-role |
verfasserin |
title_sort |
mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues |
title_auth |
Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues |
abstract |
Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. |
abstractGer |
Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. |
abstract_unstemmed |
Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues. |
collection_details |
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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 |
container_issue |
12 |
title_short |
Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues |
url |
https://doi.org/10.1016/j.isci.2023.108321 https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9 http://www.sciencedirect.com/science/article/pii/S2589004223023982 https://doaj.org/toc/2589-0042 |
remote_bool |
true |
author2 |
Maciej Dzialo Lisa Trost Kasja Malkoc Edyta Teresa Sadowska Michaela Hau Barbara Pierce Scott McWilliams Ulf Bauchinger |
author2Str |
Maciej Dzialo Lisa Trost Kasja Malkoc Edyta Teresa Sadowska Michaela Hau Barbara Pierce Scott McWilliams Ulf Bauchinger |
ppnlink |
1019532106 |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.1016/j.isci.2023.108321 |
up_date |
2024-07-03T21:22:45.967Z |
_version_ |
1803594514807390208 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ099164035</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240414015444.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240414s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.isci.2023.108321</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ099164035</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJd795d9661f5d4f99b95059ab2f5fedf9</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Stefania Casagrande</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mitochondrial metabolism in blood more reliably predicts whole-animal energy needs compared to other tissues</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Summary: Understanding energy metabolism in free-ranging animals is crucial for ecological studies. In birds, red blood cells (RBCs) offer a minimally invasive method to estimate metabolic rate (MR). In this study with European starlings Sturnus vulgaris, we examined how RBC oxygen consumption relates to oxygen use in key tissues (brain, liver, heart, and pectoral muscle) and versus the whole organism measured at basal levels. The pectoral muscle accounted for 34%–42% of organismal MR, while the heart and liver, despite their high mass-specific metabolic rate, each contributed 2.5%–3.0% to organismal MR. Despite its low contribution to organismal MR (0.03%–0.04%), RBC MR best predicted organismal MR (r = 0.70). Oxygen consumption of the brain and pectoralis was also associated with whole-organism MR, unlike that of heart and liver. Overall, our findings demonstrate that the metabolism of a systemic tissue like blood is a superior proxy for organismal energy metabolism than that of other tissues.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ornithology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Physiology</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Evolutionary biology</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Science</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Q</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Maciej Dzialo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lisa Trost</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Kasja Malkoc</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Edyta Teresa Sadowska</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Michaela Hau</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Barbara Pierce</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Scott McWilliams</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ulf Bauchinger</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">iScience</subfield><subfield code="d">Elsevier, 2019</subfield><subfield code="g">26(2023), 12, Seite 108321-</subfield><subfield code="w">(DE-627)1019532106</subfield><subfield code="x">25890042</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:26</subfield><subfield code="g">year:2023</subfield><subfield code="g">number:12</subfield><subfield code="g">pages:108321-</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.isci.2023.108321</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/d795d9661f5d4f99b95059ab2f5fedf9</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.sciencedirect.com/science/article/pii/S2589004223023982</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2589-0042</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2049</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2064</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2129</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4333</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4393</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">26</subfield><subfield code="j">2023</subfield><subfield code="e">12</subfield><subfield code="h">108321-</subfield></datafield></record></collection>
|
score |
7.4004526 |