Estimating time of death based on the biological clock

Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniq...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Kimura, Akihiko [verfasserIn] Ishida, Yuko [verfasserIn] Hayashi, Takahito [verfasserIn] Nosaka, Mizuho [verfasserIn] Kondo, Toshikazu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2010

Schlagwörter:	Time of death Biological clock Real-time RT-PCR

Übergeordnetes Werk:	Enthalten in: International journal of legal medicine - Berlin : Springer, 1922, 125(2010), 3 vom: 11. Nov., Seite 385-391
Übergeordnetes Werk:	volume:125 ; year:2010 ; number:3 ; day:11 ; month:11 ; pages:385-391

Links:	Volltext

DOI / URN:	10.1007/s00414-010-0527-4

Katalog-ID:	SPR00529410X

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245	1	0	\|a Estimating time of death based on the biological clock
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520			\|a Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death.
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700	1		\|a Kondo, Toshikazu \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t International journal of legal medicine \|d Berlin : Springer, 1922 \|g 125(2010), 3 vom: 11. Nov., Seite 385-391 \|w (DE-627)253724295 \|w (DE-600)1459222-8 \|x 1437-1596 \|7 nnns
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author_variant	a k ak y i yi t h th m n mn t k tk
matchkey_str	article:14371596:2010----::siaigiefetbsdnhb
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bklnumber	44.00 86.00 44.72
publishDate	2010
allfields	10.1007/s00414-010-0527-4 doi (DE-627)SPR00529410X (SPR)s00414-010-0527-4-e DE-627 ger DE-627 rakwb eng 340 610 ASE 44.00 bkl 86.00 bkl 44.72 bkl Kimura, Akihiko verfasserin aut Estimating time of death based on the biological clock 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death. Time of death (dpeaa)DE-He213 Biological clock (dpeaa)DE-He213 Real-time RT-PCR (dpeaa)DE-He213 Ishida, Yuko verfasserin aut Hayashi, Takahito verfasserin aut Nosaka, Mizuho verfasserin aut Kondo, Toshikazu verfasserin aut Enthalten in International journal of legal medicine Berlin : Springer, 1922 125(2010), 3 vom: 11. Nov., Seite 385-391 (DE-627)253724295 (DE-600)1459222-8 1437-1596 nnns volume:125 year:2010 number:3 day:11 month:11 pages:385-391 https://dx.doi.org/10.1007/s00414-010-0527-4 lizenzpflichtig 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_65 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_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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.00 ASE 86.00 ASE 44.72 ASE AR 125 2010 3 11 11 385-391
spelling	10.1007/s00414-010-0527-4 doi (DE-627)SPR00529410X (SPR)s00414-010-0527-4-e DE-627 ger DE-627 rakwb eng 340 610 ASE 44.00 bkl 86.00 bkl 44.72 bkl Kimura, Akihiko verfasserin aut Estimating time of death based on the biological clock 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death. Time of death (dpeaa)DE-He213 Biological clock (dpeaa)DE-He213 Real-time RT-PCR (dpeaa)DE-He213 Ishida, Yuko verfasserin aut Hayashi, Takahito verfasserin aut Nosaka, Mizuho verfasserin aut Kondo, Toshikazu verfasserin aut Enthalten in International journal of legal medicine Berlin : Springer, 1922 125(2010), 3 vom: 11. Nov., Seite 385-391 (DE-627)253724295 (DE-600)1459222-8 1437-1596 nnns volume:125 year:2010 number:3 day:11 month:11 pages:385-391 https://dx.doi.org/10.1007/s00414-010-0527-4 lizenzpflichtig 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_65 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_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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.00 ASE 86.00 ASE 44.72 ASE AR 125 2010 3 11 11 385-391
allfields_unstemmed	10.1007/s00414-010-0527-4 doi (DE-627)SPR00529410X (SPR)s00414-010-0527-4-e DE-627 ger DE-627 rakwb eng 340 610 ASE 44.00 bkl 86.00 bkl 44.72 bkl Kimura, Akihiko verfasserin aut Estimating time of death based on the biological clock 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death. Time of death (dpeaa)DE-He213 Biological clock (dpeaa)DE-He213 Real-time RT-PCR (dpeaa)DE-He213 Ishida, Yuko verfasserin aut Hayashi, Takahito verfasserin aut Nosaka, Mizuho verfasserin aut Kondo, Toshikazu verfasserin aut Enthalten in International journal of legal medicine Berlin : Springer, 1922 125(2010), 3 vom: 11. Nov., Seite 385-391 (DE-627)253724295 (DE-600)1459222-8 1437-1596 nnns volume:125 year:2010 number:3 day:11 month:11 pages:385-391 https://dx.doi.org/10.1007/s00414-010-0527-4 lizenzpflichtig 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_65 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_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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.00 ASE 86.00 ASE 44.72 ASE AR 125 2010 3 11 11 385-391
allfieldsGer	10.1007/s00414-010-0527-4 doi (DE-627)SPR00529410X (SPR)s00414-010-0527-4-e DE-627 ger DE-627 rakwb eng 340 610 ASE 44.00 bkl 86.00 bkl 44.72 bkl Kimura, Akihiko verfasserin aut Estimating time of death based on the biological clock 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death. Time of death (dpeaa)DE-He213 Biological clock (dpeaa)DE-He213 Real-time RT-PCR (dpeaa)DE-He213 Ishida, Yuko verfasserin aut Hayashi, Takahito verfasserin aut Nosaka, Mizuho verfasserin aut Kondo, Toshikazu verfasserin aut Enthalten in International journal of legal medicine Berlin : Springer, 1922 125(2010), 3 vom: 11. Nov., Seite 385-391 (DE-627)253724295 (DE-600)1459222-8 1437-1596 nnns volume:125 year:2010 number:3 day:11 month:11 pages:385-391 https://dx.doi.org/10.1007/s00414-010-0527-4 lizenzpflichtig 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_65 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_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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.00 ASE 86.00 ASE 44.72 ASE AR 125 2010 3 11 11 385-391
allfieldsSound	10.1007/s00414-010-0527-4 doi (DE-627)SPR00529410X (SPR)s00414-010-0527-4-e DE-627 ger DE-627 rakwb eng 340 610 ASE 44.00 bkl 86.00 bkl 44.72 bkl Kimura, Akihiko verfasserin aut Estimating time of death based on the biological clock 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death. Time of death (dpeaa)DE-He213 Biological clock (dpeaa)DE-He213 Real-time RT-PCR (dpeaa)DE-He213 Ishida, Yuko verfasserin aut Hayashi, Takahito verfasserin aut Nosaka, Mizuho verfasserin aut Kondo, Toshikazu verfasserin aut Enthalten in International journal of legal medicine Berlin : Springer, 1922 125(2010), 3 vom: 11. Nov., Seite 385-391 (DE-627)253724295 (DE-600)1459222-8 1437-1596 nnns volume:125 year:2010 number:3 day:11 month:11 pages:385-391 https://dx.doi.org/10.1007/s00414-010-0527-4 lizenzpflichtig 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_65 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_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_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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.00 ASE 86.00 ASE 44.72 ASE AR 125 2010 3 11 11 385-391
language	English
source	Enthalten in International journal of legal medicine 125(2010), 3 vom: 11. Nov., Seite 385-391 volume:125 year:2010 number:3 day:11 month:11 pages:385-391
sourceStr	Enthalten in International journal of legal medicine 125(2010), 3 vom: 11. Nov., Seite 385-391 volume:125 year:2010 number:3 day:11 month:11 pages:385-391
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Time of death Biological clock Real-time RT-PCR
dewey-raw	340
isfreeaccess_bool	false
container_title	International journal of legal medicine
authorswithroles_txt_mv	Kimura, Akihiko @@aut@@ Ishida, Yuko @@aut@@ Hayashi, Takahito @@aut@@ Nosaka, Mizuho @@aut@@ Kondo, Toshikazu @@aut@@
publishDateDaySort_date	2010-11-11T00:00:00Z
hierarchy_top_id	253724295
dewey-sort	3340
id	SPR00529410X
language_de	englisch
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author	Kimura, Akihiko
spellingShingle	Kimura, Akihiko ddc 340 bkl 44.00 bkl 86.00 bkl 44.72 misc Time of death misc Biological clock misc Real-time RT-PCR Estimating time of death based on the biological clock
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topic_title	340 610 ASE 44.00 bkl 86.00 bkl 44.72 bkl Estimating time of death based on the biological clock Time of death (dpeaa)DE-He213 Biological clock (dpeaa)DE-He213 Real-time RT-PCR (dpeaa)DE-He213
topic	ddc 340 bkl 44.00 bkl 86.00 bkl 44.72 misc Time of death misc Biological clock misc Real-time RT-PCR
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title	Estimating time of death based on the biological clock
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title_full	Estimating time of death based on the biological clock
author_sort	Kimura, Akihiko
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author_browse	Kimura, Akihiko Ishida, Yuko Hayashi, Takahito Nosaka, Mizuho Kondo, Toshikazu
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author-letter	Kimura, Akihiko
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title_sort	estimating time of death based on the biological clock
title_auth	Estimating time of death based on the biological clock
abstract	Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death.
abstractGer	Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death.
abstract_unstemmed	Abstract The biological clock may stop at the time of death in a dead body. Therefore, the biological clock seems useful for estimating the time of death. In this study, we tried to read the biological clock in tissues from dead bodies to estimate the time of death using molecular biological techniques. At first, we examined real-time RT-PCR analysis of gene expression for mPer2 and mBmal1, which constitutes a feedback loop in the oscillation system, in the kidney, liver, and heart of mice. We could detect circadian oscillation of these gene expressions in mouse tissues even at <48 h after death. Thus, the ratio of mPer2/mBmal1 was found to be useful for estimating the time of death. We next applied this method to the liver, kidney, and heart obtained from forensic autopsy cases with less than 72 h of postmortem interval. Significant circadian oscillation of hPer2/hBmal1 ratio could be detected in these autopsy samples. We further examined gene expression for hRev-Erbα, a component of another feedback loop. The ratios of hRev-Erbα/hBmal1 showed higher amplitude of oscillation than those of hPer2/hBmal1 and are considered more suitable for estimating the time of death. In particular, a hRev/hBmal1 ratio of >50 indicated the time of death as 0200–0900 hours, and a hRev/hBmal1 ratio that considerably exceeded 75 indicated the time of death as 0200–0800 hours. On the other hand, a hRev/hBmal1 ratio of less than 25 strongly indicated the time of death as 1000–2300 hours. Taken together, these findings indicate that gene expression analyses of the biological clock could be powerful methods for estimation of the time of death.
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title_short	Estimating time of death based on the biological clock
url	https://dx.doi.org/10.1007/s00414-010-0527-4
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author2	Ishida, Yuko Hayashi, Takahito Nosaka, Mizuho Kondo, Toshikazu
author2Str	Ishida, Yuko Hayashi, Takahito Nosaka, Mizuho Kondo, Toshikazu
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doi_str	10.1007/s00414-010-0527-4
up_date	2024-07-03T15:19:41.560Z
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