Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products
Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number...
Ausführliche Beschreibung
Autor*in: |
Irwin, Peter [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2013 |
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Schlagwörter: |
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Anmerkung: |
© Springer-Verlag Berlin Heidelberg (outside the USA) 2013 |
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Übergeordnetes Werk: |
Enthalten in: Analytical and bioanalytical chemistry - Berlin : Springer, 2002, 405(2013), 7 vom: 05. Feb., Seite 2353-2369 |
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Übergeordnetes Werk: |
volume:405 ; year:2013 ; number:7 ; day:05 ; month:02 ; pages:2353-2369 |
Links: |
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DOI / URN: |
10.1007/s00216-012-6659-2 |
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Katalog-ID: |
SPR002225298 |
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520 | |a Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. | ||
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700 | 1 | |a Brewster, Jeffrey |4 aut | |
700 | 1 | |a Nguyen, Ly |4 aut | |
700 | 1 | |a He, Yiping |4 aut | |
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10.1007/s00216-012-6659-2 doi (DE-627)SPR002225298 (SPR)s00216-012-6659-2-e DE-627 ger DE-627 rakwb eng Irwin, Peter verfasserin aut Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. Food-borne pathogens (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 PCR (dpeaa)DE-He213 MPN (dpeaa)DE-He213 Reed, Sue aut Brewster, Jeffrey aut Nguyen, Ly aut He, Yiping aut Enthalten in Analytical and bioanalytical chemistry Berlin : Springer, 2002 405(2013), 7 vom: 05. Feb., Seite 2353-2369 (DE-627)25372337X (DE-600)1459122-4 1618-2650 nnns volume:405 year:2013 number:7 day:05 month:02 pages:2353-2369 https://dx.doi.org/10.1007/s00216-012-6659-2 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 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_2056 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_2360 GBV_ILN_2446 GBV_ILN_2470 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_4277 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 AR 405 2013 7 05 02 2353-2369 |
spelling |
10.1007/s00216-012-6659-2 doi (DE-627)SPR002225298 (SPR)s00216-012-6659-2-e DE-627 ger DE-627 rakwb eng Irwin, Peter verfasserin aut Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. Food-borne pathogens (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 PCR (dpeaa)DE-He213 MPN (dpeaa)DE-He213 Reed, Sue aut Brewster, Jeffrey aut Nguyen, Ly aut He, Yiping aut Enthalten in Analytical and bioanalytical chemistry Berlin : Springer, 2002 405(2013), 7 vom: 05. Feb., Seite 2353-2369 (DE-627)25372337X (DE-600)1459122-4 1618-2650 nnns volume:405 year:2013 number:7 day:05 month:02 pages:2353-2369 https://dx.doi.org/10.1007/s00216-012-6659-2 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 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_2056 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_2360 GBV_ILN_2446 GBV_ILN_2470 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_4277 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 AR 405 2013 7 05 02 2353-2369 |
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10.1007/s00216-012-6659-2 doi (DE-627)SPR002225298 (SPR)s00216-012-6659-2-e DE-627 ger DE-627 rakwb eng Irwin, Peter verfasserin aut Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. Food-borne pathogens (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 PCR (dpeaa)DE-He213 MPN (dpeaa)DE-He213 Reed, Sue aut Brewster, Jeffrey aut Nguyen, Ly aut He, Yiping aut Enthalten in Analytical and bioanalytical chemistry Berlin : Springer, 2002 405(2013), 7 vom: 05. Feb., Seite 2353-2369 (DE-627)25372337X (DE-600)1459122-4 1618-2650 nnns volume:405 year:2013 number:7 day:05 month:02 pages:2353-2369 https://dx.doi.org/10.1007/s00216-012-6659-2 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 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_2056 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_2360 GBV_ILN_2446 GBV_ILN_2470 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_4277 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 AR 405 2013 7 05 02 2353-2369 |
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10.1007/s00216-012-6659-2 doi (DE-627)SPR002225298 (SPR)s00216-012-6659-2-e DE-627 ger DE-627 rakwb eng Irwin, Peter verfasserin aut Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. Food-borne pathogens (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 PCR (dpeaa)DE-He213 MPN (dpeaa)DE-He213 Reed, Sue aut Brewster, Jeffrey aut Nguyen, Ly aut He, Yiping aut Enthalten in Analytical and bioanalytical chemistry Berlin : Springer, 2002 405(2013), 7 vom: 05. Feb., Seite 2353-2369 (DE-627)25372337X (DE-600)1459122-4 1618-2650 nnns volume:405 year:2013 number:7 day:05 month:02 pages:2353-2369 https://dx.doi.org/10.1007/s00216-012-6659-2 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 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_2056 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_2360 GBV_ILN_2446 GBV_ILN_2470 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_4277 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 AR 405 2013 7 05 02 2353-2369 |
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10.1007/s00216-012-6659-2 doi (DE-627)SPR002225298 (SPR)s00216-012-6659-2-e DE-627 ger DE-627 rakwb eng Irwin, Peter verfasserin aut Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. Food-borne pathogens (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 PCR (dpeaa)DE-He213 MPN (dpeaa)DE-He213 Reed, Sue aut Brewster, Jeffrey aut Nguyen, Ly aut He, Yiping aut Enthalten in Analytical and bioanalytical chemistry Berlin : Springer, 2002 405(2013), 7 vom: 05. Feb., Seite 2353-2369 (DE-627)25372337X (DE-600)1459122-4 1618-2650 nnns volume:405 year:2013 number:7 day:05 month:02 pages:2353-2369 https://dx.doi.org/10.1007/s00216-012-6659-2 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_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 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_2056 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_2360 GBV_ILN_2446 GBV_ILN_2470 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_4277 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 AR 405 2013 7 05 02 2353-2369 |
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Enthalten in Analytical and bioanalytical chemistry 405(2013), 7 vom: 05. Feb., Seite 2353-2369 volume:405 year:2013 number:7 day:05 month:02 pages:2353-2369 |
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Irwin, Peter @@aut@@ Reed, Sue @@aut@@ Brewster, Jeffrey @@aut@@ Nguyen, Ly @@aut@@ He, Yiping @@aut@@ |
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Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. 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Irwin, Peter |
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Irwin, Peter misc Food-borne pathogens misc Real-time PCR misc PCR misc MPN Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products |
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Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products Food-borne pathogens (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 PCR (dpeaa)DE-He213 MPN (dpeaa)DE-He213 |
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Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products |
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Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products |
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Irwin, Peter Reed, Sue Brewster, Jeffrey Nguyen, Ly He, Yiping |
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non-stochastic sampling error in quantal analyses for campylobacter species on poultry products |
title_auth |
Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products |
abstract |
Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 |
abstractGer |
Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 |
abstract_unstemmed |
Abstract Using primers and fluorescent probes specific for the most common food-borne Campylobacter species (Campylobacter jejuni and Campylobacter coli), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: i.e., number of p positive pathogen growth responses out of n = 6 observations each of 4 mL (V) per dilution. Working with media washes of thrice frozen-thawed chicken pieces which had been spiked with known levels of C. jejuni and C. coli, we found that about 20 % of the experiments had a significant amount of error in the form of either greater than 25 % MPN calculation error (Δε) and/or a low apparent recovery rate (R less than 1 = MPN observed ÷ CFU spiked). Assuming such errors were exacerbated by an excessively small n, we examined computer-generated MPN enumeration data from the standpoint of stochastic sampling error (Δ) and found that such binomial-based assays behaved identically to Poisson-based methods (e.g., counting data) except that fewer technical replicates (n) appeared to be required for the same number of cells per test volume (μ). This result implies that the qPCR detection-based MPN protocol discussed herein should accurately enumerate a test population with a μ ≥ 1 using n = 6 observations per dilution. For our protocol, this equates to ≥ 8 cells per 400–500 g of sampled product. Based on this analysis, the error rate we saw in spiked experiments (where μ > > 1) implied a non-stochastic source. In other experiments we present evidence that this source was, at least in part, related to the cell concentration step (i.e., centrifugation). We also demonstrate that the error rate lessened (from ∼38 % to ∼13 %) at lower Campylobacter levels (μ ≤ 40) as would most likely exist in nature. Using this protocol, we were able to quantify 14 to 1,226 MPN per 450 g of naturally contaminated chicken for skinless pieces and 11 to 244 MPN per 450 g for wings, breasts, legs, and thighs (skin on) whereupon about 50 % of the 29 samples tested negative for both species. Four of these chicken wash samples did have substantially lower Campylobacter levels (1 to 6 MPN per 450 g) which might be better enumerated using a larger n. However, we established that the limit of quantification of this protocol diminishes for n > 6 because one is ever more diluting the sample, or lessening V, to achieve the requisite n. © Springer-Verlag Berlin Heidelberg (outside the USA) 2013 |
collection_details |
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7 |
title_short |
Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products |
url |
https://dx.doi.org/10.1007/s00216-012-6659-2 |
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Reed, Sue Brewster, Jeffrey Nguyen, Ly He, Yiping |
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doi_str |
10.1007/s00216-012-6659-2 |
up_date |
2024-07-04T02:15:17.702Z |
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score |
7.400154 |