Simultaneous analysis of potassium and ammonium ions in the vitreous humour by capillary electrophoresis and their integrated use to infer the post mortem interval (PMI)

Palacio, Covadonga; Gottardo, Rossella; Cirielli, Vito; Musile, Giacomo; Agard, Yvane; Bortolotti, Federica; Tagliaro, Franco

doi:10.1177/0025802420934239

Cited by 8 publications

(9 citation statements)

References 21 publications

(27 reference statements)

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“…Beckman P/ACE Station (version 8.0) software was used for instrument control, data acquisition and processing. Separations were performed as described in Palacio et al [22]. Briefly, the running buffer was composed of 5-mM imidazole, 6-mM HIBA and 5-mM 18crown-6 ether adjusted to pH 4.5 with acetic acid.…”

Section: Instrumentationmentioning

confidence: 99%

Comparative use of aqueous humour 1H NMR metabolomics and potassium concentration for PMI estimation in an animal model

et al. 2020

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Estimation of the post-mortem interval (PMI) remains a matter of concern in the forensic scenario. Traditional and novel approaches are not yet able to fully address this issue, which relies on complex biological phenomena triggered by death. For this purpose, eye compartments may be chosen for experimental studies because they are more resistant to post-mortem modifications. Vitreous humour, in particular, has been extensively investigated, with potassium concentration ([K+]) being the marker that is better correlated with PMI estimation. Recently, a 1H nuclear magnetic resonance (NMR) metabolomic approach based on aqueous humour (AH) from an animal model was proposed for PMI estimation, resulting in a robust and validated regression model. Here we studied the variation in [K+] in the same experimental setup. [K+] was determined through capillary ion analysis (CIA) and a regression analysis was performed. Moreover, it was investigated whether the PMI information related to potassium could improve the metabolome predictive power in estimating the PMI. Interestingly, we found that a part of the metabolomic profile is able to explain most of the information carried by potassium, suggesting that the rise in both potassium and metabolite concentrations relies on a similar biological mechanism. In the first 24-h PMI window, the AH metabolomic profile shows greater predictive power than [K+] behaviour, suggesting its potential use as an additional tool for estimating the time since death.

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Section: Instrumentationmentioning

confidence: 99%

Comparative use of aqueous humour 1H NMR metabolomics and potassium concentration for PMI estimation in an animal model

et al. 2020

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“…Tagliaro measured the amount potassium ion 𝐾 + in RC's vitreous humour 56 hours after her death. Here we implement the regression model proposed in Palacio et al (2021) and calculate the prediction interval for 𝐾 + at PMI = 56 hours. The model is linear with a quadratic term, the dependent variable 𝑌 is the concentration of 𝐾 + measured in mM, and the predictor 𝑥 is the PMI measured in hours.…”

Section: Prediction Intervalmentioning

confidence: 99%

“…The model is linear with a quadratic term, the dependent variable 𝑌 is the concentration of 𝐾 + measured in mM, and the predictor 𝑥 is the PMI measured in hours. Based on the data in Table 1 page Figure 14 shows the regression model based the Palacio et al (2021) data with the 95% and 99% prediction curves and highlights the corresponding interval at a PMI of 56 hours. Table 14 gives the values of the 95% and 99% prediction intervals when PMI=56 hours.…”

Section: Prediction Intervalmentioning

confidence: 99%

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Statistical Analyses in the case of an Italian nurse accused of murdering patients

Dotto¹,

Gill²,

Mortera³

2022

Preprint

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Suspicions about medical murder sometimes arise due to a surprising or unexpected series of events, such as an apparently unusual number of deaths among patients under the care of a particular nurse. But also a single disturbing event might trigger suspicion about a particular nurse, and this might then lead to investigation of events which happened when she was thought to be present. In either case, there is a statistical challenge of distinguishing event clusters that arise from criminal acts from those that arise coincidentally from other causes. We show that an apparently striking association between a nurse's presence and a high rate of deaths in a hospital ward can easily be completely spurious. In short: in a medium-care hospital ward where many patients are suffering terminal illnesses, and deaths are frequent, most deaths occur in the morning. Most nurses are on duty in the morning, too. There are less deaths in the afternoon, and even less at night; correspondingly, less nurses are on duty in the afternoon, even less during the night. Consequently, a

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“…Determining the post-mortem interval (PMI) has always been a major challenge for forensic pathologists. Although different methods have been developed over the years [1][2][3][4][5][6][7][8][9][10] accurate PMI estimation, highly required in the forensic setting, are still difficult to be obtained.…”

Section: Introductionmentioning

confidence: 99%

PMI estimation through metabolomics and potassium analysis on animal vitreous humour

Locci

Stocchero

Gottardo

et al. 2022

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IntroductionThe estimation of post-mortem interval remains a major challenge in forensic science. Most of the proposed approaches lack the reliability required to meet the rigorous forensic standards.ObjectivesWe applied1H NMR metabolomics to estimate PMI on ovine vitreous humour comparing the results with the actual scientific gold standard, namely vitreous potassium concentrations.MethodsVitreous humour samples were collected in a time frame ranging from 6 to 86 hours after death. Experiments were performed by using1H NMR metabolomics and Ion Capillary Analysis. Data were submitted to multivariate statistical data analysis.ResultsA multivariate calibration model was built to estimate PMI based on 47 vitreous humour samples. The model was validated with an independent test set of 24 samples, obtaining a prediction error on the entire range of 6.9 h for PMI<24h, 7.4 h for PMI between 24 and 48h, and 10.3 h for PMI>48 h. Time-related modifications of the1H NMR vitreous metabolomic profile could predict PMI better than potassium up to 48 hours after death, while a combination of the two is better than the single approach for higher PMIs estimation.ConclusionThe present study, although in a proof-of-concept animal model, shows that vitreous metabolomics can be a powerful tool to predict PMI providing a more accurate estimation compared to the widely studied approach based on vitreous potassium concentrations.

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Simultaneous analysis of potassium and ammonium ions in the vitreous humour by capillary electrophoresis and their integrated use to infer the post mortem interval (PMI)

Cited by 8 publications

References 21 publications

Comparative use of aqueous humour 1H NMR metabolomics and potassium concentration for PMI estimation in an animal model

Comparative use of aqueous humour 1H NMR metabolomics and potassium concentration for PMI estimation in an animal model

Statistical Analyses in the case of an Italian nurse accused of murdering patients

PMI estimation through metabolomics and potassium analysis on animal vitreous humour

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