Simultaneous measurement of formic acid, methanol and ethanol in vitreous and blood samples of postmortem by headspace GC-FID

Ghorbani, Hamideh; Nezami, Alireza; Sheikholeslami, Behjat; Hedjazi, Arya; Ahmadimanesh, Mahnaz

doi:10.1186/s12995-017-0184-3

Cited by 28 publications

(19 citation statements)

References 18 publications

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“…A bivariate logistic regression model was performed separately for the independent variables to evaluate degrees of association with risky driving behavior (dependent variable). The independent variables with a < 0.2 p value [41] in this type of analysis were exported to a multivariable analysis to examine the effects of potential confounders. We selected the forward variable selection method in the multivariable logistic regression model since it was assumed to be relatively more conservative types.…”

Section: Methodsmentioning

confidence: 99%

Factors associated with risky driving behaviors for road traffic crashes among professional car drivers in Bahirdar city, northwest Ethiopia, 2016: a cross-sectional study

Mekonnen

Tesfaye

Moges

et al. 2019

Environ Health Prev Med

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Background Road traffic injury is one of the persistent public health challenges in most regions of the world, representing substantial human and economic losses. Annually, about 1.25 million lives are lost, whereas 50 million suffer from road traffic injuries globally. It has been shown that over 60% of the reasons for traffic injuries are a risky driving behavior (RDB). Despite the problem’s pervasiveness, there is a paucity of information about level and factors influencing RDB among professional car drivers in Bahirdar city, northwest Ethiopia. Methods An institution-based cross-sectional study was conducted from February to March 2016. A systematic random sampling technique was used to select 376 participants. A self-administered driver behavior questionnaire (DBQ) was used for data collection. We performed a binary logistic regression analysis to investigate the associations of variables. Potential confounders were controlled using a multivariable logistic regression model. We ascertained the significance at < 0.05 p value and evaluated strength of associations using crude odds ratios (COR) and adjusted odds ratios (AOR) with 95% confidence intervals (CI). Results A total of 361 drivers participated (response rate, 96%). The mean age was 34 (standard deviations ± 7.97) years. The majority, 98.9% ( N = 357), were males. The level of risky driving behavior and road traffic crashes were 79.4% (95% CI 75.92, 83.97) and 16.3% (95% CI 15.91, 24.84), respectively. Average monthly salary [AOR 2.04; 95% CI (1.23, 2.74)], driving experience [AOR 2.72; 95% CI (1.07, 6.89)], distance driven per year [AOR 2.06; 95% CI (1.13, 4.10)], and previous history of involvement in traffic crashes [AOR 2.30; 95% CI (1.15, 7.35)] were significantly associated with risky driving behavior. Conclusions The study shows that risky driving behavior is common among professional car drivers in the study setting. Therefore, it is strongly advisable for policy makers and other stake holders to devise strategies that consider working conditions, like monthly salary and driving experiences. The study also suggests that it is often advisable to reduce the distance driven per year and learn from implications of previous history of involvement in traffic crashes.

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Section: Methodsmentioning

confidence: 99%

Factors associated with risky driving behaviors for road traffic crashes among professional car drivers in Bahirdar city, northwest Ethiopia, 2016: a cross-sectional study

Mekonnen

Tesfaye

Moges

et al. 2019

Environ Health Prev Med

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“…Consequently, FID gives a better overall quantitative representation in complex biological samples where traditional MS analysis often is challenged by ion interference effects (36). Further, in a comparison of the non-esterified or free fatty acids quantitative results between the TLC/GC-FID and the GC-MS platforms demonstrated that the GC-MS concentrations of palmitic acid, vaccinic acid, oleic acid, linoleic acid, dihomo-γ-linolenic acid and docosapenta-(4,7,10,13,16)-enoic acid are generally higher than those measured by TLC/GC-FID (11) indicating higher sensitivity and detector-bias as far as MS is concerned.…”

Section: Resultsmentioning

confidence: 99%

“…Combined TLC/GC-FID analysis when compared to GC-MS as the two methods for analysis of human serum lipids, allowed identification and quantification of only eight metabolites in common (arachidonic acid, eicosanoic acid, linoleic acid, oleic acid, palmitelaidic acid, palmitic acid, stearic acid and tetradecanoic acid) (11), suggesting significant complementarity of FID and MS analysis of the human metabolome. Previously, ethanol, methanol, and formate concentrations were measured by headspace GC-FID analysis in vitreous and blood samples collected postmortem (16).…”

Section: Introductionmentioning

confidence: 99%

Comparison of a GC-Orbitrap-MS with Parallel GC-FID Capabilities for Metabolomics of Human Serum

Misra

Bassey

Olivier

2019

Preprint

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Gas chromatography mass spectrometry (GC-MS) platforms for use in high throughput and discovery metabolomics have heavily relied on time of flight (ToF), and low resolution quadrupole and ion trap mass spectrometers and are typically run in electron ionization (EI) modes for matching spectral libraries. Traditionally, detectors such as flame ionization detection (FID), have also helped in identification and quantification of compounds in complex samples for diverse clinical applications, i.e., fatty acids. We probed if combination of FID in line with a high-resolution instrument like a GC-Orbitrap-MS may confer advantages over traditional mass spectrometry using EI.We used a commercially available human serum sample to enhance the chemical space of serum using an advanced high resolution mass spectrometry (HR-MS) platform (QExactive Orbitrap-MS) with an FID feature for confident metabolite identification to assess the suitability of the platform for routine clinical metabolomics research. Using the EI mode, we quantified 294 metabolites in human serum using GC-Orbitrap-MS. These metabolites belonged to 89 biological pathways in KEGG. Following a sample split, using an in-line FID analysis, 1117 peaks were quantified. Moreover, representative peaks from FID and their corresponding MS counterparts showed a good correspondence when compared for relative abundance.Our study highlights the benefits of the use of a higher mass accuracy instrument for untargeted GC-MS-based metabolomics not only with EI mode but also orthogonal detection method such as FID, for robust and orthogonal quantification, in future studies addressing complex biological samples in clinical set ups.

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“…Alcohol, in particular ethanol, is one of the most significantly consumed drugs worldwide. As far as we know, alcohol significantly contributes to the total number of hospital admissions and deaths, mainly including those due to car accidents and overdose [1,2]. The molecule which is responsible for alcohol intoxication is the ethanol (C 2 H 6 O).…”

Section: Introductionmentioning

confidence: 99%

“…Present in all alcoholic beverages, ethanol reaches the blood vessel system through normal digestion. Recognized as a toxin, ethanol is destroyed by the body; mainly in the liver, as it filters blood [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Prediction Model of Alcohol Intoxication from Facial Temperature Dynamics Based on K-Means Clustering Driven by Evolutionary Computing

et al. 2019

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Alcohol intoxication is a significant phenomenon, affecting many social areas, including work procedures or car driving. Alcohol causes certain side effects including changing the facial thermal distribution, which may enable the contactless identification and classification of alcohol-intoxicated people. We adopted a multiregional segmentation procedure to identify and classify symmetrical facial features, which reliably reflects the facial-temperature variations while subjects are drinking alcohol. Such a model can objectively track alcohol intoxication in the form of a facial temperature map. In our paper, we propose the segmentation model based on the clustering algorithm, which is driven by the modified version of the Artificial Bee Colony (ABC) evolutionary optimization with the goal of facial temperature features extraction from the IR (infrared radiation) images. This model allows for a definition of symmetric clusters, identifying facial temperature structures corresponding with intoxication. The ABC algorithm serves as an optimization process for an optimal cluster's distribution to the clustering method the best approximate individual areas linked with gradual alcohol intoxication. In our analysis, we analyzed a set of twenty volunteers, who had IR images taken to reflect the process of alcohol intoxication. The proposed method was represented by multiregional segmentation, allowing for classification of the individual spatial temperature areas into segmentation classes. The proposed method, besides single IR image modelling, allows for dynamical tracking of the alcohol-temperature features within a process of intoxication, from the sober state up to the maximum observed intoxication level.

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Simultaneous measurement of formic acid, methanol and ethanol in vitreous and blood samples of postmortem by headspace GC-FID

Cited by 28 publications

References 18 publications

Factors associated with risky driving behaviors for road traffic crashes among professional car drivers in Bahirdar city, northwest Ethiopia, 2016: a cross-sectional study

Factors associated with risky driving behaviors for road traffic crashes among professional car drivers in Bahirdar city, northwest Ethiopia, 2016: a cross-sectional study

Comparison of a GC-Orbitrap-MS with Parallel GC-FID Capabilities for Metabolomics of Human Serum

Prediction Model of Alcohol Intoxication from Facial Temperature Dynamics Based on K-Means Clustering Driven by Evolutionary Computing

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