Impact of data aggregation approaches on the relationships between operating speed and traffic safety

The impact of operating speed on traffic crash occurrence has been a controversial topic in the traffic safety discipline as some studies reported a positive association whereas others indicated a negative relationship between speed and crashes. Two major issues thought to be accountable for such conflicting findings are the application of inappropriate statistical methods and the use of sample datasets with varying levels of aggregation. The main objective of this study is therefore to investigate the impacts of data aggregation schemes on the relationships between operating speed and traffic safety. A total of three aggregation approaches were examined: (1) a segment-based dataset in which crashes are grouped by roadway segment, (2) a scenario-based dataset where crashes are aggregated by traffic operating scenarios, and (3) a disaggregated crash-level dataset consisting of information from individual crashes. The first two aggregation approaches were used in examining the relationships between operating speed and crash frequency using Bayesian random-effects negative binomial models. The third disaggregated crash risk analysis was conducted utilizing Bayesian random-effects logistic regression models. From the modeling results, it has been concluded that the scenario-based approach shared similar findings with those of the disaggregated crash risk analysis approach in which a U-shaped relationship between operating speed and crash occurrence was identified. However, the commonly adopted segment-based aggregation approach revealed a monotonous negative relationship between speed and crash frequency. The implications of the different analyses results and the potential applications of the results on speed management systems have therefore been discussed

How to determine an optimal threshold to classify real-time crash-prone traffic conditions?

One of the proactive approaches in reducing traffic crashes is to identify hazardous traffic conditions that may lead to a traffic crash, known as real-time crash prediction. Threshold selection is one of the essential steps of real-time crash prediction. And it provides the cut-off point for the posterior probability which is used to separate potential crash warnings against normal traffic conditions, after the outcome of the probability of a crash occurring given a specific traffic condition on the basis of crash risk evaluation models. There is however a dearth of research that focuses on how to effectively determine an optimal threshold. And only when discussing the predictive performance of the models, a few studies utilized subjective methods to choose the threshold. The subjective methods cannot automatically identify the optimal thresholds in different traffic and weather conditions in real application. Thus, a theoretical method to select the threshold value is necessary for the sake of avoiding subjective judgments. The purpose of this study is to provide a theoretical method for automatically identifying the optimal threshold. Considering the random effects of variable factors across all roadway segments, the mixed logit model was utilized to develop the crash risk evaluation model and further evaluate the crash risk. Cross-entropy, between-class variance and other theories were employed and investigated to empirically identify the optimal threshold. And K-fold cross-validation was used to validate the performance of proposed threshold selection methods with the help of several evaluation criteria. The results indicate that (i) the mixed logit model can obtain a good performance; (ii) the classification performance of the threshold selected by the minimum cross-entropy method outperforms the other methods according to the criteria. This method can be well-behaved to automatically identify thresholds in crash prediction, by minimizing the cross entropy between the original dataset with continuous probability of a crash occurring and the binarized dataset after using the thresholds to separate potential crash warnings against normal traffic conditions

Identification and Quantitation of Fatty Acid Double Bond Positional Isomers: A Shotgun Lipidomics Approach Using Charge-Switch Derivatization

The specific locations of double bonds in mammalian lipids have profound effects on biological membrane structure, dynamics and lipid second messenger production. Herein, we describe a shotgun lipidomics approach that exploits charge-switch derivatization with <i>N</i>-(4-aminomethylphenyl) pyridinium (AMPP) and tandem mass spectrometry for identification and quantification of fatty acid double bond positional isomers. Through charge-switch derivatization of fatty acids followed by positive-ion mode ionization and fragmentation analysis, a marked increase in analytic sensitivity (low fmol/μL) and the identification of double bond positional isomers can be obtained. Specifically, the locations of proximal double bonds in AMPP-derivatized fatty acids are identified by diagnostic fragment ions resulting from the markedly reduced 1,4-hydrogen elimination from the proximal olefinic carbons. Additional fragmentation patterns resulting from allylic cleavages further substantiated the double bond position assignments. Moreover, quantification of fatty acid double bond positional isomers is achieved by the linear relationship of the normalized intensities of characteristic fragment ions vs the isomeric compositions of discrete fatty acid positional isomers. The application of this approach for the analysis of fatty acids in human serum demonstrated the existence of two double bond isomers of linolenic acid (i.e., Δ^6,9,12 18:3, γ-linolenic acid (GLA), and Δ^9,12,15 18:3, α-linolenic acid (ALA)). Remarkably, the isomeric ratio of GLA vs ALA esterified in neutral lipids was 3-fold higher than the ratio of their nonesterified moieties. Through this developed method, previously underestimated or unidentified alterations in fatty acid structural isomers can be determined facilitating the identification of novel biomarkers and maladaptive alterations in lipid metabolism during disease

Characterization and Quantification of Diacylglycerol Species in Biological Extracts after One-Step Derivatization: A Shotgun Lipidomics Approach

Diacylglycerols (DAGs) are important intermediates of lipid metabolism and cellular signaling. It is well-known that the mass levels of DAG are altered under disease states. Therefore, quantitative analysis of DAGs in biological samples can provide critical information to uncover underlying mechanisms of various cellular functional disorders. Although great efforts on the analysis of individual DAG species have recently been made by utilizing mass spectrometry with or without derivatization, cost-effective and high throughput methodologies for identification and quantification of all DAG species including regioisomers, particularly in an approach of shotgun lipidomics, are still missing. Herein, we described a novel method for directly identifying and quantifying DAG species including regioisomers present in lipid extracts of biological samples after facile one-step derivatization with dimethylglycine based on the principles of multidimensional mass spectrometry-based shotgun lipidomics. The established method provided substantial sensitivity (low limit of quantification at amol/μL), high specificity, and broad linear dynamics range (2500-fold) without matrix effects. By exploiting this novel method, we revealed a 16-fold increase of total DAG mass in the livers of <i>ob</i>/<i>ob</i> mice compared to their wild type controls at 4 months of age (an insulin-resistant state) versus a 5-fold difference between 3 month old mice (with normal insulin). These results demonstrated the importance and power of the method for studying biochemical mechanisms underpinning disease states

Shotgun Lipidomics Approach to Stabilize the Regiospecificity of Monoglycerides Using a Facile Low-Temperature Derivatization Enabling Their Definitive Identification and Quantitation

Monoglycerides play a central role in lipid metabolism and are important signaling metabolites. Quantitative analysis of monoglyceride molecular species has remained challenging due to rapid isomerization via α-hydroxy acyl migration. Herein, we describe a shotgun lipidomics approach that utilizes a single-phase methyl <i>tert</i>-butyl ether extraction to minimize acyl migration, a facile low temperature diacetyl derivatization to stabilize regiospecificity, and tandem mass spectrometric analysis to identify and quantify regioisomers of monoglycerides in biological samples. The rapid and robust diacetyl derivatization at low temperatures (e.g., −20 °C, 30 min) prevents postextraction acyl migration and preserves regiospecificity of monoglyceride structural isomers. Furthermore, ionization of ammonium adducts of diacetyl monoglyceride derivatives in positive-ion mode markedly increases analytic sensitivity (low fmol/μL). Critically, diacetyl derivatization enables the differentiation of discrete monoglyceride regioisomers without chromatography through their distinct signature fragmentation patterns during collision induced dissociation. The application of this approach in the analysis of monoglycerides in multiple biologic tissues demonstrated diverse profiles of molecular species. Remarkably, the regiospecificity of individual monoglyceride molecular species is also diverse from tissue to tissue. Collectively, this developed approach enables the profiling, identification and quantitation of monoglyceride regioisomers directly from tissue extracts

Identification and analyses of individual molecular species present in purified bovine heart ethanolamine glycerophospholipid^a.

a<p>Bovine heart lipids were extracted by a modified Bligh and Dyer procedure <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001368#pone.0001368-Bligh1" target="_blank">[21]</a> and the ethanolamine phospholipid (PtdEtn) fraction was separated by using HPLC as previously described <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001368#pone.0001368-Gross3" target="_blank">[23]</a>. Analyses of PtdEtn molecular species were performed in the negative-ion mode by using an LTQ-Orbitrap mass spectrometer with an electrospray ion source. The determined monoisotopic masses (column 1) of PtdEtn molecular species were externally calibrated relative to the base peak. The molecular formulas listed in column 2 were derived from accurate mass analyses of monoisotopic mass and were grouped into each isobaric mass. The prefix “a”, “d”, and “p” stand for alkyl-acyl PtdEtn, diacyl PtdEtn, and plasmalogen PtdEtn, respectively. The relative abundance listed in column 3 was normalized to the isobaric base peak of the ion at <i>m/z</i> 766.5 after ¹³C de-isotoping and represents X±SD of at least four different analyses. The notation m∶n represents the fatty acyl (or ether aliphatic) chain containing m carbons and n double bonds. The numbers in the parentheses represent the relative composition of each individual molecular species of an isobaric ion. The symbols of “<” and “>” indicate that the data represent the best estimation from the analyses.</p>b<p>Identification of individual pPtdEtn molecular species was performed based on both accurate mass analyses and acidic vapor treatment. Identification of individual aPtdEtn molecular species was performed based on the accurate mass analyses, the paired rule, and the information of the identified pPtdEtn counterparts as discussed in the text. Identification of individual dPtdEtn molecular species was conducted solely based on accurate mass analyses. The abundance of each of the paired dPtdEtn molecular species cannot be accurately determined at the current stage of lipidomic technology.</p

Pathways involved in the biosynthesis of plasmenylethanolamine.

<p>The enzymes that may be involved in non-selective utilization of acyl CoA pool are highlighted with broken-lined frames. ** CDP-ethanolamine: 1-<i>O</i>-alkyl-2-acyl-<i>sn</i>-glycerol ethanolamine phosphotransferase.</p

The structures of the paired isomers of plasmenylethanolamine molecular species.

<p>The structures of the paired isomers of plasmenylethanolamine molecular species.</p

Representative negative-ion ESI/MS analyses of individual ethanolamine glycerophospholipid molecular species in mouse cerebellar lipid extracts.

<p>Mouse cerebellar lipid extracts were prepared by a modified Bligh and Dyer procedure <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001368#pone.0001368-Bligh1" target="_blank">[21]</a>. Spectrum A was acquired in the negative-ion mode by using a QqQ mass spectrometer directly from a lipid extract that was diluted to less than 50 pmol of total lipids/µl after addition of approximately 25 pmol LiOH/µl to the lipid solution. Spectrum B was taken in the negative-ion mode after the diluted lipid solution used in spectrum A was treated with acid vapor and a small amount of LiOH (approximately 25 pmol LiOH/µl) was added to the infused solution. Spectrum C was acquired in the negative-ion mode as that of spectrum A but in the precursor-ion mode. The tandem mass spectrometry of precursor-ion scanning of 196 Th (i.e., phosphoethanolamine) was conducted through scanning the first quadrupole in the interested mass range and monitoring the third quadruple with the ion at <i>m/z</i> 196 while collision activation was performed in the second quadrupole at collision energy of 50 eV. Spectrum D was acquired in the negative-ion mode directly from a diluted mouse cerebellum lipid extract after addition of Fmoc chloride as previously described <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001368#pone.0001368-Han5" target="_blank">[16]</a>. Spectrum E was acquired in the negative-ion mode as that of spectrum D but in the neutral loss mode. Tandem mass spectrometry of neutral loss scanning was conducted through coordinately scanning the first and third quadrupoles with a mass difference of 222.2 u (i.e., loss of a Fmoc) while collisional activation was performed in the second quadrupole at collision energy of 32 eV. “IS” denotes internal standard. All mass spectral traces are displayed after normalization to the base peak in each individual spectrum. All spectra are displayed after being normalized to the base peak in individual spectrum.</p

Comparison of representative aliphatic or acyl chain profiles in different lipid domains of bovine heart.

<p>The profiles of both aliphatic chains (open column in Panel A) and fatty acyl chains (closed column in Panel A) of bovine heart ether-linked ethanolamine glycerophospholipids (PtdEtn) were derived from individual molecular species listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001368#pone-0001368-t001" target="_blank">Table 1</a>. The fatty acyl chain composition of bovine heart diacyl PtdEtn (Panel B) was also calculated from the identified individual molecular species as listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001368#pone-0001368-t001" target="_blank">Table 1</a>. The profile of acyl-CoA in bovine heart (Panel C) was re-plotted from previously published data <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001368#pone.0001368-DeMar1" target="_blank">[28]</a>.</p