Learning about injury severity from no-injury crashes: A random parameters with heterogeneity in means and variances approach.

The traditional approach to injury-severity analyses does not allow in-depth understanding of no-injury crashes, as crash factors found to contribute to the various injury severities may have similar effects on the severity of vehicle damage even if no injury is recorded. Viewing no-injury crashes using the vehicle damage severities as sub-categories and bases for potential injuries can improve understanding of future injury crashes. To better understand the mechanism of no-injury crashes and the crash factors that contribute to the extent of vehicle damage beyond the single categorization of these crashes in injury severity analysis, this study presents a vehicle damage severity analysis for no-injury crashes. To compare the effects of crash contributing factors on crash outcomes, two injury severity models were also estimated. Random parameters multinomial logit models with heterogeneity in means and variances were developed to account for unobserved heterogeneity. Model estimation results revealed that several common factors (e.g., unsafe speed, distracted driving, driving under influence, vehicle age, and run-off-road) are correlated with both injury severity in injury crashes and vehicle damage severity in no-injury crashes. Therefore, the sub-categorization of no-injury crashes by vehicle damage severity can potentially improve estimates of injury severity considered in resource allocation decisions for traffic safety.

A comparative analysis of freeway crash incident clearance time using random parameter and latent class hazard-based duration model.

The effects of freeway incident clearance times on the flow of traffic have recently increased interests in understanding what factors influence incident durations. This has particularly become topical due to the financial and economic implications of traffic gridlocks caused by freeway incidents on industries and personal mobility. This paper presents two advanced econometric modeling methods, random parameters duration modeling and latent class duration modeling in understanding the factors that impact freeway incident clearance times in the State of Alabama. These two modeling approaches were further compared to identify which of them provides the best fit for the data with respect to accounting for unobserved heterogeneity. A total of 2206 freeway crash incident data from January 1 to December 31, 2018 were examined in developing the models. The study was based on a unique dataset that involved merging and matching Traffic Incident Management response data from the Alabama Department of Transportation (ALDOT) Traffic Management Center (TMC), freeway crash data from the Center for Advanced Public Safety (CAPS) at the University of Alabama, Alabama Service and Assistance Patrol (ASAP) data from ALDOT and traffic volume from ALDOT's Highway Performance Management System (HPMS). The model estimation results reveal that a total of nineteen variables were found statistically significant with five random variables (on-road, nighttime, rain, AADT, and ASAP existing coverage area) and fourteen fixed effects variables for the random parameters model. For latent class model, a total of eighteen variables were observed statistically significant within two distinct latent classes (Latent Class 1 with class membership probability of 0.23 and Latent Class 2 with class membership probability of 0.77) at a 0.05 significance level. A comparison of the two models reveals that the latent class model provides the better fit for the incident duration data. The findings of this study are expected to contribute to the body of knowledge on incident duration by employing two advanced econometric modeling methods and to inform statewide efforts in significantly reducing the duration of freeway incident clearance time. Moreover, this is to ensure that policy decisions that may arise from the findings of the study are sound and based on data-driven evidence.

Lanthanide-Binding Tags for 3D X-ray Imaging of Proteins in Cells at Nanoscale Resolution.

We report the application of lanthanide-binding tags (LBTs) for two- and three-dimensional X-ray imaging of individual proteins in cells with a sub-15 nm beam. The method combines encoded LBTs, which are tags of minimal size (ca. 15-20 amino acids) affording high-affinity lanthanide ion binding, and X-ray fluorescence microscopy (XFM). This approach enables visualization of LBT-tagged proteins while simultaneously measuring the elemental distribution in cells at a spatial resolution necessary for visualizing cell membranes and eukaryotic subcellular organelles.

X-ray Fluorescence Nanotomography of Single Bacteria with a Sub-15 nm Beam.

X-ray Fluorescence (XRF) microscopy is a growing approach for imaging the trace element concentration, distribution, and speciation in biological cells at the nanoscale. Moreover, three-dimensional nanotomography provides the added advantage of imaging subcellular structure and chemical identity in three dimensions without the need for staining or sectioning of cells. To date, technical challenges in X-ray optics, sample preparation, and detection sensitivity have limited the use of XRF nanotomography in this area. Here, XRF nanotomography was used to image the elemental distribution in individual E. coli bacterial cells using a sub-15 nm beam at the Hard X-ray Nanoprobe beamline (HXN, 3-ID) at NSLS-II. These measurements were simultaneously combined with ptychography to image structural components of the cells. The cells were embedded in small (3-20 µm) sodium chloride crystals, which provided a non-aqueous matrix to retain the three-dimensional structure of the E. coli while collecting data at room temperature. Results showed a generally uniform distribution of calcium in the cells, but an inhomogeneous zinc distribution, most notably with concentrated regions of zinc at the polar ends of the cells. This work demonstrates that simultaneous two-dimensional ptychography and XRF nanotomography can be performed with a sub-15 nm beam size on unfrozen biological cells to co-localize elemental distribution and nanostructure simultaneously.

Multilevel analysis of the role of human factors in regional disparities in crash outcomes.

A growing body of research has examined the disparities in road traffic safety among population groups and geographic regions. These studies reveal disparities in crash outcomes between people and regions with different socioeconomic characteristics. A critical aspect of the road traffic crash epidemic that has received limited attention is the influence of local characteristics on human elements that increase the risk of getting into a crash. This paper applies multilevel logistic regression modeling techniques to investigate the influence of driver residential factors on driver behaviors in an attempt to explain the area-based differences in the severity of road crashes across the State of Alabama. Specifically, the paper reports the effects of characteristics attributable to drivers and the geographic regions they reside on the likelihood of a crash resulting in serious injuries. Model estimation revealed that driver residence (postal code or region) accounted for about 7.3% of the variability in the probability of a driver getting into a serious injury crash, regardless of driver characteristics. The results also reveal disparities in serious injury crash rate as well as significant proportions of serious injury crashes involving no seatbelt usage, driving under influence (DUI), unemployed drivers, young drivers, distracted driving, and African American drivers among some regions. The average credit scores, average commute times, and populations of driver postal codes are shown to be significant predictors for risk of severe injury crashes. This approach to traffic crash analysis presented can serve as the foundation for evidence-based policies and also guide the implementation of targeted countermeasures.

How the choice of safety performance function affects the identification of important crash prediction variables.

Across the nation, researchers and transportation engineers are developing safety performance functions (SPFs) to predict crash rates and develop crash modification factors to improve traffic safety at roadway segments and intersections. Generalized linear models (GLMs), such as Poisson or negative binomial regression, are most commonly used to develop SPFs with annual average daily traffic as the primary roadway characteristic to predict crashes. However, while more complex to interpret, data mining models such as boosted regression trees have improved upon GLMs crash prediction performance due to their ability to handle more data characteristics, accommodate non-linearities, and include interaction effects between the characteristics. An intersection data inventory of 36 safety relevant parameters for three- and four-legged non-signalized intersections along state routes in Alabama was used to study the importance of intersection characteristics on crash rate and the interaction effects between key characteristics. Four different SPFs were investigated and compared: Poisson regression, negative binomial regression, regularized generalized linear model, and boosted regression trees. The models did not agree on which intersection characteristics were most related to the crash rate. The boosted regression tree model significantly outperformed the other models and identified several intersection characteristics as having strong interaction effects.

Characterization of Protein Structural Changes in Living Cells Using Time-Lapsed FTIR Imaging.

Fourier-transform infrared (FTIR) spectroscopic imaging is a widely used method for studying the chemistry of proteins, lipids, and DNA in biological systems without the need for additional tagging or labeling. This technique can be especially powerful for spatially resolved, temporal studies of dynamic changes such as in vivo protein folding in cell culture models. However, FTIR imaging experiments have typically been limited to dry samples as a result of the significant spectral overlap between water and the protein Amide I band centered at 1650 cm(-1). Here, we demonstrate a method to rapidly obtain high quality FTIR spectral images at submicron pixel resolution in vivo over a duration of 18 h and longer through the development and use of a custom-built, demountable, microfluidic-incubator and a FTIR microscope coupled to a focal plane array (FPA) detector and a synchrotron light source. The combined system maximizes ease of use by allowing a user to perform standard cell culture techniques and experimental manipulation outside of the microfluidic-incubator, where assembly can be done just before the start of experimentation. The microfluidic-incubator provides an optimal path length of 6-8 µm and a submillimeter working distance in order to obtain FTIR images with 0.54-0.77 µm pixel resolution. In addition, we demonstrate a novel method for the correction of spectral distortions caused by varying concentrations of water over a subconfluent field of cells. Lastly, we use the microfluidic-incubator and time-lapsed FTIR imaging to determine the misfolding pathway of mutant copper-zinc superoxide dismutase (SOD1), the protein known to be a cause of familial amyotrophic lateral sclerosis (FALS).

Dynamic full-field infrared imaging with multiple synchrotron beams.

Microspectroscopic imaging in the infrared (IR) spectral region allows for the examination of spatially resolved chemical composition on the microscale. More than a decade ago, it was demonstrated that diffraction-limited spatial resolution can be achieved when an apertured, single-pixel IR microscope is coupled to the high brightness of a synchrotron light source. Nowadays, many IR microscopes are equipped with multipixel Focal Plane Array (FPA) detectors, which dramatically improve data acquisition times for imaging large areas. Recently, progress been made toward efficiently coupling synchrotron IR beamlines to multipixel detectors, but they utilize expensive and highly customized optical schemes. Here we demonstrate the development and application of a simple optical configuration that can be implemented on most existing synchrotron IR beamlines to achieve full-field IR imaging with diffraction-limited spatial resolution. Specifically, the synchrotron radiation fan is extracted from the bending magnet and split into four beams that are combined on the sample, allowing it to fill a large section of the FPA. With this optical configuration, we are able to oversample an image by more than a factor of 2, even at the shortest wavelengths, making image restoration through deconvolution algorithms possible. High chemical sensitivity, rapid acquisition times, and superior signal-to-noise characteristics of the instrument are demonstrated. The unique characteristics of this setup enabled the real-time study of heterogeneous chemical dynamics with diffraction-limited spatial resolution for the first time.

FTIR spectroscopic imaging of protein aggregation in living cells.

Protein misfolding and aggregation are the hallmark of a number of diseases including Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and the prion diseases. In all cases, a naturally-occurring protein misfolds and forms aggregates that are thought to disrupt cell function through a wide range of mechanisms that are yet to be fully unraveled. Fourier transform infrared (FTIR) spectroscopy is a technique that is sensitive to the secondary structure of proteins and has been widely used to investigate the process of misfolding and aggregate formation. This review focuses on how FTIR spectroscopy and spectroscopic microscopy are being used to evaluate the structural changes in disease-related proteins both in vitro and directly within cells and tissues. Finally, ongoing technological advances will be presented that are enabling time-resolved FTIR imaging of protein aggregation directly within living cells, which can provide insight into the structural intermediates, time scale, and mechanisms of cell toxicity associated with aggregate formation. This article is part of a Special Issue entitled: FTIR in membrane proteins and peptide studies.

Comparison of unrestrained plethysmography and forced oscillation for identifying genetic variability of airway responsiveness in inbred mice.

Lung function detection in mice is currently most accurately measured by invasive techniques, which are costly, labor intensive, and terminal. This limits their use for large-scale or longitudinal studies. Noninvasive assays are often used instead, but their accuracy for measuring lung function parameters such as resistance and elastance has been questioned in studies involving small numbers of mouse strains. Here we compared parameters detected by two different methods using 29 inbred mouse strains: enhanced pause (Penh), detected by unrestrained plethysmography, and central airway resistance and lung elastance, detected by a forced oscillation technique. We further tested whether the phenotypic variations were determined by the same genomic location in genome-wide association studies using a linear mixed model algorithm. Penh, resistance, and elastance were measured in nonexposed mice or mice exposed to saline and increasing doses of aerosolized methacholine. Because Penh differed from airway resistance in several strains and because the peak genetic associations found for Penh, resistance, or elastance were located at different genomic regions, we conclude that using Penh as an indicator for lung function changes in high-throughput genetic studies (i.e., genome-wide association studies or quantitative trait locus studies) measures something fundamentally different than airway resistance and lung elastance.

Discovery of novel allosteric modulators of metabotropic glutamate receptor subtype 5 reveals chemical and functional diversity and in vivo activity in rat behavioral models of anxiolytic and antipsychotic activity.

Modulators of metabotropic glutamate receptor subtype 5 (mGluR5) may provide novel treatments for multiple central nervous system (CNS) disorders, including anxiety and schizophrenia. Although compounds have been developed to better understand the physiological roles of mGluR5 and potential usefulness for the treatment of these disorders, there are limitations in the tools available, including poor selectivity, low potency, and limited solubility. To address these issues, we developed an innovative assay that allows simultaneous screening for mGluR5 agonists, antagonists, and potentiators. We identified multiple scaffolds that possess diverse modes of activity at mGluR5, including both positive and negative allosteric modulators (PAMs and NAMs, respectively). 3-Fluoro-5-(3-(pyridine-2-yl)-1,2,4-oxadiazol-5-yl)benzonitrile (VU0285683) was developed as a novel selective mGluR5 NAM with high affinity for the 2-methyl-6-(phenylethynyl)-pyridine (MPEP) binding site. VU0285683 had anxiolytic-like activity in two rodent models for anxiety but did not potentiate phencyclidine-induced hyperlocomotor activity. (4-Hydroxypiperidin-1-yl)(4-phenylethynyl)phenyl)methanone (VU0092273) was identified as a novel mGluR5 PAM that also binds to the MPEP site. VU0092273 was chemically optimized to an orally active analog, N-cyclobutyl-6-((3-fluorophenyl)ethynyl)nicotinamide hydrochloride (VU0360172), which is selective for mGluR5. This novel mGluR5 PAM produced a dose-dependent reversal of amphetamine-induced hyperlocomotion, a rodent model predictive of antipsychotic activity. Discovery of structurally and functionally diverse allosteric modulators of mGluR5 that demonstrate in vivo efficacy in rodent models of anxiety and antipsychotic activity provide further support for the tremendous diversity of chemical scaffolds and modes of efficacy of mGluR5 ligands. In addition, these studies provide strong support for the hypothesis that multiple structurally distinct mGluR5 modulators have robust activity in animal models that predict efficacy in the treatment of CNS disorders.

CGDSNPdb: a database resource for error-checked and imputed mouse SNPs.

The Center for Genome Dynamics Single Nucleotide Polymorphism Database (CGDSNPdb) is an open-source value-added database with more than nine million mouse single nucleotide polymorphisms (SNPs), drawn from multiple sources, with genotypes assigned to multiple inbred strains of laboratory mice. All SNPs are checked for accuracy and annotated for properties specific to the SNP as well as those implied by changes to overlapping protein-coding genes. CGDSNPdb serves as the primary interface to two unique data sets, the 'imputed genotype resource' in which a Hidden Markov Model was used to assess local haplotypes and the most probable base assignment at several million genomic loci in tens of strains of mice, and the Affymetrix Mouse Diversity Genotyping Array, a high density microarray with over 600,000 SNPs and over 900,000 invariant genomic probes. CGDSNPdb is accessible online through either a web-based query tool or a MySQL public login. Database URL: http://cgd.jax.org/cgdsnpdb/

Mouse BMD quantitative trait loci show improved concordance with human genome-wide association loci when recalculated on a new, common mouse genetic map.

Bone mineral density (BMD) is a heritable trait, and in mice, over 100 quantitative trait loci (QTLs) have been reported, but candidate genes have been identified for only a small percentage. Persistent errors in the mouse genetic map have negatively affected QTL localization, spurring the development of a new, corrected map. In this study, QTLs for BMD were remapped in 11 archival mouse data sets using this new genetic map. Since these QTLs all were mapped in a comparable way, direct comparisons of QTLs for concordance would be valid. We then compared human genome-wide association study (GWAS) BMD loci with the mouse QTLs. We found that 26 of the 28 human GWAS loci examined were located within the confidence interval of a mouse QTL. Furthermore, 14 of the GWAS loci mapped to within 3 cM of a mouse QTL peak. Lastly, we demonstrated that these newly remapped mouse QTLs can substantiate a candidate gene for a human GWAS locus, for which the peak single-nucleotide polymorphism (SNP) fell in an intergenic region. Specifically, we suggest that MEF2C (human chromosome 5, mouse chromosome 13) should be considered a candidate gene for the genetic regulation of BMD. In conclusion, use of the new mouse genetic map has improved the localization of mouse BMD QTLs, and these remapped QTLs show high concordance with human GWAS loci. We believe that this is an opportune time for a renewed effort by the genetics community to identify the causal variants regulating BMD using a synergistic mouse-human approach.

Quantitative trait locus analysis using J/qtl.

Quantitative trait locus (QTL) analysis is a statistical method to link phenotypes with regions of the genome that affect the phenotypes in a mapping population. R/qtl is a powerful statistical program commonly used for analyzing rodent QTL crosses, but R/qtl is a command line program that can be difficult for novice users to run. J/qtl was developed as an R/qtl graphical user interface that enables even novice users to utilize R/qtl for QTL analyses. In this chapter, we describe the process for analyzing rodent cross data with J/qtl, including data formatting, data quality control, main scan QTL analysis, pair scan QTL analysis, and multiple regression modeling; this information should enable new users to identify QTL affecting phenotypes of interest within their rodent cross datasets.

In vitro efficiency and mechanistic role of indocyanine green as photodynamic therapy agent for human melanoma.

BACKGROUND: Photodynamic therapy (PDT) is a promising treatment for superficial cancer. However, poor therapeutic results have been reported for melanoma, due to the high melanin content. Indocyanine green (ICG) has near infrared absorption (700-800 nm) and melanins do not absorb strongly in this area. This study explores the efficiency of ICG as a PDT agent for human melanoma, and its mechanistic role in the cell death pathway. METHODS: Human skin melanoma cells (Sk-Mel-28) were incubated with ICG and exposed to a low power Ti:Sapphire laser. Synchrotron-assisted Fourier transform infrared microspectroscopy and hierarchical cluster analysis were used to assess the cell damage and changes in lipid, protein, and nucleic acids. The cell death pathway was determined by analysis of cell viability and apoptosis and necrosis markers. RESULTS: In the cell death pathway, (1)O(2) generation evoked rapid multiple consequences that trigger apoptosis after laser exposure for only 15 min including the release of cytochrome c, the activation of total caspases, caspase-3, and caspase-9, the inhibition of NF-kappaB P65, and the enhancement of DNA fragmentation, and histone acetylation. CONCLUSION: ICG/PDT can efficiently and rapidly induce apoptosis in human melanoma cells and it can be considered as a new therapeutic approach for topical treatment of melanoma.

Genetic analysis of blood pressure in 8 mouse intercross populations.

The genetic basis of hypertension is well established, yet very few genes that cause common forms of hypertension are known. Quantitative trait locus (QTL) analyses in rodent models can guide the search for human hypertension genes, but the excellent genetic resources for mice have been underused in this regard. To address this issue, we surveyed blood pressure variation in mice from 37 inbred strains and generated 2577 mice in 8 intercross populations to perform QTL analyses of blood pressure. We identified 14 blood pressure QTL in these populations, including > or =7 regions of the mouse genome not linked previously to blood pressure. Many QTL were detected in multiple crosses, either within our study or in studies published previously, which facilitates the use of bioinformatics methods to narrow the QTL and focus the search for candidate genes. The regions of the human genome that correspond to all but 1 of the 14 blood pressure QTL in mice are linked to blood pressure in humans, suggesting that these regions contain causal genes with a conserved role in blood pressure control. These results greatly expand our knowledge of the genomic regions underlying blood pressure regulation in mice and support future studies to identify the causal genes within these QTL intervals.

Discovery of molecular switches that modulate modes of metabotropic glutamate receptor subtype 5 (mGlu5) pharmacology in vitro and in vivo within a series of functionalized, regioisomeric 2- and 5-(phenylethynyl)pyrimidines.

We describe the synthesis and SAR of a series of analogues of the mGlu(5) partial antagonist 5-(phenylethynyl)pyrimidine. New molecular switches are identified that modulate the pharmacological activity of the lead compound. Slight structural modifications around the proximal pyrimidine ring change activity of the partial antagonist lead to that of potent and selective full negative allosteric modulators and positive allosteric modulators, which demonstrate in vivo efficacy in rodent models for anxiolytic and antipsychotic activity, respectively.

Synchrotron X-ray 2D and 3D elemental imaging of CdSe/ZnS quantum dot nanoparticles in Daphnia magna.

The potential toxicity of nanoparticles to aquatic organisms is of interest given that increased commercialization will inevitably lead to some instances of inadvertent environmental exposures. Cadmium selenide quantum dots (QDs) capped with zinc sulfide are used in the semiconductor industry and in cellular imaging. Their small size (<10 nm) suggests that they may be readily assimilated by exposed organisms. We exposed Daphnia magna to both red and green QDs and used synchrotron X-ray fluorescence to study the distribution of Zn and Se in the organism over a time period of 36 h. The QDs appeared to be confined to the gut, and there was no evidence of further assimilation into the organism. Zinc and Se fluorescence signals were highly correlated, suggesting that the QDs had not dissolved to any extent. There was no apparent difference between red or green QDs, i.e., there was no effect of QD size. 3D tomography confirmed that the QDs were exclusively in the gut area of the organism. It is possible that the QDs aggregated and were therefore too large to cross the gut wall.

Chronic phenethylamine hallucinogen treatment alters behavioral sensitivity to a metabotropic glutamate 2/3 receptor agonist.

Recent clinical studies in schizophrenic patients show that a selective agonist of group II metabotropic glutamate (mGlu) receptors has robust efficacy in treating positive and negative symptoms. Group II mGlu receptor agonists also modulate the in vivo activity of psychotomimetic drugs, reducing the ability of psychotomimetic hallucinogens to increase glutamatergic transmission. The use of mouse models provides an opportunity to investigate the dynamic action that mGlu2/3 receptors play in regulating the behavioral effects of hallucinogen-induced glutamatergic neurotransmission using genetic as well as pharmacological strategies. The current study sought to characterize the use of the two-lever drug discrimination paradigm in ICR (CD-1) mice, using the hallucinogenic 5-HT2A/2C receptor agonist (-)-2,5-dimethoxy-4-bromoamphetamine [(-)-DOB)] as a stimulus-producing drug. The (-)-DOB discriminative stimulus was dose-dependent, generalized to the hallucinogen lysergic acid diethylamide, and was potently blocked by the 5-HT2A receptor antagonist M100907. However, contrary to our prediction, the hallucinogen-induced discriminative stimulus was not regulated by mGlu2/3 receptors. In a series of follow-up studies using hallucinogen-induced head twitch response and phencyclidine-induced hyperlocomotion, it was additionally discovered that the repeated dosing regimen required for discrimination training attenuated the behavioral effects of the mGlu2/3 receptor agonist LY379268. Furthermore chronic studies, using a 14 day (-)-DOB treatment, confirmed that repeated hallucinogen treatment causes a loss of behavioral activity of mGlu2/3 receptors, likely resulting from persistent activation of mGlu2/3 receptors by a hallucinogen-induced hyperglutamatergic state.