In Situ Characterization of Bioaerosols at the Single-Particle Level Using Single-Particle Mass Spectrometry: A Promising Tool for Defending Human Health against Bioaerosol Transmission.

Bioaerosol transmission is one of the important transmission pathways of COVID-19 and other infectious respiratory diseases caused by viral infection. The ability to detect bioaerosols and characterize encapsulated pathogens both in situ and in real time is crucial for early warning and monitoring of the progress of an epidemic or pandemic. The lack of a powerful analytical tool for distinguishing between bioaerosols and nonbioaerosols as well as for identification of pathogen species contained in the bioaerosols is the bottleneck in related fields. Herein, a promising solution for in situ and real-time accurate and sensitive detection of bioaeorosols is proposed by integrating single-particle aerosol mass spectrometry, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, and fluorescence spectroscopy. The proposed mass spectrometry aims at detecting bioaerosols in a range of 0.5-10 µm with adequate sensitivity and specificity. This single-particle bioaerosol mass spectrometry would not only be a powerful tool that can be useful for the authorities and public health monitoring but also would be an example of advances in mass spectrometry.

Heterogeneous deposition of regular and mentholated little cigar smoke in the lungs of Sprague-Dawley rats.

BACKGROUND: Quantifying the dose and distribution of tobacco smoke in the respiratory system is critical for understanding its toxicity, addiction potential, and health impacts. Epidemiologic studies indicate that the incidence of lung tumors varies across different lung regions, suggesting there may be a heterogeneous deposition of smoke particles leading to greater health risks in specific regions. Despite this, few studies have examined the lobar spatial distribution of inhaled particles from tobacco smoke. This gap in knowledge, coupled with the growing popularity of little cigars among youth, underscores the need for additional research with little cigars. RESULTS: In our study, we analyzed the lobar deposition in rat lungs of smoke particles from combusted regular and mentholated Swisher Sweets little cigars. Twelve-week-old male and female Sprague-Dawley rats were exposed to smoke particles at a concentration of 84 ± 5 mg/m3 for 2 h, after which individual lung lobes were examined. We utilized Inductively Coupled Plasma Mass Spectrometry to quantify lobar chromium concentrations, serving as a smoke particle tracer. Our findings demonstrated an overall higher particle deposition from regular little cigars than from the mentholated ones. Higher particle deposition fraction was observed in the left and caudal lobes than other lobes. We also observed sex-based differences in the normalized deposition fractions among lobes. Animal study results were compared with the multi-path particle dosimetry (MPPD) model predictions, which showed that the model overestimated particle deposition in certain lung regions. CONCLUSIONS: Our findings revealed that the particle deposition varied between different little cigar products. The results demonstrated a heterogenous deposition pattern, with higher particle deposition observed in the left and caudal lobes, especially with the mentholated little cigars. Additionally, we identified disparities between our measurements and the MPPD model. This discrepancy highlights the need to enhance the accuracy of models before extrapolating animal study results to human lung deposition. Overall, our study provides valuable insights for estimating the dose of little cigars during smoking for toxicity research.

Emulating Near-Roadway Exposure to Traffic-Related Air Pollution via Real-Time Emissions from a Major Freeway Tunnel System.

Epidemiological and toxicological studies continue to demonstrate correlative and causal relationships between exposure to traffic-related air pollution and various metrics of adverse pulmonary, cardiovascular, and neurological health effects. The key challenge for in vivo studies is replicating real-world, near-roadway exposure dynamics in laboratory animal models that mimic true human exposures. The advantage of animal models is the accelerated time scales to show statistically significant physiological and/or behavioral response. This work describes a novel exposure facility adjacent to a major freeway tunnel system that provides a platform for real-time chronic exposure studies. The primary conclusion is that particulate matter (PM) concentrations at this facility are routinely well below the National Ambient Air Quality Standards (NAAQS), but studies completed to date still demonstrate significant neurological and cardiovascular effects. Internal combustion engines produce large numbers of ultrafine particles that contribute negligible mass to the atmosphere relative to NAAQS regulated PM2.5 but have high surface area and mobility in the body. It is posited here that current federal and state air quality standards are thus insufficient to fully protect human health, most notably the developing and aging brain, due to regulatory gaps for ultrafine particles.

Improving quantitative analysis of spark-induced breakdown spectroscopy: Multivariate calibration of metal particles using machine learning.

We have recently developed a low-cost spark-induced breakdown spectroscopy (SIBS) instrument for in-situ analysis of toxic metal aerosol particles that we call TARTA (toxic-metal aerosol real time analyzer). In this work, we applied machine learning methods to improve the quantitative analysis of elemental mass concentrations measured by this instrument. Specifically, we applied least absolute shrinkage and selection operator (LASSO), partial least squares (PLS) regression, principal component regression (PCR), and support vector regression (SVR) to develop multivariate calibration models for 13 metals (e.g., Cr, Cu, Mn, Fe, Zn, Co, Al, K, Be, Hg, Cd, Pb, and Ni), some of which are included on the US EPA hazardous air pollutants (HAPS) list. The calibration performance, adjusted coefficient of determination (R2) and normalized root mean square error (RMSE), and limit of detection (LOD) of the proposed models were compared to those of univariate calibration models for each analyte. Our results suggest that machine learning models tend to have better prediction accuracy and lower LODs than conventional univariate calibration, of which the LASSO approach performs the best with R2 > 0.8 and LODs of 40-170 ng m-3 at a sampling time of 30 min and a flow rate of 15 l min -1. We then assessed the applicability of the LASSO model for quantifying elemental concentrations in mixtures of these metals, serving as independent validation datasets. Ultimately, the LASSO model developed in this work is a very promising machine learning approach for quantifying mass concentration of metals in aerosol particles using TARTA.

The performance of an inexpensive spark-induced breakdown spectroscopy instrument for near real-time analysis of toxic metal particles.

To meet the demand for identifying and controlling toxic air contaminants in environmental justice communities, we have recently developed a cost-effective spark-induced breakdown spectroscopy (SIBS) instrument for detecting and quantifying toxic metal air pollutants. We characterized the detection limit and linearity of this SIBS instrument by analyzing nebulized elemental standard solutions. The experimental parameters affecting SIBS performance were optimized, including the time delay to observation, the distance between electrodes, and the ablation voltage. The instrument successfully detected Cr, Cu, Mn, Fe, Zn, Co, and Ni, with limits of detection ranged from 0.05 µg m-3 to 0.81 µg m-3 at a flow rate of 15 l min-1 and a 30 min sampling duration. Similar to other investigations using ion breakdown spectroscopy, we did not observe strong emissions lines for As, Sb, Se, Hg, Pb, and Cd, which were likely due to spectral overlap, matrix effects, and the limited detection range of the optical components. Overall, SIBS is a promising technique for field measurements of toxic metals for environmental justice, industrial and urban applications.

Architecture of the rat nephron-arterial network: analysis with micro-computed tomography.

Among solid organs, the kidney's vascular network stands out, because each nephron has two distinct capillary structures in series and because tubuloglomerular feedback, one of the mechanisms responsible for blood flow autoregulation, is specific to renal tubules. Tubuloglomerular feedback and the myogenic mechanism, acting jointly, autoregulate single-nephron blood flow. Each generates a self-sustained periodic oscillation and an oscillating electrical signal that propagates upstream along arterioles. Similar electrical signals from other nephrons interact, allowing nephron synchronization. Experimental measurements show synchronization over fields of a few nephrons; simulations based on a simplified network structure that could obscure complex interactions predict more widespread synchronization. To permit more realistic simulations, we made a cast of blood vessels in a rat kidney, performed micro-computed tomography at 2.5-µm resolution, and recorded three-dimensional coordinates of arteries, afferent arterioles, and glomeruli. Nonterminal branches of arcuate arteries form treelike structures requiring two to six bifurcations to reach terminal branches at the tree tops. Terminal arterial structures were either paired branches at the tops of the arterial trees, from which 52.6% of all afferent arterioles originated, or unpaired arteries not at the tree tops, yielding the other 22.9%; the other 24.5% originated directly from nonterminal arteries. Afferent arterioles near the corticomedullary boundary were longer than those farther away, suggesting that juxtamedullary nephrons have longer afferent arterioles. The distance separating origins of pairs of afferent arterioles varied randomly. The results suggest an irregular-network tree structure with vascular nodes, where arteriolar activity and local blood pressure interact.

Dynamic Mechanical Interactions Between Neighboring Airspaces Determine Cyclic Opening and Closure in Injured Lung.

OBJECTIVES: Positive pressure ventilation exposes the lung to mechanical stresses that can exacerbate injury. The exact mechanism of this pathologic process remains elusive. The goal of this study was to describe recruitment/derecruitment at acinar length scales over short-time frames and test the hypothesis that mechanical interdependence between neighboring lung units determines the spatial and temporal distributions of recruitment/derecruitment, using a computational model. DESIGN: Experimental animal study. SETTING: International synchrotron radiation laboratory. SUBJECTS: Four anesthetized rabbits, ventilated in pressure controlled mode. INTERVENTIONS: The lung was consecutively imaged at ~ 1.5-minute intervals using phase-contrast synchrotron imaging, at positive end-expiratory pressures of 12, 9, 6, 3, and 0 cm H2O before and after lavage and mechanical ventilation induced injury. The extent and spatial distribution of recruitment/derecruitment was analyzed by subtracting subsequent images. In a realistic lung structure, we implemented a mechanistic model in which each unit has individual pressures and speeds of opening and closing. Derecruited and recruited lung fractions (Fderecruited, Frecruited) were computed based on the comparison of the aerated volumes at successive time points. MEASUREMENTS AND MAIN RESULTS: Alternative recruitment/derecruitment occurred in neighboring alveoli over short-time scales in all tested positive end-expiratory pressure levels and despite stable pressure controlled mode. The computational model reproduced this behavior only when parenchymal interdependence between neighboring acini was accounted for. Simulations closely mimicked the experimental magnitude of Fderecruited and Frecruited when mechanical interdependence was included, while its exclusion gave Frecruited values of zero at positive end-expiratory pressure greater than or equal to 3 cm H2O. CONCLUSIONS: These findings give further insight into the microscopic behavior of the injured lung and provide a means of testing protective-ventilation strategies to prevent recruitment/derecruitment and subsequent lung damage.

Isotherm-based thermodynamic model for electrolyte and nonelectrolyte solutions incorporating long- and short-range electrostatic interactions.

The activities of solutes and solvents in solutions govern numerous physical phenomena in a wide range of practical applications. In prior work, we used statistical mechanics and multilayer adsorption isotherms to develop a transformative model for capturing thermodynamic properties of multicomponent aqueous solutions over the entire concentration range (Dutcher et al. J. Phys. Chem. 2011, 2012, 2013). That model needed only a few adsorption energy values to represent the solution thermodynamics of each solute. In the current work, we posit that the adsorption energies are due to dipole-dipole electrostatic forces in solute-solvent and solvent-solvent interactions. This hypothesis was tested in aqueous solutions on (a) 37 1:1 electrolytes, over a range of cation sizes, from H(+) to tetrabutylammonium, for common anions including Cl(-), Br(-), I(-), NO3(-), OH(-), ClO4(-), and (b) 20 water-soluble organic molecules including alcohols and polyols. For both electrolytes and organic solutions, the energies of adsorption can be calculated with the dipole moments of the solvent, molecular size of the solvent and solute, and the solvent-solvent and solvent-solute intermolecular bond lengths. Many of these physical properties are available in the literature, with the exception of the solute-solvent intermolecular bond lengths. For those, predictive correlations developed here enable estimation of solute and solvent solution activities for which there are little or no activity data.

Growth of Ammonium Bisulfate Clusters by Adsorption of Oxygenated Organic Molecules.

Quantum chemical calculations were employed to model the interactions of the [(NH4(+))4(HSO4(-))4] ammonium bisulfate cluster with one or more molecular products of monoterpene oxidation. A strong interaction was found between the bisulfate ion of this cluster and a carboxylic acid, aldehyde, or ketone functionality of the organic molecule. Free energies of adsorption for carboxylic acids were in the -70 to -73 kJ/mol range, while those for aldehydes and ketones were in the -46 to -50 kJ/mol range. These values suggest that a small ambient [(NH4(+))4(SO4(-))4]cluster is able to adsorb an oxygenated organic molecule. While adsorption of the first molecule is highly favorable, adsorption of subsequent molecules is less so, suggesting that sustained uptake of organic molecules does not occur, and thus is not a pathway for continuing growth of the cluster. This result is consistent with ambient measurements showing that particles below ∼1 nm grow slowly, while those above 1 nm grow at an increasing rate presumably due to a lower surface energy barrier enabling the uptake of organic molecules. This work provides insight into the molecular level interactions which affect sustained cluster growth by uptake of organic molecules.

Pulmonary inflammatory effects of source-oriented particulate matter from California's San Joaquin Valley.

The EPA regulates ambient particulate matter (PM) because substantial associations have been established between PM and health impacts. Presently, regulatory compliance involves broad control of PM emission sources based on mass concentration rather than chemical composition, although PM toxicity is likely to vary depending upon PM physicochemical properties. The overall objective of this study was to help inform source-specific PM emission control regulations. For the first time, source-oriented PM was collected from the atmosphere in Fresno, CA, onto 38 source/size substrates. Mice were exposed via oropharyngeal aspiration to equivalent mass doses [50 µg] of two size fractions: ultrafine (Dp < 0.17µm) and submicron fine (0.17 < Dp < 1 µm) during summer and winter seasons. At 24 hours post-exposure, cellular and biochemical indicators of pulmonary inflammation were evaluated in the bronchoalveolar lavage fluid. Significant inflammatory responses were elicited by vehicle, regional background, and cooking PM sources that were dependent on season and particle size. This is the first study of source-oriented toxicity of atmospheric PM and supports source-specific emissions control strategies.

Allergic airway inflammation is differentially exacerbated by daytime and nighttime ultrafine and submicron fine ambient particles: heme oxygenase-1 as an indicator of PM-mediated allergic inflammation.

Ambient particulate matter (PM) originates from a range of sources and differs in composition with respect to season, time of day, and particle size. In this study, ambient PM samples in the ultrafine and submicrometer fine range were tested for the potential to exacerbate a murine model of allergic airway inflammation when exposure occurs solely during allergic sensitization, but not during subsequent allergen challenge. Temporally resolved and size-segregated PM samples were used to understand how summer or winter, day or night, and ambient ultrafine and submicrometer fine particle size influence PM's ability to exacerbate allergic inflammation. PM was collected in urban Fresno, CA. BALB/c mice were exposed to PM and house dust mite allergen (HDM) via intranasal aspiration on d 1, 3, and 5. HDM challenge occurred on d 12-14, with inflammation assessed 24 h following final challenge. While season or particle size did not predict allergic inflammation, daytime ultrafine and submicrometer fine particles significantly increased total cellular inflammation, specifically lymphocyte and eosinophil infiltration, compared to allergic controls. Further studies examined PM-mediated changes within the lung during the period where allergen sensitization occurred by measuring direct effects of PM on pulmonary oxidative stress and inflammation. Pulmonary levels of heme oxygenase-1 (HO-1), a biomarker of oxidative stress, but not cellular inflammation, demonstrated a remarkable correlation with the degree of allergic inflammation in animals sensitized to allergen and PM concomitantly, suggesting acute PM-mediated HO-1 levels may serve as a predictive indicator of a particle's ability to exacerbate allergic airway inflammation.

Clearing the air: A systematic review of studies on air pollution and childhood brain outcomes to mobilize policy change.

Climate change, wildfires, and environmental justice concerns have drawn increased attention to the impact of air pollution on children's health and development. Children are especially vulnerable to air pollution exposure, as their brains and bodies are still developing. The objective of this systematic review was to synthesize available empirical evidence on the associations between air pollution exposure and brain outcomes in developmental samples (ages 0-18 years old). Studies were identified by searching the PubMed and Web of Science Core Collection databases and underwent a two-phase screening process before inclusion. 40 studies were included in the review, which included measures of air pollution and brain outcomes at various points in development. Results linked air pollution to varied brain outcomes, including structural volumetric and cortical thickness differences, alterations in white matter microstructure, functional network changes, metabolic and molecular effects, as well as tumor incidence. Few studies included longitudinal changes in brain outcomes. This review also suggests methodologies for incorporating air pollution measures in developmental cognitive neuroscience studies and provides specific policy recommendations to reduce air pollution exposure and promote healthy brain development by improving access to clean air.

Can lung airway geometry be used to predict autism? A preliminary machine learning-based study.

The goal of this study is to assess the feasibility of airway geometry as a biomarker for autism spectrum disorder (ASD). Chest computed tomography images of children with a documented diagnosis of ASD as well as healthy controls were identified retrospectively. Fifty-four scans were obtained for analysis, including 31 ASD cases and 23 controls. A feature selection and classification procedure using principal component analysis and support vector machine achieved a peak cross validation accuracy of nearly 89% using a feature set of eight airway branching angles. Sensitivity was 94%, but specificity was only 78%. The results suggest a measurable difference in airway branching angles between children with ASD and the control population.

Multinephron dynamics on the renal vascular network.

Tubuloglomerular feedback (TGF) and the myogenic mechanism combine in each nephron to regulate blood flow and glomerular filtration rate. Both mechanisms are nonlinear, generate self-sustained oscillations, and interact as their signals converge on arteriolar smooth muscle, forming a regulatory ensemble. Ensembles may synchronize. Smooth muscle cells in the ensemble depolarize periodically, generating electrical signals that propagate along the vascular network. We developed a mathematical model of a nephron-vascular network, with 16 versions of a single nephron model containing representations of both mechanisms in the regulatory ensemble, to examine the effects of network structure on nephron synchronization. Symmetry, as a property of a network, facilitates synchronization. Nephrons received blood from a symmetric electrically conductive vascular tree. Symmetry was created by using identical nephron models at each of the 16 sites and symmetry breaking by varying nephron length. The symmetric model achieved synchronization of all elements in the network. As little as 1% variation in nephron length caused extensive desynchronization, although synchronization was maintained in small nephron clusters. In-phase synchronization predominated among nephrons separated by one or three vascular nodes and antiphase synchronization for five or seven nodes of separation. Nephron dynamics were irregular and contained low-frequency fluctuations. Results are consistent with simultaneous blood flow measurements in multiple nephrons. An interaction between electrical signals propagated through the network to cause synchronization; variation in vascular pressure at vessel bifurcations was a principal cause of desynchronization. The results suggest that the vasculature supplies blood to nephrons but also engages in robust information transfer.

An isotherm-based thermodynamic model of multicomponent aqueous solutions, applicable over the entire concentration range.

In previous studies (Dutcher et al. J. Phys. Chem. C 2011, 115, 16474-16487; 2012, 116, 1850-1864), we derived equations for the Gibbs energy, solvent and solute activities, and solute concentrations in multicomponent liquid mixtures, based upon expressions for adsorption isotherms that include arbitrary numbers of hydration layers on each solute. In this work, the long-range electrostatic interactions that dominate in dilute solutions are added to the Gibbs energy expression, thus extending the range of concentrations for which the model can be used from pure liquid solute(s) to infinite dilution in the solvent, water. An equation for the conversion of the reference state for solute activity coefficients to infinite dilution in water has been derived. A number of simplifications are identified, notably the equivalence of the sorption site parameters r and the stoichiometric coefficients of the solutes, resulting in a reduction in the number of model parameters. Solute concentrations in mixtures conform to a modified Zdanovskii-Stokes-Robinson mixing rule, and solute activity coefficients to a modified McKay-Perring relation, when the effects of the long-range (Debye-Hückel) term in the equations are taken into account. Practical applications of the equations to osmotic and activity coefficients of pure aqueous electrolyte solutions and mixtures show both satisfactory accuracy from low to high concentrations, together with a thermodynamically reasonable extrapolation (beyond the range of measurements) to extreme concentration and to the pure liquid solute(s).

Predicting non-isometric fatigue induced by electrical stimulation pulse trains as a function of pulse duration.

BACKGROUND: Our previous model of the non-isometric muscle fatigue that occurs during repetitive functional electrical stimulation included models of force, motion, and fatigue and accounted for applied load but not stimulation pulse duration. Our objectives were to: 1) further develop, 2) validate, and 3) present outcome measures for a non-isometric fatigue model that can predict the effect of a range of pulse durations on muscle fatigue. METHODS: A computer-controlled stimulator sent electrical pulses to electrodes on the thighs of 25 able-bodied human subjects. Isometric and non-isometric non-fatiguing and fatiguing knee torques and/or angles were measured. Pulse duration (170-600 µs) was the independent variable. Measurements were divided into parameter identification and model validation subsets. RESULTS: The fatigue model was simplified by removing two of three non-isometric parameters. The third remained a function of other model parameters. Between 66% and 77% of the variability in the angle measurements was explained by the new model. CONCLUSION: Muscle fatigue in response to different stimulation pulse durations can be predicted during non-isometric repetitive contractions.

Interacting information streams on the nephron arterial network.

Blood flow and glomerular filtration in the kidney are regulated by two mechanisms acting on the afferent arteriole of each nephron. The two mechanisms operate as limit cycle oscillators, each responding to a different signal. The myogenic mechanism is sensitive to a transmural pressure difference across the wall of the arteriole, and tubuloglomerular feedback (TGF) responds to the NaCl concentration in tubular fluid flowing into the nephron's distal tubule,. The two mechanisms interact with each other, synchronize, cause oscillations in tubular flow and pressure, and form a bimodal electrical signal that propagates into the arterial network. The electrical signal enables nephrons adjacent to each other in the arterial network to synchronize, but non-adjacent nephrons do not synchronize. The arteries supplying the nephrons have the morphologic characteristics of a rooted tree network, with 3 motifs characterizing nephron distribution. We developed a model of 10 nephrons and their afferent arterioles in an arterial network that reproduced these structural characteristics, with half of its components on the renal surface, where experimental data suitable for model validation is available, and the other half below the surface, from which no experimental data has been reported. The model simulated several interactions: TGF-myogenic in each nephron with TGF modulating amplitude and frequency of the myogenic oscillation; adjacent nephron-nephron with strong coupling; non-adjacent nephron-nephron, with weak coupling because of electrical signal transmission through electrically conductive arterial walls; and coupling involving arterial nodal pressure at the ends of each arterial segment, and between arterial nodes and the afferent arterioles originating at the nodes. The model predicted full synchronization between adjacent nephrons pairs and partial synchronization among weakly coupled nephrons, reproducing experimental findings. The model also predicted aperiodic fluctuations of tubular and arterial pressures lasting longer than TGF oscillations in nephrons, again confirming experimental observations. The model did not predict complete synchronization of all nephrons.

Direct surface analysis of time-resolved aerosol impactor samples with ultrahigh-resolution mass spectrometry.

Aerosol particles in the atmosphere strongly influence the Earth's climate and human health, but the quantification of their effects is highly uncertain. The complex and variable composition of atmospheric particles is a main reason for this uncertainty. About half of the particle mass is organic material, which is very poorly characterized on a molecular level, and therefore it is challenging to identify sources and atmospheric transformation processes. We present here a new combination of techniques for highly time-resolved aerosol sampling using a rotating drum impactor (RDI) and organic chemical analysis using direct liquid extraction surface analysis (LESA) combined with ultrahigh-resolution mass spectrometry. This minimizes sample preparation time and potential artifacts during sample workup compared to conventional off-line filter or impactor sampling. Due to the high time resolution of about 2.5 h intensity correlations of compounds detected in the high-resolution mass spectra were used to identify groups of compounds with likely common sources or atmospheric history.

Hippocampal but Not Serum Cytokine Levels Are Altered by Traffic-Related Air Pollution in TgF344-AD and Wildtype Fischer 344 Rats in a Sex- and Age-Dependent Manner.

Epidemiological studies have demonstrated that air pollution is a significant risk factor for age-related dementia, including Alzheimer's disease (AD). It has been posited that traffic-related air pollution (TRAP) promotes AD neuropathology by exacerbating neuroinflammation. To test this hypothesis, serum and hippocampal cytokines were quantified in male and female TgF344-AD rats and wildtype (WT) Fischer 344 littermates exposed to TRAP or filtered air (FA) from 1 to 15 months of age. Luminex™ rat 23-cytokine panel assays were used to measure the levels of hippocampal and serum cytokines in 3-, 6-, 10-, and 15-month-old rats (corresponding to 2, 5, 9, and 14 months of exposure, respectively). Age had a pronounced effect on both serum and hippocampal cytokines; however, age-related changes in hippocampus were not mirrored in the serum and vice versa. Age-related changes in serum cytokine levels were not influenced by sex, genotype, or TRAP exposure. However, in the hippocampus, in 3-month-old TgF344-AD and WT animals, TRAP increased IL-1ß in females while increasing TNF ɑin males. In 6-month-old animals, TRAP increased hippocampal levels of M-CSF in TgF344-AD and WT females but had no significant effect in males. At 10 and 15 months of age, there were minimal effects of TRAP, genotype or sex on hippocampal cytokines. These observations demonstrate that TRAP triggers an early inflammatory response in the hippocampus that differs with sex and age and is not reflected in the serum cytokine profile. The relationship of TRAP effects on cytokines to disease progression remains to be determined.

Chronic exposure to traffic-related air pollution reduces lipid mediators of linoleic acid and soluble epoxide hydrolase in serum of female rats.

Chronic exposure to traffic-related air pollution (TRAP) is known to promote systemic inflammation, which is thought to underlie respiratory, cardiovascular, metabolic and neurological disorders. It is not known whether chronic TRAP exposure dampens inflammation resolution, the homeostatic process for stopping inflammation and repairing damaged cells. In vivo, inflammation resolution is facilitated by bioactive lipid mediators known as oxylipins, which are derived from the oxidation of polyunsaturated fatty acids. To understand the effects of chronic TRAP exposure on lipid-mediated inflammation resolution pathways, we measured total (i.e. free+bound) pro-inflammatory and pro-resolving lipid mediators in serum of female rats exposed to TRAP or filtered air (FA) for 14 months. Compared to rats exposed to FA, TRAP-exposed rats showed a significant 36-48% reduction in fatty acid alcohols, specifically, 9-hydroxyoctadecadienoic acid (9-HODE), 11,12-dihydroxyeicosatetraenoic acid (11,12-DiHETE) and 16,17-dihydroxydocosapentaenoic acid (16, 17-DiHDPA). The decrease in fatty acid diols (11,12-DiHETE and 16, 17-DiHDPA) corresponded to a significant 34-39% reduction in the diol to epoxide ratio, a marker of soluble epoxide hydrolase activity; this enzyme is typically upregulated during inflammation. The findings demonstrate that 14 months exposure to TRAP reduced pro-inflammatory 9-HODE concentration and dampened soluble epoxide hydrolase activation, suggesting adaptive immune changes in lipid mediator pathways involved in inflammation resolution.