Altering Cell-Cell Interaction in Prenatal Alcohol Exposure Models: Insight on Cell-Adhesion Molecules During Brain Development

Alcohol exposure during pregnancy disrupts the development of the brain and produces long lasting behavioral and cognitive impairments collectively known as Fetal Alcohol Spectrum Disorders (FASDs). FASDs are characterized by alterations in learning, working memory, social behavior and executive function. A large body of literature using preclinical prenatal alcohol exposure models reports alcohol-induced changes in architecture and activity in specific brain regions affecting cognition. While multiple putative mechanisms of alcohol’s long-lasting effects on morphology and behavior have been investigated, an area that has received less attention is the effect of alcohol on cell adhesion molecules (CAMs). The embryo/fetal development represents a crucial period for Central Nervous System (CNS) development during which the cell-cell interaction plays an important role. CAMs play a critical role in neuronal migration and differentiation, synaptic organization and function which may be disrupted by alcohol. In this review, we summarize the physiological structure and role of CAMs involved in brain development, review the current literature on prenatal alcohol exposure effects on CAM function in different experimental models and pinpoint areas needed for future study to better understand how CAMs may mediate the morphological, sensory and behavioral outcomes in FASDs.

Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment: an application case in Lima, Peru

We propose the use of variable resolution boundaries based on central Voronoi tessellations (CVTs) to spatially aggregate building exposure models for risk assessment to various natural hazards. Such a framework is especially beneficial when the spatial distribution of the considered hazards presents intensity measures with contrasting footprints and spatial correlations, such as in coastal environments. This work avoids the incorrect assumption that a single intensity value from hazards with low spatial correlation (e.g. tsunami) can be considered to be representative within large-sized geo-cells for physical vulnerability assessment, without, at the same time, increasing the complexity of the overall model. We present decoupled earthquake and tsunami scenario-based risk estimates for the residential building stock of Lima (Peru). We observe that earthquake loss models for far-field subduction sources are practically insensitive to the exposure resolution. Conversely, tsunami loss models and associated uncertainties depend on the spatial correlations of the hazard intensities as well as on the resolution of the exposure models. We note that for the portfolio located in the coastal area exposed to both perils in Lima, the ground shaking dominates the losses for lower-magnitude earthquakes, whilst tsunamis cause the most damage for larger-magnitude events. For the latter, two sets of existing empirical flow depth fragility models are used, resulting in large differences in the calculated losses. This study, therefore, raises awareness about the uncertainties associated with the selection of fragility models and spatial aggregation entities for exposure modelling and loss mapping.

The Residential Population Generator (RPGen): Parameterization of Residential, Demographic, and Physiological Data to Model Intraindividual Exposure, Dose, and Risk

Exposure to chemicals is influenced by associations between the individual’s location and activities as well as demographic and physiological characteristics. Currently, many exposure models simulate individuals by drawing distributions from population-level data or use exposure factors for single individuals. The Residential Population Generator (RPGen) binds US surveys of individuals and households and combines the population with physiological characteristics to create a synthetic population. In general, the model must be supported by internal consistency; i.e., values that could have come from a single individual. In addition, intraindividual variation must be representative of the variation present in the modeled population. This is performed by linking individuals and similar households across income, location, family type, and house type. Physiological data are generated by linking census data to National Health and Nutrition Examination Survey data with a model of interindividual variation of parameters used in toxicokinetic modeling. The final modeled population data parameters include characteristics of the individual’s community (region, state, urban or rural), residence (size of property, size of home, number of rooms), demographics (age, ethnicity, income, gender), and physiology (body weight, skin surface area, breathing rate, cardiac output, blood volume, and volumes for body compartments and organs). RPGen output is used to support user-developed chemical exposure models that estimate intraindividual exposure in a desired population. By creating profiles and characteristics that determine exposure, synthetic populations produced by RPGen increases the ability of modelers to identify subgroups potentially vulnerable to chemical exposures. To demonstrate application, RPGen is used to estimate exposure to Toluene in an exposure modeling case example.

Experimental Induction of Tenacibaculosis in Atlantic Salmon (Salmo salar L.) Using Tenacibaculum maritimum, T. dicentrarchi, and T. finnmarkense

There is a limited understanding of the pathogenesis of tenacibaculosis in Atlantic salmon (Salmo salar L.) and there are few reproducible exposure models for comparison. Atlantic salmon were exposed via bath to Tenacibaculum maritimum, T. dicentrarchi, or T. finnmarkense, and were then grouped with naïve cohabitants. Mortalities had exaggerated clinical signs of mouthrot, a presentation of tenacibaculosis characterized by epidermal ulceration and yellow plaques, on the mouth and less frequently on other tissues. Histopathology showed tissue spongiosis, erosion, ulceration, and necrosis ranging from mild to marked, locally to regionally extensive with mats of intralesional bacteria on the rostrum, vomer, gill rakers, gill filaments, and body surface. Exposure to T. maritimum resulted in less than a 0.4 probability of survival for both exposed and cohabitants until Day 21. Exposures to T. dicentrarchi resulted in 0 and 0.55 (exposed), and 0.8 and 0.9 (cohabitant) probability of survival to Day 12 post-exposure, while T. finnmarkense had a 0.9 probability of survival to Day 12 for all groups. This experimental infection model will be useful to further investigate the pathogenesis of tenacibaculosis, its treatment, and immunity to Tenacibaculum species.

Regional based exposure models to account for local building typologies

The development of building inventory is a fundamental step for the evaluation of the seismic risk at territorial scale. Census data are usually employed for building inventory in large scale application and their use requires suitable rules to assign buildings typologies to vulnerability classes, that is an exposure model specific for the considered vulnerability model. Several exposure models are developed proposing class assignment rules that are calibrated on building typological data available from post-earthquake survey data. However, this approach has the drawback of being based on data from specific geographic areas that have been hit by damaging earthquakes. Indeed, the distribution of building typologies can vary greatly for different areas of a country and the diffusion of one building’s typology rather than another one may depend on the availability of construction material in the area, the evolution of construction techniques and the codes in force at the time of construction. This paper aims to improve the exposure modelling at regional scale, investigating the variability of masonry building typologies distribution. It proposes a methodology to recalibrate the exposure models at regional scale and evaluates the influence of the improved characterization of regional vulnerability on damage and risk assessment. The study shows that the analysis of local building typologies may strongly impact on the evaluation of the seismic risk at territorial scale.

An Examination of Stress Generation and Stress Exposure Models in Relation to Symptoms of Borderline Personality Disorder

Research examining life stress as a precipitant, co-occurrence, and consequence of psychopathology often has implications for two explanatory models: stress exposure, where stress causes symptoms, and stress generation, where symptoms cause stress. Preliminary evidence suggests that both processes are evident in borderline personality disorder (BPD). The present study examined 101 adults who self-reported at least three symptoms of BPD at prescreen, with 30% of the sample meeting full diagnostic criteria for BPD. Cross-lagged panel analyses were used to examine the relationships between BPD symptomatology and four forms of life stress. Stress exposure and stress generation were not supported for either form of chronic life stress. Results supported stress generation in both dependent and interpersonal episodic life stress, and stress exposure for interpersonal episodic life stress. These findings evidenced small effects only. Findings point to the impact of interpersonal stress on changes in symptomatology over time.

Predictors of Osprey Nest Success In A Highly Urbanized Environment

ABSTRACT Ospreys (Pandion haliaetus) are adaptable fish-eating raptors that readily nest on artificial structures in heavily human-dominated areas. Although the Osprey is a well-studied species, few researchers have investigated the factors that influence nest success and productivity in an urban environment. We monitored Osprey nests from 2013 to 2017 in highly urbanized Pinellas County, located on the west coast of central Florida, USA. We used logistic exposure models to assess the effects of timing of nesting, nest attributes (nest substrate, height), and landscape-level variables (inter-nest distance, distance to water, and surrounding habitat type) on daily survival rate (DSR) of Osprey nests. The number of active nests (i.e., nests with eggs) in the study area ranged from 53 in 2013 to 79 in 2016, with an overall total of 329 during the 5-yr study. Although most nests produced at least one young near fledging age, 131 of the nests failed. We attributed 45% of nest failures to storm events and 50% to unknown causes. The best logistic exposure model specification included only two variables: the discrete variable representing the date incubation started and the nominal variable indicating the year 2015. Osprey nests initiated earlier in the season were more likely to survive, and later nests (initiated after 22 April) averaged only one fledgling each. Osprey nests in 2015 had the highest DSR and relatively few failed due to storms. Our results supported previous research indicating that early nesters were more successful than late nesters. Our results also indicate that storms may play a role in nest success of Ospreys in Florida. Other variables, such as the amount of urbanized land surrounding Osprey nests did not appear to influence nest survival, indicating that Ospreys can be productive even in highly urban environments.

Quantifying the short-term effects of air pollution on health in the presence of exposure measurement error: a simulation study of multi-pollutant model results

Background Most epidemiological studies estimate associations without considering exposure measurement error. While some studies have estimated the impact of error in single-exposure models we aimed to quantify the effect of measurement error in multi-exposure models, specifically in time-series analysis of PM2.5, NO2, and mortality using simulations, under various plausible scenarios for exposure errors. Measurement error in multi-exposure models can lead to effect transfer where the effect estimate is overestimated for the pollutant estimated with more error to the one estimated with less error. This complicates interpretation of the independent effects of different pollutants and thus the relative importance of reducing their concentrations in air pollution policy. Methods Measurement error was defined as the difference between ambient concentrations and personal exposure from outdoor sources. Simulation inputs for error magnitude and variability were informed by the literature. Error-free exposures with their consequent health outcome and error-prone exposures of various error types (classical/Berkson) were generated. Bias was quantified as the relative difference in effect estimates of the error-free and error-prone exposures. Results Mortality effect estimates were generally underestimated with greater bias observed when low ratios of the true exposure variance over the error variance were assumed (27.4% underestimation for NO2). Higher ratios resulted in smaller, but still substantial bias (up to 19% for both pollutants). Effect transfer was observed indicating that less precise measurements for one pollutant (NO2) yield more bias, while the co-pollutant (PM2.5) associations were found closer to the true. Interestingly, the sum of single-pollutant model effect estimates was found closer to the summed true associations than those from multi-pollutant models, due to cancelling out of confounding and measurement error bias. Conclusions Our simulation study indicated an underestimation of true independent health effects of multiple exposures due to measurement error. Using error parameter information in future epidemiological studies should provide more accurate concentration-response functions.

Novel Mouse Models of Fungal Asthma

Alternaria alternata is a ubiquitous fungus and a major allergen associated with the development of asthma. Inhalation of intact spores is the primary cause of human exposure to fungal allergen. However, allergen-rich cultured fungal filtrates are oftentimes used in the current models of fungal sensitization that do not fully reflect real-life exposures. Thus, establishing novel spore exposure models is imperative. In this study, we established novel fungal exposure models of both adult and neonate to live spores. We examined pathophysiological changes in the spore models as compared to the non-exposure controls and also to the conventional filtrate models. While both Alternaria filtrate- and spore-exposed adult BALB/c mice developed elevated airway hyperresponsiveness (AHR), filtrates induced a greater IgE mediated response and higher broncholavage eosinophils than spores. In contrast, the mice exposed to Alternaria spores had higher numbers of neutrophils. Both exposures induced comparable levels of lung tissue inflammation and mucous cell metaplasia (MCM). In the neonatal model, exposure to Alternaria spores resulted in a significant increase of AHR in both adult and neonatal mice. Increased levels of IgE in both neonatal and adult mice exposed to spores was associated with increased eosinophilia in the treatment groups. Adult demonstrated increased numbers of lymphocytes that was paralleled by increased IgG1 production. Both adults and neonates demonstrated similarly increased eosinophilia, IgE, tissue inflammation and MCM.