Systematic Review on Fractal Dimension of the Retinal Vasculature in Neurodegeneration and Stroke: Assessment of a Potential Biomarker.

Introduction: Ocular manifestations in several neurological pathologies accentuate the strong relationship between the eye and the brain. Retinal alterations in particular can serve as surrogates for cerebral changes. Offering a "window to the brain," the transparent eye enables non-invasive imaging of these changes in retinal structure and vasculature. Fractal dimension (FD) reflects the overall complexity of the retinal vasculature. Changes in FD could reflect subtle changes in the cerebral vasculature that correspond to preclinical stages of neurodegenerative diseases. In this review, the potential of this retinal vessel metric to serve as a biomarker in neurodegeneration and stroke will be explored. Methods: A literature search was conducted, following the PRISMA Statement 2009 criteria, in four large bibliographic databases (Pubmed, Embase, Web Of Science and Cochrane Library) up to 12 October 2019. Articles have been included based upon their relevance. Wherever possible, level of evidence (LOE) has been assessed by means of the Oxford Centre for Evidence-based Medicine Level of Evidence classification. Results: Twenty-one studies were included for qualitative synthesis. We performed a narrative synthesis and produced summary tables of findings of included papers because methodological heterogeneity precluded a meta-analysis. A significant association was found between decreased FD and neurodegenerative disease, mainly addressing cognitive impairment (CI) and dementia. In acute, subacute as well as chronic settings, decreased FD seems to be associated with stroke. Differences in FD between subtypes of ischemic stroke remain unclear. Conclusions: This review provides a summary of the scientific literature regarding the association between retinal FD and neurodegenerative disease and stroke. Central pathology is associated with a decreased FD, as a measure of microvascular network complexity. As retinal FD reflects the global integrity of the cerebral microvasculature, it is an attractive parameter to explore. Despite obvious concerns, mainly due to a lack of methodological standardization, retinal FD remains a promising non-invasive and low-cost diagnostic biomarker for neurodegenerative and cerebrovascular disease. Before FD can be implemented in clinic as a diagnostic biomarker, the research community should strive for uniformization and standardization.

Assessing multimedia/multipathway exposures to inorganic arsenic at population and individual level using MERLIN-Expo.

In this study, we report on model simulations performed using the newly developed exposure tool, MERLIN-Expo, in order to assess inorganic arsenic (iAs) exposure to adults resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed to estimate external iAs exposure as well as the toxicologically relevant As (tAs, i.e., iAs, MMA and DMA) body burden in adults living in the vicinity of the former industrial sites as compared to adults living in adjacent areas and a reference area. Two scenarios are discussed: a first scenario studying exposure to iAs at the aggregated population level and a second scenario studying exposure at the individual level for a random sub-sample of subjects in each of the three different study areas. These two scenarios only differ in the type of human related input data (i.e., time-activity data, ingestion rates and consumption patterns) that were used, namely averages (incl. probability density functions, PDFs) in the simulation at population level and subject-specific values in the simulation at individual level. The model predictions are shown to be lower than the corresponding biomonitoring data from the monitoring campaign. Urinary tAs levels in adults, irrespective of the area they lived in, were under-predicted by MERLIN-Expo by 40% on average. The model predictions for individual adults, by contrast, under-predict the biomonitoring data by 7% on average, but with more important under-predictions for subjects at the upper end of exposure. Still, average predicted urinary tAs levels from the simulations at population level and at individual level overlap, and, at least for the current case, lead to similar conclusions. These results constitute a first and partial verification of the model performance of MERLIN-Expo when dealing with iAs in a complex site-specific exposure scenario, and demonstrate the robustness of the modelling tool for these situations.

Multimedia & PBPK modelling with MERLIN-Expo versus biomonitoring for assessing Pb exposure of pre-school children in a residential setting.

This paper reports on a case study - conducted within the European FP7 project "4FUN" - focusing on exposure of pre-school children to lead resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed and simulated with the MERLIN-Expo tool to estimate external Pb exposure as well as the Pb body burden in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area. Simulations were run for several scenarios ranging from very simple to rather complex in order to study the effect of different simulation approaches (e.g., deterministic vs. probabilistic, individual vs. aggregated population exposure) and different exposure scenarios (e.g., with vs. without considering local food consumption or time activity patterns) on the model outcomes (predicted concentrations of Pb in environmental and human matrices). This paper discusses the two most complex scenarios, namely exposure at the aggregated population level and at the individual level for a random sub-sample of subjects, respectively. In the final and most realistic exposure scenario, simulating individual lead exposure, model predictions were shown to be higher than the biomonitoring data. Blood Pb levels in children, irrespective of the area they lived in, were overpredicted by MERLIN-Expo with a factor of about 2 on average. The model predictions for individual children overlap with the prediction interval calculated by MERLIN-Expo based on population averages, demonstrating the use of probabilistic approaches in risk assessment. While these results constitute a first verification of the model performance of MERLIN-Expo dealing with inorganic pollutants in a complex real-world exposure scenario and a demonstration of the robustness of the modelling tool, further validation and benchmarking efforts are required for a larger number of inorganic pollutants and different exposure settings.

Environmental hazard and risk characterisation of petroleum substances: a guided "walking tour" of petroleum hydrocarbons.

Petroleum substances are used in large quantities, primarily as fuels. They are complex mixtures whose major constituents are hydrocarbons derived from crude oil by distillation and fractionation. Determining the complete molecular composition of petroleum and its refined products is not feasible with current analytical techniques because of the huge number of molecular components. This complex nature of petroleum products, with their varied number of constituents, all of them exhibiting different fate and effect characteristics, merits a dedicated hazard and risk assessment approach. From a regulatory perspective they pose a great challenge in a number of REACH processes, in particular in the context of dossier and substance evaluation but also for priority setting activities. In order to facilitate the performance of hazard and risk assessment for petroleum substances the European oil company association, CONCAWE, has developed the PETROTOX and PETRORISK spreadsheet models. Since the exact composition of many petroleum products is not known, an underlying assumption of the PETROTOX and PETRORISK tools is that the behaviour and fate of a total petroleum substance can be simulated based on the physical-chemical properties of representative structures mapped to hydrocarbon blocks (HBs) and on the relative share of each HB in the total mass of the product. To assess how differing chemical compositions affect the simulated chemical fate and toxicity of hydrocarbon mixtures, a series of model simulations were run using an artificial petroleum substance, containing 386 (PETROTOX) or 160 (PETRORISK) HBs belonging to different chemical classes and molecular weight ranges, but with equal mass assigned to each of them. To this artificial petroleum substance a guided series of subsequent modifications in mass allocation to a delineated number of HBs belonging to different chemical classes and carbon ranges was performed, in what we perceived as a guided "walking tour" through the chemical space of petroleum substances. We show that the PETROTOX and PETRORISK predictions reflect changes in mass distribution introduced to selected HBs by affecting hazard and risk estimates in correspondence with what is expected based on physical-chemical properties of individual constituents in the corresponding HBs.

A risk-based methodology for ranking environmental chemical stressors at the regional scale.

A "Risk-based Tool for the Regional Ranking of Environmental Chemical Stressors" has been developed, aimed at supporting decision-makers in the identification of priority environmental contaminants, as well as priority areas, to be further assessed. The tool implements a methodology based on a quantitative Weight-of-Evidence approach, integrating three types of information, identified as "Lines-of-Evidence" (LoE), namely: LoE "Environmental Contamination" (including data on chemical contamination in environmental matrices in the region, thus providing information on potential population exposure), LoE "Intake" (including results from human biomonitoring studies, i.e. concentration of chemicals in human biological matrices, thus providing an integrated estimation of exposure) and LoE "Observed Effects" (including information on the incidence of adverse health outcomes associated with environmental exposure to chemicals). A Multi-Criteria Decision Analysis (MCDA) methodology based on fuzzy logic has been developed to support the integration of information related to these three LoEs for each chemical stressor. The tool allows one to rank chemical stressors at different spatial scales, such as at the regional level as well as within each sub-area (e.g., counties). Moreover, it supports the identification of priority sub-areas within the region, where environmental and health data suggest possible adverse health effects and thus more investigation efforts are needed. To evaluate the performance of this newly developed tool, a case-study in the Flemish region (north of Belgium) has been selected. In the case-study, data on soil contamination by metals and organic contaminants were integrated with data on exposure and effect biomarkers measured in adolescents within the framework of the human biomonitoring study performed by the Flemish Centre of Expertise on Environment and Health in the period 2002-2006. The case-study demonstrated the performance of the tool in integrating qualitative and quantitative data with expert judgement for the identification of priority contaminants and areas. The proposed approach proved to be flexible, allowing for the incorporation of individual decision-maker's preferences, and, at the same time, to be transparent since all assumptions and value attributions are traceable.