An Integrated Agent-Based Framework for Assessing Air Pollution Impacts

Air pollution has considerable impact on human health and the wellbeing. Thus many regions of the world have established air pollution standards to ensure a minimum level of air quality. Precise assessment of the health and socio-economic impacts of air pollution is, however, a complex task;indeed, methods based within an epidemiological tradition generally underestimate human risk of exposure to polluted air. In this study, we introduce an agent-based modeling approach to ascertaining the impact of changes in particulate matter (PM10) on mortality and frequency of hospital visits in the greater metropolitan region of Sydney, Australia. Our modeling approach simulates human movement and behavioral patterns in order to obtain an accurate estimate of individual exposure to a pollutant. Results of our analysis indicate that a 50% reduction in PM10 levels (relative to the baseline) could considerably lower mortality, respiratory hospital admissions and emergency room visits leading to reduced pressure on health care sector costs and placing lower stress on emergency medical facilities. Our analysis also highlights the continued need to avoid significant increases in air pollution in Sydney so that associated health impacts, including health care costs, do not increase.

Multilevel complexity of calcium signaling:Modeling angiogenesis

Intracellular calcium signaling is a universal,evolutionary conserved and versatile regulator of cell biochemistry.The complexity of calcium signaling and related cell machinery can be investigated by the use of experimental strategies,as well as by computational approaches.Vascular endothelium is a fascinating model to study the specific properties and roles of calcium signals at multiple biological levels.During the past 20 years,live cell imaging,patch clamp and other techniques have allowed us to detect and interfere with calcium signaling in endothelial cells(ECs),providing a huge amount of information on the regulation of vascularization(angiogenesis) in normal and tumoral tissues.These data range from the spatiotemporal dynamics of calcium within different cell microcompartments to those in entire multicellular and organized EC networks.Beside experimental strategies,in silico endothelial models,specifically designed for simulating calcium signaling,are contributing to our knowledge of vascular physiol-ogy and pathology.They help to investigate and predict the quantitative features of proangiogenic events moving through subcellular,cellular and supracellular levels.This review focuses on some recent developments of computational approaches for proangiogenic endothelial calcium signaling.In particular,we discuss the creation of hybrid simulation environments,which combine and integrate discrete Cellular Potts Models.They are able to capture the phenomenological mechanisms of cell morphological reorganization,migration,and intercellular adhesion,with single-cell spatiotemporal models,based on reaction-diffusion equations that describe the agonist-induced intracellular calcium events.

Modulating arousal to overcome gait impairments in Parkinson’s disease:how the noradrenergic system may act as a double-edged sword

In stressful or anxiety-provoking situations,most people with Parkinson’s disease(PD)experience a general worsening of motor symptoms,including their gait impairments.However,a proportion of patients actually report benefits from experiencing-or even purposely inducing-stressful or high-arousal situations.Using data from a large-scale international survey study among 4324 people with PD and gait impairments within the online Fox Insight(USA)and ParkinsonNEXT(NL)cohorts,we demonstrate that individuals with PD deploy an array of mental state alteration strategies to cope with their gait impairment.Crucially,these strategies differ along an axis of arousal-some act to heighten,whereas others diminish,overall sympathetic tone.Together,our observations suggest that arousal may act as a double-edged sword for gait control in PD.We propose a theoretical,neurobiological framework to explain why heightened arousal can have detrimental effects on the occurrence and severity of gait impairments in some individuals,while alleviating them in others.Specifically,we postulate that this seemingly contradictory phenomenon is explained by the inherent features of the ascending arousal system:namely,that arousal is related to task performance by an inverted u-shaped curve(the so-called Yerkes and Dodson relationship).We propose that the noradrenergic locus coeruleus plays an important role in modulating PD symptom severity and expression,by regulating arousal and by mediating network-level functional integration across the brain.The ability of the locus coeruleus to facilitate dynamic‘cross-talk’between distinct,otherwise largely segregated brain regions may facilitate the necessary cerebral compensation for gait impairments in PD.In the presence of suboptimal arousal,compensatory networks may be too segregated to allow for adequate compensation.Conversely,with supraoptimal arousal,increased cross-talk between competing inputs of these complementary networks may emerge and become dysfunctional.Because the locus coeruleus degenerates with disease progression,finetuning of this delicate balance becomes increasingly difficult,heightening the need for mental strategies to self-modulate arousal and facilitate shifting from a sub-or supraoptimal state of arousal to improve gait performance.Recognition of this underlying mechanism emphasises the importance of PD-specific rehabilitation strategies to alleviate gait disability.

Discriminative predation： Simultaneous and sequential encounter experiments

There are many situations in which the ability of animals to distinguish between two similar looking objects can have significant selective consequences. For example, the objects that require discrimination may be edible versus defended prey, predators versus non-predators, or mates of varying quality. Working from the premise that there are situations in which discrimi- nation may be more or less successful, we hypothesized that individuals find it more difficult to distinguish between stimuli when they encounter them sequentially rather than simultaneously. Our study has wide biological and psychological implications from the perspective of signal perception, signal evolution, and discrimination, and could apply to any system where individuals are making relative judgments or choices between two or more stimuli or signals. While this is a general principle that might seem intuitive, it has not been experimentally tested in this context, and is often not considered in the design of models or experiments, or in the interpretation of a wide range of studies. Our study is different from previous studies in psychology in that a） the level of similarity of stimuli are gradually varied to obtain selection gradients, and b） we discuss the implications of our study for specific areas in ecology, such as the level of perfection of mimicry in predator-prey systems. Our experiments provide evidence that it is indeed more difficult to distinguish between stimuli - and to learn to distinguish between stimuli - when they are encountered sequentially rather than simultaneously, even if the intervening time interval is short .

Social networks improve leaderless group navigation by facilitating long-distance communication

Group navigation is of great importance for many animals, such as migrating flocks of birds or shoals of fish. One theory states that group membership can improve navigational accuracy compared to limited or less accurate individual naviga- tional ability in groups without leaders （＂Many-wrongs principle＂）. Here, we simulate leaderless group navigation that includes social connections as preferential interactions between individuals. Our results suggest that underlying social networks can reduce navigational errors of groups and increase group cohesion. We use network summary statistics, in particular network motifs, to study which characteristics of networks lead to these improvements. It is networks in which preferences between individuals are not clustered, but spread evenly across the group that are advantageous in group navigation by effectively enhancing long-distance information exchange within groups. We suggest that our work predicts a base-line for the type of social structure we might expect to find in group-living animals that navigate without leaders