Clinical application of image‐based CFD for cerebral aneurysms

During the last decade, the convergence of medical imaging and computational modeling technologies has enabled tremendous progress in the development and application of image‐based computational fluid dynamics modeling of patient‐specific blood flows. These techniques have been used for studying the basic mechanisms involved in the initiation and progression of vascular diseases, for studying possible ways to improve the diagnosis and evaluation of patients by incorporating hemodynamics information to the anatomical data typically available, and for the development of computational tools that can be used to improve surgical and endovascular treatment planning. However, before these technologies can have a significant impact on the routine clinical practice, it is still necessary to demonstrate the connection between the extra information provided by the models and the natural progression of vascular diseases and the outcome of interventions. This paper summarizes some of our contributions in this direction, focusing in particular on cerebral aneurysms

Formal modeling and analysis of cognitive agent behavior

From an external perspective, cognitive agent behavior can be described by specifying (temporal) correlations of a certain complexity between stimuli (input states) and (re)actions (output states) of the agent. From an internal perspective the agent’s dynamics can be characterized by direct (causal) temporal relations between internal and mental states of the agent. The latter type of specifications can be represented in a relatively simple, executable format, which enables different types of analysis of the agent’s behavior. In particular, simulations of the agent’s behavior under different (environmental) circumstances can be explored. Furthermore, by applying verification techniques, automated analysis of the consequences of the agent’s behavior can be carried out. To enable such types of analysis when only given an external behavioral specification, this has to be transformed first into some type of executable format. An automated procedure for such a transformation is proposed in this paper. The application of the transformation procedure is demonstrated for a number of cases, showing examples of the types of analysis as mentioned for different forms of behavior

Imaging of Hereditary Hemorrhagic Telangiectasia

This pictorial review is based on our experience of the follow-up of 120 patients at our multidisciplinary center for hereditary hemorrhagic telangiectasia (HHT). Rendu-Osler-Weber disease or HHT is a multiorgan autosomal dominant disorder with high penetrance, characterized by epistaxis, mucocutaneous telangiectasis, and visceral arteriovenous malformations (AVMs). The research on gene mutations is fundamental and family screening by clinical examination, chest X-ray, research of pulmonary shunting, and abdominal color Doppler sonography is absolutely necessary. The angioarchitecture of pulmonary AVMs can be studied by unenhanced multidetector computed tomography; however, all other explorations of liver, digestive bowels, or brain require administration of contrast media. Magnetic resonance angiography is helpful for central nervous system screening, in particular for the spinal cord, but also for pulmonary, hepatic, and pelvic AVMs. Knowledge of the multiorgan involvement of HHT, mechanism of complications, and radiologic findings is fundamental for the correct management of these patients

Increasing the Depth of Current Understanding: Sensitivity Testing of Deep-Sea Larval Dispersal Models for Ecologists

Larval dispersal is an important ecological process of great interest to conservation and the establishment of marine protected areas. Increasing numbers of studies are turning to biophysical models to simulate dispersal patterns, including in the deep-sea, but for many ecologists unassisted by a physical oceanographer, a model can present as a black box. Sensitivity testing offers a means to test the models' abilities and limitations and is a starting point for all modelling efforts. The aim of this study is to illustrate a sensitivity testing process for the unassisted ecologist, through a deep-sea case study example, and demonstrate how sensitivity testing can be used to determine optimal model settings, assess model adequacy, and inform ecological interpretation of model outputs. Five input parameters are tested (timestep of particle simulator (TS), horizontal (HS) and vertical separation (VS) of release points, release frequency (RF), and temporal range (TR) of simulations) using a commonly employed pairing of models. The procedures used are relevant to all marine larval dispersal models. It is shown how the results of these tests can inform the future set up and interpretation of ecological studies in this area. For example, an optimal arrangement of release locations spanning a release area could be deduced; the increased depth range spanned in deep-sea studies may necessitate the stratification of dispersal simulations with different numbers of release locations at different depths; no fewer than 52 releases per year should be used unless biologically informed; three years of simulations chosen based on climatic extremes may provide results with 90% similarity to five years of simulation; and this model setup is not appropriate for simulating rare dispersal events. A step-by-step process, summarising advice on the sensitivity testing procedure, is provided to inform all future unassisted ecologists looking to run a larval dispersal simulation

Cross-frequency coupling of brain oscillations in studying motivation and emotion

Research has shown that brain functions are realized by simultaneous oscillations in various frequency bands. In addition to examining oscillations in pre-specified bands, interactions and relations between the different frequency bandwidths is another important aspect that needs to be considered in unraveling the workings of the human brain and its functions. In this review we provide evidence that studying interdependencies between brain oscillations may be a valuable approach to study the electrophysiological processes associated with motivation and emotional states. Studies will be presented showing that amplitude-amplitude coupling between delta-alpha and delta-beta oscillations varies as a function of state anxiety and approach-avoidance-related motivation, and that changes in the association between delta-beta oscillations can be observed following successful psychotherapy. Together these studies suggest that cross-frequency coupling of brain oscillations may contribute to expanding our understanding of the neural processes underlying motivation and emotion

Plasma ACE2 predicts outcome of COVID-19 in hospitalized patients

AimsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to angiotensin converting enzyme 2 (ACE2) enabling entrance of the virus into cells and causing the infection termed coronavirus disease of 2019 (COVID-19). Here, we investigate associations between plasma ACE2 and outcome of COVID-19.Methods and resultsThis analysis used data from a large longitudinal study of 306 COVID-19 positive patients and 78 COVID-19 negative patients (MGH Emergency Department COVID-19 Cohort). Comprehensive clinical data were collected on this cohort, including 28-day outcomes. The samples were run on the Olink® Explore 1536 platform which includes measurement of the ACE2 protein. High admission plasma ACE2 in COVID-19 patients was associated with increased maximal illness severity within 28 days with OR = 1.8, 95%-CI: 1.4-2.3 (P ConclusionThis study suggests that measuring plasma ACE2 is potentially valuable in predicting COVID-19 outcomes. Further, ACE2 could be a link between COVID-19 illness severity and its established risk factors hypertension, pre-existing heart disease and pre-existing kidney disease

Woodland Recovery after Suppression of Deer: Cascade effects for Small Mammals, Wood Mice (Apodemus sylvaticus) and Bank Voles (Myodes glareolus)

Over the past century, increases in both density and distribution of deer species in the Northern Hemisphere have resulted in major changes in ground flora and undergrowth vegetation of woodland habitats, and consequentially the animal communities that inhabit them. In this study, we tested whether recovery in the vegetative habitat of a woodland due to effective deer management (from a peak of 0.4–1.5 to <0.17 deer per ha) had translated to the small mammal community as an example of a higher order cascade effect. We compared deer-free exclosures with neighboring open woodland using capture-mark-recapture (CMR) methods to see if the significant difference in bank vole (Myodes glareolus) and wood mouse (Apodemus sylvaticus) numbers between these environments from 2001–2003 persisted in 2010. Using the multi-state Robust Design method in program MARK we found survival and abundance of both voles and mice to be equivalent between the open woodland and the experimental exclosures with no differences in various metrics of population structure (age structure, sex composition, reproductive activity) and individual fitness (weight), although the vole population showed variation both locally and temporally. This suggests that the vegetative habitat - having passed some threshold of complexity due to lowered deer density - has allowed recovery of the small mammal community, although patch dynamics associated with vegetation complexity still remain. We conclude that the response of small mammal communities to environmental disturbance such as intense browsing pressure can be rapidly reversed once the disturbing agent has been removed and the vegetative habitat is allowed to increase in density and complexity, although we encourage caution, as a source/sink dynamic may emerge between old growth patches and the recently disturbed habitat under harsh conditions