A new algorithm to diagnose atrial ectopic origin from multi lead ECG systems - insights from 3D virtual human atria and torso

Rapid atrial arrhythmias such as atrial fibrillation (AF) predispose to ventricular arrhythmias, sudden cardiac death and stroke. Identifying the origin of atrial ectopic activity from the electrocardiogram (ECG) can help to diagnose the early onset of AF in a cost-effective manner. The complex and rapid atrial electrical activity during AF makes it difficult to obtain detailed information on atrial activation using the standard 12-lead ECG alone. Compared to conventional 12-lead ECG, more detailed ECG lead configurations may provide further information about spatio-temporal dynamics of the body surface potential (BSP) during atrial excitation. We apply a recently developed 3D human atrial model to simulate electrical activity during normal sinus rhythm and ectopic pacing. The atrial model is placed into a newly developed torso model which considers the presence of the lungs, liver and spinal cord. A boundary element method is used to compute the BSP resulting from atrial excitation. Elements of the torso mesh corresponding to the locations of the placement of the electrodes in the standard 12-lead and a more detailed 64-lead ECG configuration were selected. The ectopic focal activity was simulated at various origins across all the different regions of the atria. Simulated BSP maps during normal atrial excitation (i.e. sinoatrial node excitation) were compared to those observed experimentally (obtained from the 64-lead ECG system), showing a strong agreement between the evolution in time of the simulated and experimental data in the P-wave morphology of the ECG and dipole evolution. An algorithm to obtain the location of the stimulus from a 64-lead ECG system was developed. The algorithm presented had a success rate of 93%, meaning that it correctly identified the origin of atrial focus in 75/80 simulations, and involved a general approach relevant to any multi-lead ECG system. This represents a significant improvement over previously developed algorithms

Assessing the association between oral hygiene and preterm birth by quantitative light-induced fluorescence

The aim of this study was to investigate the purported link between oral hygiene and preterm birth by using image analysis tools to quantify dental plaque biofilm. Volunteers (η = 91) attending an antenatal clinic were identified as those considered to be “at high risk” of preterm delivery (i.e., a previous history of idiopathic preterm delivery, case group) or those who were not considered to be at risk (control group). The women had images of their anterior teeth captured using quantitative light-induced fluorescence (QLF). These images were analysed to calculate the amount of red fluorescent plaque (ΔR%) and percentage of plaque coverage. QLF showed little difference in ΔR% between the two groups, 65.00% case versus 68.70% control, whereas there was 19.29% difference with regard to the mean plaque coverage, 25.50% case versus 20.58% control. A logistic regression model showed a significant association between plaque coverage and case/control status (Ρ = 0.031), controlling for other potential predictor variables, namely, smoking status, maternal age, and body mass index (BMI)

Exploring the potential of using a text-based game to inform simulation models of risky migration decisions

Background: In this paper, we explore the potential of games to collect empirical data for informing agent-based simulation models of migration. To examine the usefulness of game-based approaches, we conducted a simple, yet carefully designed psychological experiment. Methods: In a preregistered study, we used a novel, immersive experimental setting to investigate the risky migration decisions made by migrants and non-migrants. Participants (284 migrants and 284 non-migrants) played a choice-based interactive fiction game—a fully text-based game where players progress by selecting from a list of possible actions—that involved making three risky migration decisions. In one condition, participants were shown a non-linear progress bar and explicit acknowledgements of the choices they made to promote perceived agency: the feeling that one’s actions have a non-trivial impact on the game. In the other condition, the progress bar was linear, and the explicit acknowledgements were omitted. Results: Our experimental manipulation was successful; participants in the former condition self-reported higher perceived agency than participants in the latter condition, as did migrants compared to non-migrants. Nevertheless, condition and migrant status did not meaningfully affect the risky migration decisions participants made in the game. Conclusion: These findings indicate that the results of generic studies on risky migration decisions conducted on non-migrants can potentially inform simulation models of migration. However, these findings were obtained from a single experiment, and thus warrant replication and further research before definitive conclusions can be drawn. Furthermore, a simple text-based game may be too superficial to allow deep insights into the idiosyncrasies of migration decision-making. This suggests a possible trade-off between clear interpretability of the results and the usefulness for informing simulation models of complex social processes, such as migration

Assessing the Association between Oral Hygiene and Preterm Birth by Quantitative Light-Induced Fluorescence

The aim of this study was to investigate the purported link between oral hygiene and preterm birth by using image analysis tools to quantify dental plaque biofilm. Volunteers ( = 91) attending an antenatal clinic were identified as those considered to be "at high risk" of preterm delivery (i.e., a previous history of idiopathic preterm delivery, case group) or those who were not considered to be at risk (control group). The women had images of their anterior teeth captured using quantitative light-induced fluorescence (QLF). These images were analysed to calculate the amount of red fluorescent plaque (Δ %) and percentage of plaque coverage. QLF showed little difference in Δ % between the two groups, 65.00% case versus 68.70% control, whereas there was 19.29% difference with regard to the mean plaque coverage, 25.50% case versus 20.58% control. A logistic regression model showed a significant association between plaque coverage and case/control status ( = 0.031), controlling for other potential predictor variables, namely, smoking status, maternal age, and body mass index (BMI)

Judgments of learning index relative confidence, not subjective probability

The underconfidence-with-practice (UWP) effect is a common finding in calibration studies concerned with judgments of learning (JOLs) elicited on a percentage scale. The UWP pattern is present when, in a procedure consisting of multiple study-test cycles, mean scale JOLs underestimate mean recall performance on cycle 2 and beyond. Although this pattern is present both for items recalled and unrecalled on the preceding cycle, to date research has concentrated mostly on the sources of UWP for the latter type of items. The present study aimed at bridging this gap. In three experiments, we examined calibration on the third of three cycles. The results of Experiment 1 demonstrated the typical pattern of higher recall and scale JOLs for previously recalled items compared to unrecalled ones. More important, they also revealed that even though the UWP effect was found for both items previously recalled once and twice, its magnitude was greater for the former class of items. Experiments 2 and 3, which employed a binary betting task and a binary 0/100% JOL task, respectively, demonstrated that people can accurately predict future recall for previously recalled items with binary decisions. In both experiments, the UWP effect was absent both for items recalled once and twice. We suggest that the sensitivity of scale JOLs, but not binary judgments, to the number of previous recall successes strengthens the claim of Hanczakowski, Zawadzka, Pasek, and Higham (2013) that scale JOLs reflect confidence in, rather than the subjective probability of, future recall

Modelling hair follicle growth dynamics as an excitable medium

The hair follicle system represents a tractable model for the study of stem cell behaviour in regenerative adult epithelial tissue. However, although there are numerous spatial scales of observation (molecular, cellular, follicle and multi follicle), it is not yet clear what mechanisms underpin the follicle growth cycle. In this study we seek to address this problem by describing how the growth dynamics of a large population of follicles can be treated as a classical excitable medium. Defining caricature interactions at the molecular scale and treating a single follicle as a functional unit, a minimal model is proposed in which the follicle growth cycle is an emergent phenomenon. Expressions are derived, in terms of parameters representing molecular regulation, for the time spent in the different functional phases of the cycle, a formalism that allows the model to be directly compared with a previous cellular automaton model and experimental measurements made at the single follicle scale. A multi follicle model is constructed and numerical simulations are used to demonstrate excellent qualitative agreement with a range of experimental observations. Notably, the excitable medium equations exhibit a wider family of solutions than the previous work and we demonstrate how parameter changes representing altered molecular regulation can explain perturbed patterns in Wnt over-expression and BMP down-regulation mouse models. Further experimental scenarios that could be used to test the fundamental premise of the model are suggested. The key conclusion from our work is that positive and negative regulatory interactions between activators and inhibitors can give rise to a range of experimentally observed phenomena at the follicle and multi follicle spatial scales and, as such, could represent a core mechanism underlying hair follicle growth

Quantified light-induced fluorescence, review of a diagnostic tool in prevention of oral disease

Diagnostic methods for the use in preventive dentistry are being developed continuously. Few of these find their way into general practice. Although the general trend in medicine is to focus on disease prevention and early diagnostics, in dentistry this is still not the case. Nevertheless, in dental research some of these methods seem to be promising for near future use by the general dental professional. In this paper an overview is given of a method called quantitative light-induced fluorescence or (QLF) in which visible and harmless light excites the teeth in the patient's mouth to produce fluorescent images, which can be stored on disk and computer analyzed. White spots (early dental caries) are detected and quantified as well as bacterial metabolites on and in the teeth. An overview of research to validate the technique and modeling to further the understanding of the technique by Monte Carlo simulation is given and it is shown that the fluorescence phenomena can be described by the simulation model in a qualitative way. A model describing the visibility of red fluorescence from within the dental tissue is added, as this was still lacking in current literature. An overview is given of the clinical images made with the system and of the extensive research which has been done. The QLF™ technology has been shown to be of importance when used in clinical trials with respect to the testing of toothpastes and preventive treatments. It is expected that the QLF™ technology will soon find its way into the general dental practice