Elongating, entwining, and dragging: mechanism for adaptive locomotion of tubificine worm blobs in a confined environment.

Worms often aggregate through physical connections and exhibit remarkable functions such as efficient migration, survival under environmental changes, and defense against predators. In particular, entangled blobs demonstrate versatile behaviors for their survival; they form spherical blobs and migrate collectively by flexibly changing their shape in response to the environment. In contrast to previous studies on the collective behavior of worm blobs that focused on locomotion in a flat environment, we investigated the mechanisms underlying their adaptive motion in confined environments, focusing on tubificine worm collectives. We first performed several behavioral experiments to observe the aggregation process, collective response to aversive stimuli, the motion of a few worms, and blob motion in confined spaces with and without pegs. We found the blob deformed and passed through a narrow passage using environmental heterogeneities. Based on these behavioral findings, we constructed a simple two-dimensional agent-based model wherein the flexible body of a worm was described as a cross-shaped agent that could deform, rotate, and translate. The simulations demonstrated that the behavioral findings were well-reproduced. Our findings aid in understanding how physical interactions contribute to generating adaptive collective behaviors in real-world environments as well as in designing novel swarm robotic systems consisting of soft agents.

Active-sensing-based decentralized control of autonomous mobile agents for quick and smooth collision avoidance.

There is an increasing demand for multi-agent systems in which each mobile agent, such as a robot in a warehouse or a flying drone, moves toward its destination while avoiding other agents. Although several control schemes for collision avoidance have been proposed, they cannot achieve quick and safe movement with minimal acceleration and deceleration. To address this, we developed a decentralized control scheme that involves modifying the social force model, a model of pedestrian dynamics, and successfully realized quick, smooth, and safe movement. However, each agent had to observe many nearby agents and predict their future motion; that is, unnecessary sensing and calculations were required for each agent. In this study, we addressed this issue by introducing active sensing. In this control scheme, an index referred to as the "collision risk level" is defined, and the observation range of each agent is actively controlled on this basis. Through simulations, we demonstrated that the proposed control scheme works reasonably while reducing unnecessary sensing and calculations.

An agent-based model of the interrelation between the COVID-19 outbreak and economic activities.

As of July 2020, COVID-19 caused by SARS-COV-2 is spreading worldwide, causing severe economic damage. While minimizing human contact is effective in managing outbreaks, it causes severe economic losses. Strategies to solve this dilemma by considering the interrelation between the spread of the virus and economic activities are urgently needed to mitigate the health and economic damage. Here, we propose an abstract agent-based model of the COVID-19 outbreak that accounts for economic activities. The computational simulation of the model recapitulates the trade-off between the health and economic damage associated with voluntary restraint measures. Based on the simulation results, we discuss how the macroscopic dynamics of infection and economics emerge from individuals' behaviours. We believe our model can serve as a platform for discussing solutions to the above-mentioned dilemma.

Impact of contrast-induced nephropathy and cardiovascular events by serum cystatin C in renal insufficiency patients undergoing cardiac catheterization.

We assessed the usefulness of serum cystatin C for predicting contrast-induced nephropathy (CIN) in patients (n = 100) undergoing coronary catheterization. After a 12-month follow-up, the incidence of CIN was 8.3% (n = 5) in patients with mild renal insufficiency (estimated glomerular filtration rate [eGFR] 60-89 mL/min per 1.73 m²), 34.4% (n = 10) in those with moderate renal insufficiency (eGFR 30-59 mL/min per 1.73 m²), and 100% (n = 3) in those with severe renal insufficiency (eGFR 15-29 mL/min per 1.73 m²). The sensitivity was 81.8% and specificity was 90.9% at the cutoff level of serum cystatin C >1.18 mg/L. Serum cystatin C levels were significantly (P < .001) higher in the patients with moderate renal insufficiency in the CIN group than those in the non-CIN group. Multivariate logistic regression analysis demonstrated that baseline serum cystatin C independently predicted short-term mortality (odds ratio [OR], 0.311; 95% confidence interval [CI] 0.058-0.538; P = .026). Baseline serum cystatin C significantly predicted the occurrence of CIN in the patients with moderate renal insufficiency.

Listeria endocarditis with acute thoracoabdominal aortic dissection.

The patient was 71-year-old male under treatment at a clinic for hypertension, aortic regurgitation, alcoholic hepatitis and dental treatment. He mainly complained fever and anorexia. Since blood culture examination revealed Listeria monocytogenes and echocardiography exhibited vegetation at the mitral leaflet, the patient was diagnosed as infective endocarditis. Fever and inflammatory reaction were improved after penicillin administration; however, he had fever on the 24th hospital day. CT revealed type IIIb acute thoracoabdominal aortic dissection which was not observed on admission. The blood pressure was controlled with antihypertensive agents. He could leave the hospital on the 61st day.