Optimal COVID-19 testing strategy on limited resources.

The last three years have been spent combating COVID-19, and governments have been seeking optimal solutions to minimize the negative impacts on societies. Although two types of testing have been performed for this-follow-up testing for those who had close contact with infected individuals and mass-testing of those with symptoms-the allocation of resources has been controversial. Mathematical models such as the susceptible, infectious, exposed, recovered, and dead (SEIRD) model have been developed to predict the spread of infection. However, these models do not consider the effects of testing characteristics and resource limitations. To determine the optimal testing strategy, we developed a testing-SEIRD model that depends on testing characteristics and limited resources. In this model, people who test positive are admitted to the hospital based on capacity and medical resources. Using this model, we examined the infection spread depending on the ratio of follow-up and mass-testing. The simulations demonstrated that the infection dynamics exhibit an all-or-none response as infection expands or extinguishes. Optimal and worst follow-up and mass-testing combinations were determined depending on the total resources and cost ratio of the two types of testing. Furthermore, we demonstrated that the cumulative deaths varied significantly by hundreds to thousands of times depending on the testing strategy, which is encouraging for policymakers. Therefore, our model might provide guidelines for testing strategies in the cases of recently emerging infectious diseases.

A Wnt5 Activity Asymmetry and Intercellular Signaling via PCP Proteins Polarize Node Cells for Left-Right Symmetry Breaking.

Polarization of node cells along the anterior-posterior axis of mouse embryos is responsible for left-right symmetry breaking. How node cells become polarized has remained unknown, however. Wnt5a and Wnt5b are expressed posteriorly relative to the node, whereas genes for Sfrp inhibitors of Wnt signaling are expressed anteriorly. Here we show that polarization of node cells is impaired in Wnt5a-/-Wnt5b-/- and Sfrp mutant embryos, and also in the presence of a uniform distribution of Wnt5a or Sfrp1, suggesting that Wnt5 and Sfrp proteins act as instructive signals in this process. The absence of planar cell polarity (PCP) core proteins Prickle1 and Prickle2 in individual cells or local forced expression of Wnt5a perturbed polarization of neighboring wild-type cells. Our results suggest that opposing gradients of Wnt5a and Wnt5b and of their Sfrp inhibitors, together with intercellular signaling via PCP proteins, polarize node cells along the anterior-posterior axis for breaking of left-right symmetry.

The role of short-term depression in sustained neural activity in the prefrontal cortex: a simulation study.

Recent experimental researches have suggested that sustained neural activity in the prefrontal cortex is a process of memory retention in decision making. Previous theoretical studies indicate that a balance between recurrent excitation and feedback inhibition is important for sustaining the activity. To investigate a plausible balancing mechanism, we simulated a biophysically realistic network model. Our model shows that short-term depression (STD) enables the network to sustain its activity despite the presence of long-term inhibition by GABA(B) receptors and that the sustained firing rates have a bell-shaped dependence on the degree of STD. By analyzing the neural network dynamics, we show that the bell-shaped dependence on STD is formed by destabilizing the balance with either excessive or insufficient STD. We also show that the optimal degree of STD has a linear relationship with the neural network size. These results suggest that STD provides a balancing mechanism and controls levels of sustained activities of various size networks.

Multi-phasic bi-directional chemotactic responses of the growth cone.

The nerve growth cone is bi-directionally attracted and repelled by the same cue molecules depending on the situations, while other non-neural chemotactic cells usually show uni-directional attraction or repulsion toward their specific cue molecules. However, how the growth cone differs from other non-neural cells remains unclear. Toward this question, we developed a theory for describing chemotactic response based on a mathematical model of intracellular signaling of activator and inhibitor. Our theory was first able to clarify the conditions of attraction and repulsion, which are determined by balance between activator and inhibitor, and the conditions of uni- and bi-directional responses, which are determined by dose-response profiles of activator and inhibitor to the guidance cue. With biologically realistic sigmoidal dose-responses, our model predicted tri-phasic turning response depending on intracellular Ca2+ level, which was then experimentally confirmed by growth cone turning assays and Ca2+ imaging. Furthermore, we took a reverse-engineering analysis to identify balanced regulation between CaMKII (activator) and PP1 (inhibitor) and then the model performance was validated by reproducing turning assays with inhibitions of CaMKII and PP1. Thus, our study implies that the balance between activator and inhibitor underlies the multi-phasic bi-directional turning response of the growth cone.