An evidence review of face masks against COVID-19.

The science around the use of masks by the public to impede COVID-19 transmission is advancing rapidly. In this narrative review, we develop an analytical framework to examine mask usage, synthesizing the relevant literature to inform multiple areas: population impact, transmission characteristics, source control, wearer protection, sociological considerations, and implementation considerations. A primary route of transmission of COVID-19 is via respiratory particles, and it is known to be transmissible from presymptomatic, paucisymptomatic, and asymptomatic individuals. Reducing disease spread requires two things: limiting contacts of infected individuals via physical distancing and other measures and reducing the transmission probability per contact. The preponderance of evidence indicates that mask wearing reduces transmissibility per contact by reducing transmission of infected respiratory particles in both laboratory and clinical contexts. Public mask wearing is most effective at reducing spread of the virus when compliance is high. Given the current shortages of medical masks, we recommend the adoption of public cloth mask wearing, as an effective form of source control, in conjunction with existing hygiene, distancing, and contact tracing strategies. Because many respiratory particles become smaller due to evaporation, we recommend increasing focus on a previously overlooked aspect of mask usage: mask wearing by infectious people ("source control") with benefits at the population level, rather than only mask wearing by susceptible people, such as health care workers, with focus on individual outcomes. We recommend that public officials and governments strongly encourage the use of widespread face masks in public, including the use of appropriate regulation.

Why and how the nematode's early embryogenesis can be precise and robust: a mechanical perspective.

The early embryogenesis in the nematode Caenorhabditis elegans is well-known for its stereotypic precision of cell arrangements and their lineage relationship. Much research has been focused on how biochemical processes achieve the highly reproducible cell lineage tree. However, the origin of the robustness in the cell arrangements is poorly understood. Here, we set out to provide a mechanistic explanation of how combining mechanical forces with the order and orientation of cell division ensures a robust arrangement of cells. We used a simplified mechanical model to simulate the arrangement of cells in the face of different disturbances. As a result, we revealed three fail-safe principles for cell self-organization in early nematode embryogenesis: ordering, simultaneity, and the division orientation of cell division events. Our work provides insight into the developmental strategy and contributes to the understanding of how robust or variable the cell arrangement can be in developing embryos.

Entropy Production of Nanosystems with Time Scale Separation.

Energy flows in biomolecular motors and machines are vital to their function. Yet experimental observations are often limited to a small subset of variables that participate in energy transport and dissipation. Here we show, through a solvable Langevin model, that the seemingly hidden entropy production is measurable through the violation spectrum of the fluctuation-response relation of a slow observable. For general Markov systems with time scale separation, we prove that the violation spectrum exhibits a characteristic plateau in the intermediate frequency region. Despite its vanishing height, the plateau can account for energy dissipation over a broad time scale. Our findings suggest a general possibility to probe hidden entropy production in nanosystems without direct observation of fast variables.

Modulating cell proliferation by asymmetric division: A conserved pattern in the early embryogenesis of nematode species.

In the early stage of the nematode Caenorhabditis elegans embryogenesis, the zygote divides asymmetrically into a symmetric fast lineage and an asymmetric slow lineage, producing 16 and 8 cells respectively almost at the same time, followed by the onset of gastrulation. It was recently reported that this cell division pattern is optimal for rapid cell proliferation. In this work, we compare the cell lineages of 9 nematode species, revealing that this pattern is conserved for >60 million years. It further suggests that such lineage design has an important functional role and it might speed up embryonic development in the nematode kingdom, not limited to C. elegans , and independent of the maternal-zygotic transition dynamics.

Stripe formation in bacterial systems with density-suppressed motility.

Engineered bacteria in which motility is reduced by local cell density generate periodic stripes of high and low density when spotted on agar plates. We study theoretically the origin and mechanism of this process in a kinetic model that includes growth and density-suppressed motility of the cells. The spreading of a region of immotile cells into an initially cell-free region is analyzed. From the calculated front profile we provide an analytic ansatz to determine the phase boundary between the stripe and the no-stripe phases. The influence of various parameters on the phase boundary is discussed.

Volume segregation programming in a nematode's early embryogenesis.

Nematode species are well-known for their invariant cell lineage pattern during development. Combining knowledge about the fate specification induced by asymmetric division and the anti-correlation between cell cycle length and cell volume in Caenorhabditis elegans, we propose a minimal model to simulate lineage initiation by altering cell volume segregation ratio in each division, and quantify the derived pattern's performance in proliferation speed, fate diversity, and space robustness. The stereotypic pattern in C. elegans embryo is found to be one of the most optimal solutions taking minimum time to achieve the cell number before gastrulation, by programming asymmetric divisions as a strategy.

Harnessing peak transmission around symptom onset for non-pharmaceutical intervention and containment of the COVID-19 pandemic.

Within a short period of time, COVID-19 grew into a world-wide pandemic. Transmission by pre-symptomatic and asymptomatic viral carriers rendered intervention and containment of the disease extremely challenging. Based on reported infection case studies, we construct an epidemiological model that focuses on transmission around the symptom onset. The model is calibrated against incubation period and pairwise transmission statistics during the initial outbreaks of the pandemic outside Wuhan with minimal non-pharmaceutical interventions. Mathematical treatment of the model yields explicit expressions for the size of latent and pre-symptomatic subpopulations during the exponential growth phase, with the local epidemic growth rate as input. We then explore reduction of the basic reproduction number R0 through specific transmission control measures such as contact tracing, testing, social distancing, wearing masks and sheltering in place. When these measures are implemented in combination, their effects on R0 multiply. We also compare our model behaviour to the first wave of the COVID-19 spreading in various affected regions and highlight generic and less generic features of the pandemic development.

Attenuation of transcriptional bursting in mRNA transport.

Because of the stochastic nature of biochemical processes, the copy number of any given type of molecule inside a living cell often exhibits large temporal fluctuations. Here, we develop analytic methods to investigate how the noise arising from a bursting input is reshaped by a transport reaction which is either linear or of the Michaelis-Menten type. A slow transport rate smoothes out fluctuations at the output end and minimizes the impact of bursting on the downstream cellular activities. In the context of gene expression in eukaryotic cells, our results indicate that transcriptional bursting can be substantially attenuated by the transport of mRNA from nucleus to cytoplasm. Saturation of the transport mediators or nuclear pores contributes further to the noise reduction. We suggest that the mRNA transport should be taken into account in the interpretation of relevant experimental data on transcriptional bursting.

Emergence of collective oscillations in adaptive cells.

Collective oscillations of cells in a population appear under diverse biological contexts. Here, we establish a set of common principles by categorising the response of individual cells against a time-varying signal. A positive intracellular signal relay of sufficient gain from participating cells is required to sustain the oscillations, together with phase matching. The two conditions yield quantitative predictions for the onset cell density and frequency in terms of measured single-cell and signal response functions. Through mathematical constructions, we show that cells that adapt to a constant stimulus fulfil the phase requirement by developing a leading phase in an active frequency window that enables cell-to-signal energy flow. Analysis of dynamical quorum sensing in several cellular systems with increasing biological complexity reaffirms the pivotal role of adaptation in powering oscillations in an otherwise dissipative cell-to-cell communication channel. The physical conditions identified also apply to synthetic oscillatory systems.

Finite-size scaling of synchronized oscillation on complex networks.

The onset of synchronization in a system of random frequency oscillators coupled through a random network is investigated. Using a mean-field approximation, we characterize sample-to-sample fluctuations for networks of finite size, and derive the corresponding scaling properties in the critical region. For scale-free networks with the degree distribution P(k) approximately k(-gamma) at large k, we found that the finite-size exponent nu takes on the value 5/2 when gamma>5, the same as in the globally coupled Kuramoto model. For highly heterogeneous networks (3

Designability and cooperative folding in a four-letter hydrophobic-polar model of proteins.

The two-letter hydrophobic-polar (HP) model of Lau and Dill [Macromolecules 22, 3986 (1989)] has been widely used in theoretical studies of protein folding due to its conceptual and computational simplicity. Despite its success in elucidating various aspects of the sequence-structure relationship, thermodynamic behavior of the model is not in agreement with a sharp two-state folding transition of many single-domain proteins. To gain a better understanding of this discrepancy, we consider an extension of the HP model by including an "antiferromagnetic" (AF) interaction in the contact potential that favors amino acid residues with complementary attributes. With an enlarged four-letter alphabet, the density of states on the low energy side can be significantly decreased. Computational studies of the four-letter HP model are performed on 36-mer sequences on a square lattice. It is found that the designability of folded structures in the extended model exhibits strong correlation with that of the two-letter HP model, while the AF interaction alone selects a very different class of structures that resembles the Greek key motif for beta sheets. A procedure is introduced to select sequences which have the largest energy gap to the native state. Based on density of states and specific heat calculations in the full configuration space, we show that the optimized sequence is able to fold nearly as cooperatively as a corresponding Go model.

Sample-dependent first-passage-time distribution in a disordered medium.

Above two dimensions, diffusion of a particle in a medium with quenched random traps is believed to be well described by the annealed continuous-time random walk. We propose an approximate expression for the first-passage-time (FPT) distribution in a given sample that enables detailed comparison of the two problems. For a system of finite size, the number and spatial arrangement of deep traps yield significant sample-to-sample variations in the FPT statistics. Numerical simulations of a quenched trap model with power-law sojourn times confirm the existence of two characteristic time scales and a non-self-averaging FPT distribution, as predicted by our theory.

Finite-size scaling, dynamic fluctuations, and hyperscaling relation in the Kuramoto model.

We revisit the Kuramoto model to explore the finite-size scaling (FSS) of the order parameter and its dynamic fluctuations near the onset of the synchronization transition, paying particular attention to effects induced by the randomness of the intrinsic frequencies of oscillators. For a population of size N, we study two ways of sampling the intrinsic frequencies according to the same given unimodal distribution g(ω). In the "random" case, frequencies are generated independently in accordance with g(ω), which gives rise to oscillator number fluctuation within any given frequency interval. In the "regular" case, the N frequencies are generated in a deterministic manner that minimizes the oscillator number fluctuations, leading to quasiuniformly spaced frequencies in the population. We find that the two samplings yield substantially different finite-size properties with clearly distinct scaling exponents. Moreover, the hyperscaling relation between the order parameter and its fluctuations is valid in the regular case, but it is violated in the random case. In this last case, a self-consistent mean-field theory that completely ignores dynamic fluctuations correctly predicts the FSS exponent of the order parameter but not its critical amplitude.

Explicit hypoxia targeting with tumor suppression by creating an "obligate" anaerobic Salmonella Typhimurium strain.

Using bacteria as therapeutic agents against solid tumors is emerging as an area of great potential in the treatment of cancer. Obligate and facultative anaerobic bacteria have been shown to infiltrate the hypoxic regions of solid tumors, thereby reducing their growth rate or causing regression. However, a major challenge for bacterial therapy of cancer with facultative anaerobes is avoiding damage to normal tissues. Consequently the virulence of bacteria must be adequately attenuated for therapeutic use. By placing an essential gene under a hypoxia conditioned promoter, SalmonellaTyphimurium strain SL7207 was engineered to survive only in anaerobic conditions (strain YB1) without otherwise affecting its functions. In breast tumor bearing nude mice, YB1 grew within the tumor, retarding its growth, while being rapidly eliminated from normal tissues. YB1 provides a safe bacterial vector for anti-tumor therapies without compromising the other functions or tumor fitness of the bacterium as attenuation methods normally do.

Sequential establishment of stripe patterns in an expanding cell population.

Periodic stripe patterns are ubiquitous in living organisms, yet the underlying developmental processes are complex and difficult to disentangle. We describe a synthetic genetic circuit that couples cell density and motility. This system enabled programmed Escherichia coli cells to form periodic stripes of high and low cell densities sequentially and autonomously. Theoretical and experimental analyses reveal that the spatial structure arises from a recurrent aggregation process at the front of the continuously expanding cell population. The number of stripes formed could be tuned by modulating the basal expression of a single gene. The results establish motility control as a simple route to establishing recurrent structures without requiring an extrinsic pacemaker.

Entrainment transition in populations of random frequency oscillators.

The entrainment transition of coupled random frequency oscillators is revisited. The Kuramoto model (global coupling) is shown to exhibit unusual sample-dependent finite-size effects leading to a correlation size exponent nu=5/2. Simulations of locally coupled oscillators in d dimensions reveal two types of frequency entrainment: mean-field behavior at d>4 and aggregation of compact synchronized domains in three and four dimensions. In the latter case, scaling arguments yield a correlation length exponent nu=2/(d-2), in good agreement with numerical results.

Zero-temperature criticality in the two-dimensional gauge glass model.

The zero-temperature critical state of the two-dimensional gauge glass model is investigated. It is found that low-energy vortex configurations afford a simple description in terms of gapless, weakly interacting vortex-antivortex pair excitations. A linear dielectric screening calculation is presented in a renormalization group setting that yields a power law decay of spin-wave stiffness with distance. These properties are in agreement with low-temperature specific heat and spin-glass susceptibility data obtained in large-scale multicanonical Monte Carlo simulations.

Localization of denaturation bubbles in random DNA sequences.

We study the thermodynamic and dynamic behaviors of twist-induced denaturation bubbles in a long, stretched random sequence of DNA. The small bubbles associated with weak twist are delocalized. Above a threshold torque, the bubbles of several tens of bases or larger become preferentially localized to AT-rich segments. In the localized regime, the bubbles exhibit "aging" and move around subdiffusively with continuously varying dynamic exponents. These properties are derived by using results of large-deviation theory together with scaling arguments and are verified by Monte Carlo simulations.

Directional ordering of fluctuations in a two-dimensional compass model.

In the Mott insulating phase of the transition metal oxides, the effective orbital-orbital interaction is directional both in orbital space and in real space. We discuss a classical realization of directional coupling in two dimensions. Despite extensive degeneracy of the ground state, the model exhibits partial orbital ordering in the form of directional ordering of fluctuations at low temperatures stabilized by an entropy gap. Transition to the disordered phase is shown to be in the Ising universality class through exact mapping and multicanonical Monte Carlo simulations.