The global spread of coronavirus disease 2019 (COVID-19) is overwhelming many health-care systems. As a result, epidemiological models are being used to inform policy on how to effectively deal with this pandemic. The majority of existing models assume random diffusion but do not take into account differences in the amount of interactions between individuals, i.e. the underlying human interaction network

We argue that frequent sampling of the fraction of a priori non-symptomatic but infectious humans (either by random or cohort testing) significantly improves the management of the COVID-19 pandemic, when compared to intervention strategies relying on data from symptomatic cases only. This is because such sampling measures the incidence of the disease, the key variable controlled by restrictive measures

Eukaryotic cells face the challenging task of transporting a variety of particles through the complex intracellular milieu in order to deliver, distribute, and mix the many components that support cell function. In this review, we explore the biological objectives and physical mechanisms of intracellular transport. Our focus is on cytoplasmic and intra-organelle transport at the whole-cell scale. We

Bacteria across many scales are involved in a dynamic process of information exchange to coordinate activity and community structure within large and diverse populations. The molecular components bacteria use to communicate have been discovered and characterized, and recent efforts have begun to understand the potential for bacterial signal exchange to gather information from the environment and coordinate

The COVID-19 epidemic of the novel coronavirus (severe acute respiratory syndrome SARS-CoV-2) has spread around the world. While different containment policies using non-pharmaceutical interventions have been applied, their efficiencies are not known quantitatively. We show that the doubling time T d ( t ) with the success s factor , the characteristic time of the exponential growth of T d ( t ) in

A central question in eukaryotic cell biology asks, during cell division, how is the growth and distribution of organelles regulated to ensure each daughter cell receives an appropriate amount. For vacuoles in budding yeast, there are well described organelle-to-cell size scaling trends as well as inheritance mechanisms involving highly coordinated movements. It is unclear whether such mechanisms are

Fitting the probability mass functions from analytical solutions of stochastic models of gene expression to the single-cell count distributions of mRNA and protein molecules can yield valuable insights into mechanisms underlying gene expression. Solutions of chemical master equations are available for various kinetic schemes but, even for the basic ON–OFF genetic switch, they take complex forms with

Proteins interact with metabolites, nucleic acids, and other proteins to orchestrate the myriad catalytic, structural and regulatory functions that support life, from the simplest microbes to the most complex multicellular organisms. These molecular interactions are often exquisitely specific, but never perfectly so. Adventitious ‘promiscuous’ interactions are ubiquitous due to the thousands of macromolecules

Error analysis and data visualization of positive COVID-19 cases in 27 countries have been performed up to August 8, 2020. This survey generally observes a progression from early exponential growth transitioning to an intermediate power-law growth phase, as recently suggested by Ziff and Ziff. The occurrence of logistic growth after the power-law phase with lockdowns or social distancing may be described

Different ways of calculating mortality during epidemics have yielded very different results, particularly during the current COVID-19 pandemic. For example, the ‘CFR’ has been interchangeably called the case fatality ratio, case fatality rate, and case fatality risk, often without standard mathematical definitions. The most commonly used CFR is the case fatality ratio , typically constructed using

Epidemiological models usually contain a set of parameters that must be adjusted based on available observations. Once a model has been calibrated, it can be used as a forecasting tool to make predictions and to evaluate contingency plans. It is customary to employ only point estimators of model parameters for such predictions. However, some models may fit the same data reasonably well for a broad

In the absence of other tools, monitoring the effects of protective measures, including social distancing and forecasting the outcome of outbreaks is of immense interest. Real-time data is noisy and very often hampered by systematic errors in reporting. Detailed epidemic models may contain a large number of empirical parameters, which cannot be determined with sufficient accuracy. In this paper, we

Single-cell technologies have revolutionized biomedical research by enabling scalable measurement of the genome, transcriptome, proteome, and epigenome of multiple systems at single-cell resolution. Now widely applied to cancer models, these assays offer new insights into tumour heterogeneity, which underlies cancer initiation, progression, and relapse. However, the large quantities of high-dimensional

Toxic abnormal aggregation of α-synuclein (α-Syn) is a feature of Parkinson's disease. Several biochemical and biophysical studies have demonstrated that many post-translational modifications (PTM) of α-Syn could distinctly alleviate its oligomerization-mediated toxicity. Recently, a compelling link is emerging between the PTM O-GlcNAcylation (O-GlcNAc) and protein aggregation, yet the underlying molecular

We study the reported data from the SARS-CoV-2 pandemic outbreak in January - May 2020 in 119 countries. We observe that the time series of active cases in individual countries (the difference of the total number of confirmed infections and the sum of the total number of reported deaths and recovered cases) display a strong agreement with algebraic growth and at a later epidemic stage also with a combined

Single-molecule force spectroscopy techniques allow for the measurement of several static and dynamic features of macromolecules of biological origin. In particular, atomic force microscopy, used with a variable pulling rate, provides valuable information on the folding/unfolding dynamics of proteins. We propose here two different models able to describe the out-of-equilibrium statistical mechanics

Trauma arising from landmines and improvised explosive devices promotes heterotopic ossification, the formation of extra-skeletal bone in non-osseous tissue. To date, experimental platforms that can replicate the loading parameter space relevant to improvised explosive device and landmine blast wave exposure have not been available to study the effects of such non-physiological mechanical loading on

Integral feedback control is commonly used in mechanical and electrical systems to achieve zero steady-state error following an external disturbance. Equivalently, in biological systems, a property known as robust perfect adaptation guarantees robustness to environmental perturbations and return to the pre-disturbance state. Previously, Briat et al proposed a biomolecular design for integral feedback

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More and more countries are showing a significant slowdown in the number of new COVID-19 infections due to effective governmentally instituted lockdown and social distancing measures. We have analyzed the growth behavior of the top 25 most affected countries by means of a local slope analysis and found three distinct patterns that individual countries follow depending on the strictness of the lockdown

Collective cell migration is crucial in many biological processes such as wound healing, tissue morphogenesis, and tumor progression. The leading front of a collective migrating epithelial cell layer often destabilizes into multicellular finger-like protrusions, each of which is guided by a leader cell at the fingertip. Here, we develop a subcellular-element-based model of this fingering instability

In order to maintain functional robustness and species integrity, organisms must ensure high fidelity of the genome duplication process. This is particularly true during early development, where cell division is often occurring both rapidly and coherently. By studying the extreme limits of suppressing DNA replication failure due to double fork stall errors, we uncover a fundamental constant that describes

Solving the chemical master equation (CME) in biological problems can be difficult due to its extremely large or even infinite state space. One strategy to overcome this challenge is to restrict to a finite state projection (FSP) and represent the transition matrix and probability vector in quantized tensor train (QTT) format, leading to savings in storage while retaining accuracy. In an earlier adaptive

We examined PC12 cell proliferation in environments with temporally varying epidermal growth factor concentrations by means of a microfluidic system. Our measurements revealed frequency-dependent cell behaviour over an observation period of three days. The cell population either increased, decreased or remained constant depending on the frequency of epidermal growth factor applied. A plot of the apparent

The deluge of single-cell data obtained by sequencing, imaging and epigenetic markers has led to an increasingly detailed description of cell state. However, it remains challenging to identify how cells transition between different states, in part because data are typically limited to snapshots in time. A prerequisite for inferring cell state transitions from such snapshots is to distinguish whether

Cytoplasmic dynein is an important molecular motor involved in the transport of vesicular and macromolecular cargo along microtubules in cells, often in conjunction with kinesin motors. Dynein is larger and more complex than kinesin and the mechanism and regulation of its movement is currently the subject of intense research. While it was believed for a long time that dynein motors are relatively weak

Classically, gene expression is modeled as a chemical process with reaction rates dependent on the concentration of the reactants (typically, DNA loci, plasmids, RNA, enzymes, etc). Other variables like cell size are in general ignored. Size dynamics can become an important variable due to the low number of many of these reactants, imperfectly symmetric cell partitioning and molecule segregation. In

The interplay of small, noncoding microRNAs (miRNAs), mRNAs and proteins plays crucial roles in almost all cellular processes. MiR-124, widely known as a memory-related miRNA, can regulate LTM by binding to the mRNA of CREB1 stimulated with 5-HT. In this paper, we establish a regulatory network model of CREB1 and miR-124 stimulated by 5-HT, in which miR-124 inhibits CREB1, which in turn enhances miR-124

Biological cells are complex environments that are densely packed with macromolecules and subdivided by membranes, both of which affect the rates of chemical reactions. It is well known that crowding reduces the volume available to reactants, which increases reaction rates, and also inhibits reactant diffusion, which decreases reaction rates. This work investigates these effects quantitatively using

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The majority of chronic infections are caused by biofilms, which have higher levels of antibiotic resistance than planktonic growth. Violet-blue 405 nm light has recently emerged as a novel bactericide, but limited studies have been conducted on its effectiveness against biofilms. We found that in response to 405 nm light both Pseudomonas aeruginosa and Bacillus subtilis biofilms exhibited cell dispersal

The aggregation of intrinsically disordered proteins is a hallmark of neurodegenerative diseases, such as Alzheimer's, Parkinson's and Huntington's disease. Although we currently have a good molecular level understanding on how protein aggregation occurs in vitro, the details of its self-assembly in live cells are still mainly unknown. During the last ten years, we have witnessed the rapid development

Understanding how much solvents influence the structures and dynamics of proteins is important to understand functional mechanisms of solvated proteins. We propose a solvated potential model that approximates the potential energy of a solvated protein by projecting the solvent information into the protein structure. Using the model, we derive three properties of the solvent. First, the influence of

We propose a biomechanical model for the extravasation of a tumor cell (TC) through the endothelium of a blood vessel. Based on prior in vitro observations, we assume that the TC extends a protrusion between adjacent endothelial cells (ECs) that adheres to the basement membrane via focal adhesions (FAs). As the protrusion grows in size and branches out, the actomyosin contraction along the stress fibers

A cluster of neural crest cells (NCCs) may chemotax up a shallow external gradient to which a single cell is unresponsive. To explain this intriguing 'group advantage', we propose a chemo-mechanical model based on the signaling proteins Rac1 and RhoA. We represent each cell as a polygon with nodes connected by elastic membranes. Via reaction-diffusion on the membrane and exchange with their cytosolic

Messenger RNAs (mRNAs) consist of a coding region (open reading frame (ORF)) and two untranslated regions (UTRs), 5'UTR and 3'UTR. Ribosomes travel along the coding region, translating nucleotide triplets (called codons) to a chain of amino acids. The coding region was long believed to mainly encode the amino acid content of proteins, whereas regulatory signals reside in the UTRs and in other genomic

Cells are complex machines with tremendous potential for applications in medicine and biotechnology. Although much effort has been devoted to engineering the metabolic, genetic, and signaling pathways of cells, methods for systematically engineering the physical structure of cells are less developed. Here we consider how coarse-grained models for cellular geometry at the organelle level can be used

Understanding nanoscale structural changes can provide information about the physical state of cells/tissues. It has now been shown that increases in nanoscale structural alterations are associated with the progress of carcinogenesis in most cancer cases, including early carcinogenesis. Anti-cancerous therapies are designed to inhibit the growth of cancer cells; however, it is challenging to detect

In this paper, we aim to detect trapping areas (equivalently microdomains or confinement areas) within cells, corresponding to regions where molecules are trapped and thereby undergo subdiffusion. We propose an original computational approach that takes as input a set of molecule trajectories estimated by appropriate tracking methods. The core of the algorithm is based on a combination of clustering

The process by which actin polymerization generates pulling forces in cellular processes such as endocytosis is less well understood than pushing-force generation. To clarify the basic mechanisms of pulling-force generation, we perform stochastic polymerization simulations for a square array of polymerizing semiflexible actin filaments, having different interactions with the membrane. The filaments

During morphogenesis, epithelial tubes elongate. In the case of the mammalian lung, biased elongation has been linked to a bias in cell shape and cell division, but it has remained unclear whether a bias in cell shape along the axis of outgrowth is sufficient for biased outgrowth and how it arises. Here, we use our 2D cell-based tissue simulation software [Formula: see text] to investigate the conditions

We develop a method for solving mathematical models of messenger RNA (mRNA) translation based on the totally asymmetric simple exclusion process (TASEP). Our main goal is to demonstrate that the method is versatile and applicable to realistic models of translation. To this end we consider the TASEP with codon-dependent elongation rates, premature termination due to ribosome drop-off and translation

How bacteria sense local chemical gradients and decide to move has been a fascinating area of recent study. Chemotaxis of bacterial populations has been traditionally modeled using either individual-based models describing the motion of a single bacterium as a velocity jump process, or macroscopic PDE models that describe the evolution of the bacterial density. In these models, the hydrodynamic interaction

Evolution of the stem cell population responsible for homeostatic cell renewal processes is analyzed. We assume that this regime is the product of a delicate balance between symmetric divisions that, after each cell cycle, originates a new stem cell or its disappearance (through cell differentiation). This dynamics leads to a monoclonal population, that is for an initial homogeneous set of stem cells

We present a Bayesian framework for inferring spatio-temporal maps of diffusivity and potential fields from recorded trajectories of single molecules inside living cells. The framework naturally lets us regularise the high-dimensional inference problem using prior distributions in order to obtain robust results. To overcome the computational complexity of inferring thousands of map parameters from

The number of ribosomes in a cell is considered as limiting, and gene expression is thus largely determined by their cellular concentration. In this work we develop a toy model to study the trade-off between the ribosomal supply and the demand of the translation machinery, dictated by the composition of the transcript pool. Our equilibrium framework is useful to highlight qualitative behaviours and

It has been suggested that structural rigidity is connected to thermostability, e.g. in enzymes from thermophilic microorganisms. We examine the importance of correctly handling salt bridges, and interactions which we term 'strong polars', when constructing the constraint network for global rigidity analysis in these systems. Through a comparison of rigidity in citrate synthases, we clarify the relationship

Gene expression is an inherently stochastic process with transcription of mRNAs often occurring in bursts: short periods of activity followed by typically longer periods of inactivity. While a simple model involving switching between two promoter states has been widely used to analyze transcription dynamics, recent experimental observations have provided evidence for more complex kinetic schemes underlying

Recently the larval zebrafish has emerged as a model organism which is used to assist in the studies of human cardiac electrophysiology. Although they share many similar electrophysiological characteristics, it has been found that the conduction velocity (CV) of action potential (AP) propagation in larval zebrafish heart is up to two orders of magnitude smaller than in the adult mammalian heart. To

Molecular force sensors (MFSs) have grown to become an important tool to study the mechanobiology of cells and tissues. They provide a minimally invasive means to optically report mechanical interactions at the molecular level. One of the challenges in molecular force sensor studies is the interpretation of the fluorescence readout. In this review, we divide existing MFSs into three classes based on

The morphologies of cell membranes, and specifically the local curvature distributions are determined either by its intrinsic components such as lipids and membrane-associated proteins or by the adhesion forces due to membrane interactions with the cytoskeleton, extracellular matrix (ECM) and other cells in the tissue, as well as physical variables such as membrane and frame tensions. We present a

Cell division is accompanied by dramatic changes in shape that ultimately lead to the physical separation of one cell into two. In 2D microenvironments, cells round up and remain adhered onto the substrate by thin retraction fibers during division. In contrast, in 3D environments, cells divide exhibiting long protrusions that guide the orientation of the division axis. However, the mechanism of cell

Due to structural and functional abnormalities or genetic variations and mutations, there may be dysfunctional molecules within an intracellular signaling network that do not allow the network to correctly regulate its output molecules, such as transcription factors. This disruption in signaling interrupts normal cellular functions and may eventually develop some pathological conditions. In this paper

The sheet-like endoplasmic reticulum (ER) of eukaryotic cells has been found to be riddled with spiral dislocations, known as 'Terasaki ramps', in the vicinity of which the doubled bilayer membranes which make up ER sheets can be approximately modeled by helicoids. Here we analyze diffusion on a surface with locally helicoidal topological dislocations, and use the results to argue that the Terasaki

The glycolytic enzyme pyruvate kinase M2 (PKM2) exists in both catalytically inactive dimeric and active tetrameric forms. In cancer cells, PKM2 dimer predominance contributes to tumor growth by triggering glycolytic reprogramming. However, the mechanism that promotes PKM2 dimer predominance over tetramer in cancer cells remains elusive. Here, we show that pulsatile phosphofructokinase (PFK-1) activity

It is well established that gene expression can be modeled as a Markovian stochastic process and hence proper observables might be subjected to large fluctuations and rare events. Since dynamics is often more than statics, one can work with ensembles of trajectories for long but fixed times, instead of states or configurations, to study dynamics of these Markovian stochastic processes and glean more

We present a simple growth model which was developed to explain Escherichia coli growth in batch culture. Optical density measurements are used to obtain E. coli growth curves for different inoculum sizes and nutrients concentrations. The model is described by two nonlinear mutually dependent differential equations that describe time evolution of bacteria and nutrients concentration. Introduction of

Polycystic kidney disease is a disorder that leads to fluid filled cysts that replace normal renal tubes. During the process of cellular development and in the progression of the diseases, fibrocystin can lead to impaired organ formation and even cause organ defects. Besides cellular polarity, mechanical properties play major roles in providing the optimal apical-basal or anterior-posterior symmetry

Identifying the cues followed by cells is key to understand processes as embryonic development, tissue homeostasis, or several pathological conditions. Based on a durotaxis model, it is shown that cells moving on predeformed thin elastic membrane follow the direction of increasing strain of the substrate. This mechanism, straintaxis, does not distinguish the origin of the strain, but the active stresses