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Nowadays, location based service (LBS) is one of the most popular mobile apps and following with humongous of location data been produced. The publishing of location data can provide benefit for promoting the quality of service, optimizing the commercial environment as well as harmonizing the infrastructure construction. However, as location data may contain some sensitive or confidential information, the publishing may reveal privacy and bring hazards. So the published data had to be disposed to protect the privacy. In order to cope with this problem, a number of algorithms based on the strategy of k-anonymity were proposed, but this is not enough for the privacy protection, as the correlation between the sensitive region and the background knowledge can be used to infer the real location. Thus, consider about this condition, in this paper a ε-sensitive correlation privacy protection scheme is proposed, and provides correlation indistinguishable to the location data. In this scheme, entropy is first used to determine the location centroid of each cell to build up the voronoi diagram. Then the coordinate of the untreated location data that is located in the cell is transferred into the centroid vicinity. Accordingly, the sensitive correlation is destroyed by the coordinate of each published data. The process of transferring the location data is determined by metrics of ε-sensitive correlation privacy, and is rigorous in mathematical justification. At last, security analysis is proposed in this paper to verify the privacy ability of our proposed algorithm based on voronoi diagram and entropy, and then we utilize the comparative experiment to further affirm the advantage of this algorithm in the location data privacy protection as well as the availability of published data.

Infection with Citrobacter rodentium triggers robust tissue damage repair responses, manifested by secretion of IL-22, in the absence of which mice succumbed to the infection. Of the main hallmarks of C. rodentium infection are colonic crypt hyperplasia (CCH) and dysbiosis. In order to colonize the host and compete with the gut microbiota, C. rodentium employs a type III secretion system (T3SS) that injects effectors into colonic intestinal epithelial cells (IECs). Once injected, the effectors subvert processes involved in innate immune responses, cellular metabolism and oxygenation of the mucosa. Importantly, the identity of the effector/s triggering the tissue repair response is/are unknown. Here we report that the effector EspO ,an orthologue of OspE found in Shigella spp, affects proliferation of IECs 8 and 14 days post C. rodentium infection as well as secretion of IL-22 from colonic explants. While we observed no differences in the recruitment of group 3 innate lymphoid cells (ILC3s) and T cells, which are the main sources of IL-22 at the early and late stages of C. rodentium infection respectively, infection with ΔespO was characterized by diminished recruitment of sub-mucosal neutrophils, which coincided with lower abundance of Mmp9 and chemokines (e.g. S100a8/9) in IECs. Moreover, mice infected with ΔespO triggered significantly lesser nutritional immunity (e.g. calprotectin, Lcn2) and expression of antimicrobial peptides (Reg3β, Reg3γ) compared to mice infected with WT C. rodentium. This overlapped with a decrease in STAT3 phosphorylation in IECs. Importantly, while the reduced CCH and abundance of antimicrobial proteins during ΔespO infection did not affect C. rodentium colonization or the composition of commensal Proteobacteria, they had a subtle consequence on Firmicutes subpopulations. EspO is the first bacterial virulence factor that affects neutrophil recruitment and secretion of IL-22, as well as expression of antimicrobial and nutritional immunity proteins in IECs., Author summary Citrobacter rodentium is a gold standard model to study pathogen-host-microbiome interactions. Two of the hallmarks of C. rodentium infection are colonic damage repair responses and colitis; symptoms that are shared with inflammatory bowel diseases in humans. The processes leading to tissue damage repair responses and the implicated bacterial virulence factors are still elusive. In this paper, we show that the C. rodentium type III secretion system effector EspO plays a major role in triggering damage healing responses, recruitment of neutrophils to the colonic villi, secretion of IL-22 from colonic explants and expression of IL-22 regulated genes in intestinal epithelial cells. This paper is the first to report a bacterial virulence factor that impacts on both intestinal epithelial cell proliferation and immune responses.

Frailty is a common condition in older age and is a public health concern which requires integrated care and involves different stakeholders. This meta-synthesis focuses on experiences,\ud understanding, and attitudes towards screening, care, intervention and prevention for frailty across frail and healthy older persons, caregivers, health and social care practitioners.\ud Studies published since 2001 were identified through search of electronic databases; 81 eligible papers were identified and read in full, and 45 papers were finally included and synthesized. The synthesis was conducted with a meta-ethnographic approach. We identified four key themes: Uncertainty about malleability of frailty; Strategies to prevent or to respond to frailty; Capacity to care and person and family-centred service provision; Power\ud and choice. A bottom-up approach which emphasises and works in synchrony with frail older people's and their families' values, goals, resources and optimisation strategies is necessary.\ud A greater employment of psychological skills, enhancing communication abilities and tools to overcome disempowering attitudes should inform care organisation, resulting in\ud more efficient and satisfactory use of services. Public health communication about prevention and management of frailty should be founded on a paradigm of resilience, balanced\ud acceptance, and coping. Addressing stakeholders' views about the preventability of frailty was seen as a salient need.

Background A recent paper by Tomasetti and Vogelstein (Science 2015 347 78–81) suggested that the variation in natural cancer risk was largely explained by the total number of stem-cell divisions, and that most cancers arose by chance. They proposed an extra-risk score as way of distinguishing the effects of the stochastic, replicative component of cancer risk from other causative factors, specifically those due to the external environment and inherited mutations. Objectives We tested the hypothesis raised by Tomasetti and Vogelstein by assessing the degree of correlation of stem cell divisions and their extra-risk score with radiation- and tobacco-associated cancer risk. Methods We fitted a variety of linear and log-linear models to data on stem cell divisions per year and cumulative stem cell divisions over lifetime and natural cancer risk, some taken from the paper of Tomasetti and Vogelstein, augmented using current US lifetime cancer risk data, and also radiation- and tobacco-associated cancer risk. Results The data assembled by Tomasetti and Vogelstein, as augmented here, are inconsistent with the power-of-age relationship commonly observed for cancer incidence and the predictions of a multistage carcinogenesis model, if one makes the strong assumption of homogeneity of numbers of driver mutations across cancer sites. Analysis of the extra-risk score and various other measures (number of stem cell divisions per year, cumulative number of stem cell divisions over life) considered by Tomasetti and Vogelstein suggests that these are poorly predictive of currently available estimates of radiation- or smoking-associated cancer risk–for only one out of 37 measures or logarithmic transformations thereof is there a statistically significant correlation (p

Dysregulation of collagen production and secretion contributes to aging and tissue fibrosis of major organs. How procollagen proteins in the endoplasmic reticulum (ER) route as specialized cargos for secretion remains to be fully elucidated. Here, we report that TMEM39, an ER-localized transmembrane protein, regulates production and secretory cargo trafficking of procollagen. We identify the C. elegans ortholog TMEM-39 from an unbiased RNAi screen and show that deficiency of tmem-39 leads to striking defects in cuticle collagen production and constitutively high ER stress response. RNAi knockdown of the tmem-39 ortholog in Drosophila causes similar defects in collagen secretion from fat body cells. The cytosolic domain of human TMEM39A binds to Sec23A, a vesicle coat protein that drives collagen secretion and vesicular trafficking. TMEM-39 regulation of collagen secretion is independent of ER stress response and autophagy. We propose that the roles of TMEM-39 in collagen secretion and ER homeostasis are likely evolutionarily conserved., Author summary As the most abundant protein in animals, collagen plays diverse roles and its dysregulation impacts aging and many fibrotic disorders. It is important to understand how premature collagen proteins in the ER are processed and secreted, as many other aspects of collagen regulation have been elucidated in mechanistic detail. In this paper, we have characterized a novel conserved family of TMEM39 proteins, including human TMEM39A and C. elegans tmem-39 that regulates ER stress response and collagen secretion. Human TMEM39A directly interacts with SEC23A, a core component of the COPII vesicle coating complex responsible for vesicular cargo secretion to the Golgi apparatus. The function of TMEM-39 proteins in collagen secretion appears highly conserved and independent to the ER stress response and the autophagy pathway. Our results provide insights into functions and mechanisms of TMEM39 proteins in collagen secretion and suggest it as a plausible target for tissue fibrotic diseases.

[Abstract] The adjustment of transcription and translation rates to the changing needs of cells is of utmost importance for their fitness and survival. We have previously shown that the global transcription rate for RNA polymerase II in budding yeast Saccharomyces cerevisiae is regulated in relation to cell volume. Total mRNA concentration is constant with cell volume since global RNApol II-dependent nascent transcription rate (nTR) also keeps constant but mRNA stability increases with cell size. In this paper, we focus on the case of rRNA and RNA polymerase I. Contrarily to that found for RNA pol II, we detected that RNA polymerase I nTR increases proportionally to genome copies and cell size in polyploid cells. In haploid mutant cells with larger cell sizes, the rDNA repeat copy number rises. By combining mathematical modeling and experimental work with the large-size cln3 strain, we observed that the increasing repeat copy number is based on a feedback mechanism in which Sir2 histone deacetylase homeostatically controls the amplification of rDNA repeats in a volume-dependent manner. This amplification is paralleled with an increase in rRNA nTR, which indicates a control of the RNA pol I synthesis rate by cell volume., [Author summary] Synthesis rates of biological macromolecules should be strictly regulated and adjusted to the changing conditions of cells. The change in volume is one of the commonest variables along individual cell life and also when comparing different cell types. We previously found that cells with asymmetric division, such as budding yeasts, use a compensatory change in the global RNA polymerase II synthesis rate and mRNA decay rate to maintain mRNA homeostasis. In the present study, we address the same issue for the RNA polymerase that makes rRNAs, which are essential components of ribosomes and the most abundant RNAs in the cell. We found that the copy number of the gene encoding 35S rRNA, transcribed by RNA polymerase I, changes proportionally to the cell volume in budding yeast via a feedback mechanism based on the Sir2 histone deacetylase, which guarantees that yeast cells have the appropriate RNA polymerase I synthesis rate required for rRNA homeostasis., This work has been supported by grants from the Spanish Ministry of Economy and Competitiveness (https://www.ciencia.gob.es/portal/site/MICINN/) and European Union funds (FEDER) [BFU2016-77728-C3-1-P to S.C.], [BFU2016-77728-C3-3-P to J.E.P-O and RED2018-102467-REDT to J.E.P-O and S.C.], and from the Regional Valencian Government (http://innova.gva.es/va/web/ciencia) [PROMETEO II 2015/006 & AICO2019/088 to J.E.P-O]. M.B.-A. was funded by a pre-doctoral research grant (FPU17/03542) from the Spanish Ministry of Science, Innovation and Universities.

Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, from randomly adopting a phenotypic state to sensing and reacting to environmental cues. Cellular memory—the ability to track and condition the time to switch to a different phenotypic state—can help withstand environmental fluctuations. How does memory manifest itself in unicellular organisms? We describe the population-wide consequences of phenotypic memory in microbes through a combination of deterministic modelling and stochastic simulations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that memory in individual cells generates patterns at the population level coherent with overshoots and non-exponential lag times distributions experimentally observed in phenotypically heterogeneous populations. We emphasise the implications of our work in understanding antibiotic tolerance and, in general, bacterial survival under fluctuating environments., Author summary While being genetically the same, a population of cells can show phenotypic variability even under homogeneous environments. Often advantageous under heterogeneous environments, this phenotypic heterogeneity is highly relevant in the studies of antibiotic resistance evolution and cancer resurgence. Numerous theoretical models exist applying a simple model of phenotypic switching. Experimental measurements on phenotypic heterogeneity have increased in precision over the past decade, and the simple models are inadequate to explain the new observations. In this paper, we explore the role of cellular memory as a crucial component of phenotypic switching. We see that memory helps account for the hitherto unexplained observations and fundamentally extend our understanding of phenotypic heterogeneity.

Single-cell Hi-C (scHi-C) sequencing technologies allow us to investigate three-dimensional chromatin organization at the single-cell level. However, we still need computational tools to deal with the sparsity of the contact maps from single cells and embed single cells in a lower-dimensional Euclidean space. This embedding helps us understand relationships between the cells in different dimensions, such as cell-cycle dynamics and cell differentiation. We present an open-source computational toolbox, scHiCTools, for analyzing single-cell Hi-C data comprehensively and efficiently. The toolbox provides two methods for screening single cells, three common methods for smoothing scHi-C data, three efficient methods for calculating the pairwise similarity of cells, three methods for embedding single cells, three methods for clustering cells, and a build-in function to visualize the cells embedding in a two-dimensional or three-dimensional plot. scHiCTools, written in Python3, is compatible with different platforms, including Linux, macOS, and Windows., Author summary Single-cell Hi-C contact maps describe the numbers of interactions among genomic loci across the entire genome, and provide researchers 3D chromatin organization in each cell. There are growing demands for an easy and fast way to analyze and visualize single-cell Hi-C data, and analyzing single-cell Hi-C data exposes several inherent data analysis challenges. To move beyond existing computational tools and methods to analyze and visualize single-cell Hi-C data, we present a software package, scHiCTools, which is implemented in Python. The software package provides researchers a collection of methods to investigate the cell-to-cell similarity based on their 3D chromatin organization, cluster cells into groups accordingly, and visualize cells in two-dimensional or three-dimensional scatter plots. In this paper, we provide an overview of scHiCTools’ structure and capabilities. We then apply scHiCTools to several single-cell Hi-C datasets to benchmark the performance of the methods provided in our toolbox, and present some plots generated using the software package.

Since the seminal 1961 paper of Monod and Jacob, mathematical models of biomolecular circuits have guided our understanding of cell regulation. Model-based exploration of the functional capabilities of any given circuit requires systematic mapping of multidimensional spaces of model parameters. Despite significant advances in computational dynamical systems approaches, this analysis remains a nontrivial task. Here, we use a nonlinear system of ordinary differential equations to model oocyte selection in Drosophila, a robust symmetry-breaking event that relies on autoregulatory localization of oocyte-specification factors. By applying an algorithmic approach that implements symbolic computation and topological methods, we enumerate all phase portraits of stable steady states in the limit when nonlinear regulatory interactions become discrete switches. Leveraging this initial exact partitioning and further using numerical exploration, we locate parameter regions that are dense in purely asymmetric steady states when the nonlinearities are not infinitely sharp, enabling systematic identification of parameter regions that correspond to robust oocyte selection. This framework can be generalized to map the full parameter spaces in a broad class of models involving biological switches., Author summary Identification of qualitatively different regimes in models of biomolecular switches is essential for understanding dynamics of complex biological processes, including symmetry breaking in cells and cell networks. We demonstrate how topological methods, symbolic computation, and numerical simulations can be combined for systematic mapping of symmetry-broken states in a mathematical model of oocyte specification in Drosophila, a leading experimental system of animal oogenesis. Our algorithmic framework reveals global connectedness of parameter domains corresponding to robust oocyte specification and enables systematic navigation through multidimensional parameter spaces in a large class of biomolecular switches.

The transition from mitosis into the first gap phase of the cell cycle in budding yeast is controlled by the Mitotic Exit Network (MEN). The network interprets spatiotemporal cues about the progression of mitosis and ensures that release of Cdc14 phosphatase occurs only after completion of key mitotic events. The MEN has been studied intensively; however, a unified understanding of how localisation and protein activity function together as a system is lacking. In this paper, we present a compartmental, logical model of the MEN that is capable of representing spatial aspects of regulation in parallel to control of enzymatic activity. We show that our model is capable of correctly predicting the phenotype of the majority of mutants we tested, including mutants that cause proteins to mislocalise. We use a continuous time implementation of the model to demonstrate that Cdc14 Early Anaphase Release (FEAR) ensures robust timing of anaphase, and we verify our findings in living cells. Furthermore, we show that our model can represent measured cell–cell variation in Spindle Position Checkpoint (SPoC) mutants. This work suggests a general approach to incorporate spatial effects into logical models. We anticipate that the model itself will be an important resource to experimental researchers, providing a rigorous platform to test hypotheses about regulation of mitotic exit., This study presents a logical compartmental model of the yeast mitotic exit network (MEN) that represents spatial aspects of regulation. The model correctly predicts the majority of published MEN phenotypes and reveals both the role of the Cdc14 early anaphase release and a link between mitosis length and checkpoint competence.

Vascular endothelial growth factor (VEGF) is a major cytokine in tumor biology affecting tumor survival, aggressiveness and pro-angiogenetic activities. In addition, cellular stresses often result in aggressive pro-angiogenetic behavior in tumors. For in vitro study, conventional monolayer cell culture has been broadly exploited; however, it often provides limited information due to its different microenvironment from that in vivo. Recently, three-dimensional (3D) cell spheroid culture provides in vivo-like microenvironments to study tumor biology and their survival mechanisms with better predictive power. In this work, vascular endothelial growth factor of type A (VEGF-A) secretion from osteosarcoma (MG-63) cells cultured using monolayer and 3D spheroid models under two stress conditions: nutrient deficiency (reduced serum culture) and hypoxia-inducible factor (HIF) inhibition (HIF inhibitor, YC-1) are characterized and systematically compared. In order to obtain ample sample size for consistent characterization of cellular responses from cancer spheroids under the stresses and compare the responses to those from the conventional monolayer model, a microfluidic spheroid formation and culture device is utilized in the experiments. In the analysis, cell viability is estimated from captured images, and quantification of VEGF-A secreted from the cells is achieved using enzyme-linked immunosorbent assay (ELISA). The experimental results show that the viabilities decrease when the cells face higher stress levels in both monolayer and 3D spheroid culture models; however, the VEGF-A secretion profiles between the cell culture models are different. The VEGF-A secretion decreases when the cells face higher stress conditions in the monolayer cell culture. In contrast, for the 3D spheroid culture, the VEGF-A concentration decreases for low stress levels but increases while the stress level is high. The VEGF-A regulation in the 3D models mimics in vivo cases of tumor survival and can provide insightful information to investigate tumor angiogenesis in vitro. The approach developed in this paper provides an efficient method to quantitatively and statistically study tumor growth kinetics and stress responses from highly uniform samples and it can also be applied to compare the underlying biomolecular mechanisms in monolayer and 3D spheroid culture models to elucidate the effects of microenvironments on cellular response in cancer research.

金沢大学国際基幹教育院, Homeostasis is an essential concept to understand the stability of organisms and their adaptive behaviors when coping with external and internal assaults. Many hormones that take part in homeostatic control come in antagonistic pairs, such as glucagon and insulin reflecting the inflow and outflow compensatory mechanisms to control a certain internal variable, such as blood sugar levels. By including negative feedback loops homeostatic controllers can exhibit oscillations with characteristic frequencies. In this paper we demonstrate the associated frequency changes in homeostatic systems when individual controllers -in a set of interlocked feedback loops- gain control in response to environmental changes. Taking p53 as an example, we show how Per2, ATM and Mdm2 feedback loops -interlocked with p53- gain individual control in dependence to the level of DNA damage, and how each of these controllers provide certain functionalities in their regulation of p53. In unstressed cells, the circadian regulator Per2 ensures a basic p53 level to allow its rapid up-regulation in case of DNA damage. When DNA damage occurs the ATM controller increases the level of p53 and defends it towards uncontrolled degradation, which despite DNA damage, would drive p53 to lower values and p53 dysfunction. Mdm2 on its side keeps p53 at a high but sub-apoptotic level to avoid premature apoptosis. However, with on-going DNA damage the Mdm2 set-point is increased by HSP90 and other p53 stabilizers leading finally to apoptosis. An emergent aspect of p53 upregulation during cell stress is the coordinated inhibition of ubiquitin-independent and ubiquitin-dependent degradation reactions. Whether oscillations serve a function or are merely a by-product of the controllers are discussed in view of the finding that homeostatic control of p53, as indicated above, does in principle not require oscillatory homeostats., Creative Commons Attribution License 4.0

Drug resistance is a primary obstacle in cancer treatment. In many patients who at first respond well to treatment, relapse occurs later on. Various mechanisms have been explored to explain drug resistance in specific cancers and for specific drugs. In this paper, we consider resistance to anti-PD-1, a drug that enhances the activity of anti-cancer T cells. Based on results in experimental melanoma, it is shown, by a mathematical model, that resistances to anti-PD-1 can be significantly reduced by combining it with anti-TNF-α. The model is used to simulate the efficacy of the combined therapy with different range of doses, different initial tumor volume, and different schedules. In particular, it is shown that under a course of treatment with 3-week cycles where each drug is injected in the first day of either week 1 or week 2, injecting anti-TNF-α one week after anti-PD-1 is the most effective schedule in reducing tumor volume.

Coordination of fate transition and cell division is crucial to maintain the plant architecture and to achieve efficient production of plant organs. In this paper, we analysed the stem cell dynamics at the shoot apical meristem (SAM) that is one of the plant stem cells locations. We designed a mathematical model to elucidate the impact of hormonal signaling on the fate transition rates between different zones corresponding to slowly dividing stem cells and fast dividing transit amplifying cells. The model is based on a simplified two-dimensional disc geometry of the SAM and accounts for a continuous displacement towards the periphery of cells produced in the central zone. Coupling growth and hormonal signaling results in a nonlinear system of reaction-diffusion equations on a growing domain with the growth rate depending on the model components. The model is tested by simulating perturbations in the level of key transcription factors that maintain SAM homeostasis. The model provides new insights on how the transcription factor HECATE is integrated in the regulatory network that governs stem cell differentiation., Author summary Plants continuously generate new organs such as leaves, roots and flowers. This process is driven by stem cells which are located in specialized regions, so-called meristems. Dividing stem cells give rise to offspring that, during a process referred to as cell fate transition, become more specialized and give rise to organs. Plant architecture and crop yield crucially depend on the regulation of meristem dynamics. To better understand this regulation, we develop a computational model of the shoot meristem. The model describes the meristem as a two-dimensional disk that can grow and shrink over time, depending on the concentrations of the signalling factors in its interior. This allows studying how the non-linear interaction of multiple transcription factors is linked to cell division and fate-transition. We test the model by simulating perturbations of meristem signals and comparing them to experimental data. The model allows simulating different hypotheses about signal effects. Based on the model we study the specific role of the transcription factor HECATE and provide new insights in its action on cell dynamics and in its interrelation with other known transcription factors in the meristem.

The mean square displacement (MSD) is an important statistical measure on a stochastic process or a trajectory. In this paper we find an approximation to the mean square displacement for a model of cell motion. The model is a discrete-time jump process which approximates a force-based model for cell motion. In cell motion, the mean square displacement not only gives a measure of overall drift, but it is also an indicator of mode of transport. The key to finding the approximation is to find the mean square displacement for a subset of the state space and use it as an approximation for the entire state space. We give some intuition as to why this is an unexpectedly good approximation. A lower bound and upper bound for the mean square displacement are also given. We show that, although the upper bound is far from the computed mean square displacement, in rare cases the large displacements are approached.

Adult T-cell leukemia/lymphoma (ATLL) originates from human T-cell leukemia virus type 1 (HTLV-1) infection due to the activation of the nuclear factor-κB (NF-κB) signaling pathway to maintain proliferation and survival. An important mechanism of the activated NF-κB signaling pathway in ATLL is the activation of the macroautophagy (herafter referred to as autophagy in the remainder of this manuscript)-lysosomal degradation of p47 (NSFL1C), a negative regulator of the NF-κB pathway. Therefore, we considered the use of chloroquine (CQ) or hydroxychloroquine (HCQ) (CQ/HCQ) as an autophagy inhibitor to treat ATLL; these drugs were originally approved by the FDA as antimalarial drugs and have recently been used to treat autoimmune diseases, such as systemic lupus erythematosus (SLE). In this paper, we determined the therapeutic efficacy of CQ/HCQ, as NF-κB inhibitors, in ATLL mediated by blockade of p47 degradation. Administration of CQ/HCQ to ATLL cell lines and primary ATLL cells induced cell growth inhibition in a dose-dependent manner, and the majority of cells underwent apoptosis after CQ administration. As to the molecular mechanism, autophagy was inhibited in CQ-treated ATLL cells, and activation of the NF-κB pathway was suppressed with the restoration of the p47 level. When the antitumor effect of CQ/HCQ was examined using immunodeficient mice transplanted with ATLL cell lines, CQ/HCQ significantly suppressed tumor growth and improved the survival rate in the ATLL xenograft mouse model. Importantly, HCQ selectively induced ATLL cell death in the ATLL xenograft mouse model at the dose used to treat SLE. Taken together, our results suggest that the inhibition of autophagy by CQ/HCQ may become a novel and effective strategy for the treatment of ATLL.

Biological phenomena induced by terahertz (THz) irradiation are described in recent reports, but underlying mechanisms, structural and dynamical change of specific molecules are still unclear. In this paper, we performed time-lapse morphological analysis of human cells and found that THz irradiation halts cell division at cytokinesis. At the end of cytokinesis, the contractile ring, which consists of filamentous actin (F-actin), needs to disappear; however, it remained for 1 hour under THz irradiation. Induction of the functional structures of F-actin was also observed in interphase cells. Similar phenomena were also observed under chemical treatment (jasplakinolide), indicating that THz irradiation assists actin polymerization. We previously reported that THz irradiation enhances the polymerization of purified actin in vitro; our current work shows that it increases cytoplasmic F-actin in vivo. Thus, we identified one of the key biomechanisms affected by THz waves.

Tumor emergence and progression is a complex phenomenon that assumes special molecular and cellular interactions. The hierarchical structuring and communication via feedback signaling of different cell types, which are categorized as the stem, progenitor, and differentiated cells in dependence of their maturity level, plays an important role. Under healthy conditions, these cells build a dynamical system that is responsible for facilitating the homeostatic regulation of the tissue. Generally, in this hierarchical setting, stem and progenitor cells are yet likely to undergo a mutation, when a cell divides into two daughter cells. This may lead to the development of abnormal characteristics, i.e. mutation in the cell, yielding an unrestrained number of cells. Therefore, the regulation of a stem cell’s proliferation and differentiation rate is crucial for maintaining the balance in the overall cell population. In this paper, a maturity based mathematical model with feedback regulation is formulated for healthy and mutated cell lineages. It is given in the form of coupled ordinary and partial differential equations. The focus is laid on the dynamical effects resulting from acquiring a mutation in the hierarchical structure of stem, progenitor and fully differentiated cells. Additionally, the effects of nonlinear feedback regulation from mature cells into both stem and progenitor cell populations have been inspected. The steady-state solutions of the model are derived analytically. Numerical simulations and results based on a finite volume scheme underpin various expected behavioral patterns of the homeostatic regulation and cancer evolution. For instance, it has been found that the mutated cells can experience significant growth even with a single somatic mutation, but under homeostatic regulation acquire a steady-state and thus, ensuing healthy cell population to either a steady-state or a lower cell concentration. Furthermore, the model behavior has been validated with different experimentally measured tumor values from the literature.

The Epstein-Barr virus (EBV) induces B-cell proliferation with high efficiency through expression of latent proteins and microRNAs. This process takes place in vivo soon after infection, presumably to expand the virus reservoir, but can also induce pathologies, e.g. an infectious mononucleosis (IM) syndrome after primary infection or a B-cell lymphoproliferation in immunosuppressed individuals. In this paper, we investigated the growth characteristics of EBV-infected B-cells isolated from transplant recipients or patients with IM. We found that these cells grew and withstood apoptosis at highly variable rates, suggesting that the expansion rate of the infected B-cells widely varies between individuals, thereby influencing the size of the B-cell reservoir and the ability to form tumors in infected individuals. All viruses investigated were type 1 and genetically close to western strains. EBV-infected B-cells expressed the transforming EBV latent genes and microRNAs (miRNAs) at variable levels. We found that the B-cell growth rates positively correlated with the BHRF1 miRNA levels. Comparative studies showed that infected B-cells derived from transplant recipients with iEBVL on average expressed higher levels of EBV miR-BHRF1 miRNAs and grew more rapidly than B-cells from IM patients, suggesting infection by more transforming viruses. Altogether, these findings suggest that EBV infection has a highly variable impact on the B-cell compartment that probably reflects the genetic diversity of both the virus and the host. It also demonstrates the unexpected finding that B-cells from different individuals can grow at different speed under the influence of the same virus infection.

Scaffold-based cancer cell culture techniques have been gaining prominence especially in the last two decades. These techniques can potentially overcome some of the limitations of current three-dimensional cell culture methods, such as uneven cell distribution, inadequate nutrient diffusion, and uncontrollable size of cell aggregates. Porous scaffolds can provide a convenient support for cell attachment, proliferation and migration, and also allows diffusion of oxygen, nutrients and waste. In this paper, a comparative study was done on porous poly (lactic-co-glycolic acid) (PLGA) microparticles prepared using three porogens-gelatin, sodium bicarbonate (SBC) or novel poly N-isopropylacrylamide [PNIPAAm] particles, as substrates for lung cancer cell culture. These fibronectin-coated, stable particles (19-42 μm) supported A549 cell attachment at an optimal cell seeding density of 250,000 cells/ mg of particles. PLGA-SBC porous particles had comparatively larger, more interconnected pores, and favored greater cell proliferation up to 9 days than their counterparts. This indicates that pore diameters and interconnectivity have direct implications on scaffold-based cell culture compared to substrates with minimally interconnected pores (PLGA-gelatin) or pores of uniform sizes (PLGA-PMPs). Therefore, PLGA-SBC-based tumor models were chosen for preliminary drug screening studies. The greater drug resistance observed in the lung cancer cells grown on porous particles compared to conventional cell monolayers agrees with previous literature, and indicates that the PLGA-SBC porous microparticle substrates are promising for in vitro tumor or tissue development.

A central problem of neuroscience involves uncovering the principles governing the organization of nervous systems which ensure robustness in brain development. The nematode Caenorhabditis elegans provides us with a model organism for studying this question. In this paper, we focus on the invariant connection structure and spatial arrangement of the neurons comprising the somatic neuronal network of this organism to understand the key developmental constraints underlying its design. We observe that neurons with certain shared characteristics—such as, neural process lengths, birth time cohort, lineage and bilateral symmetry—exhibit a preference for connecting to each other. Recognizing the existence of such homophily and their relative degree of importance in determining connection probability within neurons (for example, in synapses, symmetric pairing is the most dominant factor followed by birth time cohort, process length and lineage) helps in connecting specific neuronal attributes to the topological organization of the network. Further, the functional identities of neurons appear to dictate the temporal hierarchy of their appearance during the course of development. Providing crucial insights into principles that may be common across many organisms, our study shows how the trajectory in the developmental landscape constrains the structural organization of a nervous system., Author summary Nervous systems of even the simplest of organisms involve a large array of neurons communicating with each other through a bewildering pattern of interconnections. What are the forces that govern the formation of this complex network? Using the somatic nervous system of the nematode Caenorhabditis elegans, we show how developmental constraints reflected by the symmetric pairing, birth times, process lengths and cell lineages of individual neurons are related to the observed spatial arrangement of neurons, as well as, the structural and functional organization of the network in the adult nematode. Our work suggests that focusing on the developmental trajectory, which complements approaches involving optimality considerations, may reveal the strategies underlying the development of a nervous system that may be robust across organisms.

Legionella pneumophila (L. pneumophila) is a gram-negative bacterium that replicates in a compartment that resembles the host endoplasmic reticulum (ER). To create its replicative niche, L. pneumophila manipulates host membrane traffic and fusion machineries. Bacterial proteins called Legionella effectors are translocated into the host cytosol and play a crucial role in these processes. In an early stage of infection, Legionella subverts ER-derived vesicles (ERDVs) by manipulating GTPase Rab1 to facilitate remodeling of the Legionella-containing vacuole (LCV). Subsequently, the LCV associates with the ER in a mechanism that remains elusive. In this study, we show that L. pneumophila recruits GTPases Rab33B and Rab6A, which regulate vesicle trafficking from the Golgi to the ER, to the LCV to promote the association of LCV with the ER. We found that recruitment of Rab6A to the LCV depends on Rab33B. Legionella effector SidE family proteins, which phosphoribosyl-ubiquitinate Rab33B, were found to be necessary for the recruitment of Rab33B to the LCV. Immunoprecipitation experiments revealed that L. pneumophila facilitates the interaction of Rab6 with ER-resident SNAREs comprising syntaxin 18, p31, and BNIP1, but not tethering factors including NAG, RINT-1, and ZW10, which are normally required for syntaxin 18-mediated fusion of Golgi-derived vesicles with the ER. Our results identified a Rab33B-Rab6A cascade on the LCV and the interaction of Rab6 with ER-resident SNARE proteins for the association of LCV with the ER and disclosed the unidentified physiological role of SidE family proteins., Author summary Legionella pneumophila causes a sever pneumonia called Legionnaires’ disease and a threat of this disease has increased on a world-wide scale. As a feature of L. pneumophila, it secrets over 300 bacterial effectors to adapt and survive inside the host and many of effectors modify the host proteins in a unique manner. L. pneumophila is known to travel inside the host and final destination of this pathogens is the host ER. In the initial step of this travel, L. pneumophila subverts host early vesicular trafficking to remodel the membrane composition of Legionella-containing vacuole (LCV). Although this remodeling process has been well characterized, the molecular machinery of association of remodeled vacuoles with the ER is still obscure. This paper shows that the host GTPases Rab6A and Rab33B, both of which control Golgi-to-ER traffic, are recruited to the LCV in a cascade manner and are required for the association of LCVs with the ER through the interaction between Rab6A and ER-resident t-SNARE proteins. Of note, we demonstrate that a bacteria-specific Rab33B modification called phosphoribosyl-ubiquitination by Legionella effectors proteins of the SidE family is essential for the recruitment of Rab33B to the LCV.

Arterial growth and remodeling at the tissue level is driven by mechanobiological processes at cellular and sub-cellular levels. Although it is widely accepted that cells seek to promote tissue homeostasis in response to biochemical and biomechanical cues—such as increased wall stress in hypertension—the ways by which these cues translate into tissue maintenance, adaptation, or maladaptation are far from understood. In this paper, we present a logic-based computational model for cell signaling within the arterial wall, aiming to predict changes in extracellular matrix turnover and cell phenotype in response to pressure-induced wall stress, flow-induced wall shear stress, and exogenous sources of angiotensin II, with particular interest in mouse models of hypertension. We simulate a number of experiments from the literature at both the cell and tissue level, involving single or combined inputs, and achieve high qualitative agreement in most cases. Additionally, we demonstrate the utility of this modeling approach for simulating alterations (in this case knockdowns) of individual nodes within the signaling network. Continued modeling of cellular signaling will enable improved mechanistic understanding of arterial growth and remodeling in health and disease, and will be crucial when considering potential pharmacological interventions., Author summary Biological soft tissues are characterized by continuous production and removal of material, which endows them with a remarkable ability to adapt to changes in their biochemical and biomechanical environments. For arteries, mechanical stimuli result primarily from changes in blood pressure or flow, and biochemical changes are induced by multiple factors, including pharmacological intervention. In order to understand how arterial properties are maintained in health, or how they adapt or fail to adapt in disease, we must understand better how these diverse stimuli affect material turnover. Extracellular matrix is tightly regulated by mechano-sensing and mechano-regulation, and therefore cell signaling, thus we present a computational model of relevant signaling pathways within the vascular wall, with the aim of predicting changes in wall composition and function in response to three main inputs: pressure-induced wall stress, flow-induced wall shear stress, and exogenous angiotensin II. We obtain qualitative agreement with a range of experimental studies from the literature, and provide illustrative examples demonstrating how such models can be used to further our understanding of arterial remodeling.

The Hybrid Automata Library (HAL) is a Java Library developed for use in mathematical oncology modeling. It is made of simple, efficient, generic components that can be used to model complex spatial systems. HAL’s components can broadly be classified into: on- and off-lattice agent containers, finite difference diffusion fields, a GUI building system, and additional tools and utilities for computation and data collection. These components are designed to operate independently and are standardized to make them easy to interface with one another. As a demonstration of how modeling can be simplified using our approach, we have included a complete example of a hybrid model (a spatial model with interacting agent-based and PDE components). HAL is a useful asset for researchers who wish to build performant 1D, 2D and 3D hybrid models in Java, while not starting entirely from scratch. It is available on GitHub at https://github.com/MathOnco/HAL under the MIT License. HAL requires the Java JDK version 1.8 or later to compile and run the source code., Author summary In this paper we introduce the Hybrid Automata Library (HAL) with the purpose of simplifying the implementation and sharing of hybrid models for use in mathematical oncology. Hybrid modeling is used in oncology to create spatial models of tissue, typically by modeling cells using agent-based techniques, and by modeling diffusible chemicals using partial differential equations (PDEs). HAL’s key components are designed to run agent-based models, PDEs, and visualization. The components are standardized and are completely decoupled, so models can be built with any combination of them. We first explore the philosophy behind HAL, then summarize the components. Lastly we demonstrate how the components work together with an example of a hybrid model, and a walk-through of the code used to construct it. HAL is open-source and will produce identical results on any machine that supports Java 8 and above, making it highly portable. We recommend HAL to modelers interested in spatial dynamics, even those outside of mathematical oncology, as the components are general enough to facilitate a variety of model types. A community page that provides a download link and online documentation can be found at https://halloworld.org.

A key challenge in the development of precision medicine is defining the phenotypic consequences of pharmacological modulation of specific target macromolecules. To address this issue, a variety of genetic, molecular and chemical tools can be used. All of these approaches can produce misleading results if the specificity of the tools is not well understood and the proper controls are not performed. In this paper we illustrate these general themes by providing detailed studies of small molecule inhibitors of the enzymatic activity of two members of the SMYD branch of the protein lysine methyltransferases, SMYD2 and SMYD3. We show that tool compounds as well as CRISPR/Cas9 fail to reproduce many of the cell proliferation findings associated with SMYD2 and SMYD3 inhibition previously obtained with RNAi based approaches and with early stage chemical probes.

© 2017 Walsh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The Min protein system creates a dynamic spatial pattern in Escherichia coli cells where the proteins MinD and MinE oscillate from pole to pole. MinD positions MinC, an inhibitor of FtsZ ring formation, contributing to the mid-cell localization of cell division. In this paper, Fourier analysis is used to decompose experimental and model MinD spatial distributions into time-dependent harmonic components. In both experiment and model, the second harmonic component is responsible for producing a mid-cell minimum in MinD concentration. The features of this harmonic are robust in both experiment and model. Fourier analysis reveals a close correspondence between the time-dependent behaviour of the harmonic components in the experimental data and model. Given this, each molecular species in the model was analysed individually. This analysis revealed that membrane-bound MinD dimer shows the mid-cell minimum with the highest contrast when averaged over time, carrying the strongest signal for positioning the cell division ring. This concurs with previous data showing that the MinD dimer binds to MinC inhibiting FtsZ ring formation. These results show that non-linear interactions of Min proteins are essential for producing the mid-cell positioning signal via the generation of second-order harmonic components in the time-dependent spatial protein distribution.

Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus, one may represent an OV by two parameters: its replication potential and its immunogenicity. In this paper we consider a combination therapy with OV and a checkpoint inhibitor, anti-PD-1. We evaluate the efficacy of the combination therapy in terms of the tumor volume at some later time, for example, 6 months from initial treatment. Since T cells kill not only virus-free cancer cells but also virus-infected cancer cells, the following question arises: Does increasing the amount of the checkpoint inhibitor always improve the efficacy? We address this question, by a mathematical model consisting of a system of partial differential equations. We use the model to construct, by simulations, an efficacy map in terms of the doses of the checkpoint inhibitor and the OV injection. We show that there are regions in the map where an increase in the checkpoint inhibitor actually decreases the efficacy of the treatment. We also construct efficacy maps with checkpoint inhibitor vs. the replication potential of the virus that show the same antagonism, namely, an increase in the checkpoint inhibitor may actually decrease the efficacy. These results have implications for clinical trials.

Viral infections are one of the major causes of death worldwide, with HIV infection alone resulting in over 1.2 million casualties per year. Antiviral drugs are now being administered for a variety of viral infections, including HIV, hepatitis B and C, and influenza. These therapies target a specific phase of the virus’s life cycle, yet their ultimate success depends on a variety of factors, such as adherence to a prescribed regimen and the emergence of viral drug resistance. The epidemiology and evolution of drug resistance have been extensively characterized, and it is generally assumed that drug resistance arises from mutations that alter the virus’s susceptibility to the direct action of the drug. In this paper, we consider the possibility that a virus population can evolve towards synchronizing its life cycle with the pattern of drug therapy. The periodicity of the drug treatment could then allow for a virus strain whose life cycle length is a multiple of the dosing interval to replicate only when the concentration of the drug is lowest. This process, referred to as “drug tolerance by synchronization”, could allow the virus population to maximize its overall fitness without having to alter drug binding or complete its life cycle in the drug’s presence. We use mathematical models and stochastic simulations to show that life cycle synchronization can indeed be a mechanism of viral drug tolerance. We show that this effect is more likely to occur when the variability in both viral life cycle and drug dose timing are low. More generally, we find that in the presence of periodic drug levels, time-averaged calculations of viral fitness do not accurately predict drug levels needed to eradicate infection, even if there is no synchronization. We derive an analytical expression for viral fitness that is sufficient to explain the drug-pattern-dependent survival of strains with any life cycle length. We discuss the implications of these findings for clinically relevant antiviral strategies., Author summary Viral infections such as HIV, hepatitis B, hepatitis C, and influenza may be treated with antiviral drug therapy. These drugs generally block a specific phase of the virus’s life cycle, preventing it from replicating in the body. Often, a virus population can evolve drug resistance by acquiring mutations that prevent the drug from binding and inhibiting it. Here, we propose a new mechanism of drug resistance. We use mathematical models and stochastic simulations to show that virus populations can build resistance to antiviral therapies by synchronizing their life cycle with the dosing pattern of the drug. This process, which we refer to as “drug tolerance by synchronization”, can allow the virus to increase its overall fitness in the presence of the drug without altering drug binding. We show that viral strains whose life cycle lengths are approximately integer multiples of the time between drug doses possess an advantage during drug therapy. They can outcompete unsynchronized strains and lead to therapy failure with drugs that would otherwise have been successful.

Budding yeast, which undergoes polarized growth during budding and mating, has been a useful model system to study cell polarization. Bud sites are selected differently in haploid and diploid yeast cells: haploid cells bud in an axial manner, while diploid cells bud in a bipolar manner. While previous studies have been focused on the molecular details of the bud site selection and polarity establishment, not much is known about how different budding patterns give rise to different functions at the population level. In this paper, we develop a two-dimensional agent-based model to study budding yeast colonies with cell-type specific biological processes, such as budding, mating, mating type switch, consumption of nutrients, and cell death. The model demonstrates that the axial budding pattern enhances mating probability at an early stage and the bipolar budding pattern improves colony development under nutrient limitation. Our results suggest that the frequency of mating type switch might control the trade-off between diploidization and inbreeding. The effect of cellular aging is also studied through our model. Based on the simulations, colonies initiated by an aged haploid cell show declined mating probability at an early stage and recover as the rejuvenated offsprings become the majority. Colonies initiated with aged diploid cells do not show disadvantage in colony expansion possibly due to the fact that young cells contribute the most to colony expansion., Author summary Budding yeast is a model organism in understanding fundamental aspects of eukaryotic cells, such as cell polarization and cell aging. Previously, extensive research has focused on the molecular mechanisms of biological processes in yeast, but many questions regarding yeast budding remain unsolved. For example, how do different budding patterns affect yeast colony growth? How does declined spatial order due to aging impact the colony at the population level? To address these questions, we developed a computational agent-based model, which incorporates key biological processes, the effect of aging, as well as cell-environment interaction. We performed and analyzed a large number of simulations for a variety of situations, and obtained insightful results. We found that axial budding pattern enhances the percentage of diploid cells at early stage and bipolar budding pattern improves colony development under nutrient limitation; the frequency of mating type switch might control the trade-off between diploidization and inbreeding; aging affects the percentage of diploid cells in colonies initiated by a single haploid cell, but does not have much influence in the expansion of colonies initiated by diploid cells. The framework of the model can be extended to study other important systems, such as tissue with stem cell lineage.

Many multicellular systems problems can only be understood by studying how cells move, grow, divide, interact, and die. Tissue-scale dynamics emerge from systems of many interacting cells as they respond to and influence their microenvironment. The ideal “virtual laboratory” for such multicellular systems simulates both the biochemical microenvironment (the “stage”) and many mechanically and biochemically interacting cells (the “players” upon the stage). PhysiCell—physics-based multicellular simulator—is an open source agent-based simulator that provides both the stage and the players for studying many interacting cells in dynamic tissue microenvironments. It builds upon a multi-substrate biotransport solver to link cell phenotype to multiple diffusing substrates and signaling factors. It includes biologically-driven sub-models for cell cycling, apoptosis, necrosis, solid and fluid volume changes, mechanics, and motility “out of the box.” The C++ code has minimal dependencies, making it simple to maintain and deploy across platforms. PhysiCell has been parallelized with OpenMP, and its performance scales linearly with the number of cells. Simulations up to 105-106 cells are feasible on quad-core desktop workstations; larger simulations are attainable on single HPC compute nodes. We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on the dynamics of hanging drop tumor spheroids and ductal carcinoma in situ (DCIS) of the breast. We demonstrate stochastic motility, chemical and contact-based interaction of multiple cell types, and the extensibility of PhysiCell with examples in synthetic multicellular systems (a “cellular cargo delivery” system, with application to anti-cancer treatments), cancer heterogeneity, and cancer immunology. PhysiCell is a powerful multicellular systems simulator that will be continually improved with new capabilities and performance improvements. It also represents a significant independent code base for replicating results from other simulation platforms. The PhysiCell source code, examples, documentation, and support are available under the BSD license at http://PhysiCell.MathCancer.org and http://PhysiCell.sf.net., Author summary This paper introduces PhysiCell: an open source, agent-based modeling framework for 3-D multicellular simulations. It includes a standard library of sub-models for cell fluid and solid volume changes, cycle progression, apoptosis, necrosis, mechanics, and motility. PhysiCell is directly coupled to a biotransport solver to simulate many diffusing substrates and cell-secreted signals. Each cell can dynamically update its phenotype based on its microenvironmental conditions. Users can customize or replace the included sub-models. PhysiCell runs on a variety of platforms (Linux, OSX, and Windows) with few software dependencies. Its computational cost scales linearly in the number of cells. It is feasible to simulate 500,000 cells on quad-core desktop workstations, and millions of cells on single HPC compute nodes. We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on hanging drop tumor spheroids (HDS) and ductal carcinoma in situ (DCIS) of the breast. We demonstrate contact- and chemokine-based interactions among multiple cell types with examples in synthetic multicellular bioengineering, cancer heterogeneity, and cancer immunology. We developed PhysiCell to help the scientific community tackle multicellular systems biology problems involving many interacting cells in multi-substrate microenvironments. PhysiCell is also an independent, cross-platform codebase for replicating results from other simulators.

In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment.

Cell intercalation is a highly directed cell rearrangement that is essential for animal morphogenesis. As such, intercalation requires orchestration of cell polarity across the plane of the tissue. CDC-42 is a Rho family GTPase with key functions in cell polarity, yet its role during epithelial intercalation has not been established because its roles early in embryogenesis have historically made it difficult to study. To circumvent these early requirements, in this paper we use tissue-specific and conditional loss-of-function approaches to identify a role for CDC-42 during intercalation of the Caenorhabditis elegans dorsal embryonic epidermis. CDC-42 activity is enriched in the medial tips of intercalating cells, which extend as cells migrate past one another. Moreover, CDC-42 is involved in both the efficient formation and orientation of cell tips during cell rearrangement. Using conditional loss-of-function we also show that the PAR complex functions in tip formation and orientation. Additionally, we find that the sole C. elegans Eph receptor, VAB-1, functions during this process in an Ephrin-independent manner. Using epistasis analysis, we find that vab-1 lies in the same genetic pathway as cdc-42 and is responsible for polarizing CDC-42 activity to the medial tip. Together, these data establish a previously uncharacterized role for polarized CDC-42, in conjunction with PAR-6, PAR-3 and an Eph receptor, during epithelial intercalation., Author Summary As embryos develop, tissues must change shape to establish an animal’s form. One key form-shaping movement, cell intercalation, often occurs when a tissue elongates in a preferred direction. How cells in epithelial sheets can intercalate while maintaining tissue integrity is not well understood. Here we use the dorsal epidermis in embryos of the nematode worm, C. elegans, to study cell intercalation. As cells begin to intercalate, they form highly polarized tips that lead their migration. While some mechanisms that polarize intercalating cells have been established in other systems, our work identifies a new role for CDC-42—a highly conserved, highly regulated protein that controls the actin cytoskeleton. We previously established that a related protein, Rac, is involved in tip extension during dorsal intercalation. CDC-42 also contributes to this process in addition to helping orient the extending tip. CDC-42 appears to work in conjunction with two other known cell polarity proteins, PAR-3 and PAR-6, and the cell surface receptor, VAB-1. Our work identifies a novel pathway involving proteins conserved from worms to humans that regulates a ubiquitous process during animal development.

Experimental and mathematical studies in immunology have revealed that the dynamics of the programmed T cell response to vigorous infection can be conveniently modelled using a sigmoidal or a discontinuous immune response function. This paper hypothesizes strong synergies between this existing work and the dynamical behaviour of engineering systems with a variable structure control (VSC) law. These findings motivate the interpretation of the immune system as a variable structure control system. It is shown that dynamical properties as well as conditions to analytically assess the transition from health to disease can be developed for the specific T cell response from the theory of variable structure control. In particular, it is shown that the robustness properties of the specific T cell response as observed in experiments can be explained analytically using a VSC perspective. Further, the predictive capacity of the VSC framework to determine the T cell help required to overcome chronic Lymphocytic Choriomeningitis Virus (LCMV) infection is demonstrated. The findings demonstrate that studying the immune system using variable structure control theory provides a new framework for evaluating immunological dynamics and experimental observations. A modelling and simulation tool results with predictive capacity to determine how to modify the immune response to achieve healthy outcomes which may have application in drug development and vaccine design.

Abdominal aortic aneurysm (AAA) is a localized enlargement of the abdominal aorta, such that the diameter exceeds 3 cm. The natural history of AAA is progressive growth leading to rupture, an event that carries up to 90% risk of mortality. Hence there is a need to predict the growth of the diameter of the aorta based on the diameter of a patient's aneurysm at initial screening and aided by non-invasive biomarkers. IL-6 is overexpressed in AAA and was suggested as a prognostic marker for the risk in AAA. The present paper develops a mathematical model which relates the growth of the abdominal aorta to the serum concentration of IL-6. Given the initial diameter of the aorta and the serum concentration of IL-6, the model predicts the growth of the diameter at subsequent times. Such a prediction can provide guidance to how closely the patient's abdominal aorta should be monitored. The mathematical model is represented by a system of partial differential equations taking place in the aortic wall, where the media is assumed to have the constituency of an hyperelastic material.

The degradation of cytosol-invading pathogens by autophagy, a process known as xenophagy, is an important mechanism of the innate immune system. Inside the host, Salmonella Typhimurium invades epithelial cells and resides within a specialized intracellular compartment, the Salmonella-containing vacuole. A fraction of these bacteria does not persist inside the vacuole and enters the host cytosol. Salmonella Typhimurium that invades the host cytosol becomes a target of the autophagy machinery for degradation. The xenophagy pathway has recently been discovered, and the exact molecular processes are not entirely characterized. Complete kinetic data for each molecular process is not available, so far. We developed a mathematical model of the xenophagy pathway to investigate this key defense mechanism. In this paper, we present a Petri net model of Salmonella xenophagy in epithelial cells. The model is based on functional information derived from literature data. It comprises the molecular mechanism of galectin-8-dependent and ubiquitin-dependent autophagy, including regulatory processes, like nutrient-dependent regulation of autophagy and TBK1-dependent activation of the autophagy receptor, OPTN. To model the activation of TBK1, we proposed a new mechanism of TBK1 activation, suggesting a spatial and temporal regulation of this process. Using standard Petri net analysis techniques, we found basic functional modules, which describe different pathways of the autophagic capture of Salmonella and reflect the basic dynamics of the system. To verify the model, we performed in silico knockout experiments. We introduced a new concept of knockout analysis to systematically compute and visualize the results, using an in silico knockout matrix. The results of the in silico knockout analyses were consistent with published experimental results and provide a basis for future investigations of the Salmonella xenophagy pathway., Author Summary Salmonellae are Gram-negative bacteria, which cause the majority of foodborne diseases worldwide. Serovars of Salmonella cause a broad range of diseases, ranging from diarrhea to typhoid fever in a variety of hosts. In the year 2010, Salmonella Typhi caused 7.6 million foodborne diseases and 52 000 deaths, and Salmonella enterica was responsible for 78.7 million diseases and 59 000 deaths. After invasion of Salmonella into host epithelial cells, a small fraction of Salmonella escapes from a specialized intracellular compartment and replicates inside the host cytosol. Xenophagy is a host defense mechanism to protect the host cell from cytosolic pathogens. Understanding how Salmonella is recognized and targeted for xenophagy is an important subject of current research. To the best of our knowledge, no mathematical model has been presented so far, describing the process of Salmonella Typhimurium xenophagy. Here, we present a manually curated and mathematically verified theoretical model of Salmonella Typhimurium xenophagy in epithelial cells, which is consistent with the current state of knowledge. Our model reproduces literature data and postulates new hypotheses for future investigations.

Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension. We seek to determine whether histologic scale measures of the erratic distribution of blood vessels within a tumour can be used to predict differing radiation response. Using a two-dimensional hybrid cellular automaton model of tumour growth, we evaluate the effect of vessel distribution on cell survival outcomes of simulated radiation therapy. Using the standard equations for the oxygen enhancement ratio for cell survival probability under differing oxygen tensions, we calculate average radiation effect over a range of different vessel densities and organisations. We go on to quantify the vessel distribution heterogeneity and measure spatial organization using Ripley’s L function, a measure designed to detect deviations from complete spatial randomness. We find that under differing regimes of vessel density the correlation coefficient between the measure of spatial organization and radiation effect changes sign. This provides not only a useful way to understand the differences seen in radiation effect for tissues based on vessel architecture, but also an alternate explanation for the vessel normalization hypothesis., Author Summary In this paper we use a mathematical model, called a hybrid cellular automaton, to study the effect of different vessel distributions on radiation therapy outcomes at the cellular level. We show that the correlation between radiation outcome and spatial organization of vessels changes signs between relatively low and high vessel density. Specifically, that for relatively low vessel density, radiation efficacy is decreased when vessels are more homogeneously distributed, and the opposite is true, that radiation efficacy is improved, when vessel organisation is normalised in high densities. This result suggests an alteration to the vessel normalization hypothesis which states that normalisation of vascular beds should improve radio- and chemo-therapeutic response, but has failed to be validated in clinical studies. In this alteration, we show that Ripley’s L function allows discrimination between vascular architectures in different density regimes in which the standard hypothesis holds and does not hold. Further, we find that this information can be used to augment quantitative histologic analysis of tumours to aid radiation dose personalisation.

It is well accepted that influenza A virus predisposes individuals to often more severe superinfections with Streptococcus pneumonia. However, the mechanisms that lead to this synergy are not clearly understood. Recent data suggests that competent Th17 immunity is crucial to clearance and protection from invasive pneumococcal disease of the lung. We demonstrate that early influenza infection significantly reduced levels of pneumococcus driven IL-12p70, IL-23 and IL-27 in human monocytes with significant impairment of IL-17A and IFN-γ in HKSP-treated allogeneic mixed lymphocyte cultures. We also provide evidence to suggest that the hemagglutinin component of the virus is at least partially responsible for this downward pressure on IL-17 responses but surprisingly this suppression occurs despite robust IL-23 levels in hemagglutinin-treated monocyte cultures. This study demonstrates that influenza can directly affect the immunological pathways that promote appropriate responses to Streptococcus pneumonia in human immune cells. Importance Influenza virus is highly contagious and poses substantial public health problems due to its strong association with morbidity and mortality. Approximately 250,000–500,000 deaths are caused by seasonal influenza virus annually, and this figure increases during periods of pandemic infections. Most of these deaths are due to secondary bacterial pneumonia. Influenza-bacterial superinfection can result in hospitalisation and/or death of both patients with pre-existing lung disease or previously healthy individuals. The importance of our research is in determining that influenza and its component haemagglutinin has a direct effect on the classic pneumococcus induced pathways to IL-17A in our human ex vivo model. Our understanding of the mechanism which leaves people exposed to influenza infection during superinfection remain unresolved. This paper demonstrates that early infection of monocytes inhibits an arm of immunity crucial to bacterial clearance. Understanding this mechanism may provide alternative interventions in the case of superinfection with antimicrobial resistant strains of bacteria.

Many different physiological processes affect the growth of malignant lesions and their response to therapy. Each of these processes is spatially and genetically heterogeneous; dynamically evolving in time; controlled by many other physiological processes, and intrinsically random and unpredictable. The objective of this paper is to show that all of these properties of cancer physiology can be treated in a unified, mathematically rigorous way via the theory of random processes. We treat each physiological process as a random function of position and time within a tumor, defining the joint statistics of such functions via the infinite-dimensional characteristic functional. The theory is illustrated by analyzing several models of drug delivery and response of a tumor to therapy. To apply the methodology to precision cancer therapy, we use maximum-likelihood estimation with Emission Computed Tomography (ECT) data to estimate unknown patient-specific physiological parameters, ultimately demonstrating how to predict the probability of tumor control for an individual patient undergoing a proposed therapeutic regimen.

Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second leading cause of cancer mortality by 2030. PDAC remains resistant to the majority of systemic chemotherapies. In this paper, we explore if epigenetic sensitization can improve chemotherapy response in PDAC. Multiple PDAC cell lines were tested with serial concentrations of the epigenetic modulators 5-azacitidine (Aza) and guadecitabine (SGI-110). Guadecitabine was effective at inhibiting the expression of DNA Methyltransferase 1 (DNMT1) and in decreasing cell viability at nanomolar concentrations. We also report that guadecitabine has increased efficacy following a delay period or as we reference, a 'rest period'. Sensitization with guadecitabine improved response to the chemotherapeutic agent-Irinotecan- as measured by decreased cell viability and accompanied by an increase in caspase activity. Additional studies are needed to understand the mechanism of action.

Cross-presentation of apoptotic cell associated antigens by immature dendritic cells prevents the activation of self reactive CD8 T cells. Tolerized self reactive CD8 T cells down-regulate IL-7R expression on their surface. Whether over-expression of IL-7R can reverse their fate and function has not been examined. In this paper, we showed forced expression of IL-7R in OT-I T cells by a transgene enhanced CD8 T cell mediated diabetes in the RIP-mOVA model. Although IL-7R Tg (transgenic) did not completely reverse the deletion of OT-I T cells, it provided a significant survival advantage over w.t OT-I T cells. Furthermore, IL7R Tg OT-I T cells isolated from diabetic pancreata displayed increased production of IFN-γ, higher expression of T-bet, and increased externalization of CD107a. We also found that immature DCs containing apoptotic cells expressed high levels of PDL-1 on their surface. Although IL-7R Tg did not change PD1 expression on activated OT-I cells in vivo, the transgene enabled a significantly lower number of OT-I T cells to induce diabetes in the absence of PDL-1. Our results demonstrated that forced expression of IL-7R not only improved the functionality of tolerized CD8 T cells, it also acted in synergy with PDL-1 deficiency to further promote CD8 T cell cytotoxicity to self antigens.

This paper proposes a method to detect corresponding vertex pairs between planar tessellation datasets. Applying an agglomerative hierarchical co-clustering, the method finds geometrically corresponding cell-set pairs from which corresponding vertex pairs are detected. Then, the map transformation is performed with the vertex pairs. Since these pairs are independently detected for each corresponding cell-set pairs, the method presents improved matching performance regardless of locally uneven positional discrepancies between dataset. The proposed method was applied to complicated synthetic cell datasets assumed as a cadastral map and a topographical map, and showed an improved result with the F-measures of 0.84 comparing to a previous matching method with the F-measure of 0.48.

We performed a systematic review to identify all original publications describing the asymmetric inheritance of cellular organelles in normal animal eukaryotic cells and to critique the validity and imprecision of the evidence. Searches were performed in Embase, MEDLINE and Pubmed up to November 2015. Screening of titles, abstracts and full papers was performed by two independent reviewers. Data extraction and validity were performed by one reviewer and checked by a second reviewer. Study quality was assessed using the SYRCLE risk of bias tool, for animal studies and by developing validity tools for the experimental model, organelle markers and imprecision. A narrative data synthesis was performed. We identified 31 studies (34 publications) of the asymmetric inheritance of organelles after mitotic or meiotic division. Studies for the asymmetric inheritance of centrosomes (n = 9); endosomes (n = 6), P granules (n = 4), the midbody (n = 3), mitochondria (n = 3), proteosomes (n = 2), spectrosomes (n = 2), cilia (n = 2) and endoplasmic reticulum (n = 2) were identified. Asymmetry was defined and quantified by variable methods. Assessment of the statistical reliability of the results indicated only two studies (7%) were judged to have low concern, the majority of studies (77%) were 'unclear' and five (16%) were judged to have 'high concerns'; the main reasons were low technical repeats (

Tudor containing protein 6 (TDRD6) is a male germ line-specific protein essential for chromatoid body (ChB) structure, elongated spermatid development and male fertility. Here we show that in meiotic prophase I spermatocytes TDRD6 interacts with the key protein arginine methyl transferase PRMT5, which supports splicing. TDRD6 also associates with spliceosomal core protein SmB in the absence of RNA and in an arginine methylation dependent manner. In Tdrd6-/- diplotene spermatocytes PRMT5 association with SmB and arginine dimethylation of SmB are much reduced. TDRD6 deficiency impairs the assembly of spliceosomes, which feature 3.5-fold increased levels of U5 snRNPs. In the nucleus, these deficiencies in spliceosome maturation correlate with decreased numbers of SMN-positive bodies and Cajal bodies involved in nuclear snRNP maturation. Transcriptome analysis of TDRD6-deficient diplotene spermatocytes revealed high numbers of splicing defects such as aberrant usage of intron and exons as well as aberrant representation of splice junctions. Together, this study demonstrates a novel function of TDRD6 in spliceosome maturation and mRNA splicing in prophase I spermatocytes., Author summary Very little is known about splicing and its regulation in germ cells, particularly during meiosis. This paper describes the role of a male germ cell-specific protein, Tudor containing protein 6 (TDRD6), in assembly of the spliceosome in spermatocytes. We show that in prophase I TDRD6 interacts with the key protein methyltransferase of the splicing pathway PRMT5. PRMT5 methylates arginines in substrate proteins. In a methylation dependent manner, TDRD6 also associates with spliceosomal core protein SmB in the absence of RNA, thus before an RNP-type spliceosome has been assembled. In Tdrd6-/- diplotene spermatocytes PRMT5’s association with SmB and arginine dimethylation of SmB are much reduced. Abrogation of arginine methylation impairs the assembly of spliceosomes and the presence of the spliceosomal RNA U5 is aberrantly increased. These deficiencies in spliceosome maturation correlate with decreased numbers of Cajal bodies and gems involved in later stages, i.e. nuclear snRNP maturation. To reveal functional consequences of these deficiencies, transcriptome analysis of primary spermatocytes showed high numbers of splicing defects such as aberrant usage of intron and exons as well as aberrant representation of splice junctions upon TDRD6 loss. This study reveals a novel function of TDRD6 in spliceosome maturation and mRNA splicing in spermatocytes

HiF-1α is the central protein driving the cellular response to hypoxia. Its accumulation in cancer cells is linked to the appearance of chemoresistant and aggressive tumor phenotypes. As a consequence, understanding the regulation of HiF-1α dynamics is a major issue to design new anti-cancer therapies. In this paper, we propose a model of the hypoxia pathway, involving HiF-1α and its inhibitor pVHL. Based on data from the literature, we made the hypothesis that the regulation of HiF-1α involves two compartments (nucleus and cytoplasm) and a constitutive shuttle of the pVHL protein between them. We first show that this model captures correctly the main features of HiF-1α dynamics, including the bi-exponential degradation profile in normoxia, the kinetics of induction in hypoxia, and the switch-like accumulation. Second, we simulated the effects of a hypoxia/reoxygenation event, and show that it generates a strong instability of HiF-1α. The protein concentration rapidly increases 3 hours after the reoxygenation, and exhibits an oscillating pattern. This effect vanishes if we do not consider compartmentalization of HiF-1α. This result can explain various counter-intuitive observations about the specific molecular and cellular response to the reoxygenation process. Third, we simulated the HiF-1α dynamics in the tumor case. We considered different types of mutations associated with tumorigenesis, and we compared their consequences on HiF-1α dynamics. Then, we tested different therapeutics strategies. We show that a therapeutic decrease of HiF-1α nuclear level is not always correlated with an attenuation of reoxygenation-induced instabilities. Thus, it appears that the design of anti-HiF-1α therapies have to take into account these two aspects to maximize their efficiency.

Huang Qin (root of Scutellaria baicalensis) is a widely used herb in different countries for adjuvant therapy of inflammation, diabetes, hypertension, different kinds of cancer and virus related diseases. Baicalin is the main flavonoid in this herb and has been extensively studied for 30 years. The angiogenic effect of herb Huang Qin extract and baicalin was found 13 years ago, however, the results were controversial with pro-angiogenic effect in some studies and anti-angiogenic effect in others. In this paper, the angiogenic effect of baicalin, its aglycone form baicalein and aqueous extract of Huang Qin was studied in chick embryo chorioallantoic membrane (CAM) model. Dose dependent dual effect was found in both aqueous extract and baicalin, but not in baicalein, in which only inhibitory effect was observed. In order to reveal the cellular and molecular mechanism of how baicalin and baicalein affect angiogenesis, cell proliferation and programmed cell death assays were performed in treated CAM. In addition, quantitative PCR array including 84 angiogenesis related genes was used to detect high and low dosage of baicalin and baicalein responsive genes. Low dose baicalin increased cell proliferation in developing blood vessels through upregulation of multiple angiogenic genes expression, but high dose baicalin induced cell death, performing inhibitory effect on angiogenesis. Both high and low dose of baicalein down regulated the expression of multiple angiogenic genes, decreased cell proliferation, and leads to inhibitory effects on angiogenesis.

Co-clustering, often called biclustering for two-dimensional data, has found many applications, such as gene expression data analysis and text mining. Nowadays, a variety of multi-dimensional arrays (tensors) frequently occur in data analysis tasks, and co-clustering techniques play a key role in dealing with such datasets. Co-clusters represent coherent patterns and exhibit important properties along all the modes. Development of robust co-clustering techniques is important for the detection and analysis of these patterns. In this paper, a co-clustering method based on hyperplane detection in singular vector spaces (HDSVS) is proposed. Specifically in this method, higher-order singular value decomposition (HOSVD) transforms a tensor into a core part and a singular vector matrix along each mode, whose row vectors can be clustered by a linear grouping algorithm (LGA). Meanwhile, hyperplanar patterns are extracted and successfully supported the identification of multi-dimensional co-clusters. To validate HDSVS, a number of synthetic and biological tensors were adopted. The synthetic tensors attested a favorable performance of this algorithm on noisy or overlapped data. Experiments with gene expression data and lineage data of embryonic cells further verified the reliability of HDSVS to practical problems. Moreover, the detected co-clusters are well consistent with important genetic pathways and gene ontology annotations. Finally, a series of comparisons between HDSVS and state-of-the-art methods on synthetic tensors and a yeast gene expression tensor were implemented, verifying the robust and stable performance of our method.

Nowadays, drug abuse and addiction are serious public health problems in the USA. Methamphetamine (METH) is one of the most abused drugs and is known to cause brain damage after repeated exposure. In this paper, we conducted a neuroproteomic study to evaluate METH-induced brain protein dynamics, following a two-week chronic regimen of an escalating dose of METH exposure. Proteins were extracted from rat brain hippocampal and olfactory bulb tissues and subjected to liquid chromatography-mass spectrometry (LC-MS/MS) analysis. Both shotgun and targeted proteomic analysis were performed. Protein quantification was initially based on comparing the spectral counts between METH exposed animals and their control counterparts. Quantitative differences were further confirmed through multiple reaction monitoring (MRM) LC-MS/MS experiments. According to the quantitative results, the expression of 18 proteins (11 in the hippocampus and 7 in the olfactory bulb) underwent a significant alteration as a result of exposing rats to METH. 13 of these proteins were up-regulated after METH exposure while 5 were down-regulated. The altered proteins belonging to different structural and functional families were involved in processes such as cell death, inflammation, oxidation, and apoptosis.

The p53 transcription factor is a regulator of key cellular processes including DNA repair, cell cycle arrest, and apoptosis. In this theoretical study, we investigate how the complex circuitry of the p53 network allows for stochastic yet unambiguous cell fate decision-making. The proposed Markov chain model consists of the regulatory core and two subordinated bistable modules responsible for cell cycle arrest and apoptosis. The regulatory core is controlled by two negative feedback loops (regulated by Mdm2 and Wip1) responsible for oscillations, and two antagonistic positive feedback loops (regulated by phosphatases Wip1 and PTEN) responsible for bistability. By means of bifurcation analysis of the deterministic approximation we capture the recurrent solutions (i.e., steady states and limit cycles) that delineate temporal responses of the stochastic system. Direct switching from the limit-cycle oscillations to the “apoptotic” steady state is enabled by the existence of a subcritical Neimark—Sacker bifurcation in which the limit cycle loses its stability by merging with an unstable invariant torus. Our analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of Wip1 and PTEN exhibit a broad spectrum of responses to DNA damage: from a fast transition to a high level of p53 killer (a p53 phosphoform which promotes commitment to apoptosis) in cells characterized by high PTEN and low Wip1 levels to long-lasting p53 level oscillations in cells having PTEN promoter methylated (as in, e.g., MCF-7 cell line)., Author Summary Cancers are diseases of signaling networks. Transcription factor p53 is a pivotal node of a network that integrates a variety of stress signals and governs critical processes of DNA repair, cell cycle arrest, and apoptosis. Somewhat paradoxically, despite the fact that carcinogenesis is prevalently caused by p53 network malfunction, most of our knowledge about p53 signaling is based on cancer or immortalized cell lines. In this paper, we construct a mathematical model of intact p53 network to understand dynamics of non-cancerous cells and then dynamics of cancerous cells by introducing perturbations to the regulatory system. Cell fate decisions are enabled by the presence of interlinked feedback loops which give rise to a rich repertoire of behaviors. We explain and analyze by means of numerical simulations how the dynamical structure of the regulatory system allows for generating unambiguous single-cell fate decisions, also in the case when the cell population splits into an apoptotic and a surviving subpopulation. Perturbation analysis provides an explanation why cancer cell lines known to have vastly diverse expression levels of p53 regulators can exhibit a broad spectrum of responses to DNA damage.

125I seeds coated with titanium are considered a safe and effective interstitial brachytherapy for tumors, while the cost of 125I seeds is a major problem for the patients implanting lots of seeds. The aim of this paper was to develop a novel silicone coating for 125I seeds with a lower cost. In order to show the radionuclide utilization ratio, the silicone was coated onto the seeds using the electro-spinning method and the radioactivity was evaluated, then the anti-tumor efficacy of silicone 125I seeds was compared with titanium 125I seeds. The seeds were divided into four groups: A (control), B (pure silicone), C (silicone 125I), D (titanium 125I) at 2 Gy or 4 Gy. Their anti-tumour activity and mechanism were assessed in vitro and in vivo using a human extrahepatic cholangiocarcinoma cell line FRH-0201 and tumor-bearing BALB/c nude mice. The silicone 125I seeds showed higher radioactivity; the rate of cell apoptosis in vitro and the histopathology in vivo demonstrated that the silicone 125I seeds shared similar anti-tumor efficacy with the titanium 125I seeds for the treatment of extrahepatic cholangiocarcinoma, while they have a much lower cost.

Desmosomes are intercellular adhesive junctions of major importance for tissue integrity. To allow cell motility and migration they are down-regulated in epidermal wound healing. Electron microscopy indicates that whole desmosomes are internalised by cells in tissues, but the mechanism of down-regulation is unclear. In this paper we provide an overview of the internalisation of half-desmosomes by cultured cells induced by calcium chelation. Our results show that: (i) half desmosome internalisation is dependent on conventional PKC isoforms; (ii) microtubules transport internalised half desmosomes to the region of the centrosome by a kinesin-dependent mechanism; (iii) desmosomal proteins remain colocalised after internalisation and are not recycled to the cell surface; (iv) internalised desmosomes are degraded by the combined action of lysosomes and proteasomes. We also confirm that half desmosome internalisation is dependent upon the actin cytoskeleton. These results suggest that half desmosomes are not disassembled and recycled during or after internalisation but instead are transported to the centrosomal region where they are degraded. These findings may have significance for the down-regulation of desmosomes in wounds.