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The breakthrough potentials of research papers can be explained by their boundary-spanning qualities. Here, for the first time, we apply the structural variation analysis (SVA) model and its affiliated metrics to investigate the extent to which such qualities characterize a group of Nobel Prize winning papers. We find that these papers share remarkable boundary-spanning traits, marked by exceptional abilities to connect disparate and topically-diverse clusters of research papers. Further, their publications exert structural variations on the scale that significantly alters the betweenness centrality distributions of existing intellectual space. Overall, SVA not only provides a set of leading indicators for describing future Nobel Prize winning papers, but also broadens our understanding of the similar prize-winning properties that may have been overlooked among other regular publications., 27 pages, 8 figures, 9 tables. Submitted to Frontiers in Research Metrics and Analytics

Efficient conversion of cellulosic sugars in cellulosic hydrolysates is important for economically viable production of biofuels from lignocellulosic biomass, but the goal remains a critical challenge. The present study reports a new approach for simultaneous fermentation of cellobiose and xylose by using the co-culture consisting of recombinant Saccharomyces cerevisiae specialist strains. The co-culture system can provide competitive advantage of modularity compared to the single culture system and can be tuned to deal with fluctuations in feedstock composition to achieve robust and cost-effective biofuel production. This study characterized fermentation kinetics of the recombinant cellobiose-consuming S. cerevisiae strain EJ2, xylose-consuming S. cerevisiae strain SR8, and their co-culture. The motivation for kinetic modeling was to provide guidance and prediction of using the co-culture system for simultaneous fermentation of mixed sugars with adjustable biomass of each specialist strain under different substrate concentrations. The kinetic model for the co-culture system was developed based on the pure culture models and incorporated the effects of product inhibition, initial substrate concentration and inoculum size. The model simulations were validated by results from independent fermentation experiments under different substrate conditions, and good agreement was found between model predictions and experimental data from batch fermentation of cellobiose, xylose and their mixtures. Additionally, with the guidance of model prediction, simultaneous co-fermentation of 60 g/L cellobiose and 20 g/L xylose was achieved with the initial cell densities of 0.45 g dry cell weight /L for EJ2 and 0.9 g dry cell weight /L SR8. The results demonstrated that the kinetic modeling could be used to guide the design and optimization of yeast co-culture conditions for achieving simultaneous fermentation of cellobiose and xylose with improved ethanol productivity, which is critically important for robust and efficient renewable biofuel production from lignocellulosic biomass.

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.

Kaempferol (kae) and its glycosides are widely distributed in nature and show multiple bioactivities, yet few reports have compared them. In this paper, we report the antitumor, antioxidant and anti-inflammatory activity differences of kae, kae-7-O-glucoside (kae-7-O-glu), kae-3-O-rhamnoside (kae-3-O-rha) and kae-3-O-rutinoside (kae-3-O-rut). Kae showed the highest antiproliferation effect on the human hepatoma cell line HepG2, mouse colon cancer cell line CT26 and mouse melanoma cell line B16F1. Kae also significantly inhibited AKT phosphorylation and cleaved caspase-9, caspase-7, caspase-3 and PARP in HepG2 cells. A kae-induced increase in DPPH and ABTS radical scavenging activity, inhibition of concanavalin A (Con A)-induced activation of T cell proliferation and NO or ROS production in LPS-induced RAW 264.7 macrophage cells were also seen. Kae glycosides were used to produce kae via environment-friendly enzymatic hydrolysis. Kae-7-O-glu and kae-3-O-rut were hydrolyzed to kae by β-glucosidase and/or α-L-rhamnosidase. This paper demonstrates the application of enzymatic catalysis to obtain highly biologically active kae. This work provides a novel and efficient preparation of high-value flavone-related products.

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.

Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as potential biomarkers for early detection. The present paper develops a mathematical model for early stage of NSCLC with emphasis on the role of the three highest overexpressed miRs, namely miR-21, miR-205 and miR-155. Simulations of the model provide quantitative relationships between the tumor volume and the total mass of each of the above miRs in the tumor. Because of the positive correlation between these miRs in the tumor tissue and in the blood, the results of the paper may be viewed as a first step toward establishing a combination of miRs 21, 205, 155 and possibly other miRs as serum biomarkers for early detection of NSCLC.

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

Experiments on tumor spheroids have shown that compressive stress from their environment can reversibly decrease tumor expansion rates and final sizes. Stress release experiments show that nonuniform anisotropic elastic stresses can be distributed throughout. The elastic stresses are maintained by structural proteins and adhesive molecules, and can be actively relaxed by a variety of biophysical processes. In this paper, we present a new continuum model to investigate how the growth-induced elastic stresses and active stress relaxation, in conjunction with cell size control feedback machinery, regulate the cell density and stress distributions within growing tumors as well as the tumor sizes in the presence of external physical confinement and gradients of growth-promoting chemical fields. We introduce an adaptive reference map that relates the current position with the reference position but adapts to the current position in the Eulerian frame (lab coordinates) via relaxation. This type of stress relaxation is similar to but simpler than the classical Maxwell model of viscoelasticity in its formulation. By fitting the model to experimental data from two independent studies of tumor spheroid growth and their cell density distributions, treating the tumors as incompressible, neo-Hookean elastic materials, we find that the rates of stress relaxation of tumor tissues can be comparable to volumetric growth rates. Our study provides insight on how the biophysical properties of the tumor and host microenvironment, mechanical feedback control and diffusion-limited differential growth act in concert to regulate spatial patterns of stress and growth. When the tumor is stiffer than the host, our model predicts tumors are more able to change their size and mechanical state autonomously, which may help to explain why increased tumor stiffness is an established hallmark of malignant tumors., Author summary The mechanical state of cells can modulate their growth and division dynamics via mechanotransduction, which affects both the cell size distribution and the tissue size as a whole. Experiments on tumor spheroids have shown that compressive stress from their environment can reversibly decrease tumor expansion rates and final sizes. Besides external confinement and compression on the tumor border, a heterogeneous stress field can be generated inside the tumor by nutrient-driven differential growth. Such growth-induced mechanical stresses can be relaxed by tissue rearrangement, which happens during cell neighbor exchanges, cell divisions, and extracellular matrix renewal. In this study, we have developed a continuum model that describes the above mechanical interactions and the dynamics of tissue rearrangement explicitly. Motivated by published experimental data, we consider mechanotransduction where the local compressive stress slows down cell growth and cell size reduction limits cell division. We have analyzed how external mechanical stimuli and internal processes influence the outcome of cell-and-tissue sizes and spatial patterns of cell density and mechanical stress in growing tumors.

The conserved adapter protein Scribble (Scrib) plays essential roles in a variety of cellular processes, including polarity establishment, proliferation, and directed cell migration. While the mechanisms through which Scrib promotes epithelial polarity are beginning to be unraveled, its roles in other cellular processes including cell migration remain enigmatic. In C. elegans, the Scrib ortholog LET-413 is essential for apical–basal polarization and junction formation in embryonic epithelia. However, whether LET-413 is required for postembryonic development or plays a role in migratory events is not known. Here, we use inducible protein degradation to investigate the functioning of LET-413 in larval epithelia. We find that LET-413 is essential in the epidermal epithelium for growth, viability, and junction maintenance. In addition, we identify a novel role for LET-413 in the polarized outgrowth of the epidermal seam cells. These stem cell-like epithelial cells extend anterior and posterior directed apical protrusions in each larval stage to reconnect to their neighbors. We show that the role of LET-413 in seam cell outgrowth is likely mediated largely by the junctional component DLG-1 discs large, which we demonstrate is also essential for directed outgrowth of the seam cells. Our data uncover multiple essential functions for LET-413 in larval development and show that the polarized outgrowth of the epithelial seam cells is controlled by LET-413 Scribble and DLG-1 Discs large., Author summary Most cells in multicellular organisms are organized along a directional axis of cell polarity. One protein that is important for this polarized organization is the conserved polarity regulator Scribble. This protein has several functions, including forming the basolateral domains of cells, promoting the formation of cell junctions, and promoting cell migration. How Scribble performs these functions is not fully understood. In this paper we study the role of Scribble during larval development of the small nematode Caenorhabditis elegans using an inducible protein degradation system. We show that Scribble, called LET-413 in C. elegans, is essential in the epidermal epithelium for animal development, as depletion of LET-413 in only this tissue blocks growth. We also demonstrate that LET-413 is required for the polarized outgrowth of an epithelial cell type called the seam cells, a process resembling cell migration. Finally, we show that one major function of LET-413 in seam cell outgrowth is the localization of the junctional component Discs large (DLG-1), which we demonstrate is also essential for this process. Our data thus uncover multiple essential functions for LET-413 in larval development and provide new insights into how the directional outgrowth of epithelial seam cells is controlled.

Architectural changes at the cellular and organism level are integral and necessary to successful development and growth. During mammalian preimplantation development, cells reduce in size and the architecture of the embryo changes significantly. Such changes must be coordinated correctly to ensure continued development of the embryo and, ultimately, a successful pregnancy. However, the nature of such transformations is poorly defined during mammalian preimplantation development. In order to quantitatively describe changes in cell environment and organism architecture, we designed Internal Versus External Neighbourhood (IVEN). IVEN is a user-interactive, open-source pipeline that classifies cells into different populations based on their position and quantifies the number of neighbours of every cell within a dataset in a 3D environment. Through IVEN-driven analyses, we show how transformations in cell environment, defined here as changes in cell neighbourhood, are related to changes in embryo geometry and major developmental events during preimplantation mammalian development. Moreover, we demonstrate that modulation of the FGF pathway alters spatial relations of inner cells and neighbourhood distributions, leading to overall changes in embryo architecture. In conjunction with IVEN-driven analyses, we uncover differences in the dynamic of cell size changes over the preimplantation period and determine that cells within the mammalian embryo initiate growth phase only at the time of implantation., This paper presents IVEN (Internal Versus External Neighbourhood), a new user-interactive tool for the quantitative description of cell environment and organismal architecture, and uses it to reveal how changes in embryo architecture relate to changes in cell neighbourhood, identifying nuanced effects of FGF treatment on embryo morphology.

Individual cells show variability in their signaling dynamics that often correlates with phenotypic responses, indicating that cell-to-cell variability is not merely noise but can have functional consequences. Based on this observation, we reasoned that cell-to-cell variability under the same treatment condition could be explained in part by a single signaling motif that maps different upstream signals into a corresponding set of downstream responses. If this assumption holds, then repeated measurements of upstream and downstream signaling dynamics in a population of cells could provide information about the underlying signaling motif for a given pathway, even when no prior knowledge of that motif exists. To test these two hypotheses, we developed a computer algorithm called MISC (Motif Inference from Single Cells) that infers the underlying signaling motif from paired time-series measurements from individual cells. When applied to measurements of transcription factor and reporter gene expression in the yeast stress response, MISC predicted signaling motifs that were consistent with previous mechanistic models of transcription. The ability to detect the underlying mechanism became less certain when a cell’s upstream signal was randomly paired with another cell’s downstream response, demonstrating how averaging time-series measurements across a population obscures information about the underlying signaling mechanism. In some cases, motif predictions improved as more cells were added to the analysis. These results provide evidence that mechanistic information about cellular signaling networks can be systematically extracted from the dynamical patterns of single cells., Author summary Cells use molecular signaling networks to translate dynamically changing stimuli into appropriate downstream responses. Specialized network structures, or motifs, allow cells to properly decode a variety of temporal input signals. In this paper, we present an algorithm that infers signaling motifs from multiple examples of an upstream signal paired with its downstream response in a population of single cells. We compare the predictive power of single-cell versus averaged time-series traces and the incremental benefit of adding more single-cell traces to the algorithm. We use this approach to understand how yeast respond to environmental stresses.

Bistability is a common mechanism to ensure robust and irreversible cell cycle transitions. Whenever biological parameters or external conditions change such that a threshold is crossed, the system abruptly switches between different cell cycle states. Experimental studies have uncovered mechanisms that can make the shape of the bistable response curve change dynamically in time. Here, we show how such a dynamically changing bistable switch can provide a cell with better control over the timing of cell cycle transitions. Moreover, cell cycle oscillations built on bistable switches are more robust when the bistability is modulated in time. Our results are not specific to cell cycle models and may apply to other bistable systems in which the bistable response curve is time-dependent., Author summary Many systems in nature show bistability, which means they can evolve to one of two stable steady states under exactly the same conditions. Which state they evolve to depends on where the system comes from. Such bistability underlies the switching behavior that is essential for cells to progress in the cell division cycle. A quick switch happens when the cell jumps from one steady state to another steady state. Typical of this switching behavior is its robustness and irreversibility. In this paper, we expand this viewpoint of the dynamics of the cell cycle by considering bistable switches which themselves are changing in time. This gives the cell an extra layer of control over transitions both in time and in space, and can make those transitions more robust. Such dynamically changing bistability can appear very naturally. We show this in a model of mitotic entry, in which we include a nuclear and cytoplasmic compartment. The activity of a crucial cell cycle protein follows a bistable switch in each compartment, but the shape of its response is changing in time as proteins are imported into and exported from the nucleus.

This research proposes a new multi-membrane search algorithm (MSA) based on cell biological behavior. Cell secretion protein behavior and cell division and fusion strategy are the main inspirations for the algorithm. In order to verify the performance of the algorithm, we used 19 benchmark functions to compare the MSA test results with MVO, GWO, MFO and ALO. The number of iterations of each algorithm on each benchmark function is 100, the population number is 10, and the running is repeated 50 times, and the average and standard deviation of the results are recorded. Tests show that the MSA is competitive in unimodal benchmark functions and multi-modal benchmark functions, and the results in composite benchmark functions are all superior to MVO, MFO, ALO, and GWO algorithms. This paper also uses MSA to solve two classic engineering problems: welded beam design and pressure vessel design. The result of welded beam design is 1.7252, and the result of pressure vessel design is 5887.7052, which is better than other comparison algorithms. Statistical experiments show that MSA is a high-performance algorithm that is competitive in unimodal and multimodal functions, and its performance in compound functions is significantly better than MVO, MFO, ALO, and GWO algorithms.

On the basis of analyzing the movement law of 3D circular braided yarn, the three-cell model of 3D five-direction circular braiding composite material is established. By analyzing the node position relationship in various cell models, the calculation formulas of braiding angle, cell volume, fiber volume and fiber volume content in various cell models are obtained. It is found that there are four different braiding angles in four internal cells, and the braiding angles in internal cells gradually increase from inside to outside. The braiding angles of upper and lower surface cells are approximately equal. With the increase of the length of the knuckles, the braiding angles of each cell decrease, and the braiding angles of the four inner cells decrease greatly, while the braiding angles of upper and lower surfaces decrease slightly. The results of parametric analysis showed that with the increase of the length of the knuckles and the inner diameter of cells, the mass of cells increased proportionally, while the total fiber volume content of cells decreased. With the increase of braiding yarn number and axial yarn number, the unit cell mass decreases in direct proportion, and the unit cell total fiber volume content increases. Through the research results of this paper, the geometrical characteristics of the cell model under different braided parameters can be obtained, which greatly improves the analysis efficiency.

Cell death experiments are routinely done in many labs around the world, these experiments are the backbone of many assays for drug development. Cell death detection is usually performed in many ways, and requires time and reagents. However, cell death is preceded by slight morphological changes in cell shape and texture. In this paper, we trained a neural network to classify cells undergoing cell death. We found that the network was able to highly predict cell death after one hour of exposure to camptothecin. Moreover, this prediction largely outperforms human ability. Finally, we provide a simple python tool that can broadly be used to detect cell death.

Alpha-synuclein pre-formed fibrils (PFFs) represent a promising model system for the study of cellular processes underlying cell-to-cell transmission of alpha-synuclein proteopathic aggregates. However, the ability to differentiate the fate of internalized PFFs from those which remain in the extracellular environment remains limited due to the propensity for PFFs to adhere to the cell surface. Removal of PFFs requires repeated washing and/or specific quenching of extracellular fluorescent PFF signals. In this paper we present a new method for analyzing the fate of internalized alpha-synuclein. We inserted a tobacco etch virus (TEV) protease cleavage site between alpha-synuclein and green fluorescent protein and subjected cells to brief treatment with TEV protease after incubation with tagged PFFs. As the TEV protease is highly specific, non-toxic, and active under physiological conditions, protection from TEV cleavage can be used to distinguish internalized PFFs from those which remain attached to the cell surface. Using this experimental paradigm, downstream intracellular events can be analyzed via live or fixed cell microscopy as well as by Western blotting. We suggest that this method will be useful for understanding the fate of PFFs after endocytosis under various experimental manipulations.

Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish the efficacy of cancer drugs. Efficacious combination therapies are thus needed to block drug-tolerant cells via minimizing the impact of heterogeneity. Probabilistic models such as Bliss independence have been developed to evaluate drug interactions and their combination efficacy based on probabilities of specific actions mediated by drugs individually and in combination. In practice, however, these models are often applied to conventional dose-response curves in which a normalized parameter with a value between zero and one, generally referred to as fraction of cells affected (fa), is used to evaluate the efficacy of drugs and their combined interactions. We use basic probability theory, computer simulations, time-lapse live cell microscopy, and single-cell analysis to show that fa metrics may bias our assessment of drug efficacy and combination effectiveness. This bias may be corrected when dynamic probabilities of drug-induced phenotypic events, i.e. induction of cell death and inhibition of division, at a single-cell level are used as metrics to assess drug efficacy. Probabilistic phenotype metrics offer the following three benefits. First, in contrast to the commonly used fa metrics, they directly represent probabilities of drug action in a cell population. Therefore, they deconvolve differential degrees of drug effect on tumor cell killing versus inhibition of cell division, which may not be correlated for many drugs. Second, they increase the sensitivity of short-term drug response assays to cell-to-cell heterogeneities and the presence of drug-tolerant subpopulations. Third, their probabilistic nature allows them to be used directly in unbiased evaluation of synergistic efficacy in drug combinations using probabilistic models such as Bliss independence. Altogether, we envision that probabilistic analysis of single-cell phenotypes complements currently available assays via improving our understanding of heterogeneity in drug response, thereby facilitating the discovery of more efficacious combination therapies to block drug-tolerant cells., Author summary Resistance to therapy due to tumor cell heterogeneity poses a major challenge to the use of cancer drugs. Cell-to-cell variability generates subpopulations of drug-tolerant cells that diminish therapeutic efficacy, even in populations of cells that are scored as highly sensitive based on drug potency. Overcoming such heterogeneity and blocking subpopulations of drug-tolerant cells motivate efforts toward identifying efficacious combination therapies. The success of these efforts depends on our ability to distinguish how heterogeneous populations of cells respond to individual drugs, and how these responses are influenced by combined drug interactions. In this paper, we propose mathematical and experimental frameworks to evaluate time-dependent drug interactions based on probabilistic metrics that quantify drug-induced tumor cell killing or inhibition of division at a single-cell level. These metrics can reveal heterogeneous drug responses and their changes with time and drug combinations. Thus, they have important implications for designing efficacious combination therapies, especially those designed to block or overcome drug-tolerant subpopulations of cancer cells.

Cell homeostasis requires the correct levels of reactive oxygen species (ROS) to be maintained as these regulate the proliferation and differentiation of cells, and control the immune response and inflammation. High levels of ROS can cause oxidative stress, leading to protein, lipid and DNA damage, or even cell death. Under physiological conditions, the rate of autophagy remains stable; however, it can be accelerated by a number of exogenous stimuli such as oxidative stress, starvation or hypoxia, leading to cell death. The present paper examines the effect of Conidiobolus coronatus infection on the immune response, oxidative stress processes and autophagy in the greater wax moth, Galleria mellonella. Fungal infection was found to result in the disorganization of the cytoskeleton of the larval immune cells and the enhancement of oxidative defense processes. Lipid peroxidation and autophagy were also induced in the hemocytes. Our findings show that G. mellonella is an ideal model for exploring immune mechanisms.

Anticarsia gemmatalis (Hübner, 1818) and Chrysodeixis includens (Walker, 1858) are species of Lepidoptera that cause great damages in the soybean plantations of Brazil. Despite the importance they have in this regard, there are no studies on the chromosomal organization of these species and recently, A. gemmatalis, which belonged to the Noctuidae family, was allocated to the Erebidae family. Therefore, the objective of this paper was to analyze, through conventional and molecular cytogenetic markers, both species of Lepidoptera. A 2n = 62 was observed, with ZZ/ZW sex chromosome system and holokinetic chromosomes for both species. There was homogeneity in the number of 18S rDNA sites for both species. However, variations in heterochromatin distribution were observed between both species. The cytogenetic analyses enabled separation of the species, corroborating the transference of A. gemmatalis, from the family Noctuidae to the family Erebidae, suggesting new cytotaxonomic characteristics.

Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only about 6 days after reprogramming initiation, iPS cells can be experimentally determined via fluorescent probes. What is more, the ratio of progenitor cells during early reprograming period is below 5%, which is too low to capture experimentally in the early stage. In this paper, we propose a novel computational approach for the identification of iPS progenitor cells based on machine learning and microscopic image analysis. Firstly, we record the reprogramming process using a live cell imaging system after 48 hours of infection with retroviruses expressing Oct4, Sox2 and Klf4, later iPS progenitor cells and normal murine embryonic fibroblasts (MEFs) within 3 to 5 days after infection are labeled by retrospectively tracing the time-lapse microscopic image. We then calculate 11 types of cell morphological and motion features such as area, speed, etc., and select best time windows for modeling and perform feature selection. Finally, a prediction model using XGBoost is built based on the selected six types of features and best time windows. Our model allows several missing values/frames in the sample datasets, thus it is applicable to a wide range of scenarios. Cross-validation, holdout validation and independent test experiments show that the minimum precision is above 52%, that is, the ratio of predicted progenitor cells within 3 to 5 days after viral infection is above 52%. The results also confirm that the morphology and motion pattern of iPS progenitor cells is different from that of normal MEFs, which helps with the machine learning methods for iPS progenitor cell identification., Author summary Identification of induced pluripotent stem (iPS) progenitor cells could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only after about 6 days of induction, iPS cells can be experimentally determined via fluorescent probes. What is more, the percentage of the progenitor cells during the early induction period is below 5%, too low to capture experimentally in early stage. In this work, we proposed an approach for the identification of iPS progenitor cells, the iPS forming cells, based on machine learning and microscopic image analysis. The aim is to help biologists to enrich iPS progenitor cells during the early stage of induction, which allows experimentalists to select iPS progenitor cells with much higher probability, and furthermore to study the biomarkers which trigger the reprogramming process.

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 nuclear pore complex (NPC) forms a gateway for nucleocytoplasmic transport. The outer ring protein complex of the NPC (the Nup107-160 subcomplex in humans) is a key component for building the NPC. Nup107-160 subcomplexes are believed to be symmetrically localized on the nuclear and cytoplasmic sides of the NPC. However, in S. pombe immunoelectron and fluorescence microscopic analyses revealed that the homologous components of the human Nup107-160 subcomplex had an asymmetrical localization: constituent proteins spNup132 and spNup107 were present only on the nuclear side (designated the spNup132 subcomplex), while spNup131, spNup120, spNup85, spNup96, spNup37, spEly5 and spSeh1 were localized only on the cytoplasmic side (designated the spNup120 subcomplex), suggesting the complex was split into two pieces at the interface between spNup96 and spNup107. This contrasts with the symmetrical localization reported in other organisms. Fusion of spNup96 (cytoplasmic localization) with spNup107 (nuclear localization) caused cytoplasmic relocalization of spNup107. In this strain, half of the spNup132 proteins, which interact with spNup107, changed their localization to the cytoplasmic side of the NPC, leading to defects in mitotic and meiotic progression similar to an spNup132 deletion strain. These observations suggest the asymmetrical localization of the outer ring spNup132 and spNup120 subcomplexes of the NPC is necessary for normal cell cycle progression in fission yeast., Author summary The nuclear pore complexes (NPCs) form gateways to transport intracellular molecules between the nucleus and the cytoplasm across the nuclear envelope. The Nup107-160 subcomplex, that forms nuclear and cytoplasmic outer rings, is a key complex responsible for building the NPC by symmetrical localization on the nuclear and cytoplasmic sides of the nuclear pore. This structural characteristic was found in various organisms including humans and budding yeasts, and therefore believed to be common among “all” eukaryotes. However, in this paper, we revealed an asymmetrical localization of the homologous components of the human Nup107-160 subcomplex in fission yeast by immunoelectron and fluorescence microscopic analyses: in this organism, the Nup107-160 subcomplex is split into two pieces, and each of the split pieces is differentially distributed to the nuclear and cytoplasmic side of the NPC: one piece is only in the nuclear side while the other piece is only in the cytoplasmic side. This contrasts with the symmetrical localization reported in other organisms. In addition, we confirmed that the asymmetrical configuration of the outer ring structure is necessary for cell cycle progression in fission yeast. This study provides notions of diverse structures and functions of NPCs evolved in eukaryotes.

This paper considers a novel dynamical behaviour of two microbial populations, competing in a chemostat over a single substrate, that is only possible through the use of population balance equations (PBEs). PBEs are partial integrodifferential equations that represent a distribution of cells according to some internal state, mass in our case. Using these equations, realistic parameter values and the assumption that one population can deploy an emergency mechanism, where it can change the mean mass of division and hence divide faster, we arrive at two different steady states, one oscillatory and one non-oscillatory both of which seem to be stable. A steady state of either form is normally either unstable or only attainable through external control (cycling the dilution rate). In our case no external control is used. Finally, in the oscillatory case we attempt to explain how oscillations appear in the biomass without any explicit dependence on the division rate (the function that oscillates) through the approximation of fractional moments as a combination of integer moments. That allows an implicit dependence of the biomass on the number of cells which in turn is directly dependent on the division rate function.

Sudangrass, Sorghum sudanense (Piper) Stapf, is a vigorous forage crop that has also been used for biogas, paper, and electricity production. Due to the large biomass yields achieved by sudangrass and the large area of potential growth in Argentina seven sudangrass accessions from a collection of S. sudanense were analyzed to evaluate their potential as feedstocks for lignocellulosic bioethanol production, and to assess whether there is an association between the response to biotic and abiotic stresses and the composition of the biomass. The biomass composition was analyzed for major cell wall polymers, monosaccharides, and elemental composition. On average, 68% of stem lignocellulosic biomass was comprised of matrix polysaccharides and crystalline cellulose, representing a potential source of sugars for bioethanol production. Xylose was the predominant matrix polysaccharide monosaccharide comprising, on average, 45% of the total sugars, followed by arabinose, glucose, galactose, galacturonic acid, mannose, glucuronic acid, and fucose. Rhamnose was not detected in any of the biomasses analyzed. Silica was the most abundant element in sudangrass stem, followed by chloride, calcium, phosphorus and sulfur. We performed saccharification analyses after pretreatments. Alkaline pretreatment was more effective than water pretreatment. Sodium hydroxide pretreatment exposed different levels of recalcitrance among sudangrass accessions, whereas the water pretreatment did not. Phenological traits were also evaluated, showing significant variability among accessions. The comparison of major cell wall polymers and monosaccharide composition between tolerant and susceptible accessions to abiotic and biotic stresses suggests an association between the composition of the biomass and the response to stress. Instituto de Suelos Fil: Acevedo, Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina Fil: Simister, Rachael. University of York. Department of Biology. Centre for Novel Agricultural Products; Reino Unido Fil: McQueen-Mason, Simon J. University of York. Department of Biology. Centre for Novel Agricultural Products; Reino Unido Fil: Gómez, Leonardo D. University of York. Department of Biology. Centre for Novel Agricultural Products; Reino Unido

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.

Single-cell RNA sequencing (scRNA-seq) has been widely applied to discover new cell types by detecting sub-populations in a heterogeneous group of cells. Since scRNA-seq experiments have lower read coverage/tag counts and introduce more technical biases compared to bulk RNA-seq experiments, the limited number of sampled cells combined with the experimental biases and other dataset specific variations presents a challenge to cross-dataset analysis and discovery of relevant biological variations across multiple cell populations. In this paper, we introduce a method of variance-driven multitask clustering of single-cell RNA-seq data (scVDMC) that utilizes multiple single-cell populations from biological replicates or different samples. scVDMC clusters single cells in multiple scRNA-seq experiments of similar cell types and markers but varying expression patterns such that the scRNA-seq data are better integrated than typical pooled analyses which only increase the sample size. By controlling the variance among the cell clusters within each dataset and across all the datasets, scVDMC detects cell sub-populations in each individual experiment with shared cell-type markers but varying cluster centers among all the experiments. Applied to two real scRNA-seq datasets with several replicates and one large-scale droplet-based dataset on three patient samples, scVDMC more accurately detected cell populations and known cell markers than pooled clustering and other recently proposed scRNA-seq clustering methods. In the case study applied to in-house Recessive Dystrophic Epidermolysis Bullosa (RDEB) scRNA-seq data, scVDMC revealed several new cell types and unknown markers validated by flow cytometry. MATLAB/Octave code available at https://github.com/kuanglab/scVDMC., Author summary scRNA-seq enables detailed profiling of heterogeneous cell populations and can be used to reveal lineage relationships or discover new cell types. In the literature, there has been little effort directed towards developing computational methods for cross-population transcriptome analysis of multiple single-cell populations. The cross-cell-population clustering problem is different from the traditional clustering problem because single-cell populations can be collected from different patients, different samples of a tissue, or different experimental replicates. The accompanying biological and technical variation tends to dominate the signals for clustering the pooled single cells from the multiple populations. In this work, we have developed a multitask clustering method to address the cross-population clustering problem. The method simultaneously clusters each individual cell population and controls variance among the cell-type cluster centers within each cell population and across the cell populations. We demonstrate that our multitask clustering method significantly improves clustering accuracy and marker discovery in three public scRNA-seq datasets and also apply the method to an in-house Recessive Dystrophic Epidermolysis Bullosa (RDEB) dataset. Our results make it evident that multitask clustering is a promising new approach for cross-population analysis of scRNA-seq data.

This paper was supported by Konkuk University in 2014. The cellular dispersion and therapeutic control of glioblastoma, the most aggressive type of primary brain cancer, depends critically on the migration patterns after surgery and intracellular responses of the individual cancer cells in response to external biochemical cues in the microenvironment. Recent studies have shown that miR-451 regulates downstream molecules including AMPK/CAB39/MARK and mTOR to determine the balance between rapid proliferation and invasion in response to metabolic stress in the harsh tumor microenvironment. Surgical removal of the main tumor is inevitably followed by recurrence of the tumor due to inaccessibility of dispersed tumor cells in normal brain tissue. In order to address this complex process of cell proliferation and invasion and its response to conventional treatment, we propose a mathematical model that analyzes the intracellular dynamics of the miR-451-AMPK- mTOR-cell cycle signaling pathway within a cell. The model identifies a key mechanism underlying the molecular switches between proliferative phase and migratory phase in response to metabolic stress in response to fluctuating glucose levels. We show how up- or down-regulation of components in these pathways affects the key cellular decision to infiltrate or proliferate in a complex microenvironment in the absence and presence of time delays and stochastic noise. Glycosylated chondroitin sulfate proteoglycans (CSPGs), a major component of the extracellular matrix (ECM) in the brain, contribute to the physical structure of the local brain microenvironment but also induce or inhibit glioma invasion by regulating the dynamics of the CSPG receptor LAR as well as the spatiotemporal activation status of resident astrocytes and tumor-associated microglia. Using a multi-scale mathematical model, we investigate a CSPG-induced switch between invasive and non-invasive tumors through the coordination of ECM-cell adhesion and dynamic changes in stromal cells. We show that the CSPG-rich microenvironment is associated with non-invasive tumor lesions through LAR-CSGAG binding while the absence of glycosylated CSPGs induce the critical glioma invasion. We illustrate how high molecular weight CSPGs can regulate the exodus of local reactive astrocytes from the main tumor lesion, leading to encapsulation of non-invasive tumor and inhibition of tumor invasion. These different CSPG conditions also change the spatial profiles of ramified and activated microglia. The complex distribution of CSPGs in the tumor microenvironment can determine the nonlinear invasion behaviors of glioma cells, which suggests the need for careful therapeutic strategies. Publisher PDF

In this paper, two kinds of titanium surfaces with novel micro/nano hierarchical structures, namely Etched (E) surface and Sandblast and etched (SE) surface, were successfully fabricated by NH4OH and H2O2 mixture. And their cellular responses of MG63 were investigated compared with Sandblast and acid-etching (SLA) surface. Scanning electron microscope (SEM), Surface profiler, X-ray photoelectron spectroscopy (XPS), and Contact angle instrument were employed to assess the surface morphologies, roughness, chemistry and wettability respectively. Hierarchical structures with micro holes of 10-30 μm in diameter and nano pits of tens of nanometers in diameter formed on both E and SE surfaces. The size of micro holes is very close to osteoblast cell, which makes them wonderful beds for osteoblast. Moreover, these two kinds of surfaces possess similar roughness and superior hydrophilicity to SLA. Reactive oxygen species were detected on E and SE surface, and thus considerable antimicrobial performance and well fixation can be speculated on them. The cell experiments also demonstrated a boost in cell attachment, and that proliferation and osteogenic differentiation were achieved on them, especially on SE surface. The results indicate that the treatment of pure titanium with H2O2/NH4OH is an effective technique to improve the initial stability of implants and enhance the osseointegration, which may be a promising surface treatment to titanium implant.

We refine and clinically parameterize a mathematical model of the humoral immune response against Shigella, a diarrheal bacteria that infects 80-165 million people and kills an estimated 600,000 people worldwide each year. Using Latin hypercube sampling and Monte Carlo simulations for parameter estimation, we fit our model to human immune data from two Shigella EcSf2a-2 vaccine trials and a rechallenge study in which antibody and B-cell responses against Shigella′s lipopolysaccharide (LPS) and O-membrane proteins (OMP) were recorded. The clinically grounded model is used to mathematically investigate which key immune mechanisms and bacterial targets confer immunity against Shigella and to predict which humoral immune components should be elicited to create a protective vaccine against Shigella. The model offers insight into why the EcSf2a-2 vaccine had low efficacy and demonstrates that at a group level a humoral immune response induced by EcSf2a-2 vaccine or wild-type challenge against Shigella′s LPS or OMP does not appear sufficient for protection. That is, the model predicts an uncontrolled infection of gut epithelial cells that is present across all best-fit model parameterizations when fit to EcSf2a-2 vaccine or wild-type challenge data. Using sensitivity analysis, we explore which model parameter values must be altered to prevent the destructive epithelial invasion by Shigella bacteria and identify four key parameter groups as potential vaccine targets or immune correlates: 1) the rate that Shigella migrates into the lamina propria or epithelium, 2) the rate that memory B cells (BM) differentiate into antibody-secreting cells (ASC), 3) the rate at which antibodies are produced by activated ASC, and 4) the Shigella-specific BM carrying capacity. This paper underscores the need for a multifaceted approach in ongoing efforts to design an effective Shigella vaccine.

Background Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. Methods In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. Results Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs associated with different traits that are responsive to multiple stresses. Ontology mapping was used to validate the identified genes, while reconstruction of the phylogenetic tree was instrumental to infer the evolutionary relationship of the sorghum orthologs. The results also show specific genes responsible for various interrelated components of drought response mechanism such as drought tolerance, drought avoidance and drought escape. Conclusions We submit that this approach is novel and to our knowledge, has not been used previously in any other research; it enables us to perform cross-species queries for genes that are likely to be associated with multiple stress tolerance, as a means to identify novel targets for engineering stress resistance in sorghum and possibly, in other crop species.

Bacteria, yeast and human cancer cells possess mechanisms of mutagenesis upregulated by stress responses. Stress-inducible mutagenesis potentially accelerates adaptation, and may provide important models for mutagenesis that drives cancers, host pathogen interactions, antibiotic resistance and possibly much of evolution generally. In Escherichia coli repair of double-strand breaks (DSBs) becomes mutagenic, using low-fidelity DNA polymerases under the control of the SOS DNA-damage response and RpoS general stress response, which upregulate and allow the action of error-prone DNA polymerases IV (DinB), II and V to make mutations during repair. Pol IV is implied to compete with and replace high-fidelity DNA polymerases at the DSB-repair replisome, causing mutagenesis. We report that up-regulated Pol IV is not sufficient for mutagenic break repair (MBR); damaged bases in the DNA are also required, and that in starvation-stressed cells, these are caused by reactive-oxygen species (ROS). First, MBR is reduced by either ROS-scavenging agents or constitutive activation of oxidative-damage responses, both of which reduce cellular ROS levels. The ROS promote MBR other than by causing DSBs, saturating mismatch repair, oxidizing proteins, or inducing the SOS response or the general stress response. We find that ROS drive MBR through oxidized guanines (8-oxo-dG) in DNA, in that overproduction of a glycosylase that removes 8-oxo-dG from DNA prevents MBR. Further, other damaged DNA bases can substitute for 8-oxo-dG because ROS-scavenged cells resume MBR if either DNA pyrimidine dimers or alkylated bases are induced. We hypothesize that damaged bases in DNA pause the replisome and allow the critical switch from high fidelity to error-prone DNA polymerases in the DSB-repair replisome, thus allowing MBR. The data imply that in addition to the indirect stress-response controlled switch to MBR, a direct cis-acting switch to MBR occurs independently of DNA breakage, caused by ROS oxidation of DNA potentially regulated by ROS regulators., Author summary Mutagenesis mechanisms upregulated by stress responses promote de novo antibiotic resistance and cross resistance in bacteria, anti-fungal-drug resistance in yeasts, and genome instability in cancer cells under hypoxic stress. Stress-induced mutagenesis is implicated as the main source of spontaneous mutagenesis that drives bacterial evolution, and may drive much of evolution generally. A widely useful model mechanism is mutagenic DNA break repair in Escherichia coli, in which activation of two stress responses allows error-prone DNA polymerase in the break-repair replisome and introduce misincorporations, later fixed as mutations. Both stress responses upregulate the error-prone mutagenic DNA polymerase Pol IV (DinB), suggesting that the regulation of mutagenesis to times of stress is accomplished by indirect gene upregulation, followed by DNA polymerase competition. This paper describes the discovery that the stress responses are not sufficient to allow mutagenesis caused by error-prone DNA polymerases in the break-repair replisome—damaged DNA bases must also be present—and that these are caused by reactive oxygen species in starving E. coli. We hypothesize that damaged bases may inhibit the progress of the highly processive and high fidelity replicative DNA polymerase, thus allowing the switch to error-prone DNA polymerases and mutagenesis. These findings suggest the possibility that the spontaneous mutation rate is regulated by the generation and removal of reactive oxygen, a very common byproduct of metabolism.

Attribute based encryption (ABE) is a good way to achieve flexible and secure access control to data, and attribute revocation is the extension of the attribute-based encryption, and the keyword search is an indispensable part for cloud storage. The combination of both has an important application in the cloud storage. In this paper, we construct a searchable attribute-based encryption scheme with attribute revocation in cloud storage, the keyword search in our scheme is attribute based with access control, when the search succeeds, the cloud server returns the corresponding cipher text to user and the user can decrypt the cipher text definitely. Besides, our scheme supports multiple keywords search, which makes the scheme more practical. Under the assumption of decisional bilinear Diffie-Hellman exponent (q-BDHE) and decisional Diffie-Hellman (DDH) in the selective security model, we prove that our scheme is secure.

The multiple extremes resistant bacterium Deinococcus radiodurans is able to withstand harsh conditions of simulated outer space environment. The Tanpopo orbital mission performs a long-term space exposure of D. radiodurans aiming to investigate the possibility of interplanetary transfer of life. The revealing of molecular machinery responsible for survivability of D. radiodurans in the outer space environment can improve our understanding of underlying stress response mechanisms. In this paper, we have evaluated the molecular response of D. radiodurans after the exposure to space-related conditions of UVC irradiation and vacuum. Notably, scanning electron microscopy investigations showed that neither morphology nor cellular integrity of irradiated cells was affected, while integrated proteomic and metabolomic analysis revealed numerous molecular alterations in metabolic and stress response pathways. Several molecular key mechanisms of D. radiodurans, including the tricarboxylic acid cycle, the DNA damage response systems, ROS scavenging systems and transcriptional regulators responded in order to cope with the stressful situation caused by UVC irradiation under vacuum conditions. These results reveal the effectiveness of the integrative proteometabolomic approach as a tool in molecular analysis of microbial stress response caused by space-related factors.

Esophageal squamous cell carcinoma (ESCC) is an aggressive malignancy with poor prognosis in China. Chemotherapy now is one of the most frequently used treatments for patients with ESCC in middle or late stage, however the effects were often limited by increased chemoresistance or treatment toxicity. So it is urgent to find new drugs to treat ESCC patients. Metformin with low cost and toxicity has proved to have anti-cancer effects in a numerous cancers, while its role and mechanism in ESCC has seldom been studied. In the present study, we found that metformin exhibited not only an anti-proliferation ability in a dose and time dependent manner but also a proapoptosis effect in a dose dependent manner in ESCC cell line KYSE450. Our in vivo experiment also showed that metformin markedly inhibited KYSE450 xenograft tumors growth compared to those treated with normal saline. What’s more, no obvious toxic reactions were observed. To further explore the underlying mechanism, we found that metformin treatment could significantly damp the expression of 4EBP1 and S6K1 in KYSE 450 cells in vitro and in vivo, furthermore, the p-4EBP1 and p-S6K1 expression in KYSE 450 cells were also inhibited greatly in vitro and in vivo. During the therapy of cancer, in order to overcome side effects, combination therapy was often used. In this paper, we demonstrated that metformin potentiated the effects of cisplatin via inhibiting cell proliferation and promoting cell apoptosis. Taken together, metformin owned the potential anti-cancer effect on ESCC in monotherapy or was combined with cisplatin and these results laid solid basis for the use of metformin in ESCC.

The positioning of the DNA replication machinery (replisome) has been the subject of several studies. Two conflicting models for replisome localization have been proposed: In the Factory Model, sister replisomes remain spatially co-localized as the replicating DNA is translocated through a stationary replication factory. In the Track Model, sister replisomes translocate independently along a stationary DNA track and the replisomes are spatially separated for the majority of the cell cycle. Here, we used time-lapse imaging to observe and quantify the position of fluorescently labeled processivity-clamp (DnaN) complexes throughout the cell cycle in two highly-divergent bacterial model organisms: Bacillus subtilis and Escherichia coli. Because DnaN is a core component of the replication machinery, its localization patterns should be an appropriate proxy for replisome positioning in general. We present automated statistical analysis of DnaN positioning in large populations, which is essential due to the high degree of cell-to-cell variation. We find that both bacteria show remarkably similar DnaN positioning, where any potential separation of the two replication forks remains below the diffraction limit throughout the majority of the replication cycle. Additionally, the localization pattern of several other core replisome components is consistent with that of DnaN. These data altogether indicate that the two replication forks remain spatially co-localized and mostly function in close proximity throughout the replication cycle. The conservation of the observed localization patterns in these highly divergent species suggests that the subcellular positioning of the replisome is a functionally critical feature of DNA replication., Author Summary Cell proliferation depends on efficient replication of the genome. Bacteria typically have a single origin of replication on a circular chromosome. After replication initiation, two replisomes assemble at the origin and each copy one of the two arms of the chromosome until they reach the terminus. There have been conflicting reports about the subcellular positioning and putative co-localization of the two replication forks during this process. It has remained controversial whether the two replisomes remain relatively close to each other with the DNA being pulled through, or separate as they translocate along the DNA like a track. Existing studies have relied heavily on snapshot images and these experiments cannot unambiguously distinguish between these two models: i.e. two resolvable forks versus two pairs of co-localized forks. The ability of replication to re-initiate before cell division in bacterial cells further complicates the interpretation of these types of imaging studies. In this paper, we use a combination of snapshot imaging, time-lapse imaging, and quantitative analysis to measure the fraction of time forks are co-localized during each cell cycle. We find that the forks are co-localized for the majority (80%) of the replication cycle in two highly-divergent model organisms: B. subtilis and E. coli. Our observations are consistent with proximal localization of the two forks, but also some transient separations of sister forks during replication. The conserved behavior of sub-cellular positioning of the replisomes in these two highly divergent species implies a potential functional relevance of this feature.

Background Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Results Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Conclusion Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

During wound healing, skin function is restored by the action of several cell types that undergo differentiation, migration, proliferation and/or apoptosis. These dynamics are tightly regulated by the evolution of the extra cellular matrix (ECM) contents along the process. Pharmacologically active flavonoids have shown to exhibit useful physiological properties interesting in pathological states. Among them, oleanolic acid (OA), a pentacyclic triterpene, shows promising properties over wound healing, as increased cell migration in vitro and improved wound resolution in vivo. In this paper, we pursued to disclose the molecular mechanisms underlying those effects, by using an in vitro scratch assay in two epithelial cell lines of different linage: non-malignant mink lung epithelial cells, Mv1Lu; and human breast cancer cells, MDA-MB-231. In every case, we observed that OA clearly enhanced cell migration for in vitro scratch closure. This correlated with the stimulation of molecular pathways related to mitogen-activated protein (MAP) kinases, as ERK1,2 and Jun N-terminal kinase (JNK) 1,2 activation and c-Jun phosphorylation. Moreover, MDA-MB-231 cells treated with OA displayed an altered gene expression profile affecting transcription factor genes (c-JUN) as well as proteins involved in migration and ECM dynamics (PAI1), in line with the development of an epithelial to mesenchymal transition (EMT) status. Strikingly, upon OA treatment, we observed changes in the epidermal growth factor receptor (EGFR) subcellular localization, while interfering with its signalling completely prevented migration effects. This data provides a physiological framework supporting the notion that lipophilic plant extracts used in traditional medicine, might modulate wound healing processes in vivo through its OA contents. The molecular implications of these observations are discussed.

Rottlerin is a natural polyphenolic compound that was initially indicated as a PKCδ inhibitor. However, it was recently revealed that it may target a number of molecules and have biological effects on various cell types and is considered as a possible agent for tumor and cell proliferative diseases. Psoriasis is a chronic inflammatory cutaneous disorder with undefined etiology and is characterized by abnormal cellular proliferation, angiogenesis, and inflammation. Therefore, this paper investigates the regulatory effects of rottlerin on normal human epidermal keratinocytes (NHEKs) and imiquimod (IMQ)-induced psoriasiform (IPI) lesions. In vitro results showed that rottlerin inhibited cell proliferation in NHEKs through growth arrest and NFκB inhibition. It may also induce apoptosis in an autophagy-dependent pathway. We found that rottlerin inhibited human microvascular endothelial cells tube formation on matrigel. Rottlerin also decreased the cell senescence of keratinocytes and intracellular ROS generation, which indicated its antioxidant effect. We also showed that rottlerin affects the expression of keratinocyte proliferation biomarkers. In 12-O-tetradecanoylphorbol13-acetate (TPA)-induced keratinocytes, rottlerin significantly inhibited the expression of the induced pro-inflammatory cytokines in keratinocytes. An animal experiment provided the corresponding evidence based on this evidence in vitro, by using IPI model, we found that rottlerin could relieve the psoriasiform of BALB/c mice by inhibiting keratinocyte proliferation, inflammatory cell infiltration, and vascular proliferation. In conclusion, our results suggest that rottlerin may prove useful in the development of therapeutic agents against psoriasis. However, the deep mechanism still requires further study.

SOX14 is a member of the SOX family of transcription factors mainly involved in the regulation of neural development. Recently, it became evident that SOX14 is one of four hypermethylated genes in cervical carcinoma, considered as a tumor suppressor candidate in this type of malignancy. In this paper we elucidated the role of SOX14 in the regulation of malignant properties of cervical carcinoma cells in vitro. Functional analysis performed in HeLa cells revealed that SOX14 overexpression decreased viability and promoted apoptosis through altering the expression of apoptosis related genes. Our results demonstrated that overexpression of SOX14 initiated accumulation of p53, demonstrating potential cross-talk between SOX14 and the p53 signaling pathway. Further analysis unambiguously showed that SOX14 triggered posttranslational modification of p53 protein, as detected by the significantly increased level of phospho-p53 (Ser-15) in SOX14-overexpressing HeLa cells. Moreover, the obtained results revealed that SOX14 activated p53 protein, which was confirmed by elevated p21Waf1/Cip1, a well known target gene of p53. This study advances our understanding about the role of SOX14 and might explain the molecular mechanism by which this transcription factor could exert tumor suppressor properties in cervical carcinoma.

A fundamental feature of sexual reproduction in plants and animals is the specification of reproductive cells that conduct meiosis to form gametes, and the associated somatic cells that provide nutrition and developmental cues to ensure successful gamete production. The anther, which is the male reproductive organ in seed plants, produces reproductive microsporocytes (pollen mother cells) and surrounding somatic cells. The microsporocytes yield pollen via meiosis, and the somatic cells, particularly the tapetum, are required for the normal development of pollen. It is not known how the reproductive cells affect the differentiation of these somatic cells, and vice versa. Here, we use molecular genetics, cell biological, and biochemical approaches to demonstrate that TPD1 (TAPETUM DETERMINANT1) is a small secreted cysteine-rich protein ligand that interacts with the LRR (Leucine-Rich Repeat) domain of the EMS1 (EXCESS MICROSPOROCYTES1) receptor kinase at two sites. Analyses of the expressions and localizations of TPD1 and EMS1, ectopic expression of TPD1, experimental missorting of TPD1, and ablation of microsporocytes yielded results suggesting that the precursors of microsporocyte/microsporocyte-derived TPD1 and pre-tapetal-cell-localized EMS1 initially promote the periclinal division of secondary parietal cells and then determine one of the two daughter cells as a functional tapetal cell. Our results also indicate that tapetal cells suppress microsporocyte proliferation. Collectively, our findings show that tapetal cell differentiation requires reproductive-cell-secreted TPD1, illuminating a novel mechanism whereby signals from reproductive cells determine somatic cell fate in plant sexual reproduction., Author Summary The differentiation of distinct somatic and reproductive cells in flowers is required for the successful sexual reproduction of plants. The anther produces reproductive microsporocytes (pollen mother cells) that give rise to pollen (male gametophytes), as well as surrounding somatic cells (particularly the tapetal cells) that support the normal development of pollen. In animals, signals from somatic cells are known to influence reproductive cell fate determination, and vice versa. However, little is known about the molecular mechanisms underlying somatic and reproductive cell fate determination in plants. In this paper, we demonstrate that TPD1 (TAPETUM DETERMINANT1) is processed into a small secreted cysteine-rich protein ligand for the EMS1 (EXCESS MICROSPOROCYTES1) leucine-rich repeat receptor-like kinase (LRR-RLK). TPD1 is secreted from reproductive cells to the plasma membrane of somatic cells, where activated TPD1-EMS1 signaling first promotes periclinal cell division and then determines tapetal cell fate. Moreover, tapetal cells suppress microsporocyte proliferation. Our findings illuminate a novel mechanism by which reproductive cells determine somatic cell fate, and somatic cells in turn limit reproductive cell proliferation. Plants extensively employ LRR-RLKs to control growth, development, and defense. Our identification of TPD1 as the first small protein ligand for all LRR-RLKs characterized to date will provide a valuable system for studying how small protein ligands activate LRR-RLK signaling complexes.

It has been hypothesized that continuously releasing drug molecules into the tumor over an extended period of time may significantly improve the chemotherapeutic efficacy by overcoming physical transport limitations of conventional bolus drug treatment. In this paper, we present a generalized space- and time-dependent mathematical model of drug transport and drug-cell interactions to quantitatively formulate this hypothesis. Model parameters describe: perfusion and tissue architecture (blood volume fraction and blood vessel radius); diffusion penetration distance of drug (i.e., a function of tissue compactness and drug uptake rates by tumor cells); and cell death rates (as function of history of drug uptake). We performed preliminary testing and validation of the mathematical model using in vivo experiments with different drug delivery methods on a breast cancer mouse model. Experimental data demonstrated a 3-fold increase in response using nano-vectored drug vs. free drug delivery, in excellent quantitative agreement with the model predictions. Our model results implicate that therapeutically targeting blood volume fraction, e.g., through vascular normalization, would achieve a better outcome due to enhanced drug delivery. Author Summary Cancer treatment efficacy can be significantly enhanced through the elution of drug from nano-carriers that can temporarily stay in the tumor vasculature. Here we present a relatively simple yet powerful mathematical model that accounts for both spatial and temporal heterogeneities of drug dosing to help explain, examine, and prove this concept. We find that the delivery of systemic chemotherapy through a certain form of nano-carriers would have enhanced tumor kill by a factor of 2 to 4 over the standard therapy that the patients actually received. We also find that targeting blood volume fraction (a parameter of the model) through vascular normalization can achieve more effective drug delivery and tumor kill. More importantly, this model only requires a limited number of parameters which can all be readily assessed from standard clinical diagnostic measurements (e.g., histopathology and CT). This addresses an important challenge in current translational research and justifies further development of the model towards clinical translation.

Background The treatment for leishmaniasis is currently based on pentavalent antimonials and amphotericin B; however, these drugs result in numerous adverse side effects. The lack of affordable therapy has necessitated the urgent development of new drugs that are efficacious, safe, and more accessible to patients. Natural products are a major source for the discovery of new and selective molecules for neglected diseases. In this paper, we evaluated the effect of apigenin on Leishmania amazonensis in vitro and in vivo and described the mechanism of action against intracellular amastigotes of L. amazonensis. Methodology/Principal Finding Apigenin reduced the infection index in a dose-dependent manner, with IC50 values of 4.3 μM and a selectivity index of 18.2. Apigenin induced ROS production in the L. amazonensis-infected macrophage, and the effects were reversed by NAC and GSH. Additionally, apigenin induced an increase in the number of macrophages autophagosomes after the infection, surrounding the parasitophorous vacuole, suggestive of the involvement of host autophagy probably due to ROS generation induced by apigenin. Furthermore, apigenin treatment was also effective in vivo, demonstrating oral bioavailability and reduced parasitic loads without altering serological toxicity markers. Conclusions/Significance In conclusion, our study suggests that apigenin exhibits leishmanicidal effects against L. amazonensis-infected macrophages. ROS production, as part of the mechanism of action, could occur through the increase in host autophagy and thereby promoting parasite death. Furthermore, our data suggest that apigenin is effective in the treatment of L. amazonensis-infected BALB/c mice by oral administration, without altering serological toxicity markers. The selective in vitro activity of apigenin, together with excellent theoretical predictions of oral availability, clear decreases in parasite load and lesion size, and no observed compromises to the overall health of the infected mice encourage us to supports further studies of apigenin as a candidate for the chemotherapeutic treatment of leishmaniasis., Author Summary Leishmaniasis is an important neglected disease caused by protozoa of the genus Leishmania and affects more than 12 million people worldwide. Pentavalent antimonials and amphotericin B have been used for decades to treat leishmaniasis; however, these drugs result in numerous adverse side effects, have variable efficacy and are subject to parasite resistance. The lack of suitable therapy necessitates the development of novel antileishmanial compounds. In this study, we investigated the antileishmanial activity of apigenin in vitro and in vivo and described the mechanism of action against intracellular amastigotes of Leishmania amazonensis. Apigenin reduced the infection index in a dose-dependent manner and increased reactive oxygen species (ROS) generation. Additionally, apigenin induced an increase in the number of macrophages autophagosomes after the infection, surrounding the parasitophorous vacuole, suggestive of the involvement of host autophagy probably due to ROS generation induced by apigenin. Furthermore, treatment with apigenin was also effective in vivo, showing oral bioavailability and significantly reducing lesion sizes and parasite burden without altering serological toxicity markers.

With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations.

In this paper we have systematically investigated the fundamental structure and the reproduction of spiral wave in a two-dimensional excitable lattice. A periodically rotating spiral wave is introduced as the model to reproduce spiral wave artificially. Interestingly, by using the dominant phase-advanced driving analysis method, the fundamental structure containing the loop structure and the wave propagation paths has been revealed, which can expose the periodically rotating orbit of spiral tip and the charity of spiral wave clearly. Furthermore, the fundamental structure is utilized as the core for artificial spiral wave. Additionally, the appropriate parameter region, in which the artificial spiral wave can be reproduced, is studied. Finally, we discuss the robustness of artificial spiral wave to defects.