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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.

The presence of treatment-resistant cells is an important factor that limits the efficacy of cancer therapy, and the prospect of resistance is considered the major cause of the treatment strategy. Several recent studies have employed mathematical models to elucidate the dynamics of generating resistant cancer cells and attempted to predict the probability of emerging resistant cells. The purpose of this paper is to present numerical approach to compute the number of resistant cells and the emerging probability of resistance. Stochastic model was designed and developed a method to approximately but efficiently compute the number of resistant cells and the probability of resistance. To model the progression of cancer, a discrete-state, two-dimensional Markov process whose states are the total number of cells and the number of resistant cells was employed. Then exact analysis and approximate aggregation approaches were proposed to calculate the number of resistant cells and the probability of resistance when the cell population reaches detection size. To confirm the accuracy of computed results of approximation, relative errors between exact analysis and approximation were computed. The numerical values of our approximation method were very close to those of exact analysis calculated in the range of small detection size M = 500, 100, and 1500. Then computer simulation was performed to confirm the accuracy of computed results of approximation when the detection size was M = 10000,30000,50000,100000 and 1000000. All the numerical results of approximation fell between the upper level and the lower level of 95% confidential intervals and our method took less time to compute over a broad range of cell size. The effects of parameter change on emerging probabilities of resistance were also investigated by computed values using approximation method. The results showed that the number of divisions until the cell population reached the detection size is important for emerging the probability of resistance. The next step of numerical approach is to compute the emerging probabilities of resistance under drug administration and with multiple mutation. Another effective approximation would be necessary for the analysis of the latter case., Author summary Drug therapies for cancer have dramatically succeeded since molecular-targeted drugs have been introduced in medical practice; however, drug treatment often fails owing to the emergence of drug-resistant cells. A variety of approaches, including mathematical modeling, has been undertaken to clarify the mechanism of resistance and subsequently avoid resistance to therapy. This paper proposes one of the mathematical approaches that uses a stochastic model and provides the emerging probabilities of resistance at detection size.

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.

High-fat diet is associated with hypercholesterolemia and seminal alterations in White New Zealand rabbits. We have previously reported disorders in the development of the manchette-acrosome complex during spermiogenesis and decreased testicular efficiency in hypercholesterolemic rabbits. On the other hand, olive oil incorporated into the diet improves cholesterolemia and semen parameters affected in hypercholesterolemic rabbits. In this paper, we report the recovery—with the addition of olive oil to diet—from the sub-cellular mechanisms involved in the shaping of the sperm cell and testicular efficiency altered in hypercholesterolemic rabbits. Using morphological (structural, ultra-structural and immuno-fluorescence techniques) and cell biology techniques, a reorganization of the manchette and related structures was observed when olive oil was added to the high-fat diet. Specifically, actin filaments, microtubules and lipid rafts—abnormally distributed in hypercholesterolemic rabbits—were recovered with dietary olive oil supplementation. The causes of the decline in sperm count were studied in the previous report and here in more detail. These were attributed to the decrease in the efficiency index and also to the increase in the apoptotic percentage in testis from animals under the high-fat diet. Surprisingly, the addition of olive oil to the diet avoided the sub-cellular, efficiency and apoptosis changes observed in hypercholesterolemic rabbits. This paper reports the positive effects of the olive oil addition to the diet in the recovery of testicular efficiency and normal sperm shaping, mechanisms altered by hypercholesterolemia. Fil: Simón, Layla Yamila. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina Fil: Funes, Abi Karenina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina Fil: Monclus, Maria de Los Angeles. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. Universidad del Aconcagua; Argentina Fil: Colombo, Regina Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina Fil: Cabrillana, María Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. Universidad del Aconcagua; Argentina Fil: Saez Lancellotti, Tania Emilce Estefania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. Universidad del Aconcagua; Argentina Fil: Fornes, Miguel Walter. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas. Instituto de Histología y Embriología de Mendoza Dr. Mario H. Burgos; Argentina. Universidad del Aconcagua; Argentina

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

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.

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.

To deal with the conflicts between left-turn and through traffic streams and increase the discharge capacity, this paper addresses the pre-signal which is implemented at a signalized intersection. Such an intersection with pre-signal is termed as a tandem intersection. For the tandem intersection, phase swap sorting strategy is deemed as the most effective phasing scheme in view of some exclusive merits, such as easier compliance of drivers, and shorter sorting area. However, a major limitation of the phase swap sorting strategy is not considered in previous studies: if one or more vehicle is left at the sorting area after the signal light turns to red, the capacity of the approach would be dramatically dropped. Besides, previous signal control studies deal with a fixed timing plan that is not adaptive with the fluctuation of traffic flows. Therefore, to cope with these two gaps, this paper firstly takes an in-depth analysis of the traffic flow operations at the tandem intersection. Secondly, three groups of loop detectors are placed to obtain the real-time vehicle information for adaptive signalization. The lane selection behavior in the sorting area is considered to set the green time for intersection signals. With the objective of minimizing the vehicle delay, the signal control parameters are then optimized based on a dynamic programming method. Finally, numerical experiments show that average vehicle delay and maximum queue length can be reduced under all scenarios.

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.

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.

Glycosylphosphatidylinositol (GPI) anchoring of proteins is an essential post-translational modification in all eukaryotes that occurs at the endoplasmic reticulum (ER) and serves to deliver GPI-anchored proteins (GPI-APs) to the cell surface where they play a wide variety of vital physiological roles. This paper describes a specialized method for purification and structural analysis of the GPI glycan of individual GPI-APs in yeast. The protocol involves the expression of a specific GPI-AP tagged with GFP, enzymatic release from the cellular membrane fraction, immunopurification, separation by electrophoresis and analysis of the peptides bearing GPI glycans by mass spectrometry after trypsin digestion. We used specifically this protocol to address the structural remodeling that undergoes the GPI glycan of a specific GPI-AP during its transport to the cell surface. This method can be also applied to investigate the GPI-AP biosynthetic pathway and to directly confirm predicted GPI-anchoring of individual proteins., MM. BFU2017-89700-P. FEDER/Ministerio de Ciencia, Innovación y Universidades—Agencia Estatal de Investigación. http://www.aei.gob.es/. MN and KF. JP19H02922. Japan Society for the Promotion of Science. https://www.jsps.go.jp/english/.

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.

Neurofilaments(NFs) are the most abundant intermediate filaments that make up the inner volume of axon, with possible phosphorylation on their side arms, and their slow axonal transport by molecular motors along microtubule tracks in a “stop-and-go” manner with rapid, intermittent and bidirectional motion. The kinetics of NFs and morphology of axon are dramatically different between myelinate internode and unmyelinated node of Ranvier. The NFs in the node transport as 7.6 times faster as in the internode, and the distribution of NFs population in the internode is 7.6 folds as much as in the node of Ranvier. We hypothesize that the phosphorylation of NFs could reduce the on-track rate and slow down their transport velocity in the internode. By modifying the ‘6-state’ model with (a) an extra phosphorylation kinetics to each six state and (b) construction a new ‘8-state’ model in which NFs at off-track can be phosphorylated and have smaller on-track rate, our model and simulation demonstrate that the phosphorylation-induced decrease of on-track rate could slow down the NFs average velocity and increase the axonal caliber. The degree of phosphorylation may indicate the extent of velocity reduction. The Continuity equation used in our paper predicts that the ratio of NFs population is inverse proportional to the ratios of average velocity of NFs between node of Ranvier and internode. We speculate that the myelination of axon could increase the level of phosphorylation of NF side arms, and decrease the possibility of NFs to get on-track of microtubules, therefore slow down their transport velocity. In summary, our work provides a potential mechanism for understanding the phosphorylation kinetics of NFs in regulating their transport and morphology of axon in myelinated axons, and the different kinetics of NFs between node and internode.

Colorectal cancer (CRC) is one of the most prevalent types of cancer in the world and ranks second in cancer deaths in the US. Despite the recent improvements in screening and treatment, the number of deaths associated with CRC is still very significant. The complexities involved in CRC therapy stem from multiple oncogenic mutations and crosstalk between abnormal pathways. This calls for using advanced molecular genetics to understand the underlying pathway interactions responsible for this cancer. In this paper, we construct the CRC pathway from the literature and using an existing public dataset on healthy vs tumor colon cells, we identify the genes and pathways that are mutated and are possibly responsible for the disease progression. We then introduce drugs in the CRC pathway, and using a boolean modeling technique, we deduce the drug combinations that produce maximum cell death. Our theoretical simulations demonstrate the effectiveness of Cryptotanshinone, a traditional Chinese herb derivative, achieved by targeting critical oncogenic mutations and enhancing cell death. Finally, we validate our theoretical results using wet lab experiments on HT29 and HCT116 human colorectal carcinoma cell lines.

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

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.

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.

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.

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

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.

A recent result obtained by means of an in vitro experiment with cancer cultured cells has configured the endoplasmic reticulum as the preferential site for the accumulation of 2-deoxy-2-[18F]fluoro-D-glucose (FDG). Such a result is coherent with cell biochemistry and is made more significant by the fact that the reticular accumulation rate of FDG is dependent upon extracellular glucose availability. The objective of the present paper is to confirm in vivo the result obtained in vitro concerning the crucial role played by the endoplasmic reticulum in FDG cancer metabolism. This study utilizes data acquired by means of a Positron Emission Tomography scanner for small animals in the case of CT26 models of cancer tissues. The recorded concentration images are interpreted within the framework of a three-compartment model for FDG kinetics, which explicitly assumes that the endoplasmic reticulum is the dephosphorylation site for FDG in cancer cells. The numerical reduction of the compartmental model is performed by means of a regularized Gauss-Newton algorithm for numerical optimization. This analysis shows that the proposed three-compartment model equals the performance of a standard Sokoloff’s two-compartment system in fitting the data. However, it provides estimates of some of the parameters, such as the phosphorylation rate of FDG, more consistent with prior biochemical information. These results are made more solid from a computational viewpoint by proving the identifiability and by performing a sensitivity analysis of the proposed compartment model.

The DEFECTIVE EMBRYO AND MERISTEMS 1 (DEM1) gene encodes a protein of unknown biochemical function required for meristem formation and seedling development in tomato, but it was unclear whether DEM1’s primary role was in cell division or alternatively, in defining the identity of meristematic cells. Genome sequence analysis indicates that flowering plants possess at least two DEM genes. Arabidopsis has two DEM genes, DEM1 and DEM2, which we show are expressed in developing embryos and meristems in a punctate pattern that is typical of genes involved in cell division. Homozygous dem1 dem2 double mutants were not recovered, and plants carrying a single functional DEM1 allele and no functional copies of DEM2, i.e. DEM1/dem1 dem2/dem2 plants, exhibit normal development through to the time of flowering but during male reproductive development, chromosomes fail to align on the metaphase plate at meiosis II and result in abnormal numbers of daughter cells following meiosis. Additionally, these plants show defects in both pollen and embryo sac development, and produce defective male and female gametes. In contrast, dem1/dem1 DEM2/dem2 plants showed normal levels of fertility, indicating that DEM2 plays a more important role than DEM1 in gamete viability. The increased importance of DEM2 in gamete viability correlated with higher mRNA levels of DEM2 compared to DEM1 in most tissues examined and particularly in the vegetative shoot apex, developing siliques, pollen and sperm. We also demonstrate that gamete viability depends not only on the number of functional DEM alleles inherited following meiosis, but also on the number of functional DEM alleles in the parent plant that undergoes meiosis. Furthermore, DEM1 interacts with RAS-RELATED NUCLEAR PROTEIN 1 (RAN1) in yeast two-hybrid and pull-down binding assays, and we show that fluorescent proteins fused to DEM1 and RAN1 co-localize transiently during male meiosis and pollen development. In eukaryotes, RAN is a highly conserved GTPase that plays key roles in cell cycle progression, spindle assembly during cell division, reformation of the nuclear envelope following cell division, and nucleocytoplasmic transport. Our results demonstrate that DEM proteins play an essential role in cell division in plants, most likely through an interaction with RAN1., Author summary Up to half of the genes predicted from genome projects lack a known biological and biochemical function. Many of these genes are likely to play essential roles but it is difficult to reveal their function because minor changes in the genetic sequence can result in lethality and genetic redundancy can obscure analysis. Genome projects predict that flowering plants have at least two DEM genes that encode a protein of unknown cellular and biochemical function. In this paper, we use multiple combinations of dem mutants in Arabidopsis to show that DEM genes are essential for cell division and gamete viability. Interestingly, gamete viability depends not only on the number of functional copies of DEM genes in the gametes, but also on the number of functional copies of DEM genes in the parent plant that produces the gametes. We also show that DEM proteins interact with RAN, a highly conserved protein that controls cell division in all eukaryotic organisms.

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.

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

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

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

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

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

The accurate segmentation and tracking of cells in microscopy image sequences is an important task in biomedical research, e.g., for studying the development of tissues, organs or entire organisms. However, the segmentation of touching cells in images with a low signal-to-noise-ratio is still a challenging problem. In this paper, we present a method for the segmentation of touching cells in microscopy images. By using a novel representation of cell borders, inspired by distance maps, our method is capable to utilize not only touching cells but also close cells in the training process. Furthermore, this representation is notably robust to annotation errors and shows promising results for the segmentation of microscopy images containing in the training data underrepresented or not included cell types. For the prediction of the proposed neighbor distances, an adapted U-Net convolutional neural network (CNN) with two decoder paths is used. In addition, we adapt a graph-based cell tracking algorithm to evaluate our proposed method on the task of cell tracking. The adapted tracking algorithm includes a movement estimation in the cost function to re-link tracks with missing segmentation masks over a short sequence of frames. Our combined tracking by detection method has proven its potential in the IEEE ISBI 2020 Cell Tracking Challenge (http://celltrackingchallenge.net/) where we achieved as team KIT-Sch-GE multiple top three rankings including two top performances using a single segmentation model for the diverse data sets., 25 pages, 14 figures, methods of the team KIT-Sch-GE for the IEEE ISBI 2020 Cell Tracking Challenge

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.

Counting chromosomes is the first step towards a better understanding of the karyotype evolution and the role of chromosome evolution in species diversification within Carex; however, the chromosome count is not known yet for numerous sedges. In this paper chromosome counts were performed for 23 Carex taxa from Armenia, Austria, the Czech Republic, and Poland. Chromosome numbers were determined for the first time in three species (Carex cilicica, 2n = 54; C. phyllostachys, 2n = 56; C. randalpina, 2n = 78), two subspecies (C. muricata subsp. ashokae, 2n = 58; C. nigra subsp. transcaucasica, 2n = 84) and two hybrids (C. ×decolorans, 2n = 74; C. ×walasii, 2n = 108). Among the taxa whose number of chromosomes had been known before, the largest difference was found in C. hartmaniorum (here 2n = 52) and C. aterrima subsp. medwedewii (here 2n = 52). A difference in the chromosome count was demonstrated for C. cilicica (2n = 54) versus the species of the section Aulocystis (2n = 30 to 40) and for C. tomentosa (2n = 48) versus the species of the section Acrocystis (2n = 18 to 38). The results of this study indicate that the position of C. cilicica in Aulocystis section may raise doubts. Attention was paid to the relationship between C. phyllostachys and taxa of the subgenus Carex section Gynobasidae.

International audience; Classical stochastic models of protein production usually do not consider several phenomena within the cell such as cell volume growth, cell division or gene replication, furthermore concentrations of RNA-polymerases and ribosomes are in general assumed to be constant. In this paper we study the effects induced by all these different aspects on protein variability. Starting from the classical two-stage protein production model, we successively integrate the volume growth, the random partition of compounds at division, the gene replication and the sharing of RNA-polymerases and ribosomes for the production of all types of proteins. Experimental measures are used to determine the numerical values of the parameters of our models. We are then able to investigate the impact of these different phenomena on the variability of a large class of proteins. The main conclusions are that, among all different mechanisms studied, the random partitioning of macro-molecules at division is the only one which may have a significant impact on the variance of protein concentration. In particular, the variability induced by the sharing of RNA-polymerases and ribosomes seems to be of a smaller order of magnitude than what is generally suggested in the literature.

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.

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

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.

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

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

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

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.

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

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

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

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

The cell cycle is the fundamental process of cell populations, it is regulated by environmental cues and by intracellular checkpoints. Cell cycle variability in clonal cell population is caused by stochastic processes such as random partitioning of cellular components to progeny cells at division and random interactions among biomolecules in cells. One of the important biological questions is how the dynamics at the cell cycle scale, which is related to family dependencies between the cell and its descendants, affects cell population behavior in the long-run. We address this question using a “mechanistic” model, built based on observations of single cells over several cell generations, and then extrapolated in time. We used cell pedigree observations of NIH 3T3 cells including FUCCI markers, to determine patterns of inheritance of cell-cycle phase durations and single-cell protein dynamics. Based on that information we developed a hybrid mathematical model, involving bifurcating autoregression to describe stochasticity of partitioning and inheritance of cell-cycle-phase times, and an ordinary differential equation system to capture single-cell protein dynamics. Long-term simulations, concordant with in vitro experiments, demonstrated the model reproduced the main features of our data and had homeostatic properties. Moreover, heterogeneity of cell cycle may have important consequences during population development. We discovered an effect similar to genetic drift, amplified by family relationships among cells. In consequence, the progeny of a single cell with a short cell cycle time had a high probability of eventually dominating the population, due to the heritability of cell-cycle phases. Patterns of epigenetic heritability in proliferating cells are important for understanding long-term trends of cell populations which are either required to provide the influx of maturing cells (such as hematopoietic stem cells) or which started proliferating uncontrollably (such as cancer cells)., Author summary All cells in multicellular organisms obey orchestrated sequences of signals to ensure developmental and homeostatic fitness under a variety of external stimuli. However, there also exist self-perpetuating stem-cell populations, the function of which is to provide a steady supply of differentiated progenitors that in turn ensure persistence of organism functions. This “cell production engine” is an important element of biological homeostasis. A similar process, albeit distorted in many respects, plays a major role in cancer development; here the robustness of homeostasis contributes to difficulty in eradication of malignancy. An important role in homeostasis seems to be played by generation of heterogeneity among cell phenotypes, which then can be shaped by selection and other genetic forces. In the present paper, we present a model of a cultured cell population, which factors in relationships among related cells and the dynamics of cell growth and important proteins regulating cell division. We find that the model not only maintains homeostasis, but that it also responds to perturbations in a manner that is similar to that exhibited by the Wright-Fisher model of population genetics. The model-cell population can become dominated by the progeny of the fittest individuals, without invoking advantageous mutations. If confirmed, this may provide an alternative mode of evolution of cell populations.

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.

The genus Cyphostemma (Planch.) Alston (Vitaceae) includes about 150 species distrib- uted in eastern and southern Africa and Madagascar. Some species are used in traditional medicine and their biological activities, including antiproliferative effects against cancer cell lines, have been demonstrated. To date no investigations on Cyphostemma essential oils have been carried out. Essential oils, which play important roles in plant defenses have been demonstrated to be active in the treatment of several human diseases and to enhance bioavability of other drugs. The aim of this paper was to identify the chemical composition of the essential oil of the leaves of Cyphostemma juttae (Dinter & Gilg) Desc. and to verify some biological activities on two triple negative breast cancer cell lines (MDA-MB-231, SUM 149), characterized by the over-expression of the transcription factor NF-κB. In the essential oil, obtained by hydrodistillation and analysed by gas chromatography-mass spectrometry, 39 compounds were detected and with phytol (30%) dominating the chemical composition. C. juttae essential oil reduced cell growth and showed a pro-oxidant activity in both cell lines. Moreover, C. juttae essential oil caused a substantial decrease of NF-κB activation and consequently a significant reduction of some NF-κB target genes. The present study shows for the first time the cytotoxic properties of C. juttae essential oil and highlight its avail- ability to interfere with NF-κB pathway, suggesting a potential therapeutic use in triple nega- tive breast cancers (TNBCs) of this essential oil.