Effective recognition of foreign antigens by the adaptive immune system relies on T cells being activated by antigen-presenting cells (APCs) in lymph nodes. Here, diffusing T cells may encounter cognate APCs that present matching antigen fragments or non-cognate ones that do not; they are also subject to degradation. We develop a stochastic model in which T cell-APCs interact via a sequence of recognition steps, represented as a multistage Markov chain. T cells are successfully activated only if the terminal state associated with a cognate APC is reached. We compute the probability of successful activation in the presence of interfering non-cognate APCs, T cell degradation, and lymph node exit, and analyze the mean first-passage time to activation. We also incorporate a kinetic proofreading mechanism that enables state resetting, and show how this enhances specificity toward cognate APCs.
The biochronometers used to keep time in eukaryotes include short-period biochronometer (SPB) and long-period biochronometer (LPB). Because the circadian clock reflects the biological time rhythm of a day, it is considered as SPB. Telomere shortening, which reflects the decreasing of telomere DNA length of chromosomes with the increase of cell division times, can be used to time the lifespan of organisms, so it is regarded as LPB. It is confirmed that SPB and LPB exist in most eukaryotes, and it is speculated that SPB and LPB are closely related. In this paper, based on existing studies, it is speculated that SPB and LPB of most eukaryotes can be co-attenuated with cell division in the process of aging. Due to the attenuated phenomenon of key components in the biochronometers during the growth and development of organisms, the biochronometers attenuate with the aging. Based on existing research results, it is preliminarily determined that the biochronometers can be rebuilt in the co-attenuated process. When the key components of biochronometers are reversed and increased in the organism, it can lead to the reversal of biochronometers, which further leads to the phenomenon of biological rejuvenation and makes the organism younger. In addition, the rebuilding of biochronometers can also lead to the acceleration of biochronometers and the shortening of the original timing time of biochronometers, thus shortening the life span of organisms. The rebuilding of biochronometers includes the reversal of biochronometers, the truncation of biochronometers timing and Uncoordinated co-attenuation of biochronometer and so on. The reversal of the biochronometers, which leads to rejuvenation, can give us a whole new understanding of life expectancy to be different from anti-aging.
Ricardo Omar Ramirez Flores, Philipp Sven Lars Schäfer, Leonie Küchenhoff
et al.
The application of single-cell molecular profiling coupled with spatial technologies has enabled charting cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single cell and spatial datasets, to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.
Mohammed Mouhcine, Youness Kadil1, Imane Rahmoune
et al.
Colorectal cancer is a public health problem.Approximately 30 to 50 \% of colorectal tumors are caused by mutations in the KRAS gene.These mutations induce uncontrolled proliferation.To date,There is no approved effective treatment for the mutated KRAS oncogene.Farnesyltransferase (FTI) inhibitors are considered a therapeutic target against the mutated KRAS oncogene.Tipifarnib is a farnesyltransferase inhibitor that was analyzed in a Phase II trial.In the present study, the three-dimensional structure of farnesyltransferase complexed with tipifarnib [1SA4] was used as a basis to exploit the characteristics of tipifarnib.A pharmacophore model was generated based on the structure using the Asinex (Gold and Platinum Collections) database.A total of 299 molecules were obtained after screening.The 299 molecules were anchored to the tipifarnib binding site in the farnesyltransferase crystal structure for docking analysis.During the molecular docking process, the pharmacophore that was modeled, and was used as a constraint to eliminate the molecules that do not satisfy the pharmacophore.Finally, four Hits identified as farnesyltransferase inhibitors for biological tests. Keywords: colorectal cancer, structure-based pharmacophore, molecular docking, KRAS, farnesyltransferase inhibitors, Virtual Screening.
Carlos Lopez-Franco, Dario Diaz, Jesus Hernandez-Barragan
et al.
Due to the complexity of manipulator robots, the trajectory tracking task is very challenging. Most of the current algorithms depend on the robot structure or its number of degrees of freedom (DOF). Furthermore, the most popular methods use a Jacobian matrix that suffers from singularities. In this work, the authors propose a general method to solve the trajectory tracking of robot manipulators using metaheuristic optimization methods. The proposed method can be used to find the best joint configuration to minimize the end-effector position and orientation in 3D, for robots with any number of DOF.
Daniel Ríos-Rivera, Alma Y. Alanis, Edgar N. Sanchez
In this work, a neural impulsive pinning controller for a twenty-node dynamical discrete complex network is presented. The node dynamics of the network are all different types of discrete versions of chaotic attractors of three dimensions. Using the V-stability method, we propose a criterion for selecting nodes to design pinning control, in which only a small fraction of the nodes is locally controlled in order to stabilize the network states at zero. A discrete recurrent high order neural network (RHONN) trained with extended Kalman filter (EKF) is used to identify the dynamics of controlled nodes and synthesize the control law.
Sandrine Lavenus, Élie Simard, Élie Besserer-Offroy
et al.
Angiotensin II (AngII) type 1 receptor (AT1R) is a G protein-coupled receptor known for its role in numerous physiological processes and its implication in many vascular diseases. Its functions are mediated through G protein dependent and independent signaling pathways. AT1R has several endogenous peptidic agonists, all derived from angiotensinogen, as well as several synthetic ligands known to elicit biased signaling responses. Here, surface plasmon resonance (SPR) was used as a cell- based and label-free technique to quantify, in real time, the response of HEK293 cells stably expressing the human AT1R. The goal was to take advantage of the integrative nature of this assay to identify specific signaling pathways in the features of the response profiles generated by numerous endogenous and synthetic ligands of AT1R. First, we assessed the contributions of Gq, G12/13, Gi, Gbg, ERK1/2 and \b{eta}- arrestins pathways in the cellular responses measured by SPR where Gq, G12/Rho/ROCK together with \b{eta}-arrestins and ERK1/2 were found to play significant roles. More specifically, we established a major role for G12 in the early events of the AT1R-dependent response, which was followed by a robust ERK1/2 component associated to the later phase of the signal. Interestingly, endogenous AT1R ligands (AngII, AngIII and AngIV) exhibited distinct responses signatures with a significant increase of the ERK1/2-like components for both AngIII and AngIV, which points toward possibly distinct physiological roles for the later. We also tested AT1R biased ligands, all of which affected both the early and later events. Our results support SPR-based integrative cellular assays as a powerful approach to delineate the contribution of specific signaling pathways for a given cell response and reveal response differences associated with ligands with distinct pharmacological properties.
Jake P. Taylor-King, Etienne Baratchart, Andrew Dhawan
et al.
Intra-tumour phenotypic heterogeneity limits accuracy of clinical diagnostics and hampers the efficiency of anti-cancer therapies. Dealing with this cellular heterogeneity requires adequate understanding of its sources, which is extremely difficult, as phenotypes of tumour cells integrate hardwired (epi)mutational differences with the dynamic responses to microenvironmental cues. The later come in form of both direct physical interactions, as well as inputs from gradients of secreted signalling molecules. Furthermore, tumour cells can not only receive microenvironmental cues, but also produce them. Despite high biological and clinical importance of understanding spatial aspects of paracrine signaling, adequate research tools are largely lacking. Here, a partial differential equation (PDE) based mathematical model is developed that mimics the process of cell ablation. This model suggests how each cell might contribute to the microenvironment by either absorbing or secreting diffusible factors, and quantifies the extent to which observed intensities can be explained via diffusion mediated signalling. The model allows for the separation of phenotypic responses to signalling gradients within tumour microenvironments from the combined influence of responses mediated by direct physical contact and hardwired (epi)genetic differences. The differential equation is solved around cell membrane outlines using a finite element method (FEM). The method is applied to a multi-channel immunofluorescence in situ hybridization (iFISH) stained breast cancer histological specimen and correlations are investigated between: HER2 gene amplification; HER2 protein expression; and cell interaction with the diffusible microenvironment. This approach allows partial deconvolution of the complex inputs...
Eduardo P. Olimpio, Diego R. Gomez-Alvarez, Hyun Youk
Living systems, particularly multicellular systems, often seem hopelessly complex. But recent studies have suggested that beneath this complexity, there may be unifying quantitative principles that we are only now starting to unravel. All cells interact with their environments and with other cells. Communication among cells is a primary means for cells to interact with each other. The complexity of these multicellular systems, due to the large numbers of cells and the diversity of intracellular and intercellular interactions, makes understanding multicellular systems a daunting task. To overcome this challenge, we will likely need judicious simplifications and conceptual frameworks that can reveal design principles that are shared among diverse multicellular systems. Here we review some recent progress towards developing such frameworks.
Andrew Mugler, Mark Kittisopikul, Luke Hayden
et al.
Gene regulatory circuits must contend with intrinsic noise that arises due to finite numbers of proteins. While some circuits act to reduce this noise, others appear to exploit it. A striking example is the competence circuit in Bacillus subtilis, which exhibits much larger noise in the duration of its competence events than a synthetically constructed analog that performs the same function. Here, using stochastic modeling and fluorescence microscopy, we show that this larger noise allows cells to exit terminal phenotypic states, which expands the range of stress levels to which cells are responsive and leads to phenotypic heterogeneity at the population level. This is an important example of how noise confers a functional benefit in a genetic decision-making circuit.
Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated) decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.
Edén Bojórquez, Alfredo Reyes-Salazar, Sonia E. Ruiz
et al.
Several studies have been devoted to calibrate damage indices for steel and reinforced concrete members with the purpose of overcoming some of the shortcomings of the parameters currently used during seismic design. Nevertheless, there is a challenge to study and calibrate the use of such indices for the practical structural evaluation of complex structures. In this paper, an energy-based damage model for multidegree-of-freedom (MDOF) steel framed structures that accounts explicitly for the effects of cumulative plastic deformation demands is used to estimate the cyclic drift capacity of steel structures. To achieve this, seismic hazard curves are used to discuss the limitations of the maximum interstory drift demand as a performance parameter to achieve adequate damage control. Then the concept of cyclic drift capacity, which incorporates information of the influence of cumulative plastic deformation demands, is introduced as an alternative for future applications of seismic design of structures subjected to long duration ground motions.
T11 Target structure (T11TS), a membrane glycoprotein isolated from sheep erythrocytes, reverses the immune suppressed state of brain tumor induced animals by boosting the functional status of the immune cells. This study aims at aiding in the design of more efficacious brain tumor therapies with T11 target structure. We propose a mathematical model for brain tumor (glioma) and the immune system interactions, which aims in designing efficacious brain tumor therapy. The model encompasses considerations of the interactive dynamics of macrophages, cytotoxic T lymphocytes, glioma cells, TGF-$β$, IFN-$γ$ and the T11TS. The system undergoes sensitivity analysis, that determines which state variables are sensitive to the given parameters and the parameters are estimated from the published data. Computer simulations were used for model verification and validation, which highlight the importance of T11 target structure in brain tumor therapy.
Microbes require several complex organic molecules for growth. A species may obtain a required factor by taking up molecules released by other species or by synthesizing the molecule. The patterns of uptake and synthesis set a flow of resources through the multiple species that create a microbial community. This article analyzes a simple mathematical model of the tradeoff between uptake and synthesis. Key factors include the influx rate from external sources relative to the outflux rate, the rate of internal decay within cells, and the cost of synthesis. Aspects of demography also matter, such as cellular birth and death rates, the expected time course of a local resource flow, and the associated lifespan of the local population. Spatial patterns of genetic variability and differentiation between populations may also strongly influence the evolution of metabolic regulatory controls of individual species and thus the structuring of microbial communities. The widespread use of optimality approaches in recent work on microbial metabolism has ignored demography and genetic structure.
Kathryn Osterday, Thomas Chew, Phillip Loury
et al.
In this paper, we study how cytoskeletal remodeling is correlated to changes in subcellular microrheology. We analyze the changes in the magnitude and directionality of the shear and elastic moduli of bovine aortic endothelial cells (BAECs) exposed to cyclical, uniaxial stretch. We find that, when stretched, BAECs stiffen and align their softest direction of mechanical polarization perpendicular to stretch. We hypothesize that the response of VECs to stretch acts to minimize intracellular strain in response to stress.
Sayak Mukherjee, Stephanie Rigaud, Sang-Cheol Seok
et al.
The inositol-phosphate messenger inositol(1,3,4,5)tetrakisphosphate (IP4) is essential for thymocyte positive selection by regulating plasma-membrane association of the protein tyrosine kinase Itk downstream of the T cell receptor (TCR). IP4 can act as a soluble analog of the phosphoinositide 3-kinase (PI3K) membrane lipid product phosphatidylinositol(3,4,5)trisphosphate (PIP3). PIP3 recruits signaling proteins such as Itk to cellular membranes by binding to PH and other domains. In thymocytes, low-dose IP4 binding to the Itk PH domain surprisingly promoted and high-dose IP4 inhibited PIP3 binding of Itk PH domains. However, the mechanisms that underlie the regulation of membrane recruitment of Itk by IP4 and PIP3 remain unclear. The distinct Itk PH domain ability to oligomerize is consistent with a cooperative-allosteric mode of IP4 action. However, other possibilities cannot be ruled out due to difficulties in quantitatively measuring the interactions between Itk, IP4 and PIP3, and in generating non-oligomerizing Itk PH domain mutants. This has hindered a full mechanistic understanding of how IP4 controls Itk function. By combining experimentally measured kinetics of PLCγ1 phosphorylation by Itk with in silico modeling of multiple Itk signaling circuits and a maximum entropy (MaxEnt) based computational approach, we show that those in silico models which are most robust against variations of protein and lipid expression levels and kinetic rates at the single cell level share a cooperative-allosteric mode of Itk regulation by IP4 involving oligomeric Itk PH domains at the plasma membrane. This identifies MaxEnt as an excellent tool for quantifying robustness for complex TCR signaling circuits and provides testable predictions to further elucidate a controversial mechanism of PIP3 signaling.
Microtubules (MTs) are cytoplasmic protein polymers that are essential for fundamental cellular processes including the maintenance of cell shape, organelle transport and formation of the mitotic spindle. Microtubule dynamic instability is critical for these processes, but it remains poorly understood, in part because the relationship between the structure of the MT tip and the growth/depolymerization transitions is enigmatic. What are the functionally significant aspects of a tip structure that is capable of promoting MT growth, and how do changes in these characteristics cause the transition to depolymerization (catastrophe)? Here we use computational models to investigate the connection between cracks (laterally unbonded regions) between protofilaments and dynamic instability. Our work indicates that it is not the depth of the cracks per se that governs MT dynamic instability. Instead it is whether the cracks terminate in GTP-rich or GDP-rich areas of the MT that governs whether a particular MT tip structure is likely to grow, shrink, or transition: the identity of the crack-terminating subunit pairs has a profound influence on the moment-by-moment behavior of the MT.