The impact of environmental noise on animal communication:pattern formation in a class of deterministic and stochastic hyperbolic models for self-organised biological aggregations

The collective movement of animalsoccurs as a result of communication between the members of the community. However, inter-individual communication can be aected by the stochasticity of the environment, leading to changes in the perception of neighbours and subsequent changes in  individual behaviour, which then in uence the overall behaviour of the animal aggregations. To investigate the eect of noise on the overall behaviour of animal aggregations, we consider a class of nonlocal stochastic and deterministic hyperbolic models for the collective movement of animals. We show numerically that strong noise does not seem to in uence the spatio-temporal pattern (i.e., travelling aggregations) observed when all neighbours are perceived with the same intensity (i.e., the environment is homogeneous). However, when neighbours ahead/behind are perceived dierently by a reference individual, noise can lead to the destruction of the spatio-temporal pattern. Moreover, we show that the increase in noise can lead to dierent transitions between different spatio-temporal patterns, and these transitions are relatively similar to the transitions between patterns when we perturb deterministically some parameters

Modeling communication and movement: from cells to animals and humans

Communication forms the basis of biological interactions. While the use of a single communication mechanism (for example visual communication) by a species is quite well understood, in nature the majority of species communicate via multiple mechanisms. Here, I review some mathematical results on the unexpected behaviors that can be observed in biological aggregations where individuals interact with each other via multiple communication mechanisms

THE MAIN REASONS UNDERLYING PERSONAL INVESTMENT IN EDUCATION

In a globalized world where information means power, we are witnessing a reorganization of the labor market, consisting in its computerization, thus, in order to successfully cope with an increasingly sophisticated job, certain skills, advanced knowledge and a diploma of higher education in the field are required. In this context, young people are considering more than ever to invest in their training level, strongly motivated to increase their earnings and quality of life. Throughout life, individuals are encouraged and find reasons to determine them to invest in education and professional development because through the educational system they acquire abilities and knowledge, which are reflected by the change of a person towards the benefit of the entire society.motivation, education investment, earnings, higher education

The Role of Education within a Knowledge Based Society: Teachers’ Perception on how e-Learning Systems can be integrated in Classroom Activities

The development of the interactive, collaborative and dynamic e-learning methods is considered the primary mode of evolution of the Romanian and international educational systems. Most of the studies have revealed the widespread benefits of these technologies and exemplifying their applicability and their evolution within the education systems. However, few studies clearly identify the role that e-learning platforms have in the improvement of teaching - learning and how these technologies can be integrated into the classroom. This article proposes a new approach related to the integration of these systems while providing educational acts, starting by identifying and understanding the perceptions that teachers have regarding this type of innovative technology, explaining and interpreting the results of a qualitative research conducted within Romanian educational market. Teacher’s perception on the role of e-learning education is interpreted as a factor, which influences the quality of the use and the integration of these technologies in the Romanian educational environment, reaffirming the need for a coherent implementation of these instruments at a specific school level but also at general educational environment integration

Improving cancer detection through combinations of cancer and immune biomarkers:a modelling approach

Abstract Background Early cancer diagnosis is one of the most important challenges of cancer research, since in many cancers it can lead to cure for patients with early stage diseases. For epithelial ovarian cancer (which is the leading cause of death among gynaecologic malignancies) the classical detection approach is based on measurements of CA-125 biomarker. However, the poor sensitivity and specificity of this biomarker impacts the detection of early-stage cancers. Methods Here we use a computational approach to investigate the effect of combining multiple biomarkers for ovarian cancer (e.g., CA-125 and IL-7), to improve early cancer detection. Results We show that this combined biomarkers approach could lead indeed to earlier cancer detection. However, the immune response (which influences the level of secreted IL-7 biomarker) plays an important role in improving and/or delaying cancer detection. Moreover, the detection level of IL-7 immune biomarker could be in a range that would not allow to distinguish between a healthy state and a cancerous state. In this case, the construction of solution diagrams in the space generated by the IL-7 and CA-125 biomarkers could allow us predict the long-term evolution of cancer biomarkers, thus allowing us to make predictions on cancer detection times. Conclusions Combining cancer and immune biomarkers could improve cancer detection times, and any predictions that could be made (at least through the use of CA-125/IL-7 biomarkers) are patient specific

Modelling the collective response of heterogeneous cell populations to stationary gradients and chemical signal relay

The directed motion of cell aggregates toward a chemical source occurs in many relevant biological processes. Understanding the mechanisms that control this complex behavior is of great relevance for our understanding of developmental biological processes and many diseases. In this paper, we consider a self-propelled particle model for the movement of heterogeneous subpopulations of chemically interacting cells towards an imposed stable chemical gradient. Our simulations show explicitly how self-organisation of cell populations (which could lead to engulfment or complete cell segregation) can arise from the heterogeneity of chemotactic responses alone. This new result complements current theoretical and experimental studies that emphasise the role of differential cell–cell adhesion on self-organisation and spatial structure of cellular aggregates. We also investigate how the speed of individual cell aggregations increases with the chemotactic sensitivity of the cells, and decreases with the number of cells inside the aggregates

A mathematical model for the role of macrophages in the persistence and elimination of oncolytic viruses

Replicating oncolytic viruses provide promising treatment strategies against cancer. However, the success of these viral therapies depends mainly on the complex interactions between the virus particles and the host immune cells. Among these immune cells, macrophages represent one of the first line of defence against viral infections. In this paper, we consider a mathematical model that describes the interactions between a commonly-used oncolytic virus, the Vesicular Stomatitis Virus (VSV), and two extreme types of macrophages: the pro-inflammatory M1 cells (which seem to resist infection with VSV) and the anti-inflammatory M2 cells (which can be infected with VSV). We first show the existence of bounded solutions for this differential equations model. Then we investigate the long-term behaviour of the model by focusing on steady states and limit cycles, and study changes in this long-term dynamics as we vary different model parameters. Moreover, through sensitivity analysis we show that the parameters that have the highest impact on the level of virus particles in the system are the viral burst size (from infected macrophages), the virus infection rate, the M1$\to$M2 polarisation rate, and the M1-induced anti-viral immunity