Stochastic multi-scale models of competition within heterogeneous cellular populations: simulation methods and mean-field analysis

We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age. The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. We then formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size: cells consume oxygen which in turns fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established three main results. First, we have shown that the age to the G1/S transition, which essentially determines the birth rate, exhibits a remarkably simple scaling behaviour. This allows for a huge simplification of our numerical methodology. A further result is the observation that heterogeneous populations undergo an internal process of quasi-neutral competition. Finally, we investigated the effects of cell-cycle-phase dependent therapies (such as radiation therapy) on heterogeneous populations. In particular, we have studied the case in which the population contains a quiescent sub-population. Our mean-field analysis and numerical simulations confirm that, if the survival fraction of the therapy is too high, rescue of the quiescent population occurs. This gives rise to emergence of resistance to therapy since the rescued population is less sensitive to therapy

Minimum Action Path theory reveals the details of stochastic biochemical transitions out of oscillatory cellular states

Cell state determination is the outcome of intrinsically stochastic biochemical reactions. Tran- sitions between such states are studied as noise-driven escape problems in the chemical species space. Escape can occur via multiple possible multidimensional paths, with probabilities depending non-locally on the noise. Here we characterize the escape from an oscillatory biochemical state by minimizing the Freidlin-Wentzell action, deriving from it the stochastic spiral exit path from the limit cycle. We also use the minimized action to infer the escape time probability density function

Exploring Students’ Beliefs about Autonomy in an EFL Setting

89 páginasThe present study aims to explore the beliefs students hold about autonomy in reference to responsibility, ability and willingness to plan, motivate and evaluate learning. This study was carried out at Universidad Cooperativa de Colombia, Pasto campus, where English language courses require learners to approach learning from an autonomous perspective. However, no previous studies have been carried out to determine whether or not learners have the characteristics of autonomous learners. A total of 432 students participated in the study. They answered a 30 closed-item multiple choice format questionnaire created to elicit students’ beliefs about autonomy. The results showed that learners consider learning to be a shared process in terms of responsibility. Nevertheless, conventional tasks are still observed as a responsibility for teachers. Results also showed that learners considered themselves to be able and felt willing to make decisions concerning planning, motivation and evaluation

Collective action in ant control:

Leaf-cutting ants (Atta. cephalotes) represents a serious problem to farmers in many parts of Latin America and accounts of ants eating up a whole cassava plot or destroying one or more fruit trees overnight are not uncommon. Ants do not respect farm boundaries. Therefore, farmers who control anthills on their own fields might still face damage on their crops caused by ants coming from neighboring fields where no control measures are taken. In that sense, crop damage caused by leaf-cutting ants constitutes a transboundary natural resource management problem which, in addition to technical interventions, requires organizational interventions to ensure a coordinated effort among farmers to be solved. This paper reports on a research effort initiated by CIAT and implemented jointly between CIAT and farmers in La Laguna - a small community in the Andean Hillsides of Southwestern Colombia. The objective of the research effort was two-fold: i) to identify low cost technical options for ant control, and ii) to analyze and visualize the transboundary nature of the ant control problem and thus identify organizational options to enable collective or coordinated ant control.

Event-Based Regression with Spiking Networks

Spiking Neuron Networks (SNNs), also known as the third generation of neural networks, are inspired from natural computing in the brain and recent advances in neuroscience. SNNs can overcome the computational power of neural networks made of threshold or sigmoidal units. Recent advances on event-based devices along with their great power, considering the time factor, make SNNs a cutting-edge priority research objective. SNNs have been used mainly for classification problems, but their application to regression tasks remains challenging due to the complexity of training with continuous output data. In the literature we can find some first approximations in regression, specifically, for problems of a single variable of continuous values. This work deals with the analysis of the behavior of SNNs as predictors of multivariable continuous values. For this, a data set based on events has been generated from a bouncing ball and an event-based camera. The goal is to predict the next position of the ball over time

SpikeBALL: Neuromorphic Dataset for Object Tracking

Most of widely used datasets are not suitable for Spiking Neural Networks (SNNs) due to the need to encode the static data into spike trains and then put them into the network. In addition, the majority of these datasets have been generated to classify objects and can not be used to solve object tracking problems. Therefore, we propose a new neuromorphic dataset, SpikeBALL, for object tracking that contributes to improve the development of the SNN algorithm for these type of problems

Biorefinery concept in the meat industry: From slaughterhouse biowastes to superaborbent materials

The expansion of food production has a large environmental impact in many ways. More specifically, 30–40% of total food production is lost as wastes and/or by-products before it reaches the market. In this sense, blood is an inevitable by-product in the meat industry that typically consists of 3–5% of the total weight of the animal. The dry organic matter present in blood is mostly protein, which can be employed more efficiently as raw material in the development of biodegradable materials. In the present manuscript, the blood collected after slaughtering of Iberian pigs was centrifuged and the upper (i.e., plasma) and bottom (i.e., red cells) layers were separated. Three freeze-dried fractions were characterized and evaluated on terms of their potential in the field of bioplastics: whole blood, plasma and bottom layer. Albumin was detected clearly in the plasma fraction, while globulins in red cells. After their characterization samples were mixed thoroughly with glycerol and injection molded at 120 ◦C. Special applications may be proposed for every fraction (i.e., whole blood, plasma or red cells), as the materials displayed different properties depending on the raw material employed. Thus, plasma resulted in materials with a greater deformability and swelling capacity during immersion, resulting in superabsorbent materials when processed at milder conditions (80 ◦C)The authors acknowledge the projects PID2021-124294OB-C21 and PID2021-124294OB-C22 funded by MCIN/AEI/10.13039/ 501100011033/ and by “ERDF A way of making Europe” which sup- ported this study. K.C. and P.G. thank the Basque Government for BIOMAT funding (IT1658-22). The authors would like to thank the Spanish Ministerio de Universidades for the PhD grant PRE2019-089815 awarded to E. ´Alvarez-Castillo. The blood used was collected from a local slaughterhouse, Mataderos del Sur, S.A. Authors also would like to thank for kindly supplying the raw material employed in the study. The authors also acknowledge to the Microanalysis and Microscopy services from CITIUS (Universidad de Sevilla) for providing full access and assistance to equipment used