Biology subjects

Marcati, P.

Publications and source records attributed to Marcati, P..

4 recordsLinked to original sources

bioRxiv2022

A mechanistic model towards ecological inclusion for a better plant growth understanding

Plants growth is a complex and delicate balance among different factors involving environmental and physiological conditions. In this context, we propose a mechanistic model that considers the main internal processes of plant growth and reproduces a wide range of plant behaviors observed experimentally. In particular, we describe the model plant of Arabidopsis thaliana in a realistic environment with a day-and-night cycle, which considers different inputs as light, water, phosphorus, nitrogen, starch and sucrose. In addition, we propose a new function that describes the affinity between the plant and a specific nutrient, and a novel feedback signal to model how plants have the remarkable capacity to distribute resources among their organs. The result is an efficient tool applicable in ecological and agricultural studies, which can estimate several parameters, simulate several soil conditions and analyze how limiting or toxic resources can affect the plant development. We improve our understanding of plant adaptive strategies, reproducing results in line with experiments.

plant biology↗

bioRxiv2020

A general 3D model for growth dynamics of sensory-growth systems: from plants to robotics

In recent years there has been a rise in interest in the development of self-growing robotics inspired by the moving-by-growing paradigm of plants. In particular, climbing plants capitalize on their slender structures to successfully negotiate unstructured environments, while employing a combination of two classes of growth-driven movements: tropic responses, which direct growth in the direction of an external stimulus, and inherent nastic movements, such as periodic circumnutations, which promote exploration. In order to emulate these complex growth dynamics in a 3D environment, a general and rigorous mathematical framework is required. Here we develop a general 3D model for rod-like organs adopting the Frenet-Serret frame, providing a useful framework from the standpoint of robotics control. Differential growth drives the dynamics of the organ, governed by both internal and external cues. We describe the numerical method required to implement this model, and perform numerical simulations of a number of key scenarios, showcasing the applicability of our model. In the case of responses to external stimuli, we consider a distant stimulus (such as sunlight and gravity), a point stimulus (a point light source), and a line stimulus which emulates twining of a climbing plant around a support. We also simulate circumnutations, the response to an internal oscillatory cue, associated with search processes. Lastly we also demonstrate the superposition of both the response to an external stimulus together with circumnutations. Lastly we consider a simple example illustrating the possible use of an optimal control approach in order to recover tropic dynamics, in a way which may be relevant for robotics use. In all, the model presented here is general and robust, paving the way for a deeper understanding of plant response dynamics, as well as novel control systems for newly developed self-growing robots.

biophysics↗

bioRxiv2019

A comparison of two mathematical models of the cerebrospinal fluid dynamics

In this paper we provide the numerical simulations of two cerebrospinal fluid dynamics models by comparing our results with the real data available in literature (see Section 4). The models describe different processes in the cerebrospinal fluid dynamics: the cerebrospinal flow in the ventricles of the brain and the reabsorption of the fluid. In the appendix we show in detail the mathematical analysis of both models and we identify the set of initial conditions for which the solutions of the systems of equations do not exhibit blow up. We investigate step by step the accuracy of these theoretical outcomes with respect to the real cerebrospinal physiology and dynamics.\n\nThe plan of the paper is provided in Section 1.5.

neuroscience↗

bioRxiv2018

Plant behaviour: A mathematical approach for understandingintra-plant communication

Plants are far from being passive organisms being able to exhibit complex behaviours in response to environmental stimuli. How these stimuli are combined, triggered and managed is still an open and complex issue in biology. Mathematical models have helped in understanding some of the pieces in the complexity of intra-plant communication, but a larger and brighter view, setting together multiple key processes, is still missing. This paper proposes a fully coupled system of nonlinear, non-autonomous, discontinuous, ordinary differential equations to describe with accuracy the adapting behaviour and growth of a single plant, by deeply analysing the main stimuli affecting plant behaviour. The proposed model was developed, and here sustained, with the knowledge at the state of the art; and validated with a comparison among numerical results and a wide number of biological data collected from the literature, demonstrating its robustness and reliability. From the proposed analysis it is also shown an emerging self-optimisation of internal resources and feedback stimuli, without the need for defining an optimisation function for the wellness of the plant. The model is ultimately able to highlight the stimulus-signal of the intra-communication in plant, and it can be expanded and adopted as useful tool at the crossroads of disciplines as mathematics, robotics, biology, for instance for validation of biological hypothesis, translation of biological principles into control strategies or resolution of combinatorial problems.\n\nAuthor summaryPlants are able to adapt themselves to a wide range of conditions. The complexity and efficiency of this behaviour suggest a richness of signals exchanged that allowed scientists to talk about communication. Understanding this network of stimuli is an important challenge to increase biological knowledge as well as to adapt plant mechanisms to different research fields. To address this quest we developed a mathematical model able to describe what cues are fundamental in plant communication and how they interact each other.

plant biology↗