Modelling of neuronal circuits by using block-oriented programming techniques

This project consists in the implementation of a complete reflex arc model based in biological neurons and in the subsequent study of its dynamic behavior. The basic circuit of the reflex arc is composed by a receptor and its afferent fibers, one or several interneurons located in the spinal cord, a motoneuron and an effector connected to its muscle. The attributes of a reflex arc depend on the features of the sensory receptor that initiates the reflex and also on the physical nature of the medullar circuits and the motoneurons involved in it. The implementation of the neural circuit has been done using causal modeling techniques, which reflect rather the dynamics equations than the very structure of the system. The Simulink environment has been used for this purpose since it is based in a hierarchically block diagramming tool, which makes very efficient the implementation of compartmental models. The model of the neural circuit has been built following a mathematical approach based in membrane and action potentials. It includes the four major components that embody a neuron: cell body, dendrite, axon and presynaptic terminals, as well as the muscle spindle and the motor junction, which behave as transductors. The mathematical equations that model the system are calculated from the circuit analogy that recreates the ion traffic across cellular membranes. Once the model is completely built, the excitation and conduction mechanisms, as well as the stimulus transmission, are studied. The system is analyzed under physiological and pathological conditions, studying the effects that some drugs produce in the model and using a qualitative analysis methodology to evaluate the obtained results.El presente trabajo consiste en la implementación de un modelo del circuito completo del arco reflejo basado en la neurona biológica y en el estudio de su comportamiento dinámico. El circuito reflejo modular básico está compuesto por un receptor y su fibra aferente, una o más neuronas medulares intercalares, una motoneurona y un efector y su músculo. Las propiedades de cualquier reflejo son una función de las características de los receptores que inician el estímulo y de la naturaleza de los circuitos medulares y de las motoneuronas implicados. Para la implementación del circuito neuronal se ha optado por técnicas de modelado causal, en las que tienen más importancia las ecuaciones dinámicas que la estructura física del sistema. Para ello se ha utilizado la herramienta Simulink, que permite implementar la configuración utilizada basada en modelos compartimentales mediante la utilización de una estructura jerarquizada de diagramas de bloques. El modelado del circuito neuronal se realiza siguiendo un modelo matemático en términos de potenciales de membrana y potenciales de acción, implementando los cuatro elementos principales que componen una neurona: cuerpo celular o soma, dendritas, axón y terminales presinápticos, además del huso muscular y la placa motora, que actúan como transductores. Las ecuaciones matemáticas que definen el sistema se obtienen a partir de la analogía circuital que reproduce el tránsito de iones a través de la membrana. Construido el modelo se estudian los mecanismos de excitación, conducción y transmisión de estímulos en las distintas etapas que lo componen, el comportamiento en condiciones fisiológicas y patológicas, y los efectos que se producen tras la aplicación de tratamientos farmacológicos siguiendo una metodología de análisis cualitativa

Towards Vascularized Tissue Blocks Using a Suspension Bioprinted Blood Vessel

In order for engineered tissue grafts and eventually organs to successfully integrate in a clinical setting, a functional vascular network is imperative. Without vasculature, the tissue constructs cannot receive nutrients essential for their survival, but also lack the stimuli that determine the tissue’s biophysical properties i.e. cell fate determination, cell to cell junctions, and cell orientation. In order for the vascular network to functionally connect to the patient, a hierarchical organization, resembling the vascular tree, is important. From previous studies it is known that fluid flow is a crucial component in controlling the formation of the vascular tree, and that the organization of the vascular network can be further controlled using gradients of angiogenic growth factors such as VEGF. By utilizing spheroid bioprinting within a microgel suspension, an artificial vessel structure was assembled. The deposited spheroids maintained viability and fused over time into perfusable vessels.The subsequent formation of small-diameter vascular structures and capillaries was regulated by an on-demand flow through the bioprinted vessel, resulting in controllable fluid flow shear stresses. Furthermore, VEGF was spatially patterned in the tissue block by locally doping the suspension with growth factor releasing microparticles. By varying both these stimuli, the location of vascular sprout formation and subsequent growth of the new vascular structures could be influenced. This spheroid 3D bioprinting platform offers a dynamic, customizable and accurate method to trigger and control the process of angiogenesis in vitro. By stimulating an artificial blood vessel with controlled fluid flow and growth factor gradients, a vascular complex vascular network can be produced and modulated. The combination of this approach with a gradual replacement of the microgel suspension with cells, can pave the way for the production of vascularized tissue blocks