Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for intensive care unit patients. I. ICP-model Designed for Medical Education We developed a comprehensive cerebral blood flow and intracranial pressure model to simulate and study the complex interactions in cerebrovascular dynamics caused by multiple simultaneous alterations, including normal and abnormal functional states of auto-regulation of the brain. Individual published equations (derived from prior animal and human studies) were implemented into a comprehensive simulation program. Included in the normal physiological modelling was: intracranial pressure, cerebral blood flow, blood pressure, and carbon dioxide (CO2) partial pressure. We also added external and pathological perturbations, such as head up position and intracranial haemorrhage. The model performed clinically realistically given inputs of published traumatized patients, and cases encountered by clinicians. The pulsatile nature of the output graphics was easy for clinicians to interpret. The manoeuvres simulated include changes of basic physiological inputs (e.g. blood pressure, central venous pressure, CO2 tension, head up position, and respiratory effects on vascular pressures) as well as pathological inputs (e.g. acute intracranial bleeding, and obstruction of cerebrospinal outflow). Based on the results, we believe the model would be useful to teach complex relationships of brain haemodynamics and study clinical research questions such as the optimal head-up position, the effects of intracranial haemorrhage on cerebral haemodynamics, as well as the best CO2 concentration to reach the optimal compromise between intracranial pressure and perfusion. We believe this model would be useful for both beginners and advanced learners. It could be used by practicing clinicians to model individual patients (entering the effects of needed clinical manipulations, and then running the model to test for optimal combinations of therapeutic manoeuvres). II. A Heterogeneous Cerebrovascular Mathematical Model Cerebrovascular pathologies are extremely complex, due to the multitude of factors acting simultaneously on cerebral haemodynamics. In this work, the mathematical model of cerebral haemodynamics and intracranial pressure dynamics, described in the point I, is extended to account for heterogeneity in cerebral blood flow. The model includes the Circle of Willis, six regional districts independently regulated by autoregulation and CO2 reactivity, distal cortical anastomoses, venous circulation, the cerebrospinal fluid circulation, and the intracranial pressure-volume relationship. Results agree with data in the literature and highlight the existence of a monotonic relationship between transient hyperemic response and the autoregulation gain. During unilateral internal carotid artery stenosis, local blood flow regulation is progressively lost in the ipsilateral territory with the presence of a steal phenomenon, while the anterior communicating artery plays the major role to redistribute the available blood flow. Conversely, distal collateral circulation plays a major role during unilateral occlusion of the middle cerebral artery. In conclusion, the model is able to reproduce several different pathological conditions characterized by heterogeneity in cerebrovascular haemodynamics and can not only explain generalized results in terms of physiological mechanisms involved, but also, by individualizing parameters, may represent a valuable tool to help with difficult clinical decisions. III. Effect of Cushing Response on Systemic Arterial Pressure. During cerebral hypoxic conditions, the sympathetic system causes an increase in arterial pressure (Cushing response), creating a link between the cerebral and the systemic circulation. This work investigates the complex relationships among cerebrovascular dynamics, intracranial pressure, Cushing response, and short-term systemic regulation, during plateau waves, by means of an original mathematical model. The model incorporates the pulsating heart, the pulmonary circulation and the systemic circulation, with an accurate description of the cerebral circulation and the intracranial pressure dynamics (same model as in the first paragraph). Various regulatory mechanisms are included: cerebral autoregulation, local blood flow control by oxygen (O2) and/or CO2 changes, sympathetic and vagal regulation of cardiovascular parameters by several reflex mechanisms (chemoreceptors, lung-stretch receptors, baroreceptors). The Cushing response has been described assuming a dramatic increase in sympathetic activity to vessels during a fall in brain O2 delivery. With this assumption, the model is able to simulate the cardiovascular effects experimentally observed when intracranial pressure is artificially elevated and maintained at constant level (arterial pressure increase and bradicardia). According to the model, these effects arise from the interaction between the Cushing response and the baroreflex response (secondary to arterial pressure increase). Then, patients with severe head injury have been simulated by reducing intracranial compliance and cerebrospinal fluid reabsorption. With these changes, oscillations with plateau waves developed. In these conditions, model results indicate that the Cushing response may have both positive effects, reducing the duration of the plateau phase via an increase in cerebral perfusion pressure, and negative effects, increasing the intracranial pressure plateau level, with a risk of greater compression of the cerebral vessels. This model may be of value to assist clinicians in finding the balance between clinical benefits of the Cushing response and its shortcomings. IV. Comprehensive Cardiopulmonary Simulation Model for the Analysis of Hypercapnic Respiratory Failure We developed a new comprehensive cardiopulmonary model that takes into account the mutual interactions between the cardiovascular and the respiratory systems along with their short-term regulatory mechanisms. The model includes the heart, systemic and pulmonary circulations, lung mechanics, gas exchange and transport equations, and cardio-ventilatory control. Results show good agreement with published patient data in case of normoxic and hyperoxic hypercapnia simulations. In particular, simulations predict a moderate increase in mean systemic arterial pressure and heart rate, with almost no change in cardiac output, paralleled by a relevant increase in minute ventilation, tidal volume and respiratory rate. The model can represent a valid tool for clinical practice and medical research, providing an alternative way to experience-based clinical decisions. In conclusion, models are not only capable of summarizing current knowledge, but also identifying missing knowledge. In the former case they can serve as training aids for teaching the operation of complex systems, especially if the model can be used to demonstrate the outcome of experiments. In the latter case they generate experiments to be performed to gather the missing data.

Modelling the effects of nitrogen deposition and carbon dioxide enrichment on forest carbon balance

Atmospheric CO2 concentration ([CO2]) has increased over the last 250 years, mainly due to human activities. Of total anthropogenic emissions, almost 31% has been sequestered by the terrestrial biosphere. A considerable contribution to this sink comes from temperate and boreal forest ecosystems of the northern hemisphere, which contain a large amount of carbon (C) stored as biomass and soil organic matter. Several potential drivers for this forest C sequestration have been proposed, including increasing atmospheric [CO2], temperature, nitrogen (N) deposition and changes in management practices. However, it is not known which of these drivers are most important. The overall aim of this thesis project was to develop a simple ecosystem model which explicitly incorporates our best understanding of the mechanisms by which these drivers affect forest C storage, and to use this model to investigate the sensitivity of the forest ecosystem to these drivers. I firstly developed a version of the Generic Decomposition and Yield (G’DAY) model to explicitly investigate the mechanisms leading to forest C sequestration following N deposition. Specifically, I modified the G’DAY model to include advances in understanding of C allocation, canopy N uptake, and leaf trait relationships. I also incorporated a simple forest management practice subroutine. Secondly, I investigated the effect of CO2 fertilization on forest productivity with relation to the soil N availability feedback. I modified the model to allow it to simulate short-term responses of deciduous forests to environmental drivers, and applied it to data from a large-scale forest Free-Air CO2 Enrichment (FACE) experiment. Finally, I used the model to investigate the combined effects of recent observed changes in atmospheric [CO2], N deposition, and climate on a European forest stand. The model developed in my thesis project was an effective tool for analysis of effects of environmental drivers on forest ecosystem C storage. Key results from model simulations include: (i) N availability has a major role in forest ecosystem C sequestration; (ii) atmospheric N deposition is an important driver of N availability on short and long time-scales; (iii) rising temperature increases C storage by enhancing soil N availability and (iv) increasing [CO2] significantly affects forest growth and C storage only when N availability is not limiting.

Influence of nitrogen and soil physical characteristics on belowground carbon flux dynamics of woody plants

At ecosystem level soil respiration (Rs) represents the largest carbon (C) flux after gross primary productivity, being mainly generated by root respiration (autotrophic respiration, Ra) and soil microbial respiration (heterotrophic respiration, Rh). In the case of terrestrial ecosystems, soils contain the largest C-pool, storing twice the amount of C contained in plant biomass. Soil organic matter (SOM), representing the main C storage in soil, is decomposed by soil microbial community. This process produces CO2 which is mainly released as Rh. It is thus relevant to understand how microbial activity is influenced by environmental factors like soil temperature, soil moisture and nutrient availability, since part of the CO2 produced by Rh, directly increases atmospheric CO2 concentration and therefore affects the phenomenon of climate change. Among terrestrial ecosystems, agricultural fields have traditionally been considered as sources of atmospheric CO2. In agricultural ecosystems, in particular apple orchards, I identified the role of root density, soil temperature, soil moisture and nitrogen (N) availability on Rs and on its two components, Ra and Rh. To do so I applied different techniques to separate Rs in its two components, the ”regression technique” and the “trenching technique”. I also studied the response of Ra to different levels of N availability, distributed either in a uniform or localized way, in the case of Populus tremuloides trees. The results showed that Rs is mainly driven by soil temperature, to which it is positively correlated, that high levels of soil moisture have inhibiting effects, and that N has a negligible influence on total Rs, as well as on Ra. Further I found a negative response of Rh to high N availability, suggesting that microbial decomposition processes in the soil are inhibited by the presence of N. The contribution of Ra to Rs was of 37% on average.

Studio del metodo dell'assorbimento diretto della CO2 per l'analisi del radiocarbonio

L’attuale rilevanza rappresentata dalla stretta relazione tra cambiamenti climatici e influenza antropogenica ha da tempo posto l’attenzione sull’effetto serra e sul surriscaldamento planetario così come sull’aumento delle concentrazioni atmosferiche dei gas climaticamente attivi, in primo luogo la CO2. Il radiocarbonio è attualmente il tracciante ambientale per eccellenza in grado di fornire mediante un approccio “top-down” un valido strumento di controllo per discriminare e quantificare il diossido di carbonio presente in atmosfera di provenienza fossile o biogenica. Ecco allora che ai settori applicativi tradizionali del 14C, quali le datazioni archeometriche, si affiancano nuovi ambiti legati da un lato al settore energetico per quanto riguarda le problematiche associate alle emissioni di impianti, ai combustibili, allo stoccaggio geologico della CO2, dall’altro al mercato in forte crescita dei cosiddetti prodotti biobased costituiti da materie prime rinnovabili. Nell’ambito del presente lavoro di tesi è stato quindi esplorato il mondo del radiocarbonio sia dal punto di vista strettamente tecnico e metodologico che dal punto di vista applicativo relativamente ai molteplici e diversificati campi d’indagine. E’ stato realizzato e validato un impianto di analisi basato sul metodo radiometrico mediante assorbimento diretto della CO2 ed analisi in scintillazione liquida apportando miglioramenti tecnologici ed accorgimenti procedurali volti a migliorare le performance del metodo in termini di semplicità, sensibilità e riproducibilità. Il metodo, pur rappresentando generalmente un buon compromesso rispetto alle metodologie tradizionalmente usate per l’analisi del 14C, risulta allo stato attuale ancora inadeguato a quei settori applicativi laddove è richiesta una precisione molto puntuale, ma competitivo per l’analisi di campioni moderni ad elevata concentrazione di 14C. La sperimentazione condotta su alcuni liquidi ionici, seppur preliminare e non conclusiva, apre infine nuove linee di ricerca sulla possibilità di utilizzare questa nuova classe di composti come mezzi per la cattura della CO2 e l’analisi del 14C in LSC.

Polymeric membranes for CO2 separation: effect of aging, humidity and facilitated transport

Polymeric membranes represent a promising technology for gas separation processes, thanks to low costs, reduced energy consumption and limited waste production. The present thesis aims at studying the transport properties of two membrane materials, suitable for CO2 purification applications. In the first part, a polyimide, Matrimid 5218, has been throughout investigated, with particular reference to the effect of thermal treatment, aging and the presence of water vapor in the gas transport process. Permeability measurements showed that thermal history affects relevantly the diffusion of gas molecules across the membrane, influencing also the stability of the separation performances. Subsequently, the effect of water on Matrimid transport properties has been characterized for a wide set of incondensable penetrants. A monotonous reduction of permeability took place at increasing the water concentration within the polymer matrix, affecting the investigated gaseous species to the same extent, despite the different thermodynamic and kinetic features. In this view, a novel empirical model, based on the Free Volume Theory, has been proposed to qualitatively describe the phenomenon. Moreover, according to the accurate representation of the experimental data, the suggested approach has been combined with a more rigorous thermodynamic tool (NELF Model), allowing an exhaustive description of water influence on the single parameters contributing to the gas permeation across the membrane. In the second part, the study has focused on the synthesis and characterization of facilitated transport membranes, able to achieving outstanding separation performances thanks to the chemical enhancement of CO2 permeability. In particular, the transport properties have been investigated for high pressure CO2 separation applications and specific solutions have been proposed to solve stability issues, frequently arising under such severe conditions. Finally, the effect of different process parameters have been investigated, aiming at the identification of the optimal conditions capable to maximize the separation performance.