Contributions to modelling and control for improved hypoglycaemia and variability mitigation by dual-hormone artificial pancreas systems

[ES] Las personas con diabetes tipo 1 carecen de la capacidad de secretar insulina y, por lo tanto, necesitan regular su glucosa en sangre con la administración de insulina exógena. El páncreas artificial se presenta como la solución tecnológica ideal para alcanzar los objetivos terapéuticos de la normoglucemia, liberando al paciente de la carga actual de autocontrol y manejo. Sin embargo, el riesgo de hipoglucemia y la variabilidad glucémica siguen siendo factores limitantes en los algoritmos de control actuales integrados en el páncreas artificial. El propósito de la presente tesis es profundizar en el conocimiento de la hipoglucemia y avanzar los algoritmos de control del páncreas artificial para minimizar la incidencia de hipoglucemia y reducir la variabilidad glucémica. Después de proporcionar una visión general del estado del arte del control de la glucosa y el páncreas artificial, esta tesis aborda temas relacionados con el modelado y el control, con las siguientes contribuciones: Se presenta una extensión del modelo de Bergman Minimal que tiene en cuenta la respuesta contrarreguladora a la hipoglucemia. Este modelo explica la relación entre los diversos cambios fisiológicos producidos durante la hipoglucemia, con la adrenalina y los ácidos grasos libres como actores principales. Como resultado, se obtiene una mejor comprensión de la hipoglucemia, lo que permite explicar una auto-potenciación paradójica de la hipoglucemia como se modela a través de enfoques funcionales en el ampliamente utilizado simulador de diabetes tipo 1 UVA-Padova, que se utilizará en esta tesis para la validación in silico de los controladores desarrollados. Se realiza una evaluación de las métricas de variabilidad de la glucosa y los índices de calidad de control. La evaluación de la variabilidad glucémica en el desempeño de los controladores es necesaria; pero todavía no hay un conjunto de métricas de variabilidad glucémica que sea considerado como el "gold estándar". Por tanto, se lleva a cabo un análisis de las métricas de variabilidad disponibles en la literatura para definir un conjunto de indicadores recomendables. Debido a las limitaciones de los sistemas de páncreas artificiales unihormonales para mitigar la hipoglucemia en escenarios difíciles como el ejercicio, esta tesis se centra en el desarrollo de nuevos algoritmos de control bihormonales, con infusión simultanea de insulina y glucagón. Se propone un controlador coordinado bihormonal con estructuras de control paralelas como un algoritmo de control factible para la mitigación de la hipoglucemia y la reducción de la variabilidad glucémica, demostrando un rendimiento superior al de las estructuras de control utilizadas actualmente con lazos de control independientes de insulina y glucagón. Los controladores están diseñados y evaluados in silico en escenarios desafiantes y su rendimiento se evalúa principalmente con el conjunto de métricas definidas previamente como las recomendables.[CA] Les persones amb diabetis tipus 1 no tenen la capacitat de secretar insulina secreta i per tant, necessiten regular la seva glucosa en sang amb l'administració d'insulina exògena. El Pàncrees Artificial es presenta com la solució tecnològica ideal per assolir els objectius terapèutics de la normoglucèmia, alliberant al pacient de la càrrega actual d'autocontrol. No obstant, el risc d'hipoglucèmia i l'alta variabilitat glucèmica continuen sent un factor limitant en els algoritmes de control actuals integrats en el Pàncrees Artificials. El propòsit de la present tesi és aprofundir en el coneixement de la hipoglucèmia i millorar els algoritmes de control per corregir amb antelació la dosi excessiva d'insulina, minimitzant la incidència d'hipoglucèmia i reduint la variabilitat glucèmica. Després de donar una visió general de l'estat de l'art del control de la glucosa i el pàncrees artificial, aquesta tesi aborda aspectes de modelització i control, amb les següents contribucions: Es presenta una extensió del model Minimal de Bergman amb la contrarregulació. Aquest model explica la relació entre els diversos canvis siològics produïts durant la hipoglucèmia. Així, permet comprendre millor la hipoglucèmia i comparar els resultats amb els proporcionats per l'enfocament funcional del simulador de diabetis tipus 1 més utilitzat a la comunitat científica. Es realitza una avaluació de les mètriques de variabilitat glucèmica i dels índexs de qualitat de control. Es necessària l'avaluació de la variabilitat glucèmica en el rendiment dels controladors; però encara no hi ha un conjunt de mètriques considerades com les "gold standard". Per tant, es realitza una anàlisi de les mètriques de variabilitat disponibles a la literatura per definir un conjunt d'indicadors recomanables. Es proposa un controlador bi-hormonal coordinat amb estructures de control paral.leles com un algoritme de control viable per a la mitigació d'hipoglucèmia i la reducció de la variabilitat glucèmica. Els controladors estan dissenyats i avaluats in-silico en escenaris desafiadors i el seu rendiment es valora principalment amb el conjunt de mètriques definides prèviament com les mètriques recomanables.[EN] People with Type 1 Diabetes lack the ability to secrete insulin and therefore need to regulate their blood glucose with exogenous insulin delivery. The Artificial Pancreas is presented as the ideal technological solution to reach the therapeutic goals of normoglycaemia, freeing the patient from the current burden of self-control and management. Nevertheless, the risk of hypoglycaemia and the high glycaemic variability are still a limiting factors in the current control algorithms integrated in the Artificial Pancreas. The purpose of the present thesis is to delve into knowledge of hypoglycaemia and to advance in the artificial pancreas control algorithms in order to minimise hypoglycaemia incidence and reduce glycaemic variability. After providing an overview of the state of the art in the eld of glucose control and articial pancreas, this thesis addresses issues on modelling and control, with the following contributions: An extension of the Bergman Minimal model accounting for counterregulatory response to hypoglycaemia is presented. This model explains the relationship between the several physiological changes produced during hypoglycaemia, with adrenaline and free fatty acids as main players. As a result, a better understanding of hypoglycaemia is gained, allowing to explain a paradoxical auto-potentiation of hypoglycaemia as modeled through functional approaches in the widespread used UVA-Padova Type 1 Diabetes simulator, which will be used in this thesis for in silico validation of the developed controllers. An assessment of glucose variability metrics and control quality indices is carried out. The evaluation of the glycaemic variability on the controllers performance is necessary; but there is not a gold standard variability metrics yet. Therefore, an analysis of the variability metrics available in literature is conducted in order to define a recommendable set of indicators. Due to the limitations of single-hormone artificial pancreas systems in mitigating hypoglycaemia in challenging scenarios such as exercise, this thesis focuses on the developement of new dual-hormone control algorithms, with concomitant infusion of insulin and glucagon. A coordinated dual-hormone controller with parallel control structures is proposed as a feasible control algorithm for hypoglycaemia mitigation and glycaemic variability reduction, demonstrating superior performance as currently used control structures with independent insulin and glucagon control loops. The controllers are designed and evaluated in-silico under challenging scenarios and their performance are assessed mainly with the set of metrics defined previously as the recommendable ones.Moscardó García, V. (2019). Contributions to modelling and control for improved hypoglycaemia and variability mitigation by dual-hormone artificial pancreas systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/120456TESI

ArcUHI: A GIS add-in for automated modelling of the Urban Heat Island effect through machine learning

Increased urbanisation is boosting the intensity and frequency of the Urban Heat Island (UHI) effect in highly developed cities. The advances in satellite measurement are facilitating the analysis of this phenomenon using Land Surface Temperature (LST) as an indicator of the Surface UHI (SUHI). Due to the spatial implications of using remote sensing data, this research developed ArcUHI, a Geographic Information System (GIS) add-in for modelling SUHI. The tool was designed in ArcGIS, which was bound with R to run machine learning algorithms in the background. ArcUHI was tested using the metropolitan area of Madrid (Spain) in 2006, 2012 and 2018 as a case study. The add-in was found to predict observed LST with high accuracy, especially when using Random Forest Regression (RFR). Building height and albedo were identified as the main drivers of SUHI, whose magnitude and extension increased with time. In view of these results, strategic roof and wall greening was suggested as a measure to mitigate the street canyon effect entailed by buildings and offset the heat retention capacity of built-up surfaces.This research was funded by the Spanish Ministry of Science, Innovation, and Universities with funds from the State General Budget (PGE) and the European Regional Development Fund (ERDF), grant number RTI2018-094217-B-C32 (MCIU/AEI/FEDER, UE). Alejandro Roldán-Valcarce thanks the Spanish Ministry of Science, Innovation and Universities for funding his investigations at the University of Cantabria through a Researcher Formation Fellowship, grant number PRE2019-089450

Effect of 2% Chlorhexidine Following Acid Etching on Microtensile Bond Strength of Resin Restorations: A Meta-Analysis

Background and Objectives: The aim of this systematic review was to examine the effect of 2% chlorhexidine following acid etching on the microtensile bond strength of resin restorations for different follow-up times. Materials and Methods: A thorough search of PubMed, Scopus, and Embase databases were conducted. In vitro experimental studies or in vivo studies published up to December 2018 with an experimental group treated with a 2% chlorhexidine solution following acid etching and a control group were included, wherein the final restoration used a resin composite in both the groups. Results: Twenty-one articles were identified for qualitative analysis and 18 for meta-analysis. The difference in the means of microtensile bond strength between the two groups was calculated for the different follow-up times. The differences were significant for 6 months (4.30 MPa; 95% CI 2.72–5.89), 12 months (8.41 MPa; 95% CI 4.93–11.88), and 2–5 years including aged and thermocycling samples (9.08 MPa; 95% CI 5.36–12.81). There were no significant differences for the type of adhesive used. A meta-regression model showed a significant effect of time on the microtensile bond strength. Conclusions: The application of a 2% chlorhexidine solution after acid etching increased the microtensile bond strength significantly for follow-up times of 6 months or more. The adhesive type had no influence