Electrical and microfluidic technologies for organs-on-chips:Mimicking blood-brain barrier and gut tissues

The goal of the research presented in this thesis is to develop new technologies for organs-on-chips to enable direct measurements of cell layer functions and to move towards high-throughput. In this introduction, a brief description is included of the tissues that were mimicked in the organs-on-chips described in this thesis. Next, conventional in vitro setups for mimicking these tissues are discussed as well as the advantages of organs-on-chips over these conventional in vitro models. Then, the most important tests of tissue function are described. Subsequently, the larger framework for the research described in this thesis is sketched and lastly an outline of the thesis is given

A novel multi-frequency trans-endothelial electrical resistance (MTEER) sensor array to monitor blood-brain barrier integrity

© 2021 Elsevier B.V. The blood-brain barrier (BBB) is a dynamic cellular barrier that regulates brain nutrient supply, waste efflux, and paracellular diffusion through specialized junctional complexes. Finding a system to mimic and monitor BBB integrity (i.e., to be able to assess the effect of certain compounds on opening or closing the barrier) is of vital importance in several pathologies. This work aims to overcome some limitations of current barrier integrity measuring techniques thanks to a multi-layer microfluidic platform with integrated electrodes and Multi-frequency Trans-Endothelial Electrical Resistance (MTEER) in synergy with machine learning algorithms. MTEER measurements are performed across the barrier in a range of frequencies up to 10 MHz highlighting the presence of information on different frequency ranges. Results show that the proposed platform can detect barrier formation, opening, and regeneration afterwards, correlating with the results obtained from immunostaining of junctional complexes. This model presents novel techniques for a future biological barrier in-vitro studies that could potentially help on elucidating barrier opening or sealing on treatments with different drugs

Microfluidic platform for multiple parameters readouts in a point-of-care

The research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired risk acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory

Microfluidic platform for multiple parameters readouts in a point-of-care

The research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired risk acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory

Microfluidic platform for multiple parameters readouts in a point-of-care

Tesi amb una secció retallada per drets de l'editorThe research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired risk acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory.Postprint (published version

Photonic microfluidic technologies for phytoplankton research

Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world’s vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed.This work was supported by Ministerio de Ciencia e Innovación and Agencia Estatal de Investigación (PID2019-107270RB-C21/AIE/10.13039/501100011033. J.F.A. received funding from Ministerio de Ciencia, Innovación y Universidades of Spain under Juan de la Cierva Incorporación grant

A simulation study of single cell inside an integrated dual nanoneedle-microfludic system

Electrical properties of living cells have been proven to play significant roles in understanding of various biological activities including disease progression both at the cellular and molecular levels. Analyzing the cell’s electrical states especially in single cell analysis (SCA) lead to differentiate between normal cell and cancer cell. This paper presents a simulation study of micro-channel and nanoneedle structure, fluid manipulation and current flow through HeLa cell inside a microfluidic channel. To perform electrical measurement, gold dual nanoneedle has been utilized. The simulation result revealed, the cell penetration occurs at microchannel dimension and solution flow rate is 22 µm x 70 µm x 25 µm (width x length x height) and 0.396 pL/min, respectively. The purposed device has capability to characterize the electrical property of single cells can be used as a novel method for cell viability detection in instantaneous manner

Development of microelectrodes for electrical measurements in a microfluidic system

Transendothelial electrical resistance (TEER) measurements are used to quantitatively monitor cell barrier formation in in vitro models of the blood-brain barrier. TEER measurements in microfluidic in vitro systems are technically problematic and have suffered from poor measurement reproducibility. The aim of this Master’s thesis project was to develop fully integrated electrodes for measuring TEER in a microfluidic blood-brain barrier model. Two patterns of thin film electrodes – one with electrodes placed in the microfluidic channels, and one with electrodes directly above and below the cell culture membrane – were designed, fabricated and embedded in the microfluidic system. Electrodes were fabricated in silver and in platinum, and their reproducibility was evaluated using impedance spectroscopy. Results showed that electrodes fabricated in platinum and placed directly over the membrane could measure impedance with the highest precision. Measurement variation from the electrodes placed in the channels was shown to effectively be reduced by employing a technique of combining six measurements from four electrodes. Based on the reproducibility studies presented in this report, both types of electrodes were believed to have sufficient sensitivity and robustness to be used for TEER measurements. A robust technique to measure TEER enables real-time monitoring of cells in microfluidic systems, and offers a quantitative validation parameter for easy comparison and benchmarking of different system.Sensorer för elektriska mätningar i mikrofluida system Behandling av neurodegenerativa sjukdomar, så som Alzheimers och Parkinsons, är en av vår tids största utmaningar. Med en växande åldrade befolkning förväntas antalet patienter öka, och att hitta effektiva behandlingsmetoder blir alltmer brådskande. Den stora utmaningen ligger i att få läkemedel att nå centrala nervsystemet. På grund av blod-hjärnbarriärer har hjärnan en effektivt skyddande barriär som hindrar substanser från att ta sig in i hjärnan. Inom läkemedelsindustrin läggs enorma resurser på forskning kring hur läkemedel på ett säkert och effektiv sätt ska kunna passera blod-hjärnbarriären. Mycket av denna forskning bedrivs med djurmodeller. Förutom att djurmodeller är etiskt omtvistade, är de kostsamma, arbetsintensiva och på många sätt olika från människokroppen. För att minska användningen av djurmodeller behövs alternativa modeller, där blod-hjärnbarriären kan studeras in vitro. Det senaste årtiondet har en ny klass av in vitro-modeller framträtt, organs-on-chips. Organs-on-chips är mikrofluida system där levande celler kan odlas på ett chip. Dessa modeller har påvisat flera fördelar jämfört med tidigare in vitro-modeller. Genom att utsätta cellkulturen för fluidflöde, kan de bättre efterlikna miljön av blodflöde. I dessa system kan även elektriska sensorer integreras för att studera cellkulturen i realtid. Sensorer kan integreras i en modell av blod-hjärnbarriärer för att mäta den elektriska resistansen över cellbarriären. Dessa mätningar utgör en kvantitativ parameter för hur effektiv barriär cellerna utgör. Mätningarna är dock tekniskt utmanande. På grund av mikrosystemens små dimensioner har de en hög inre resistans som kan vara flera gånger större än resistansen över cellbarriären. Små variationer och mätfel kan därför skapa relativt stor osäkerhet kring resistansen som utgörs av cellbarriären. I detta projekt utvecklades mikrosensorer för resistansmätningar i en modell av blod-hjärnbarriären. Elektrodernas geometri, placering, och material utvärderades med impedans-mätningar för att minimera mätvariation och skapa ett stabilt system. Med de sensorer som presenteras här, kan resistans mätas med god precision. Resistansmätningar av hög kvalitet kan utgöra en parameter för validering, vilket potentiellt kan accelerera utvecklingen av organs-on-chips