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Staff member

Maria José López Martínez

Staff member publications

Pereira, I, Lopez-Martinez, MJ, Samitier, J, (2023). Advances in current in vitro models on neurodegenerative diseases Frontiers In Bioengineering And Biotechnology 11, 1260397

Many neurodegenerative diseases are identified but their causes and cure are far from being well-known. The problem resides in the complexity of the neural tissue and its location which hinders its easy evaluation. Although necessary in the drug discovery process, in vivo animal models need to be reduced and show relevant differences with the human tissues that guide scientists to inquire about other possible options which lead to in vitro models being explored. From organoids to organ-on-a-chips, 3D models are considered the cutting-edge technology in cell culture. Cell choice is a big parameter to take into consideration when planning an in vitro model and cells capable of mimicking both healthy and diseased tissue, such as induced pluripotent stem cells (iPSC), are recognized as good candidates. Hence, we present a critical review of the latest models used to study neurodegenerative disease, how these models have evolved introducing microfluidics platforms, 3D cell cultures, and the use of induced pluripotent cells to better mimic the neural tissue environment in pathological conditions.

JTD Keywords: 3d in vitro models, bioprinting, ipsc cell culture, microfluidic device, 3d in vitro models, Bioprinting, Blood-brain-barrier, Cerebral organoids, Culture model, Endothelial-cells, Expression profile, Extracellular-matrix, Ipsc cell culture, Microfluidic device, Neurodegenerative diseases, On-a-chip, Pluripotent stem-cells, Shear-stress, Substrate stiffness


Pereira, I, Lopez-Martinez, MJ, Villasante, A, Introna, C, Tornero, D, Canals, JM, Samitier, J, (2023). Hyaluronic acid-based bioink improves the differentiation and network formation of neural progenitor cells Frontiers In Bioengineering And Biotechnology 11, 1110547

Introduction: Three-dimensional (3D) bioprinting is a promising technique for the development of neuronal in vitro models because it controls the deposition of materials and cells. Finding a biomaterial that supports neural differentiation in vitro while ensuring compatibility with the technique of 3D bioprinting of a self-standing construct is a challenge.Methods: In this study, gelatin methacryloyl (GelMA), methacrylated alginate (AlgMA), and hyaluronic acid (HA) were examined by exploiting their biocompatibility and tunable mechanical properties to resemble the extracellular matrix (ECM) and to create a suitable material for printing neural progenitor cells (NPCs), supporting their long-term differentiation. NPCs were printed and differentiated for up to 15 days, and cell viability and neuronal differentiation markers were assessed throughout the culture.Results and Discussion: This composite biomaterial presented the desired physical properties to mimic the ECM of the brain with high water intake, low stiffness, and slow degradation while allowing the printing of defined structures. The viability rates were maintained at approximately 80% at all time points. However, the levels of beta-III tubulin marker increased over time, demonstrating the compatibility of this biomaterial with neuronal cell culture and differentiation. Furthermore, these cells showed increased maturation with corresponding functional properties, which was also demonstrated by the formation of a neuronal network that was observed by recording spontaneous activity via Ca2+ imaging.

JTD Keywords: biomaterials, bioprinting, differentiation, in vitro models, neural progenitor cells, 2d, Biomaterials, Bioprinting, C17.2, Differentiation, Extracellular-matrix, Hydrogels, In vitro models, In-vitro, Neural progenitor cells, Neuronal models, Proliferation, Scaffolds, Stem-cells, Substrate stiffness


Mencattini, A, Rizzuto, V, Antonelli, G, Di Giuseppe, D, D'Orazio, M, Filippi, J, Comes, MC, Casti, P, Corrons, JLV, Garcia-Bravo, M, Segovia, JC, Manu-Pereira, MD, Lopez-Martinez, MJ, Samitier, J, Martinelli, E, (2023). Machine learning microfluidic based platform: Integration of Lab-on-Chip devices and data analysis algorithms for red blood cell plasticity evaluation in Pyruvate Kinase Disease monitoring Sensors And Actuators A-Physical 351, 114187

Microfluidics represents a very promising technological solution for conducting massive biological experiments. However, the difficulty of managing the amount of information available often precludes the wide potential offered. Using machine learning, we aim to accelerate microfluidics uptake and lead to quantitative and reliable findings. In this work, we propose complementing microfluidics with machine learning (MLM) approaches to enhance the diagnostic capability of lab-on-chip devices. The introduction of data analysis methodologies within the deep learning framework corroborates the possibility of encoding cell morphology beyond the standard cell appearance. The proposed MLM platform is used in a diagnostic test for blood diseases in murine RBC samples in a dedicated microfluidics device in flow. The lack of plasticity of RBCs in Pyruvate Kinase Disease (PKD) is measured massively by recognizing the shape deformation in RBCs walking in a forest of pillars within the chip. Very high accuracy results, far over 85 %, in recognizing PKD from control RBCs either in simulated and in real experiments demonstrate the effectiveness of the platform.

JTD Keywords: Blood disease, Deep transfer learning, Deficiency, Deformability, Machine learning microfluidics, Video analysis


Mir, M, Palma-Florez, S, Lagunas, A, Lopez-Martinez, MJ, Samitier, J, (2022). Biosensors Integration in Blood-Brain Barrier-on-a-Chip: Emerging Platform for Monitoring Neurodegenerative Diseases Acs Sensors 7, 1237-1247

Over the most recent decades, the development of new biological platforms to study disease progression and drug efficacy has been of great interest due to the high increase in the rate of neurodegenerative diseases (NDDs). Therefore, blood-brain barrier (BBB) as an organ-on-a-chip (OoC) platform to mimic brain-barrier performance could offer a deeper understanding of NDDs as well as a very valuable tool for drug permeability testing for new treatments. A very attractive improvement of BBB-oC technology is the integration of detection systems to provide continuous monitoring of biomarkers in real time and a fully automated analysis of drug permeably, rendering more efficient platforms for commercialization. In this Perspective, an overview of the main BBB-oC configurations is introduced and a critical vision of the BBB-oC platforms integrating electronic read out systems is detailed, indicating the strengths and weaknesses of current devices, proposing the great potential for biosensors integration in BBB-oC. In this direction, we name potential biomarkers to monitor the evolution of NDDs related to the BBB and/or drug cytotoxicity using biosensor technology in BBB-oC.

JTD Keywords: biosensors, blood−brain barrier (bbb), neurodegenerative diseases (ndds), organ-on-a-chip (ooc), Bbb, Biosensors, Blood-brain barrier (bbb), Electrical-resistance, Electrochemical biosensors, Endothelial-cells, In-vitro model, Matrix metalloproteinases, Mechanisms, Neurodegenerative diseases (ndds), Organ-on-a-chip (ooc), Permeability, Stress, Transendothelial electrical resistance (teer), Transepithelial, Transepithelial/transendothelial electrical resistance (teer), Transport


Blanco-Cabra, N, López-Martínez, MJ, Arévalo-Jaimes, BV, Martin-Gómez, MT, Samitier, J, Torrents, E, (2021). A new BiofilmChip device for testing biofilm formation and antibiotic susceptibility Npj Biofilms And Microbiomes 7, 62

Currently, three major circumstances threaten the management of bacterial infections: increasing antimicrobial resistance, expansion of chronic biofilm-associated infections, and lack of an appropriate approach to treat them. To date, the development of accelerated drug susceptibility testing of biofilms and of new antibiofouling systems has not been achieved despite the availability of different methodologies. There is a need for easy-to-use methods of testing the antibiotic susceptibility of bacteria that form biofilms and for screening new possible antibiofilm strategies. Herein, we present a microfluidic platform with an integrated interdigitated sensor (BiofilmChip). This new device allows an irreversible and homogeneous attachment of bacterial cells of clinical origin, even directly from clinical specimens, and the biofilms grown can be monitored by confocal microscopy or electrical impedance spectroscopy. The device proved to be suitable to study polymicrobial communities, as well as to measure the effect of antimicrobials on biofilms without introducing disturbances due to manipulation, thus better mimicking real-life clinical situations. Our results demonstrate that BiofilmChip is a straightforward tool for antimicrobial biofilm susceptibility testing that could be easily implemented in routine clinical laboratories.

JTD Keywords: cells, model, resistance, shear, technology, In-vitro


Rizzuto, V, Mencattini, A, Alvarez-González, B, Di Giuseppe, D, Martinelli, E, Beneitez-Pastor, D, Mañú-Pereira, MD, Lopez-Martinez, MJ, Samitier, J, (2021). Combining microfluidics with machine learning algorithms for RBC classification in rare hereditary hemolytic anemia Scientific Reports 11, 13553

Combining microfluidics technology with machine learning represents an innovative approach to conduct massive quantitative cell behavior study and implement smart decision-making systems in support of clinical diagnostics. The spleen plays a key-role in rare hereditary hemolytic anemia (RHHA), being the organ responsible for the premature removal of defective red blood cells (RBCs). The goal is to adapt the physiological spleen filtering strategy for in vitro study and monitoring of blood diseases through RBCs shape analysis. Then, a microfluidic device mimicking the slits of the spleen red pulp area and video data analysis are combined for the characterization of RBCs in RHHA. This microfluidic unit is designed to evaluate RBC deformability by maintaining them fixed in planar orientation, allowing the visual inspection of RBC's capacity to restore their original shape after crossing microconstrictions. Then, two cooperative learning approaches are used for the analysis: the majority voting scheme, in which the most voted label for all the cell images is the class assigned to the entire video; and the maximum sum of scores to decide the maximally scored class to assign. The proposed platform shows the capability to discriminate healthy controls and patients with an average efficiency of 91%, but also to distinguish between RHHA subtypes, with an efficiency of 82%.

JTD Keywords: chip, disease, Red-blood-cell


Badiola-Mateos, M, Di Giuseppe, D, Paoli, R, Lopez-Martinez, MJ, Mencattini, A, Samitier, J, Martinelli, E, (2021). A novel multi-frequency trans-endothelial electrical resistance (MTEER) sensor array to monitor blood-brain barrier integrity Sensors And Actuators B-Chemical 334, 129599

© 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.

JTD Keywords: blood-brain barrier, cellular barrier integrity monitoring, impedance sensors, machine learning, microelectrodes, mteer, rapid prototyping, Blood-brain barrier, Cellular barrier integrity monitoring, Electrical impedance spectroscopy, Impedance sensors, Machine learning, Microelectrodes, Mteer, Rapid prototyping


Paoli, R, Di Giuseppe, D, Badiola-Mateos, M, Martinelli, E, Lopez-Martinez, MJ, Samitier, J, (2021). Rapid manufacturing of multilayered microfluidic devices for organ on a chip applications Sensors 21, 1382

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. Microfabrication and Polydimethylsiloxane (PDMS) soft-lithography techniques became popular for microfluidic prototyping at the lab, but even after protocol optimization, fabrication is yet a long, laborious process and partly user-dependent. Furthermore, the time and money required for the master fabrication process, necessary at any design upgrade, is still elevated. Digital Manufacturing (DM) and Rapid-Prototyping (RP) for microfluidics applications arise as a solution to this and other limitations of photo and soft-lithography fabrication techniques. Particularly for this paper, we will focus on the use of subtractive DM techniques for Organ-on-a-Chip (OoC) applications. Main available thermoplastics for microfluidics are suggested as material choices for device fabrication. The aim of this review is to explore DM and RP technologies for fabrication of an OoC with an embedded membrane after the evaluation of the main limitations of PDMS soft-lithography strategy. Different material options are also reviewed, as well as various bonding strategies. Finally, a new functional OoC device is showed, defining protocols for its fabrication in Cyclic Olefin Polymer (COP) using two different RP technologies. Different cells are seeded in both sides of the membrane as a proof of concept to test the optical and fluidic properties of the device.

JTD Keywords: digital manufacturing, microfluidics, organ on a chip, rapid prototyping, Digital manufacturing, Microfluidics, Organ on a chip, Rapid prototyping