Ana Zubiarrain Laserna

Ms. Ana Zubiarrain Laserna

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 January 2022 in Polymers
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Journal Article
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IGIzar Gorroñogoitia
Izar Gorroñogoitia
UUUzuri Urtaza
Uzuri Urtaza
ALAna Zubiarrain Laserna
Ana Zubiarrain Laserna
Ana Alonso-VaronaAna Alonso-Varona
Ana Alonso-Varona
AZAne Miren Zaldua
Ane Miren Zaldua
Three-dimensional bioprinting combined with natural hydrogels is a promising technology for the treatment of several pathologies and different tissue regeneration. One of the most studied tissues is cartilage, a complex and avascular tissue that displays a limited self-repair capacity after injuries. Herein, the development of alginate-based hydrogels and scaffolds containing different microstructure is presented and the printability of alginate by 3D bioprinting is studied. Rheological characterization was performed for the determination of viscosity and viscoelastic properties of hydrogels and mechanical characterization was carried out for the determination of compressive modulus of alginate hydrogels. All these characteristics were correlated with alginate behaviour during 3D bioprinting process. For the printability evaluation filament diameter, perimeter of the pores, area of the pores and shrinkage of alginate scaffolds were measured. The results demonstrate that alginate microstructure has a great influence on its printability and on hydrogels’ physicochemical properties. Molecular weight of alginate determines its viscosity while M/G ratio determines cross-linking conditions and mechanical properties that vary with cross-linking density. These results suggest the importance of an exhaustive control of the viscoelastic and mechanical properties of alginate hydrogels to obtain structures with high resolution and precision.

24 July 2024 in Biofabrication
Verified
Journal Article
Open access
ALAna Zubiarrain Laserna
Ana Zubiarrain Laserna
DMDaniel Martínez-Moreno
Daniel Martínez-Moreno
JAJulia López de Andrés
Julia López de Andrés
LLLaura de Lara-Peña
Laura de Lara-Peña
OLOlatz Guaresti Larrea
Olatz Guaresti Larrea
Juan Antonio MarchalJuan Antonio Marchal
Juan Antonio Marchal
There is increasing evidence that cancer progression is linked to tissue viscoelasticity, which challenges the commonly accepted notion that stiffness is the main mechanical hallmark of cancer. However, this new insight has not reached widespread clinical use, as most clinical trials focus on the application of tissue elasticity and stiffness in diagnostic, therapeutic, and surgical planning. Therefore, there is a need to advance the fundamental understanding of the effect of viscoelasticity on cancer progression, to develop novel mechanical biomarkers of clinical significance. Tissue viscoelasticity is largely determined by the extracellular matrix (ECM), which can be simulated in vitro using hydrogel-based platforms. Since the mechanical properties of hydrogels can be easily adjusted by changing parameters such as molecular weight and crosslinking type, they provide a platform to systematically study the relationship between ECM viscoelasticity and cancer progression. This review begins with an overview of cancer viscoelasticity, describing how tumor cells interact with biophysical signals in their environment, how they contribute to tumor viscoelasticity, and how this translates into cancer progression. Next, an overview of clinical trials focused on measuring biomechanical properties of tumors is presented, highlighting the biomechanical properties utilized for cancer diagnosis and monitoring. Finally, this review examines the use of biofabricated tumor models for studying the impact of ECM viscoelasticity on cancer behavior and progression and it explores potential avenues for future research on the production of more sophisticated and biomimetic tumor models, as well as their mechanical evaluation.

27 June 2022 in Biomedical Materials
Verified
Journal Article
Closed access
UUUzuri Urtaza
Uzuri Urtaza
OLOlatz Guaresti Larrea
Olatz Guaresti Larrea
IGIzar Gorroñogoitia
Izar Gorroñogoitia
ALAna Zubiarrain Laserna
Ana Zubiarrain Laserna
EMEmma Muiños-López
Emma Muiños-López
JAJon Anakabe
Jon Anakabe
This work identifies and describes different material-scaffold geometry combinations for cartilage tissue engineering (CTE). Previously reported potentially interesting scaffold geometries were tuned and printed using bioresorbable polycaprolactone and poly(lactide-b-ethylene) block copolymer. Medical grades of both polymers were 3D printed with fused filament fabrication technology within an ISO 7 classified cleanroom. Resulting scaffolds were then optically, mechanically and biologically tested. Results indicated that a few material-scaffold geometry combinations present potential for excellent cell viability as well as for an enhance of the chondrogenic properties of the cells, hence suggesting their suitability for CTE applications.

1 May 2020 in ECS Meeting Abstracts
Verified
Journal Article
Closed access
JDJohnson Dalmieda
Johnson Dalmieda
ALAna Zubiarrain Laserna
Ana Zubiarrain Laserna
RSRavi Selvaganapathy
Ravi Selvaganapathy
Peter KrusePeter Kruse
Peter Kruse
Silver is a precious metal that is commonly used in water filters to reduce growth of biofilm within the filter itself. Ionic silver is used as an effective disinfectant for potable water, giving a log10 reduction for L. pneumophilia, P. aeruginosa, and E. coli of 2.4, 4, and 7, respectively.1 In terms of human exposure, silver is not an essential metal therefore any exposure to silver is unwanted. When silver is ingested orally, the most common adverse effect is argyria, which is an extreme blue pigmentation of the skin and abdominal viscera.2 Occupational exposure to silver nitrate has been correlated to respiratory tract irritation.3 Currently there are no guidelines for silver ions in drinking water, and the World Health Organization (WHO) has set a health advisory (not a guideline value) of 100 ppb. The only country with a Maximum Allowable Content (MAC) is Germany, whose drinking water regulations (Trinkwasserverordnung) have a MAC of 80 ppb.4 Here we demonstrate a chemiresistive sensor for the in situ detection of silver (I) in aqueous media. Chemiresistive sensors function through the changes that occur in the electronic structure of the sensor itself. A graphite film attached to two copper contacts at either end is exposed to the silver ions such that only the graphite and not the contacts interact with the ions. To functionalize the graphite, silver (I)-specific ligands, such as bathocuproine, can be deposited onto the film to adsorb onto it, protecting it from interfering ions.5 Chemiresistive sensors have been demonstrated before for the detection of free chlorine in aqueous media. Rather than using graphite, carbon nanotubes (CNT) were utilized as the conductive film, with phenyl-capped aniline tetramer (PCAT) as the chlorine-specific ligand. As the PCAT doped CNT was exposed to chlorine, the PCAT oxidized, and the electronic changes were probed using a bias voltage. The linear range for this sensor was from 60 ppb to 60 ppm, providing sufficient sensitivity for household use.6 When testing other common ions, there were no significant interference's that compete with the response of silver (I) in solution, making this sensor quite selective to silver (I). pH tests show that there is no change in current induced by pH between the range of 6-10 pH. Below 6, the sensor functions as a "proton sensor" due to the protonation of the adsorbed bathocuproine. Above pH 10, AgOH may be formed, which will precipitate out of solution. All tests were performed at an analyte conductance of 31 μS/cm, which is typical for freshwater samples.7 When the fabricated sensor was exposed to silver (I) in aqueous solution, detection of the ions was observed through a step up in the current going through the sensor. Each step up in current was proportional to the concentration of silver (I) in solution. Based on this, a calibration curve was made using the Langmuir Isotherm model and a first-order exponential decay model. For the range of 3 ppb to 1 ppm, both the Langmuir Isotherm and the first-order exponential decay model gave R2 values of 0.9982 and 0.9939, respectively. The sensor could also be reliably reset to the same 0 ppm baseline after use by exposing it to a pH 3 solution. When exposed to silver (I) post-reset, current changes were also quite reproducible, with the values having a relative standard deviation no greater than 1.24%, highlighting the re-usability of this sensor. The limit of detection, calculated using a signal:noise ratio of 3, for this sensor would be 3 ppb. We have therefore demonstrated that chemiresistors based on functionalized nanocarbon films can be used as selective ion sensors in addition to their previously demonstrated application as redox sensors. The toolbox of organometallic chemistry can now be applied to extend this sensing platform to other cations for water quality sensing. References 1. Kim, J. S.; Kuk, E.; Yu, K. N.; Kim, J.-H.; Park, S. J.; Lee, H. J.; Kim, S. H.; Park, Y. K.; Park, Y. H.; Hwang, C.-Y.; et al. Antimicrobial Effects of Silver Nanoparticles. Nanomedicine: Nanotechnology, Biology and Medicine 2007, 3 (1), 95–101. 2. Marshall, J. P. Systemic Argyria Secondary to Topical Silver Nitrate. Archives of Dermatology 1977, 113 (8), 1077. 3. Toxicological Profile for Silver. Agency for Toxic Substances and Disease Registry 1990. 4. Silver as a Drinking-Water Disinfectant. World Health Organization 2018. 5. Saito, T. Transport of Silver(I) Ion through a Supported Liquid Membrane Using Bathocuproine as a Carrier. Separation Science and Technology 1998, 33 (6), 855–866. 6. Hsu, L. H. H.; Hoque, E.; Kruse, P.; Selvaganapathy, P. R. A Carbon Nanotube Based Resettable Sensor for Measuring Free Chlorine in Drinking Water. Applied Physics Letters 2015, 106 (6), 063102. 7. https://www.ontario.ca/data/provincial-stream-water-quality-monitoring-network (accessed on October 22, 2019) Figure 1