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Amaya Catano, J.

Publications and source records attributed to Amaya Catano, J..

2 recordsLinked to original sources

Modelling and measuring effects of shear stress in extrusion bioprinting of endothelial- epithelial cell co-cultures

Extrusion-based bioprinting enables the development of tissue-like constructs; however, the impact of printing-associated shear stress on cell viability and function remains a critical consideration. To address this, we developed a comprehensive workflow combining rheological characterization, computational fluid dynamics (CFD) modelling, and experimental validation to predict and assess shear stress effects during bioprinting. The rheological properties of gelatin methacryloyl (GelMA) at 5 % (w/v, 20 {degrees}C) and 10 % (30 {degrees}C) concentrations were modelled, comparing various non-Newtonian regression models. CFD simulations were validated using micro-particle image velocimetry, showing agreement between predicted and measured velocities. The impact of bioprinting-associated shear stress on cell viability was assessed using a co-culture of human umbilical vein endothelial cells and breast epithelial cells. Immediate post-printing analysis revealed increased apoptosis in GelMA 5 % (w/v, 20 {degrees}C), although 10 % (w/v) GelMA demonstrated higher shear stress levels compared to 5 % GelMA. After 1 day of culture in crosslinked hydrogels, apoptosis increased in extrusion pressure, demonstrating the impact of low levels of acute shear stress. This workflow provides a robust methodology for predicting acute shear stress impacts during bioprinting, laying the foundation for future optimization studies.

bioengineering↗

Dissecting Immune-Epithelial Interactions in Airway Infection at Single-Cell Resolution Using a Compartmentalised Microfluidic Device

Immune-epithelial interactions govern the initiation and progression of airway diseases, yet their heterogeneity is difficult to capture using existing in vitro models. Although conventional Transwell and lung-on-chip systems reproduce airway compartmentalisation and permit epithelial-immune interactions, they lack the spatial and analytical resolution needed to visualise dynamic immune behaviour during infection. Here, we present the "Single Cell resolved Airway-Immune Recruitment" (scAIR) platform designed to interrogate immune-epithelial interactions during airway infection. The scAIR device features a modular central chamber accommodating a Transwell insert with primary airway epithelial cells (AECs) pre-differentiated under air-liquid interface (ALI), flanked by immune compartments connected through a precision-patterned microchannel array. This architecture enables real-time single-cell imaging of immune cell migration while preserving epithelial physiology. The scAIR device coupled with a machine learning analysis (MLA) pipeline enables automated tracking and quantification of individual immune cell speed, direction, and behavioural heterogeneity. Using this platform, respiratory syncytial virus (RSV) infection is modelled to generate a type 1 inflammatory airway epithelium that drives neutrophil recruitment. TNF-alpha neutralisation with adalimumab reveals distinct migratory behaviours that are obscured by population-averaged measurements. This integrated platform quantifies airway immune responses during infection and therapeutic modulation, enabling mechanistic studies, drug evaluation, and precision modelling of airway inflammation.

bioengineering↗