journal article·2025-10Open access

Tuning the physico-chemical properties of 3D-printed pectin-constructs for regulating mesenchymal stem cell differentiation in an endochondral ossification in vitro

Dalila Petta, Anna Lapomarda, Maria Vittoria Colombo, Mike A. Geven, Elena Pulidori, Chiara Arrigoni, Celia Duce, Irene Chiesa, Christian Candrian, Giovanni Vozzi, Matteo Moretti, Carmelo De Maria

Materials & Design· Volume 258

Abstract

Pectin is a sustainable biomaterial, with mechanical and rheological properties with tunable mechanical and rheological properties upon crosslinking. In this context, we aimed at developing an in vitro model of endochondral ossification (ECO) process by investigating how pectin physico-chemical properties affected the differentiation of human bone marrow-derived mesenchymal stromal cells (hBMSCs) towards cartilage and hypertrophic cartilage. We printed pectin scaffolds with increasing content of (3-glycidyloxypropyl)trimethoxysilane (GPTMS) crosslinker, with or w/o hydroxyapatite (HAp), and seeded them with hBMSCs, chondrogenically differentiated for 14 days, followed by 14 days of hypertrophic differentiation. We showed that a 50 % increase of the GPTMS content led to an almost three-fold increase in compressive modulus, in the range of hundreds of kPa. As expected, the different mechanical properties influenced cell differentiation, whereby the lowest GPTMS content and no HAp) led to increased expression of chondrogenic markers (ACAN, Col2A1 and SOX9), both at gene and at protein level. Taking a step forward and more surprisingly, hypertrophic marker (Col10A1, MMP13 and RUNX2) expression was also the highest in the same construct. Our findings suggest that mechanical and biochemical properties that promotes the chondrogenic phase of the ECO process would also better foster the subsequent hypertrophy.
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Research context

OpenAlex topics: 3D Printing in Biomedical Research · Bone Tissue Engineering Materials · Hydrogels: synthesis, properties, applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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