Multi-material 3D Bioprinting of Complex Constructs for In-vitro Mechanobiology Studies in Pulmonary Fibrosis
Bibliographic record
Abstract
Abstract Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by progressive tissue stiffening, which modifies fibroblasts behavior and drives to disease progression. Previous mechanobiology studies have demonstrated that mechanical cues affect fibroblasts activation and ECM remodeling in the lung. However, current in-vitro models fail to capture the heterogeneous stiffness found in fibrotic lung tissue. Multi-material 3D bioprinting is a technology that enables the fabrication of physiological relevant constructs with different stiffness regions that can mimic in detail the mechanical heterogeneity of diseased tissue. This study aimed to create complex, heterogeneous constructs with stiffness variations to assess their potential as models for mechanobiology studies, focusing on human lung fibroblast (HLF) activation, morphology and density. We developed two- and three- material 3D bioprinted constructs with defined stiffness regions going from 1 to 35 kPa modulus. Gelatin methacrylate (GelMA) or poly(ethylene glycol) diacrylate (PEGDA) based biomaterial inks at different concentrations were used to control stiffness. To obtain rheological consistency for extrusion bioprinting, Carbopol (CBP) was incorporated to the inks formulations as a rheological modifier. Geometrically complex structures, including meshes and cylinders, were printed to demonstrate the versatility and precision of these inks to create multi-material constructs with regions of defined stiffnesses. We evaluated how material mechanical properties and single- vs multi-material constructs impacted HLF behaviour by culturing them on GelMA-three-material constructs, using α-SMA expression to assess fibroblast-to-myofibroblast transition. In parallel, F-actin and nuclear stains were used to observe changes in cell morphology and density. As expected, HLFs showed stiffness-dependent activation, with increased α-SMA expression in stiffer regions. Multi-material constructs also enhanced regional differences in fibroblast activation compared to the single-material ones. This suggests that fibroblasts in heterogeneous environments may respond more strongly to local stiffness gradients, potentially due to mechanical coupling or signaling across the different regions. These findings align with prior lung mechanobiology studies, reinforcing the role of ECM stiffness in fibroblast activation and disease progression in IPF. By comparing single- and multi-material systems, this study demonstrates the potential of multi-material 3D bioprinting for modeling lung fibrosis, highlighting the unique insights that can be accessed by having a heterogeneous model. This platform could provide a robust tool for disease modeling, drug screening, and therapeutic development for IPF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".