Development of a Functional 3D Bioprinted Vascular Smooth Muscle Tissue Model Using a Stiffness‐Modifiable Alginate‐Collagen‐Fibrinogen Based Bioink
Notice bibliographique
Résumé
Background Blood vessels are soft tissues whose cellular functions are regulated in part by mechanical signals from the extracellular matrix. Structural defects including increased vascular wall stiffness are known contributors to the initiation and progression of diseases like pulmonary hypertension and atherosclerosis. However, studying the effects of wall stiffness using traditional 2 dimensional (2D) cell culture models pose challenges: the flat plastic surface is very stiff and incapable of accurately replicating altered tissue structure. Using 3D bioprinting technology and a stiffness‐modifiable alginate‐collagen‐fibrinogen bioink, we aimed to fabricate functional tissue mimicking the medial smooth muscle layer of healthy and diseased blood vessels. Methods Pulmonary and coronary arterial smooth muscle cells (PASM and CASM respectively) were encapsulated at 2.5x10 7 cells/mL in a bioink comprised of 0.25% to 1.0% w/v sodium alginate, 1 mg/mL collagen‐I, and 5 mg/mL fibrinogen. Tissues were bioprinted with an Aspect Biosystems RX‐1 bioprinter as an 8–10 mm ring, free‐floating or constrained within a stiff (0.75–1.25% alginate) acellular load bearing frame, then treated with thrombin (1.25 U/mL, 30 min) for fibrin polymerisation. To assess tissue integrity and function, tissue compaction was assessed by reduction of lumen area and cell organization was determined using filamentous actin staining. Results Stiff (1% alginate) PASM biorings without a frame were mechanically stable, but cells remained ‘balled up’ and were unable to spread within the structure. Softer (0.25% and 0.5% alginate) PASM biorings showed signs of cell spreading but exhibited excessive compaction (>70% lumen area reduction) within 24 hours. Addition of a 1% alginate frame to PASM biorings reduced compaction to 6.94% (0.25% cellular alginate) and 3.69% (0.5% cellular alginate), while still allowing cells to elongate and form cell‐cell networks. Similar results were observed with CASM biorings, which compacted >50% when printed without a frame. We demonstrated that the degree of tissue compaction is controllable using frames of different stiffnesses; soft (0.375% alginate) CASM biorings printed with a 0.75% alginate frame had >15% compaction, whereas biorings with stiffer 1% and 1.25% alginate frames exhibited <5% compaction. In all cases, cells printed in soft biorings with stiff frames had well‐organised bundles of actin filaments consistent with real vascular smooth muscle. Conclusion Our stiffness‐modifiable 3D bioprinted smooth muscle represents a novel experimental model for studying vascular tissue. The bioink composition and physical design, where muscle compaction can be easily controlled by altering the acellular load bearing frame, allows us to better mimic the structural defects seen in vascular diseases than is possible with 2D models. This makes our model a powerful tool that will enable us to understand how wall stiffness affects the initiation and progression of vascular diseases. Support or Funding Information NSERC Discovery Grant (ARW), Research Manitoba Studentship (SS, JO), CHRIM Operating Grant
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».