journal article·2013-06

Increased mucociliary differentiation and aquaporins formation of respiratory epithelial cells on retinoic acid-loaded hyaluronan-derivative membranes

Tsung-Wei Huang, Yen-Hui Chan, Huang-Wei Su, Ya-Shuan Chou, Tai-Horng Young

Acta Biomaterialia· Volume 9· Issue 6
Publisher page

Abstract

While playing a major role in maintaining the mucociliary phenotype of respiratory epithelial cells (RECs), retinoids are critical determinants of their normal function. However, despite being a powerful biological agent, retinoic acid (RA) is generally not used in regenerative medicine due to its scarce bioavailability via conventional administration. Therefore, the ability to incorporate RA into biomaterials allows for a combination of the biological effects of RA and biomaterials in influencing cellular behavior. This study attempts to develop RA-loaded hyaluronan-derivative membrane (RA-HAm) and investigates how this membrane affects the mucociliary differentiation and aquaporins (AQP) formation of RECs. In a simulated in vitro culture condition, the RA release from membranes is maintained for 7days. On the seventh day, the cumulative release rate of RA from supportive biomaterials is ~87% under detect limitation. RECs cultured on RA-HAm reveal numerous mature ciliated cells and microvilli compared to aggregated cilia-like structures on hyaluronan-derivative membrane (HAm). Moreover, the expression levels of MUC5AC and AQP on RA-HAm are higher than those on HAm. The proposed model elucidates the release of hydrophobic RA from hyaluronan-derivative biomaterials. We believe that RA-loaded hyaluronan biomaterials are highly promising biomaterials for use in sinonasal surgery and tissue engineering of the respiratory system.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Neonatal Respiratory Health Research · Proteoglycans and glycosaminoglycans research · Fibroblast Growth Factor Research

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

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