Back

Paracrine Factor Local Gradient-Generating System for Engineering Perfusable Vascularized Hepatocyte Tissues with Perfusion-Induced Proliferation

Huang, Y.-H.; Yamashita, T.; Sudo, R.

2025-11-12 bioengineering
10.1101/2025.11.10.687539 bioRxiv
Show abstract

Donor organ shortages drive the urgent need for engineered hepatocyte tissues, yet functional vascular integration remains a major bottleneck in liver tissue engineering. Current vascularization strategies struggle to achieve perfusable microvessels that penetrate hepatocyte tissue. Furthermore, in vitro recapitulation of hepatic regeneration remains a major challenge. This study presents a paracrine factor local gradient (PFLG)-generating system that constructs vascularized, perfusable hepatocyte tissues and recapitulates the perfusion-mediated proliferative capacity of primary hepatocytes. The PFLG-generating platform integrates fibroblast-loaded cryogels with a microfluidic device to direct angiogenesis prior to hepatocyte seeding, thereby enabling microvessels to penetrate three-dimensional hepatocyte tissue. Within the vascularized constructs, microvessels directly penetrated the hepatocyte parenchyma, recapitulating intimate hepatocyte-microvessel contact in vivo. These constructs enhanced hepatocyte polarity and functional bile canaliculi. Importantly, under perfusion culture, robust hepatocyte proliferation was induced, with Ki67-positive hepatocytes increasing significantly, including mitotic cells while preserving polarity. By contrast, this proliferative response was minimal under static conditions. Time-lapse imaging and functional assays confirmed perfusion through penetrating microvessels. These findings demonstrate that perfusion-mediated cues are essential for inducing hepatocyte proliferation while maintaining functional polarity. This modular and programmable culture platform lays the foundation for scale-up toward transplantable liver tissues.

Published in Advanced Healthcare Materials (predicted rank #1) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.