Fabrication of Perfusable Vascular Channels and Capillaries in 3D Liver-like Tissue
Bibliographic record
Abstract
Although various production methods for 3D vascularised tissues have been developed, constructing capillary-like structures branching from perfusable large channels remains difficult. This study describes a method to fabricate tube-shaped 3D liver-like tissue (tubular liver tissue) with large channels and capillary-like structures using a perfusion device. The perfusion device functions as an interface between the tissue and an external pump, as it has connectors equipped with anchors that hold the tissue in response to its shrinkage, which is accompanied by the self-organisation of capillary-like structures. Histological analysis revealed that perfusion via the large channel induced capillary formation around the channel and maintained proper tissue functions. Accompanied by structural examinations, global gene expression analysis supported this finding; specifically, genes involved in angiogenesis were enriched in the perfused condition. Furthermore, we confirmed the penetrability of the capillary-like structures by infusing India ink, as well as substance exchange by measuring the amounts of secreted albumin. These lines of evidence indicate that our method can be used to construct 3D tissues, which is useful for fields of in vitro tissue regeneration for drug development and regenerative medicine.
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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 | 0.001 | 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".