Tissue-in-a-Tube: three-dimensional in vitro tissue constructs with integrated multimodal environmental stimulation
Bibliographic record
Abstract
Three-dimensional (3D) in vitro tissue models are superior to two-dimensional (2D) cell cultures in replicating natural physiological/pathological conditions by recreating the cellular and cell-matrix interactions more faithfully. Nevertheless, current 3D models lack either the rich multicellular environment or fail to provide appropriate biophysical stimuli both of which are required to properly recapitulate the dynamic in vivo microenvironment of tissues and organs. Here, we describe the rapid construction of multicellular, tubular tissue constructs termed Tissue-in-a-Tube using self-assembly process in tubular molds with the ability to incorporate a variety of biophysical stimuli such as electrical field, mechanical deformation, and shear force of the fluid flow. Unlike other approaches, this method is simple, requires only oxygen permeable silicone tubing that molds the tissue construct and thin stainless-steel pins inserted in it to anchor the construct and could be used to provide electrical and mechanical stimuli, simultaneously. The annular region between the tissue construct and the tubing is used for perfusion. Highly stable, macroscale, and robust constructs anchored to the pins form as a result of self-assembly of the extracellular matrix (ECM) and cells in the bioink that is filled into the tubing. We demonstrate patterning of grafts containing cell types in the constructs in axial and radial modes with clear interface and continuity between the layers. Different environmental factors affecting cell behavior such as compactness of the structure and size of the constructs can be controlled through parameters such as initial cell density, ECM content, tubing size, as well as the distance between anchor pins. Using connectors, network of tubing can be assembled to create complex macrostructured tissues (centimeters length) such as fibers that are bifurcated or columns with different axial thicknesses which can then be used as building blocks for biomimetic constructs or tissue regeneration. The method is versatile and compatible with various cell types including endothelial, epithelial, skeletal muscle cells, osteoblast cells, and neuronal cells. As an example, long mature skeletal muscle and neuronal fibers as well as bone constructs were fabricated with cellular alignment dictated by the applied electrical field. The versatility, speed, and low cost of this method is suited for widespread application in tissue engineering 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 | 0.001 |
| 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".