Bio‐electrospraying 3‐D Organotypic Human Skin Cultures
Bibliographic record
Abstract
Organotypic 3D tissue models have greatly contributed to understand a wide range of molecular and cellular characteristics within a functional or diseased tissue. Human skin reconstructs which act as models are most useful for a wide range of investigations, ranging from tissue engineering and regenerative medicine, drug development, screening, and discovery to name a few. There are many approaches for reconstructing 3D skin tissue models, however, to date there have been very few that are able to generate organotypic 3D constructs with a single technology having minimal processing steps to finally scalability. The many manifestations of 3D bioprinting have contributed to this endeavor, having said that, the technology's limitations have tempered those reconstructed models, as they are known to contain low cell numbers/concentrations to those having damaged/dead molecules/cells within the reconstructed tissue, which are not desirable, for exploring as tissues models. Contrary to 3D bioprinting approaches, bio-electrosprays have been demonstrated to possess the ability to handle large concentrations of cells and molecules to whole fertilized embryos without damaging them from a molecular level upwards. Consequently, this article demonstrates, for the first time, bio-electrospray's capacity to reconstruct skin-like structures in vitro and its potential in reconstructing full-thickness 3D organotypic human skin tissues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".