Avant-garde Approach to Life: Reviewing the Current Applications of 3D Bioprinting
Bibliographic record
Abstract
Introduction: The promise of bioprinting tissue constructs that could potentially serve the same function in the human body as native tissues has taken the world of regenerative medicine by storm. The current review describes system-wide clinical applications of three-dimensional (3D) bioprinting and aims to address ethical and social considerations, while also discussing the scope of this technology in the near future. Discussion: 3D bioprinting is believed to present new approaches to conventional treatment, offering the advantage of customization and on-time availability. It facilitates simultaneous deposition of appropriate bioinks and biomaterials onto scaffolds which can then be employed to develop tissue fabricates that can potentially mimic native tissues in both structure and functionality. It has been extensively employed to regenerate viable tissue constructs of skin, bone, cartilage, vasculature, myocardial tissue and heart valves, nervous tissue, lung and tracheal tissue, liver, pancreatic, and corneal tissue. Conclusion: To obviate the current restrictions associated with this technology, it is imperative to understand where we currently stand in terms of current clinical applications of 3D bioprinting. This technology is anticipated to contribute significantly to the fields of tissue engineering and regenerative medicine (TERM), where it can be employed to fabricate functional tissues that can simulate their counterparts in the human body. Relevance: The increasing disparity between organ demand and supply as well as the shortcomings associated with antiquated approaches to treatment call for utilizing 3D bioprinting to develop viable tissue constructs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".