Autophagy and Biomaterials: A Brief Overview of the Impact of Autophagy in Biomaterial Applications
Bibliographic record
Abstract
Macroautophagy (hereafter autophagy), a tightly regulated physiological process that obliterates dysfunctional and damaged organelles and proteins, has a crucial role when biomaterials are applied for various purposes, including diagnosis, treatment, tissue engineering, and targeted drug delivery. The unparalleled physiochemical properties of nanomaterials make them a key component of medical strategies in different areas, such as osteogenesis, angiogenesis, neurodegenerative disease treatment, and cancer therapy. The application of implants and their modulatory effects on autophagy have been known in recent years. However, more studies are necessary to clarify the interactions and all the involved mechanisms. The advantages and disadvantages of nanomaterial-mediated autophagy need serious attention in both the biological and bioengineering fields. In this mini-review, the role of autophagy after biomaterial exploitation and the possible related mechanisms are explored.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".