Carbon‐Based Nanobiomaterials
Bibliographic record
Abstract
Nanobiomaterials and microfabrication technologies have recently found many applications in biology and medicine resembling micro- and nanofeatures of extracellular matrix (ECM), cell–ECM interaction, and biological processes. In particular, carbon-based nanomaterials (carbon nanotubes (CNTs) and graphene) have received much attention and applications as functional biomaterials in tissue regeneration, delivery of biomolecules, biosensing, and bioimaging because of their significant properties such as high mechanical properties, high electrical conductivity, visibility in near-infrared frequencies, and high surface area. Here, we summarize some applications of CNTs and graphene as scaffolds and cell culture substrates in tissue engineering and stem cell differentiation. Other biomedical applications of CNTs and graphene as carriers in the delivery of biomolecules, as biosensors, and as bioimaging agents are also described. Future research direction may be applications of CNTs and graphene as biocompatible, multifaceted, and functional biomaterials in preclinical and clinical studies.
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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 | 0.000 |
| 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) | 0.004 | 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".