Multifunctional Carbon-Based Nanomaterials: Applications in Biomolecular Imaging and Therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Molecular imaging has been widely used not only as an important detection technology in the field of medical imaging for cancer diagnosis but also as a theranostic approach for cancer in recent years. Multifunctional carbon-based nanomaterials (MCBNs), characterized by unparalleled optical, electronic, and thermal properties, have attracted increasing interest and demonstrably hold the greatest promise in biomolecular imaging and therapy. As such, it should come as no surprise that MCBNs have already revealed a great deal of potential applications in biomedical areas, such as bioimaging, drug delivery, and tumor therapy. Carbon nanomaterials can be categorized as graphene, single-walled carbon nanotubes, mesoporous carbon, nanodiamonds, fullerenes, or carbon dots on the basis of their morphologies. In this article, reports of the use of MCBNs in various chemical conjugation/functionalization strategies, focusing on their applications in cancer molecular imaging and imaging-guided therapy, will be comprehensively summarized. MCBNs show the possibility to serve as optimal candidates for precise cancer biotheranostics.
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.
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) | 0.000 | 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 it