Design and Construction of Fluorescent Cellulose Nanocrystals for Biomedical Applications
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
Abstract Cellulose nanocrystals (CNCs) are featured with low toxicity, non‐trivial biocompatibility, and cell membrane penetration capability, which allow the constructions of nanoplatforms for biosensing and in vivo imaging. Interfacing CNCs and fluorescent materials into sensors/probes is thus highly topical and has received tremendous interest. This review covers the development of CNC extraction methods and, in particular, their impacts on the surficial properties of CNCs. Whereafter, recently reported strategies for fluorescent functionalizations of CNCs are summarized based on chemical modification, physical adsorption, or in situ growth. Choosing the most suitable strategy, according to the properties of both CNCs and fluorophores, for constructing fluorescent CNCs is also emphasized. With regard to applications of the fluorescent CNCs, this work focuses on the studies which have involved but not been limited to metal ion sensing, physiological pH detection, cell imaging, and tumor antiproliferation. Being aware of the highly flexible construction, appealing structural/optical properties, and outstanding performances in analysis/imaging, it is believed that CNCs are bound to be increasingly investigated in the future and widely applied in the biomedical area.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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