Cellulose nanocrystals with tunable surface charge for nanomedicine
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
Crystalline nanoparticles of cellulose exhibit attractive properties as nanoscale carriers for bioactive molecules in nanobiotechnology and nanomedicine. For applications in imaging and drug delivery, surface charge is one of the most important factors affecting the performance of nanocarriers. However, current methods of preparation offer little flexibility for controlling the surface charge of cellulose nanocrystals, leading to compromised colloidal stability under physiological conditions. We report a synthesis method that results in nanocrystals with remarkably high carboxyl content (6.6 mmol g(-1)) and offers continuous control over surface charge without any adjustment to the reaction conditions. Six fractions of nanocrystals with various surface carboxyl contents were synthesized from a single sample of softwood pulp with carboxyl contents varying from 6.6 to 1.7 mmol g(-1) and were fully characterized. The proposed method resulted in highly stable colloidal nanocrystals that did not aggregate when exposed to high salt concentrations or serum-containing media. Interactions of these fractions with four different tissue cell lines were investigated over a wide range of concentrations (50-300 μg mL(-1)). Darkfield hyperspectral imaging and confocal microscopy confirmed the uptake of nanocrystals by selected cell lines without any evidence of membrane damage or change in cell density; however a charge-dependent decrease in mitochondrial activity was observed for charge contents higher than 3.9 mmol g(-1). A high surface carboxyl content allowed for facile conjugation of fluorophores to the nanocrystals without compromising colloidal stability. The cellular uptake of fluoresceinamine-conjugated nanocrystals exhibited a time-dose dependent relationship and increased significantly with doubling of the surface charge.
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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 | 0.000 |
| 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