Impact of physiological media and sterilization methods on the physicochemical characteristics of engineered CNCs, and the effects on nanomaterial-protein interactions and immunological activity
Bibliographic record
Abstract
The biological properties of nanomaterials are impacted by their interactions with biomolecules. The interaction of nanomaterials with proteins is highly influenced by the intrinsic physicochemical properties of the nanomaterials as well as by the surrounding environment. In this study, we assessed surface charge, apparent particle size and size distribution of autoclaved and filtered colloidal suspensions of cellulose nanocrystals (CNCs) in different physiologically media. We also investigated the protein corona of these preparations of CNCs in cell culture medium with serum, using gel electrophoresis and silver staining. Furthermore, we evaluated their immune properties in cell-based assays. Our results indicated that regardless of the sterilization methods, their intrinsic physicochemical properties were most affected by the medium. The autoclaved suspensions of CNCs showed the most quantity of associated proteins, while the filtered suspensions showed the greatest variety of it. The immune activity of colloidal suspensions of CNCs was cell type- and cytokine- dependent.
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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 | 0.001 |
| 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) | 0.001 | 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 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".