Recent advances in nanoengineering cellulose for cargo delivery
Bibliographic record
Abstract
The recent decade has witnessed a growing demand to substitute synthetic materials with naturally-derived platforms for minimizing their undesirable footprints in biomedicine, environment, and ecosystems. Among the natural materials, cellulose, the most abundant biopolymer in the world with key properties, such as biocompatibility, biorenewability, and sustainability has drawn significant attention. The hierarchical structure of cellulose fibers, one of the main constituents of plant cell walls, has been nanoengineered and broken down to nanoscale building blocks, providing an infrastructure for nanomedicine. Microorganisms, such as certain types of bacteria, are another source of nanocelluloses known as bacterial nanocellulose (BNC), which benefit from high purity and crystallinity. Chemical and mechanical treatments of cellulose fibrils made up of alternating crystalline and amorphous regions have yielded cellulose nanocrystals (CNC), hairy CNC (HCNC), and cellulose nanofibrils (CNF) with dimensions spanning from a few nanometers up to several microns. Cellulose nanocrystals and nanofibrils may readily bind drugs, proteins, and nanoparticles through physical interactions or be chemically modified to covalently accommodate cargos. Engineering surface properties, such as chemical functionality, charge, area, crystallinity, and hydrophilicity, plays a pivotal role in controlling the cargo loading/releasing capacity and rate, stability, toxicity, immunogenicity, and biodegradation of nanocellulose-based delivery platforms. This review provides insights into the recent advances in nanoengineering cellulose crystals and fibrils to develop vehicles, encompassing colloidal nanoparticles, hydrogels, aerogels, films, coatings, capsules, and membranes, for the delivery of a broad range of bioactive cargos, such as chemotherapeutic drugs, anti-inflammatory agents, antibacterial compounds, and probiotics. SYNOPSIS: Engineering certain types of microorganisms as well as the hierarchical structure of cellulose fibers, one of the main building blocks of plant cell walls, has yielded unique families of cellulose-based nanomaterials, which have leveraged the effective delivery of bioactive molecules.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".