Multifunctional Applications of Bacterial Cellulose: Bridging Food, Cosmetic and Environmental Sectors
Bibliographic record
Abstract
In recent years, with increasing demand for sustainable, environmentally friendly materials, bacterial cellulose (BC) has attracted significant attention as a promising biomaterial. BC possesses excellent mechanical strength, good biocompatibility, extremely high water-holding capacity (more than 100 times its own weight), and can be easily modified. These unique properties make BC superior to plant cellulose in many applications. This review summarizes recent progress in BC across several important fields. In the food industry, BC has been widely used as edible films and coatings, enhancing the shelf life of fresh products. Moreover, when natural antimicrobial agents or pH indicators were incorporated, active and intelligent packaging were developed. As a food additive, BC acts as a high-quality dietary fiber that can adsorb cholesterol and bile salts in the gastrointestinal tract. BC also improves the texture of low-calorie foods and protects probiotic bacteria during storage. In the cosmetic field, BC is well-suited for facial masks because its three-dimensional structure can hold a large amount of active compounds and conform well to the skin surface. When BC was combined with propolis or other natural extracts, the antioxidant and anti-aging effects were greatly enhanced. In wastewater treatment, the abundant hydroxyl groups and large surface area enable heavy metal ions and organic dyes to be removed effectively. Besides, BC has been used as a reinforcement material in the paper and textile industries. The addition of BC greatly increases tensile strength and provides hydrophobicity while maintaining complete biodegradability. Although BC has numerous excellent properties and great potential in many fields, large-scale production still faces some challenges, mainly high costs and low yields. The use of agro-industrial waste as a substrate and the development of new bioreactors can significantly reduce production costs. Based on the above-mentioned research, it is clear that BC will play an important role in the future sustainable industry.
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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) | 0.000 | 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".