The versatile biopolymer chitosan: potential sources, evaluation of extraction methods and 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
Among the biopolymers, chitin and its derivative chitosan (CTS) have been receiving increasing attention. Both are composed of randomly distributed β-(1-4)-linked d-glucosamine and N-acetyl glucosamine units. On commercial scale, CTS is mainly obtained from the crustacean shells. The chemical methods employed for extraction of CTS from crustacean shells are laden with many disadvantages. Waste fungal biomass represents a potential biological source of CTS, in fact with superior physico-chemical properties, such as high degree of deacetylation, low molecular weight, devoid of protein contamination and high bioactivity. Researchers around the globe are attempting to commercialize CTS production and extraction from fungal sources. Fungi are promising and environmentally benign source of CTS and they have the potential to completely replace crustacean-derived CTS. Waste fungal biomass resulting from various pharmaceutical and biotechnological industries is grown on inexpensive agro-industrial wastes and its by-products are a rich and inexpensive source of CTS. CTS is emerging as an important natural polymer having broad range of applications in different fields. In this context, the present review discusses the potential sources of CTS and their advantages and disadvantages. This review also deals with potential applications of CTS in different fields. Finally, the various attributes of CTS sought in different applications are discussed.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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