Plant-Based Polysaccharides and their Health Functions
Bibliographic record
Abstract
Plants are valuable source of polysaccharides that make a large portion of our daily diet. These are natural polymers that are essential to sustain life. They provide high-value nutrition and positively help the immune system and improve the digestive properties. They also help in the elimination of toxic by-products from the human body. Polysaccharides and human health are inextricably linked and intertwined. These are also important components of the cell wall that provides its strength and integrity. Due to their indispensable role in human health, it is very important to know the different modifications and loss of nutritional value during the processing of plant material. Nowadays, these plant-based polysaccharides are used for diverse applications including wound dressing, drug delivery, laxative, cosmetic and pharmaceutical preparations. As an emerging area of plant-based medicines to reduce the side effects of synthetic sources, these polysaccharides are used to enhance the immunogenic response against a specific antigen. This review envisages some important polysaccharides (e.g. mucilages and gums, glycosamine glycans and chitin/chitosan) and their medical, cosmetic, and pharmaceutical applications, with emphasis on the relationship between their structure and function.Keywords: Polysaccharides; Nutrition; Health Functions; Cosmetics; Vaccine; Nutraceuticals
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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) | 0.000 | 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) | 0.002 | 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".