Prebiotic mechanisms, functions and applications - A review
Bibliographic record
Abstract
In October 2012, a group of scientists met at the 10th Meeting of the International Scientific Association of Probiotics and Prebiotics (ISAPP) in Cork, Ireland to discuss issues surrounding prebiotics and their development. This article summarises outputs from the meeting. Various prebiotic definitions were discussed and how the concept has evolved from targeting the colonic microbiome, through to the entire gastrointestinal tract and finally the ISAPP definition, which specifies fermentation as a key criterion. Structure and function relationships are becoming clearer with effects upon microbial diversity, determinations of selectivity and enhanced biological activity being major outcomes. Immune modulation and metal chelation were further facets. Biomass can be a useful, and economic, means of generating new prebiotics. Pectic oligomers from citrus are model examples. Testing aspects range from in vitro batch culture fermenters to multiple stage models, immobilized systems, animal, cellular studies and human trials. Analytical processes around microbiota characterization and functionality were compared. Human studies were seen as the definitive outcome, including 13C labeling of key interventions. For extra intestinal effects, atopic disease, respiratory infections, vaginal issues, oral disease, adiposity, liver damage and skin infections are all feasible. The general outcome was that microbiota modulation was the key mechanism that linked these interactions. In pet food applications, the market potential for prebiotics is huge. Health targets are similar to those of humans. Issues include monomeric composition, chain length, linkages, branching, microbiota beyond bifidobacteria, metabolic function, mechanisms of health effects. Molecular biology has unraveled some of the explanations for prebiotic influences e.g. gene clusters to show transporters, regulators, permeases, hydrolases, lacS. In Lactobacillus ruminis, fermentation studies have been aligned to genome annotations, showing an energy efficient and rapid transport of GOS. In bifidobacteria, functional genome analyses have demonstrated uptake of trisaccharides. Questions relating to patients were then raised. For example, are prebiotics related to disease treatment or health maintenance? If a prebiotic does not change the microbiota, then how does it operate? Case study trials in Inflammatory Bowel Disease were presented on patient access to prebiotics and information. These showed that their knowledge of prebiotics was poor, compared to probiotics. The group then discussed the next generation of prebiotics (e.g. anti-adhesive activities). The comparator was Human Milk Oligosaccharides, which both reduce adherence of pathogens and act as prebiotics. Studies with galactooligosacchardes (GOS) have used pyrosequencing to demonstrate varying species level effects. This has relevance for infant formulae. Prebiotic aspects of whole foods and their complexity was covered. Trials were described where cross feeding and co-metabolism had been investigated. Suggestions on other prebiotic influences, aside from bifidobacteria, were made and included metagenomics, metabonomics, gene expression, mRNA global sequencing, bile deconjugation, enzyme profiles, lipids, phenolics. The discussion suggested how prebiotics could move forward with a wider expansion of the concept, target populations, expanded microorganisms, health benefits, application of new technologies and improved consumer understanding being the main goals. Copyright © 2013 by New Century Health Publishers, LLC. Chemicals/CAS: pectin, 9000-69-5
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".