Human Milk Oligosaccharides as Essential Tools for Basic and Application Studies on Galectins
Bibliographic record
Abstract
It is now recognized that human milk oligosaccharides (HMOs) can function both as prebiotics and as decoy receptors that inhibit the attachment of pathogenic microorganisms to the colonic mucosa. They can also act as immune modulators and as colonic maturation stimulators in breast-fed infants. These functions could be mediated by biological interaction between a variety of HMOs and lectins including galectins, selectins and siglecs. There are more than 100 HMOs; they have structural units such as H type 1: Fucα1-2Galβ1-3GlcNAc, Lewis a: Galβ1-3(Fucα1-4)GlcNAc, Lewis b: Fucα1-2Galβ1-3(Fucα1-4)GlcNAc, Lewis x: Galβ1-4(Fucα1-3)GlcNAc, sialyl Lewis a: Neu5Acα2-3Galβ1-3(Fucα1-4)GlcNAc, and sialyl Lewis x: Neu5Acα2-3Galβ1-4(Fucα1-3)GlcNAc. It can be expected that these units may be utilized as tools for studies on the sugar-binding specificities of lectins including galectins, monoclonal antibodies, virus capsid proteins and bacterial toxins. This mini-review presents the dataset of comprehensive HMO structures, including recently clarified ones, in tabular form, for its utilization in such studies, including those of carbohydrate-binding specificity of galectins. In addition, this review introduces recent in vivo and clinical studies, which may be relevant to the biological functions and future utilization of HMOs.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".