Human milk oligosaccharides produced by synthetic biology
Bibliographic record
Abstract
The benefits of human breast milk (HBM) to newborn growth, development, and overall health have been well investigated. As breastfeeding rate has declined significantly, the use of infant formula has risen and remains a significant component of the infant's diet. HBM contains several essential nutritional components, with human milk oligosaccharides (HMO) being the third most abundant following lactose and lipids. A diverse array of HMOs is known to exert great benefits in intestinal, immune, and cognitive functions. In contrast to HBM, infant formula containing mainly bovine milk lacks the diversity of HMOs. Efforts have been made to replicate this characteristic in infant formula through chemical and chemoenzymatic synthesis as well as microbial production. Utilizing microbial hosts appears to be more favourable due to its accessibility and cost-efficiency. Escherichia coli has been preferably used due to its high incorporation of DNA, high-level expression capability, and rapid growth. However, potential endotoxin contamination raises health concerns and prevents approval as Generally Recognized as Safe (GRAS) by the FDA. This prompts the use of other microbes such as Bacillus subtilis. Future research in this area is needed to optimize effective procedures using microbial hosts, high yield production, and economic feasibility. This may lead to infant formulas closely mimicking HBM and its health benefits.
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".