Human milk oligosaccharides protect bladder epithelial cells against uropathogenic <i>E. coli</i> and <i>Streptococcus agalactiae</i> infections (38.5)
Bibliographic record
Abstract
Urinary tract infection (UTI) is primarily caused by uropathogenic E. coli (UPEC) and sometimes Streptococcus agalactiae (GBS). Recurrent infection that can progress to life‐threatening renal failure has remained as a serious global health concern in infants. Human milk oligosaccharides (HMOs) have been detected in urine of breast‐fed, but not formula‐fed neonates. We investigated the antimicrobial properties and mechanisms HMOs deploy to elicit protection in human bladder epithelial cells. We found HMO‐pretreated epithelial cells were significantly more resistant to invasion by UPEC CFT073, a prototypic strain causing urosepsis. However, HMO pre‐treatment had no significant effect in interfering with UPEC adhesion. Conversely, HMO pre‐treated cells suffer significantly less GBS COH‐1 adhesion and invasion. This result was recapitulated in vivo, in which significantly less GBS was recovered from the bladder of mice treated with HMOs. While HMOs do not play a role in maintaining host cell viability during GBS infection, we found HMOs treatment rapidly UPEC‐mediated host cell cytotoxicity. Moreover, the sialic acid‐containing fraction of HMOs reduced UPEC‐mediated MAPK and NF‐κB activation. Collectively, we showed that HMOs protect the urinary tract from microbial infection, and may be a contributing mechanism underlying the epidemiological evidence of reduced UTI incidence in breast‐fed infants. Grant Funding Source : Canadian Institutes of Health Research (CIHR)
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 | 0.000 |
| 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".