Gut microbiota and its diet‐related activity in children with intestinal failure receiving long‐term parenteral nutrition
Bibliographic record
Abstract
BACKGROUND: This study characterized gut microbiota and its diet-related activity in children with intestinal failure (IF) receiving parenteral nutrition (PN) compared with those of healthy controls (HC) and in relation to disease characteristics. METHODS: The fecal microbiota and short-chain fatty acids (SCFAs) were measured in 15 IF patients (n = 68) and 25 HC (n = 25). RESULTS: Patients with IF had a lower bacterial load (P = .003), diversity (P < .001), evenness (P < .001) and richness (P = 0.006) than HC. Patients with surgical IF had lower diversity (P < .039) than those with functional IF. Propionic acid and butyric acid (p < .001) were lower and d-lactate and l-lactate were higher (p < 0.001) in IF patients than in HC. The energy supplied by PN (%PN) was negatively associated with microbiota diversity and SCFA profile. IF patients had more Escherichia-Shigella (P = .006), Cronobacter (P = .001), and Staphylococcus (Operational Taxonomic Unit 14, P < .001) and less Faecalibacterium (P < 0.001) and Ruminococcus 1 and 2 (P < .001). Duration of PN (P = .005), %PN (P = .005), and fiber intake (P = .011) were predictive of microbiota structure. Higher intake of enteral nutrition was associated with microbiota structure and function closer to those of HC. CONCLUSIONS: Microbiota composition and its diet-related function are altered in IF, with depletion of beneficial SCFAs and species and supraphysiological increase of potentially harmful pathobionts. The influence of this compositional and functional microbial dysbiosis on patients' outcomes and management warrants further exploration.
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 | 0.001 |
| 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".