Microbiome changes under enteral deprivation are dynamic and dependent on intestinal location
Bibliographic record
Abstract
BACKGROUND: The microbiome has a pivotal role in intestinal health, and nutrition has a major role shaping its structure. Enteral deprivation, in which no oral/enteral nutrition is administered, is common in hospitalized/gastrointestinal patients. The dynamics that enteral deprivation exerts on the microbial community, specifically in the small intestine, are not well understood. METHODS: Enteral deprivation was modeled with exclusive parenteral nutrition (EPN) mice. Mice were allocated to receive either EPN or saline and chow (control) and euthanized after 0, 2, 4, or 6 days. DNA was extracted from jejunum, ileum, and colon content. 16S sequencing was used to compare changes in microbial communities between groups. Functional pathways were predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States. RESULTS: EPN-treated mice showed community changes throughout the intestine. Beta diversity in colon showed clear separation between the groups (Bray-Curtis, P < 0.001). Time-dependent dynamics were seen in ileal but not jejunal samples. Alpha diversity was lower in the colon of EPN mice compared with control/baseline mice (Chao1, P < 0.01) but not in ileum/jejunum. Progressive loss of single-taxon domination was seen, most notably in the small intestine. This was accompanied by increases/decreases in specific taxa. A clear separation was seen in the functional capacity of the community between fed and enterally deprived mice at the ileum and colon, which was observed early on. CONCLUSIONS: Enteral deprivation disturbs the microbial community in a spatial and dynamic manner. There should be further focus on studying the effect of these changes on the host.
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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) | 0.000 | 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".