Lipid Emulsion Formulation of Parenteral Nutrition Affects Intestinal Microbiota and Host Responses in Neonatal Piglets
Bibliographic record
Abstract
BACKGROUND: Total parenteral nutrition (TPN) is a cause of intestinal microbial dysbiosis and impaired gut barrier function. This may contribute to life-threatening parenteral nutrition-associated liver disease and sepsis in infants. We compared the effects of a lipid emulsion containing long-chain ω-3 polyunsaturated fatty acids (PUFAs; SMOFlipid) and a predominantly ω-6 PUFA emulsion (Intralipid) on microbial composition and host response at the mucosal surface. MATERIALS AND METHODS: Neonatal piglets were provided isocaloric, isonitrogenous TPN for 14 days versus sow-fed (SF) controls. Equivalent lipid doses (10 g/kg/d) were given of either SMOFlipid (ML; n = 10) or Intralipid (SO; n = 9). Ileal segments and mucosal scrapings were used to characterize microbial composition by 16S rRNA gene sequencing and quantitative gene expression of tight junction proteins, mucins, antimicrobial peptides, and inflammatory cytokines. RESULTS: The microbial composition of TPN piglets differed from SF, while ML and SO differed from each other (analysis of molecular variance; P < .05); ML piglets were more similar to SF, as indicated by UniFrac distance ( P < .05). SO piglets showed a specific and dramatic increase in Parabacteroides ( P < .05), while ML showed an increase in Enterobacteriaceae ( P < .05). Gene expression of mucin, claudin 1, β-defensin 2, and interleukin 8 were higher in TPN; overall increases were significantly less in ML versus SO ( P < .05). CONCLUSION: The formulation of parenteral lipid is associated with differences in the gut microbiota and host response of TPN-fed neonatal piglets. Inclusion of ω-3 long-chain PUFAs appears to improve host-microbial interactions at the mucosal surface, although mechanisms are yet to be defined.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".