Crosstalk within peripheral blood mononuclear cells mediates anti-inflammatory effects of n-3 PUFA-rich lipid emulsions in parenteral nutrition
Bibliographic record
Abstract
BACKGROUND AND AIMS: Parenteral nutrition (PN) rich in n-6 and n-3 long-chain fatty acids is used in clinical practice for nourishing patients who are unable to receive adequate nutrition through their digestive systems. In this study, we compare the effect on inflammation of the commonly used lipid emulsions Omegaven (n-3-rich) and Intralipid (n-6-rich) in human peripheral blood mononuclear cells (PBMCs). METHODS: PBMCs were treated with different doses of n-3-rich Omegaven and n-6-rich Intralipid and the immune cells were characterized by flow cytometry. RESULTS: We show that incubation of PBMCs with n-3-rich Omegaven leads to an increase in expression of CD1d and CD86 in CD14+monocytes. At the same time, an increased number of NKT cells expressing cytotoxic T cell antigen 4 is observed, suggesting immunological synapse formation. Both CD14+monocytes and NKT cells showed an increase in IL-10 production and a reduction in the pro-inflammatory cytokines IFN-γ, TNF-α, and IL-4, which led to an increase in the number of FOXP3+T regulatory cells. In addition, we show that n-3-rich Omegaven reduces the expression of TNFα, IFNγ and IL-4 in CD4+T and CD8+T cells independent of the presented interaction between CD14+monocytes and NKT cells. The described mechanism of n-3 rich lipid emulsions was confirmed in PBMCs from patients with inflammatory bowel disease but not in colorectal cancer patients which seem to lack the interaction between CD14+monocytes and NKT cells. CONCLUSIONS: These results show a mechanism for the beneficial effect of the n-3-rich Omegaven in patients with inflammatory conditions but questions its use in patients with cancer. Hence, our results may assist in choosing the best lipid emulsion for patients who require PN.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".