Endotoxin and cytokine released during parenteral nutrition
Bibliographic record
Abstract
BACKGROUND: Apart from its benefits, parenteral nutrition (PN)-related complications have been reported. Studies have shown that PN could alter cytochrome P450 (CYP) activity. One of the possible mechanisms is through cytokine and nitrite release, which is triggered by endotoxin. The purpose of this study is to investigate the potential release of endotoxin, cytokines, and nitrite during PN. METHODS: Rats were randomly assigned into either (a) the PN group, which received continuous PN infusion only; or (b) the control group, which received normal chow with saline infusion. The infusions were administered continuously for 7 days, and then blood was collected and microsomes were prepared from the excised livers. RESULTS: Endotoxin levels in the PN group were significantly higher in portal vein but not in inferior vena cava when compared with those of the controls. TNF-alpha and IL-6 levels were significantly higher in the PN group (p < .05). However, IL-1 beta levels were not significantly different in the 2 groups (p > .05). The nitrite levels, the end product of nitric oxide formation, were found to be almost 2 times higher after PN (p < .05). CONCLUSIONS: It is confirmed that a 7-day infusion treatment of PN in rat may be linked to bacterial translocation, which leads to increased levels of endotoxin. This increase could trigger cytokine release, which could down regulate CYP activities.
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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".