Enteral feeding decreases gut apoptosis, permeability, and lung inflammation during murine endotoxemia
Bibliographic record
Abstract
We tested the hypothesis that endotoxemia and fasting are associated with increased gut apoptotic activity, gut permeability, and inflammation in a distant organ. Fed or fasted CD-1 mice were studied 6 h after intraperitoneal injection of either saline (sham) or endotoxin (4 mg/kg of 0111:B4 Escherichia coli lipopolysaccharide). We found that endotoxin increased gut caspase-3 and -6 activity by 4.9 +/- 0.6- and 4.5 +/- 0.5-fold, respectively (P < 0.001), and increased terminal deoxynucleotidyltransferase-mediated dUTP nick-end labeling (TUNEL) staining of mucosal cells (P < 0.05). Feeding decreased caspase-3 activity by 40% (P < 0.05) and decreased endotoxin-induced TUNEL staining (P < 0.05). Endotoxin increased gut poly(ADP-ribose) polymerase activity by 15% (P < 0.05). Endotoxin increased gut permeability by 44% (P < 0.05), an effect reduced 36% by feeding (P < 0.05). Similarly, endotoxin increased pulmonary neutrophil infiltration (6.0 +/- 1.0-fold, P < 0.001) and increased lung interleukin (IL)-6 (5.9 +/- 0.1-fold, P < 0.001) and macrophage inflammatory protein (MIP)-2 expression (290 +/- 40-fold, P < 0.001), whereas feeding decreased this effect by 43% for neutrophils, 40% for IL-6 (P < 0.05), and 35% for MIP-2 (P < 0.05). Thus endotoxin increases gut apoptotic activity, gut permeability, and pulmonary inflammation. Enteral feeding may decrease the distant organ inflammation by reducing gut apoptosis, thereby maintaining gut mucosal function during endotoxemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".