Effect of nitric oxide on capillary hemodynamics and cell injury in the pancreas during<i>Pseudomonas</i>pneumonia-induced sepsis
Bibliographic record
Abstract
Sepsis-induced nitric oxide (NO) overproduction has been implicated in a redistribution of flow from the pancreas making it vulnerable to ischemic injury in septic shock. To test this hypothesis in a remote injury model of normotensive sepsis, we induced Pseudomonas pneumonia in the rat and used intravital video microscopy (IVVM) of the pancreas to measure functional capillary density, capillary hemodynamics [red blood cell (RBC) velocity, lineal density, and supply rate], and lethal cellular damage (propidium iodine staining) at 6 and 24 h after the induction of pneumonia. With pneumonia, plasma nitrite/nitrate [NO2(-)/NO3(-)(NOx(-))] levels were doubled by 21 h (P < 0.05). To assess the effect of NO overproduction on microvascular perfusion, N6-(1-iminoethyl)-L-lysine (L-NIL) was administered to maintain NOx(-) levels at baseline. Pneumonia did cause a decrease in RBC velocity of 23% by 6 h, but by 24 h RBC velocity and supply rate had increased relative to sham by 22 and 38%, respectively (P < 0.05). L-NIL treatment demonstrated that this increase was due to NO overproduction. With pneumonia, there was no change in functional capillary density and only modest increases in cellular damage. We conclude that, in this normotensive pneumonia model of sepsis, NO overproduction was protective of microvascular perfusion in the pancreas.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".