Normal saline resuscitation induces increased sinusoidal MIP‐2 expression in early sepsis
Bibliographic record
Abstract
Fluid resuscitation is an integral part of the treatment of patients with severe sepsis. Common fluids administered within the first 6 hours of diagnosis include normal saline and Ringer's lactate, however, currently there is no clear evidence that support the use of one resuscitation fluid over another. Previous work in our lab demonstrated that normal saline increases leukocyte‐endothelial cell interactions. The objective in this study was to determine the mechanisms for saline‐induced hepatic leukocyte recruitment. Sepsis was induced by cecal ligation and perforation in C57Bl/6 mice. Septic, sham‐operated or naïve mice received an IV bolus (20mL/kg) of Ringer's lactate or normal saline (0.9% NaCl). Six hours later the hepatic microcirculation was examined by confocal intravital microscopy to visualize the neutrophil chemokine macrophage inflammatory protein‐2 (MIP‐2) expression using an Alexafluor conjugated monoclonal antibody. MIP‐2 expression, as measured by mean fluorescent intensity, was significantly higher in the hepatic sinusoids of septic mice treated with normal saline compare to septic mice given Ringer's lactate. The use of normal saline as an intravenous resuscitation fluid was associated with increased chemokine expression in the both sinusoids and post‐sinusoidal venules. These data suggest that saline treatment in early sepsis augments neutrophil recruitment by increasing endothelial cell chemokine expression.
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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".