Decreased Systemic Polymorphonuclear Neutrophil (PMN) Rolling Without Increased PMN Adhesion in Peritonitis at Remote Sites
Bibliographic record
Abstract
BACKGROUND: Previous in vitro studies have demonstrated that the host response to intra-abdominal infection produces increased generalized polymorphonuclear neutrophil (PMN) adherence to vascular endothelial cells (ECs), which may lead to subsequent endothelial damage, leaky capillaries, and organ dysfunction. There are scant data to demonstrate this enhanced systemic PMN adherence in vivo or the influence of PMN rolling on PMN endothelial adherence. HYPOTHESIS: Systemic PMN adherence in the animal with sepsis is increased. DESIGN: In vivo murine model of a 2-front infection using intravital microscopy of the cremasteric muscle to quantify PMN-EC adherence in a septic response. SETTING: Basic science laboratory and animal surgical facility. PATIENTS OR OTHER PARTICIPANTS: One hundred CD1 male mice. INTERVENTIONS: Animals underwent cecal ligation and puncture peritonitis, cremasteric muscle Escherichia coli infection, both infections, or neither (controls). Eighteen hours later, the mice underwent exteriorization of the cremasteric muscle under an intravital microscope for measurement of PMN-EC interactions. Blood was then drawn for calculation of circulating PMN counts. MAIN OUTCOME MEASURES: Adherence of PMNs, PMN rolling flux, PMN rolling velocity, and circulating PMN counts. RESULTS: Circulatory mechanics did not differ between the groups. Unlike static in vitro systems, we could not detect an increase in PMN adherence after peritonitis with this dynamic in vivo model. A local (cremasteric) infection was associated with marked PMN adherence. Peritonitis was associated with reduced PMN adherence at a local infection site as well as reduced rolling adhesion and PMN rolling velocity. CONCLUSIONS: The data suggest that intra-abdominal infection does not increase remote PMN adherence, and may actually result in reduction of systemic adherence via modulation of PMN rolling.
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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 | 0.001 | 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) | 0.002 | 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".