Lipopolysaccharide reduces intercellular coupling in vitro and arteriolar conducted response in vivo
Bibliographic record
Abstract
Our recent in vitro study (Lidington et al. J Cell Physiol 185: 117-125, 2000) suggested that lipopolysaccharide (LPS) reduces communication along blood vessels. The present investigation extended this study to determine whether any effect of LPS and/or inflammatory cytokines [tumor necrosis factor-alpha, interleukin (IL)-1beta, and IL-6] on endothelial cell coupling in vitro could also be demonstrated for an arteriolar conducted response in vivo. Using an electrophysiological approach in monolayers of microvascular endothelial cells, we found that LPS (10 microg/ml) but not these cytokines reduced intercellular conductance (c(i)) (an index of cell communication) and that LPS together with these cytokines did not further reduce c(i). Also, c(i) was restored after LPS washout, and the LPS-induced reduction was prevented by protein tyrosine kinase (PTK) inhibitors (1.5 microM Tyr A9 and 10 nM PP-2). In our in vivo experiments in arterioles of the mouse cremaster muscle, local electrical stimulation evoked vasoconstriction that conducted along arterioles. LPS in the muscle superfusate did not alter local vasoconstriction but reduced the conducted response. Washout of LPS restored the conducted response, whereas PTK inhibitors prevented the effect of LPS. On the basis of a newly developed mathematical model, the LPS-induced reduction in conducted response was predicted to reduce the arteriolar ability to increase resistance to blood flow. We conclude that LPS can reduce communication in in vitro and in vivo systems comparably in a reversible and tyrosine kinase-dependent manner. Based on literature and present results, we suggest that LPS may compromise microvascular hemodynamics at both the arteriolar responsiveness and the conduction levels.
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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) | 0.000 | 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) | 0.002 | 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".