Role of LPS-induced microfilament depolymerization in MIP-2 production from rat pneumocytes
Bibliographic record
Abstract
We have previously demonstrated that lipopolysaccharide (LPS) induces production of macrophage inflammatory protein-2 (MIP-2), a C-X-C chemokine for neutrophil recruitment and activation, in primary cultured rat lung alveolar epithelial cells. We have also demonstrated that LPS depolymerizes microfilaments in rat alveolar epithelial cells. To determine whether the polymerization status of microfilaments affects LPS-induced MIP-2 production, we treated rat alveolar epithelial cells with cytochalasin D (CytoD), a microfilament-disrupting agent, before and during LPS stimulation. A lower concentration (0.1 microM) of CytoD inhibited LPS-induced MIP-2 production without affecting microfilament polymerization. In contrast, LPS-induced MIP-2 production was enhanced by a higher concentration (10 microM) of CytoD, which disrupted the filamentous structure of actin. Jasplakinolide (1 nM to 1 microM), a polymerizing agent for microfilaments, decreased LPS-induced MIP-2 secretion. Jasplakinolide (1 microM) also blocked LPS-induced depolymerization of microfilaments. These results suggest that, in alveolar epithelial cells, LPS-induced MIP-2 production is at least partially regulated by microfilament depolymerization.
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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 | 0.000 |
| 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".