Lipopolysaccharide modulates neutrophil recruitment and macrophage polarization on lymphatic vessels and impairs lymphatic function in rat mesentery
Bibliographic record
Abstract
Impairment of the lymphatic system is apparent in multiple inflammatory pathologies connected to elevated endotoxins such as LPS. However, the direct mechanisms by which LPS influences the lymphatic contractility are not well understood. We hypothesized that a dynamic modulation of innate immune cell populations in mesentery under inflammatory conditions perturbs tissue cytokine/chemokine homeostasis and subsequently influences lymphatic function. We used rats that were intraperitoneally injected with LPS (10 mg/kg) to determine the changes in the profiles of innate immune cells in the mesentery and in the stretch-mediated contractile responses of isolated lymphatic preparations. Results demonstrated a reduction in the phasic contractile activity of mesenteric lymphatic vessels from LPS-injected rats and a severe impairment of lymphatic pump function and flow. There was a significant reduction in the number of neutrophils and an increase in monocytes/macrophages present on the lymphatic vessels and in the clear mesentery of the LPS group. This population of monocytes and macrophages established a robust M2 phenotype, with the majority showing high expression of CD163 and CD206. Several cytokines and chemoattractants for neutrophils and macrophages were significantly changed in the mesentery of LPS-injected rats. Treatment of lymphatic muscle cells (LMCs) with LPS showed significant changes in the expression of adhesion molecules, VCAM1, ICAM1, CXCR2, and galectin-9. LPS-TLR4-mediated regulation of pAKT, pERK pI-κB, and pMLC20 in LMCs promoted both contractile and inflammatory pathways. Thus, our data provide the first evidence connecting the dynamic changes in innate immune cells on or near the lymphatics and complex cytokine milieu during inflammation with lymphatic dysfunction.
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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".