Regulatory mechanisms in lymphatic vessel contraction under normal and inflammatory conditions
Bibliographic record
Abstract
The lymphatic system is composed of a dense network of lymphatic vessels, which are critical components of physiological interstitial fluid transport. These vessels possess intrinsic contractile properties providing the driving force for the fluid to be drained away from the tissues and propelled, as lymph, back into the bloodstream. Lymphatic pumping is also important to carry immune cells, bacteria, macromolecules, viruses and their products to and through lymph nodes, the other component of the lymphatic system, to initiate the adaptive immune response. In addition, among the many circulating mediators known to modulate lymphatic contractile activity and thus lymph flow, mediators of inflammation have potent excitatory or inhibitory actions. The involvement of lymphatic vessels in edema resolution, immune cell trafficking and their sensitivity to inflammatory mediators make them pivotal players of the inflammation process. The ability of lymphatic vessels to generate and regulate lymph flow is provided by the lymphatic muscle present in the vessels' wall. Although molecular studies investigating the mechanisms of lymphatic vessel contraction are still very limited, recent findings suggest that lymphatic pumping requires complicated muscle activities that have similarities to those seen in both the heart (striated muscle) and blood vessels (smooth muscle). This review article focuses on presenting and discussing the mechanisms that regulate lymphatic vessel contraction under normal and pathophysiological states, specifically pertaining to inflammatory conditions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".