Hyaluronan promotes intracellular ROS production and apoptosis in TNFα-stimulated neutrophils
Bibliographic record
Abstract
Background: Hyaluronan (HA) is an important structural component of the extracellular matrix and has well-described roles in maintaining tissue integrity and homeostasis. With inflammation, HA metabolism (synthesis and degradation) increases and results in higher concentrations of soluble HA. Previously, we demonstrated that (soluble) HA primed resting neutrophils for the oxidative burst in response to a secondary stimulus. Notably, HA-mediated priming was not dependent on degranulation, which is a hallmark of priming by classical agents such as TNFα. In this study, we queried the ability of HA to prime neutrophils to different stimuli and its capacity to modulate neutrophil function in the presence of TNFα. Methods: with HA in the absence and presence of classic neutrophil agonists, inclusive of TNFα. Western blotting was used to assess the activation (phosphorylation) of p38 MAPK, and key neutrophil functions associated with priming and activation, such as intracellular and extracellular ROS production, degranulation, and apoptosis, were evaluated by standard chemiluminescence assays (ROS) and flow cytometry. Results: Hyaluronan is capable of atypical priming and, with TNFα, co-priming neutrophils for an enhanced (rate and/or magnitude) oxidative burst to various secondary stimuli. In addition, HA can augment intracellular ROS production that is directly induced by TNFα in resting neutrophils, which coincided with the activation of p38 MAPK and apoptosis. Conclusions: These data demonstrate that the extracellular matrix component HA is a key modulator of neutrophil function(s) in the presence of inflammatory agents such as TNFα. Moreover, it provides additional evidence for the diversity and complexity of neutrophil priming and activation during inflammation.
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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".