Endotoxin free hyaluronan and hyaluronan fragments do not stimulate TNF-α, interleukin-12 or upregulate co-stimulatory molecules in dendritic cells or macrophages
Bibliographic record
Abstract
The extracellular matrix glycosaminoglycan, hyaluronan, has been described as a regulator of tissue inflammation, with hyaluronan fragments reported to stimulate innate immune cells. High molecular mass hyaluronan is normally present in tissues, but upon inflammation lower molecular mass fragments are generated. It is unclear if these hyaluronan fragments induce an inflammatory response or are a consequence of inflammation. In this study, mouse bone marrow derived macrophages and dendritic cells (DCs) were stimulated with various sizes of hyaluronan from different sources, fragmented hyaluronan, hyaluronidases and heavy chain modified-hyaluronan (HA-HC). Key pro-inflammatory molecules, tumour necrosis factor alpha, interleukin-1 beta, interleukin-12, CCL3, and the co-stimulatory molecules, CD40 and CD86 were measured. Only human umbilical cord hyaluronan, bovine testes and Streptomyces hyaluronlyticus hyaluronidase stimulated macrophages and DCs, however, these reagents were found to be contaminated with endotoxin, which was not fully removed by polymyxin B treatment. In contrast, pharmaceutical grade hyaluronan and hyaluronan fragments failed to stimulate in vitro-derived or ex vivo macrophages and DCs, and did not induce leukocyte recruitment after intratracheal instillation into mouse lungs. Hence, endotoxin-free pharmaceutical grade hyaluronan does not stimulate macrophages and DCs in our inflammatory models. These results emphasize the importance of ensuring hyaluronan preparations are endotoxin free.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".