Inonotus obliquus attenuates histamine-induced microvascular inflammation
Bibliographic record
Abstract
Cell-to-cell communication is a key element of microvascular blood flow control, including rapidly carrying signals through the vascular endothelium in response to local stimuli. This cell-to-cell communication is negatively impacted during inflammation through the disruption of junctional integrity. Such disruption is associated with promoting the onset of cardiovascular diseases as a result of altered microvascular blood flow regulation. Therefore, understanding the mechanisms how inflammation drives microvascular dysfunction and compounds that mitigate such inflammation and dysfunction are of great interest for development. As such we aimed to investigate extracts of mushrooms as potential novel compounds. Using intravital microscopy, the medicinal mushroom, Inonotus obliquus was observed, to attenuate histamine-induced inflammation conducted vasodilation in second-order arterioles in the gluteus maximus muscle of C57BL/6 mice. Mast cell activation by C48/80 similarly disrupted endothelial junctions and conducted vasodilation but only histamine was blocked by the histamine antagonist, pyrilamine not C48/80 suggesting the importance of mast cell activation. Data presented here supports that histamine induced inflammation is a major disruptor of junctional integrity, and highlights the important anti-inflammatory properties of Inonotus obliquus focusing future assessment of mast cells as putative target for Inonotus obliquus.
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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".