Activation of human neutrophils by Esenbeckia leiocarpa: comparison between the crude hydroalcoholic extract (CHE) and an alkaloid (Alk) fraction
Bibliographic record
Abstract
Esenbeckia leiocarpa, a wide spread native Brazilian tree, was reported recently to possess anti-inflammatory effects in vivo, but the mechanisms involved are still not fully understood and its role in neutrophils is poorly documented. The aim of this study was to compare the effects of a crude hydroalcoholic extract (CHE) and an alkaloid-enriched (Alk) fraction obtained from Esenbeckia leiocarpa bark on human neutrophils by investigating the effect of each fraction alone or in a mixture with classical neutrophil agonists. CHE inhibited intracellular reactive oxygen species (ROS) production but increased the extracellular superoxide (O2-) production, while Alk increased the former and also slightly increased O2- production. We found that CHE and Alk also induced phagocytosis accompanied by Syk activation, adhesion and degranulation. However, neither CHE nor Alk potentiated the effect of classical neutrophil agonists, namely the cytokines GM-CSF for phagocytosis and TNF-α for adhesion or N-formyl-methionyl-leucyl-phenylalanine (fMLP) for degranulation. In addition, based on catalase treatment, CHE and Alk induced neutrophil apoptosis by a hydrogen peroxide (H2O2)-dependent mechanism. Since the elimination of apoptotic neutrophils by professional phagocytes is important for the resolution of inflammation, the ability of CHE and Alk to induce neutrophil apoptosis has to be considered as one possible mechanism associated with the anti-inflammatory activity of these fractions previously reported in vivo.
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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".