Effects of Cotinus coggygria extract on human blood T and NK cells activity in vitro
Bibliographic record
Abstract
It is an important research area to define the bioactivities of plant fractions and to create appropriate utilization areas for them. Although Cotinus coggygria, which is widely used in folk medicine, which grows from Europe to the center of China, has a wide variety of bioactivities, there is limited information about its influence on the immune system.The anti-proliferative effects of Cotinus coggygria extract on stimulated peripheral blood mononuclear cells (PBMC) were determined by CFSE dilution method. The effects of the extract on peripheral blood T and natural killer (NK) cells were followed by their proliferative responses. Annexin V / PI staining method was used to evaluate the apoptotic effects of the extract on PBMCs. The effects of the extracts on expression levels of IL-1?, IL-2, IL-4 and IL-10 genes were investigated.Effect of Cotinus coggygria on the proliferation of T cells and NK cell subsets were decreased in a dose dependent manner. Anti-proliferative effect of Cotinus coggygria extract on stimulated PBMCs was not directly related to its apoptotic properties, it also changes the cytokine genes expression on PBMCs. Our study suggests that Cotinus coggygria methanol extract, whose anti-inflammatory effects have not been investigated yet, may be a pioneer in the identification of new molecules with anti-inflammatory properties and the development of related therapies.
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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) | 0.002 | 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".