Rosmarinic Acid Induces p56 <i>lck</i> -Dependent Apoptosis in Jurkat and Peripheral T Cells via Mitochondrial Pathway Independent from Fas/Fas Ligand Interaction
Bibliographic record
Abstract
Apoptosis is one way of controlling immune responses, and a variety of immunosuppressive drugs suppress harmful immune responses by inducing apoptosis of lymphocytes. In this study we observed that rosmarinic acid, a secondary metabolite of herbal plants, induced apoptosis in an p56(lck) (Lck)-dependent manner; Lck(+) Jurkat T cells undergo apoptosis in response to rosmarinic acid (RosA) treatment, whereas Lck(-) Jurkat subclone J.CaM1.6 cells do not. J.CaM1.6 cells with various Lck mutants indicated that Lck SH2 domain, but not Lck kinase activity, was required for RosA-induced apoptosis. RosA induced apoptosis in the absence of a TCR stimulus, and this was not prevented by interruption of the Fas/Fas ligand interaction. Instead, RosA-mediated apoptosis involved a mitochondrial pathway as indicated by cytochrome c release and the complete blockage of apoptosis by an inhibitor of mitochondrial membrane depolarization. Both caspase-3 and -8 were indispensable in RosA-induced apoptosis and work downstream of mitochondria and caspase-9 in the order of caspase-9/caspase-3/caspase-8. In freshly isolated human PBMC, RosA specifically induced apoptosis of Lck(+) subsets such as T and NK cells, but not Lck-deficient cells, including B cells and monocytes. Moreover, RosA's ability to kill T and NK cells was restricted to actively proliferating cells, but not to resting cells. In conclusion, Lck-dependent apoptotic activity may make RosA an attractive therapeutic tool for the treatment of diseases in which T cell apoptosis is beneficial.
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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) | 0.002 | 0.001 |
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".