Generation of Lymphocytic Microparticles and Detection of their Proapoptotic Effect on Airway Epithelial Cells
Bibliographic record
Abstract
Interest in the biological roles of cell membrane-derived vesicles in cell-cell communication has increased in recent years. Microparticles (MPs) are one such type of vesicles, ranging in diameter from 0.1 μm to 1 μm, and typically shed from the plasma membrane of eukaryotic cells undergoing activation or apoptosis. Here we describe the generation of T lymphocyte-derived microparticles (LMPs) from apoptotic CEM T cells stimulated with actinomycin D. LMPs are isolated through a multistep differential centrifugation process and characterized using flow cytometry. This protocol also presents an in situ cell death detection method for demonstrating the proapoptotic effect of LMPs on bronchial epithelial cells derived from mouse primary respiratory bronchial tissue explants. Methods described herein provide a reproducible procedure for isolating abundant quantities of LMPs from apoptotic lymphocytes in vitro. LMPs derived in this manner can be used to evaluate the characteristics of various disease models, and for pharmacology and toxicology testing. Given that the airway epithelium offers a protective physical and functional barrier between the external environment and underlying tissue, use of bronchial tissue explants rather than immortalized epithelial cell lines provides an effective model for investigations requiring airway tract tissue.
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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".