Geldanamycin-Induced Phosphatidylserine Translocation in the Erythrocyte Membrane
Bibliographic record
Abstract
BACKGROUND/AIMS: Geldanamycin, a benzoquinone ansamycin antibiotic, and its analogues induce apoptosis of tumor cells and are thus considered for the treatment of cancer. Similar to apoptosis of nucleated cells, erythrocytes may enter eryptosis, the suicidal erythrocyte death characterized by cell shrinkage and by cell membrane scrambling with phosphatidylserine-exposure at the erythrocyte surface. Triggers of eryptosis include increase of cytosolic Ca(2+)-concentration ([Ca(2+)]i) and formation of ceramide. The present study explored, whether geldanamycin modifies [Ca(2+)]i, ceramide formation, cell volume and phosphatidylserine abundance at the erythrocyte surface. METHODS: Erythrocyte volume was estimated from forward scatter, phosphatidylserine-abundance from annexin V binding, hemolysis from hemoglobin release, ceramide formation from binding of fluorescent antibodies and [Ca(2+)]i from Fluo3-fluorescence. RESULTS: A 48 hours exposure to geldanamycin significantly decreased forward scatter (≥ 5 µM), significantly increased annexin-V-binding (≥ 25 µM), but did not significantly modify Fluo3-fluorescence (up to 50 µM). The annexin-V-binding following geldanamycin treatment was not significantly modified by removal of extracellular Ca(2+) but was paralleled by significantly increased ceramide formation (50 µM). CONCLUSIONS: Geldanamycin stinulated eryptosis, an effect at least partially due to ceramide formation.
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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".