Accelerated apoptotic death and in vivo turnover of erythrocytes in mice lacking functional mitogen- and stress-activated kinase MSK1/2
Bibliographic record
Abstract
The mitogen- and stress-activated kinase MSK1/2 plays a decisive role in apoptosis. In analogy to apoptosis of nucleated cells, suicidal erythrocyte death called eryptosis is characterized by cell shrinkage and cell membrane scrambling leading to phosphatidylserine (PS) externalization. Here, we explored whether MSK1/2 participates in the regulation of eryptosis. To this end, erythrocytes were isolated from mice lacking functional MSK1/2 (msk(-/-)) and corresponding wild-type mice (msk(+/+)). Blood count, hematocrit, hemoglobin concentration and mean erythrocyte volume were similar in both msk(-/-) and msk(+/+) mice, but reticulocyte count was significantly increased in msk(-/-) mice. Cell membrane PS exposure was similar in untreated msk(-/-) and msk(+/+) erythrocytes, but was enhanced by pathophysiological cell stressors ex vivo such as hyperosmotic shock or energy depletion to significantly higher levels in msk(-/-) erythrocytes than in msk(+/+) erythrocytes. Cell shrinkage following hyperosmotic shock and energy depletion, as well as hemolysis following decrease of extracellular osmolarity was more pronounced in msk(-/-) erythrocytes. The in vivo clearance of autologously-infused CFSE-labeled erythrocytes from circulating blood was faster in msk(-/-) mice. The spleens from msk(-/-) mice contained a significantly greater number of PS-exposing erythrocytes than spleens from msk(+/+) mice. The present observations point to accelerated eryptosis and subsequent clearance of erythrocytes leading to enhanced erythrocyte turnover in MSK1/2-deficient mice.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".