Disruption of erythroid K-Cl cotransporters alters erythrocyte volume and partially rescues erythrocyte dehydration in SAD mice
Bibliographic record
Abstract
K-Cl cotransport activity in rbc is a major determinant of rbc volume and density. Pathologic activation of erythroid K-Cl cotransport activity in sickle cell disease contributes to rbc dehydration and cell sickling. To address the roles of individual K-Cl cotransporter isoforms in rbc volume homeostasis, we disrupted the Kcc1 and Kcc3 genes in mice. As rbc K-Cl cotransport activity was undiminished in Kcc1(-/-) mice, decreased in Kcc3(-/-) mice, and almost completely abolished in mice lacking both isoforms, we conclude that K-Cl cotransport activity of mouse rbc is mediated largely by KCC3. Whereas rbc of either Kcc1(-/-) or Kcc3(-/-) mice were of normal density, rbc of Kcc1(-/-)Kcc3(-/-) mice exhibited defective volume regulation, including increased mean corpuscular volume, decreased density, and increased susceptibility to osmotic lysis. K-Cl cotransport activity was increased in rbc of SAD mice, which are transgenic for a hypersickling human hemoglobin S variant. Kcc1(-/-)Kcc3(-/-) SAD rbc lacked nearly all K-Cl cotransport activity and exhibited normalized values of mean corpuscular volume, corpuscular hemoglobin concentration mean, and K(+) content. Although disruption of K-Cl cotransport rescued the dehydration phenotype of most SAD rbc, the proportion of the densest red blood cell population remained unaffected.
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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) | 0.002 | 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".