Molecular origin of Na+/Li+ exchanger: Evidence against the involvement of major cloned erythrocyte transporters
Bibliographic record
Abstract
Numerous studies have demonstrated heightened Na(+)/Li(+) countertransport (NLCT) activity in erythrocytes of patients with essential hypertension or diabetic nephropathy. The same carrier also contributes to the therapeutic action of lithium salt, widely used in the treatment of psychiatric disorders. However, the molecular origin of NLCT remains unknown. This study examined the role of major ion transporters in NLCT by comparative analysis of its activity and that of ion transporters providing inwardly directed (86)Rb, (22)Na and (32)P fluxes. NLCT was below the detection limit in rat erythrocytes and ∼50-fold higher in rabbits compared to humans. Unlike NLCT, the activities of Na(+),K(+)-ATPase, Na(+),K(+),2Cl(-) cotransporter and anion exchanger were somewhat similar in the erythrocytes of these species, whereas Na(+),P(i) cotransport was in 1:2:6 proportion in rats, humans and rabbits, respectively. Loading of erythrocytes with Li(+) for NLCT measurement did not affect the activity of Na(+),P(i) cotransporter. Keeping in mind that NLCT is much higher in rabbits vs humans and rats, we compared the set of membrane proteins in these species using 2-dimensional gel electrophoresis. This approach revealed 174 common spots, whereas 132 proteins were detected only in human and rabbit erythrocyte membranes. Among these proteins, we found 17 spots whose expression was higher by more than 5-fold in rabbit compared to human erythrocytes. Thus, our results argue against the involvement of major ion transporters in NLCT. They also show that comparative proteomics is a potent tool to identify the molecular origin of this carrier.
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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".