Bibliographic record
Abstract
The monoclonal antibody PL/IM430 has previously been reported to uncouple Ca(2+) transport from ATP hydrolysis in platelet membranes (Hack, N., Wilkinson, J. M., and Crawford, N. (1988) Biochem. J. 250, 355-361). More recently, we have demonstrated that this antibody is specific for human SERCA3 (Poch, E., Leach, S., Snape, S., Cacic, T., MacLennan, D. H., and Lytton, J. (1998) Am. J. Physiol. 275, C1449-C1458). In this paper, we have extended the analysis of the PL/IM430-SERCA3 interaction. Using HEK293 cells to express human SERCA3a, we were able to measure both ATP-mediated, oxalate-dependent (45)Ca(2+) uptake and Ca(2+)-dependent ATP hydrolysis activities due exclusively to SERCA3. Treatment with PL/IM430 inhibited both activities almost identically, with a maximal inhibition of 81 and 73% and a half-maximal concentration of 8.3 and 5.9 microg/ml, for Ca(2+) uptake and ATP hydrolysis, respectively. We conclude that PL/IM430 does inhibit SERCA3 activity but does not uncouple Ca(2+) transport from ATP hydrolysis. Using a combination of partial proteolysis, GST fusion protein expression, and mutation of residues that differ between rat and human SERCA3, we have identified human SERCA3 amino acids Pro(8) and Glu(192) as essential to forming the PL/IM430 epitope. PL/IM430 thus recognizes a linearly noncontiguous set of amino acids within the actuator domain of human SERCA3. We propose that PL/IM430 inhibits SERCA3 activity by sterically preventing movement of the actuator domain into a catalytically critical position in the E2 conformation of the enzyme.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".