Structural characterization of mixed wt/mutant aquaporin‐2 tetramers using dual‐colored fluorescent subunit counting (1133.1)
Bibliographic record
Abstract
Mutations in Aquaporin‐2 (AQP2) induce nephrogenic diabetes insipidus, a water reabsorption defect of the kidney. Using co‐immunoprecipitation and functional assays, we have recently shown that (at least) some mild recessive (rec) AQP2 mutants can adequately associate to its wild‐type (wt) counterpart to generate fully functional wt/rec heterotetramers. To better characterize actual subunit distributions within wt/rec AQP2 populations, we have developed a dual‐colored fluorescent subunit counting approach in TIRF condition, in order to identify and quantify individual monomers through bleaching of linked fluorophores. Assays performed on both Xenopus oocyte and transfected cell line have confirmed that mild mutations (K228E, D150E and V24A), similar to wt‐AQP2, adequately oligomerize in tetramer, unlike the severe R187C mutant which only displays monomeric structures. In dual transfections (sfGFP‐wt‐AQP2 + RFP‐rec‐AQP2), we also confirm the presence of mixed wt/rec tetramers for mild mutations, but not with R187C, which remains monomeric. Ultimately, we aim at describing subunit distributions within wt/rec tetramers in order to evaluate the properties, limitations and functional outcome of such heteromeric associations.
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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".