Polycystin-2 Expression Is Regulated by a PC2-binding Domain in the Intracellular Portion of Fibrocystin
Bibliographic record
Abstract
Autosomal dominant (ADPKD) and autosomal recessive (ARPKD) polycystic kidney disease are caused by mutations in Pkd1/Pkd2 and Pkhd1, which encode polycystins (PCs) and fibrocystin/polyductin (FPC). Our recent study reported that a deficiency in FPC increases the severity of cystic disease in Pkd2 mutants and down-regulates PC2 in vivo, but the precise molecular mechanism of these effects is unknown (Kim, I., Fu, Y., Hui, K., Moeckel, G., Mai, W., Li, C., Liang, D., Zhao, P., Ma, J., Chen, X.-Z., George, A. L., Jr., Coffey, R. J., Feng, Z. P., and Wu, G. (2008) J. Am. Soc. Nephrol. 19, 455-468). In this study, through the use of deletion and mutagenesis strategies, we identified a PC2-binding domain in the intracellular C terminus of FPC and an FPC-binding domain in the intracellular N terminus of PC2. These binding domains provide a molecular basis for the physical interaction between PC2 and FPC. In addition, we also found that physical interaction between the binding domains of PC2 and FPC is able to prevent down-regulation of PC2 induced by loss of FPC. In vivo, we generated a mouse model of ADPKD with hypomorphic Pkd2 alleles (Pkd2nf3/nf3) and show that PC2 down-regulation is accompanied by a phenotype similar to that of Pkhd1(-/-) mice. These findings demonstrate a common mechanism underlying cystogenesis in ADPKD and ARPKD and provide insight into the molecular relationship between PC2 and FPC.
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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".