Polycystin-1 Inhibits Cell Proliferation through Phosphatase PP2A/B56<i>α</i>
Bibliographic record
Abstract
Autosomal<?tex id="Q1" staff-cmt="It is very important for the corresponding author to have a linked ORCID (Open Researcher and Contributor ID) account on MTS. To register a linked ORCID account, <?tlsb -.1pt>please go to the Account Update page ( http://mts.hindawi.com/update/ ) in our Manuscript Tracking System and after you have logged in click on the ORCID link at the top of the page. This link will take you to the ORCID website where you will be able to create an account for yourself. Once you have done so, your new ORCID will be saved in our Manuscript Tracking System automatically."?> dominant polycystic kidney disease (ADPKD) is associated with a number of cellular defects such as hyperproliferation, apoptosis, and dedifferentiation. Mutations in polycystin-1 (PC1) account for ∼85% of ADPKD. Here, we showed that wild-type (WT) or mutant PC1 composed of the last five transmembrane (TM) domains and the C-terminus (termed PC1-5TMC) inhibits cell proliferation and protein translation, as well as the downstream effectors of mTOR, consistent with previous reports. Knockdown of B56α, a subunit of the protein phosphatase 2A (PP2A) complex, or application of PP2A inhibitor okadaic acid or calyculin A, abolished the inhibitory effect of PC1 and PC1-5TMC on proliferation, indicating that PP2A/B56α mediates the regulation of cell proliferation by PC1. In addition to the phosphorylated S6 and 4EBP1, B56α was also downregulated by PC1 and PC1-5TMC. Furthermore, the downregulation of B56α, which may be mediated by mTOR but not AKT, can account for the dependence of PC1-inhibited proliferation on PP2A.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".