Polycystin‐2 cation channel function in the human syncytiotrophoblast is regulated by microtubular structures
Bibliographic record
Abstract
Polycystin-2 (PC2), encoded by PKD2, which is one of the genes whose mutations cause polycystic kidney disease, is abundantly produced in the apical domain of the syncytiotrophoblast (hST) of term human placenta. PC2, a TRP-type (TRPP2) non-selective cation channel, is present in primary cilia of renal epithelial cells, a microtubule-based ancillary structure with sensory function. The hST has abundant cytoskeletal structures, and actin filament dynamics regulate PC2 channel function in this epithelium. However, it is expected that the apical hST excludes microtubular structures. Here, we demonstrated by Western blot and immunocytochemical analyses that hST apical vesicles indeed contain microtubule structural components, including tubulin isoforms, acetylated alpha-tubulin, and the kinesin motor proteins KIF3A and KIF3B. PC2 and tubulin were substantially colocalized in hST vesicles. Treatment of hST vesicles with either the microtubular disrupter colchicine (15 microM) or the microtubular stabilizer paclitaxel (taxol, 15 microM) resulted in distinct patterns of microtubular re-organization and PC2 redistribution. We also observed that changes in microtubular dynamics regulate PC2 channel function. Addition of colchicine rapidly inhibited PC2 channel activity in lipid-bilayer reconstituted hST membranes. Addition of either tubulin and GTP, or taxol, however, stimulated PC2 channel activity in control hST membranes. Interestingly, we found that the kinesin motor protein KIF3A was capable of increasing PC2 channel activity in hST. We believe that the data are the first to provide a direct demonstration of a microtubular interaction with PC2 in the hST. This interaction thus plays an important regulatory role in the control of ion transport in the human placenta.
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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) | 0.000 | 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".