ER stress inducing agents that cause induction of TDAG51 and epithelial adhesion disruption result in epithelial to mesenchymal transition via β‐catenin signaling
Bibliographic record
Abstract
Epithelial to mesenchymal transition (EMT) is a process through which endoplasmic reticulum (ER) stress may mediate the progression of chronic kidney disease. Thapsigargin (Tg) induced ER stress produced an EMT response in two human renal proximal tubular epithelial cell (hRPTEC) lines, HK-2 and primary hRPTEC. We hypothesized that changes in cell shape induced by Tg were mediated by TDAG51 upregulation, resulting in an EMT response through β-catenin signaling. Tg caused shape change as shown by F-actin cytoskeletal rearrangement. This was accompanied by ER stress induction, TDAG51 upregulation and β-catenin cytoplasmic and nuclear translocation. Transfection of TDAG51-GFP plasmid into HK-2 cells caused shape change and cytoskeletal rearrangement compared to eGFP controls. Scratch assays showed β-catenin signaling augmented EMT induced by TGFβ1. Cells on the scratch edge showed greater β-catenin signaling with vehicle and TGFβ1 treatment and also displayed greater EMT marker α-smooth muscle actin (SMA) expression. However, Tg disrupted the monolayer and caused β-catenin signaling accompanied by α-SMA expression both at the scratch edge and in the monolayer. In conclusion, it appears that Tg induces hRPTEC EMT via β-catenin signaling. TDAG51 induction via Tg treatment may mediate this effect. Supported by CIHR MOP-67116 and St. Joseph's Healthcare Hamilton.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".