RETRACTED ARTICLE: Modulation of the TGF-β1-induced epithelial to mesenchymal transition (EMT) mediated by P1 and P2 purine receptors in MDCK cells
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
Epithelial to mesenchymal transition (EMT) occurs during embryogenesis or under pathological conditions such as hypoxia, injury, chronic inflammation, or tissue fibrosis. In renal tubular epithelial cells (MDCK), TGF-β1 induces EMT by reducing or increasing epithelial or mesenchymal marker expression, respectively. In this study, we confirmed that the cAMP analogues, 8-CPT-cAMP or N6-Ph-cAMP, inhibited the TGF-β1-driven overexpression of the mesenchymal markers ZEB-1, Slug, Fibronectin, and α-SMA. Furthermore, we showed that A1, A2A, P2Y1, P2Y11, and P2X7 purine receptor agonists modulated the TGF-β1-induced EMT through the involvement of PKA and/or MAPK/ERK signaling. The stimulation of A2A receptor reduced the overexpression of the EMT-related markers, mainly through the cAMP-dependent PKA pathway, as confirmed by cell pre-treatment with Myr-PKI. Both A1 and P2Y1 receptor stimulation exacerbated the TGF-β1-driven effects, which were reduced by cell pre-treatment with the MAPK inhibitor PD98059, according to the increased ERK1/2 phosphorylation upon receptor activation. The effects induced by P2Y11 receptor activation were oppositely modulated by PKA or MAPK inhibition, in line with the dual nature of the Gs- and Gq-coupled receptor. Differently, P2X7 receptor induced, per se, similar and not additive effects compared to TGF-β1, after prolonged cell exposure to BzATP. These results suggest a putative role of purine receptors as target for anti-fibrotic agents.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.059 | 0.024 |
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".