Silencing of both ATF4 and PERK inhibits cell cycle progression and promotes the apoptosis of differentiating chondrocytes
Bibliographic record
Abstract
In the current study, we demonstrate that the silencing of protein kinase R (PKR)-like endoplasmic reticulum (ER) kinase (PERK) and activating transcription factor 6 (ATF4) (using small interfering RNA expression constructs) inhibits the chondrocyte cell cycle and proliferation in vitro and ex vivo. The silencing of PERK alone using siRNA against PERK (siPERK) led to arrest in the G1 phase, it decreased the number of cells in the S phase, and delayed progressoin to the G2‑M phase. Co-transfection with siRNA against ATF (siATF4) led to a more profound inhibitory effect on cell cycle progression. Moreover, transfection with siPERK was associated with enhanced endoplasmic reticulum (ER) stress‑induced apoptosis during bone morphogenetic protein 2 (BMP2)‑induced chondrogenesis, and transfection with siATF4 exacerbated ER stress‑related cell death. Data from flow cytometry (FCM), immunohistochemistry and TUNEL assays supported these findings in vitro and ex vivo. As shown by our results, the combined effect of the silencing of ATF4 and PERK led to the activation of an ER stress‑specific caspase cascade in the cartilage tissue. On the whole, these findings reveal a new crucial combined effect of the silencing of PERK and ATF4 in modulating ER stress‑mediated apoptosis during chondrocyte differentiation and proliferation.
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 | 0.000 |
| 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".