Zhangfei/CREB-ZF – A Potential Regulator of the Unfolded Protein Response
Bibliographic record
Abstract
Cells respond to perturbations in the microenvironment of the endoplasmic reticulum (ER), and to the overloading of its capacity to process secretory and membrane-associate proteins, by activating the Unfolded Protein Response (UPR). Genes that mediate the UPR are regulated by three basic leucine-zipper (bLZip) motif-containing transcription factors - Xbp1s, ATF4 and ATF6. A failure of the UPR to achieve homeostasis and its continued stimulation leads to apoptosis. Mechanisms must therefore exist to turn off the UPR if it successfully restores normalcy. The bLZip protein Zhangfei/CREBZF/SMILE is known to suppress the ability of several, seemingly structurally unrelated, transcription factors. These targets include Luman/CREB3 and CREBH, ER-resident bLZip proteins known to activate the UPR in some cell types. Here we show that Zhangfei had a suppressive effect on most UPR genes activated by the calcium ionophore thapsigargin. This effect was at least partially due to the interaction of Zhangfei with Xbp1s. The leucine zipper of Zhangfei was required for this interaction, which led to the subsequent proteasomal degradation of Xbp1s. Zhangfei suppressed the ability of Xbp1s to activate transcription from a promoter containing unfolded protein response elements and significantly reduced the ability to Xbp1s to activate the UPR as measured by RNA and protein levels of UPR-related genes. Finally, specific suppression of endogenous Zhangfei in thapsigargin-treated primary rat sensory neurons with siRNA directed to Zhangfei transcripts, led to a significant increase in transcripts and proteins of UPR genes, suggesting a potential role for Zhangfei in modulating the UPR.
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) | 0.002 | 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".