GABARAP is a determinant of apoptosis in growth-arrested chicken embryo fibroblasts
Bibliographic record
Abstract
Nutrient depletion triggers a series of adaptive processes as part of the unfolded protein response or UPR. These processes reduce stress to the endoplasmic reticulum by enhancing its protein folding capacity or ability to promote the degradation of dysfunctional proteins. Failure to restore ER homeostasis causes the activation of lethal pathways. The expression of a dominant negative mutant of C/EBPβ (Δ184-C/EBPβ) alters this balance in chicken embryo fibroblasts (CEF). As a result, CEF display enhanced survival upon prolonged nutrient depletion. Starved Δ184-C/EBPβ-expressing CEF display pronounced features of autophagy characterized by the appearance of large vesicles containing amorphous material, the formation of smaller double-membrane vesicles (autophagosomes) and processing of LC3 and GABARAP. However, there were marked differences in the expression and processing of these proteins. In both normal and Δ184-C/EBPβ expressing CEF, the lipidated form of LC3 (form II) accumulated during starvation but was detectable even when cells were actively dividing in complete medium. In contrast, GABARAP expression and lipidation were strongly stimulated in response to starvation. Inhibition of LC3 expression by RNA interference led to apoptosis in normal CEF even in the absence of starvation but stable and near complete repression of GABARAP was tolerated. Moreover, the inhibition of GABARAP enhanced CEF survival and abolished the expression of the pro-apoptotic CHOP factor in conditions of starvation, suggesting a reduced level of ER stress. Therefore, GABARAP is a determinant of apoptosis in CEF subjected to prolonged nutrient depletion.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".