ATF4 Signaling in HIV Infection: Viral Subversion of a Stress Response Transcription Factor
Bibliographic record
Abstract
Cellular Integrated Stress Response (ISR), the mitochondrial Unfolded Protein Response (UP-Rmt) and the IFN signaling are associated with viral infections. The Activating transcription fac-tor 4 (ATF4) plays a pivotal role in these pathways and controls the expression of many genes involved in redox processes, amino acid metabolism, protein misfolding, autophagy and apop-tosis. The precise role of ATF4 during viral infection is unclear and depends on cell hosts, viral agents and models. Furthermore, ATF4 signaling can be hijacked by pathogens to favor viral in-fection and replication. In this review, we summarize the ATF4-mediated signaling pathways in response to viral infections, focusing on human immunodeficiency virus (HIV). We examine the consequences of ATF4 activation for HIV replication and reactivation. The role of ATF4 in au-tophagy and apoptosis is explored as in the context of HIV infection programmed cell deaths contribute to the depletion of CD4 T cells. Furthermore, ATF4 can also participate in the estab-lishment of innate and adaptive immunity that are essential for the host to control viral infec-tions. We finally discuss the putative role of the ATF4 paralogue, named ATF5, in HIV infection. This review underlines the role of ATF4 at the crossroads of multiple processes reflecting host-pathogen interactions.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".