TLR-9 agonist protects human monocytic cells against HIV-Vpr-induced apoptosis: a critical role for Calmodulin-dependent protein kinase-II, c-JUN N terminal kinase and anti-apoptotic c-IAP-2 gene (154.11)
Bibliographic record
Abstract
Abstract Monocytic cells unlike CD4+ T cells survive HIV induced apoptosis and serve as key viral reservoirs. Mechanisms underlying the development of resistance to HIV-induced cytopathic effects are poorly understood. In chronic HIV infections, microbial products translocate from the gut and may activate lymphocytes conferring anti-apoptotic signals. By using Vpr52-96 peptide, an accessory protein of HIV known to cause apoptosis in various cell types, as a model for apoptosis-inducing protein, we demonstrate that Vpr52-96 induced apoptosis in primary monocytes and undifferentiated THP-1 cells. However, monocyte-derived macrophages and PMA-differentiated THP-1 cells exhibited profound resistance to Vpr-induced apoptosis. Interestingly, prior treatment of primary monocytes and undifferentiated THP-1 cells with TLR-9 agonist, CpG, induced resistance to Vpr-mediated apoptosis. This resistance was found to be mediated by extracellular calcium influx, activation of c-Jun N terminal kinase via Calmodulin-dependent kinase II and induction of anti apoptotic cIAP2 gene. Our results also revealed a novel pathway by which Vpr may dysregulate TLR signaling in monocytes by targeting MyD88. Interestingly, CpG protected these cells by blocking the Vpr-induced inhibition of MyD88. Overall, our results suggest that anti-apoptotic cIAP2 gene and calcium activated JNK signaling play a crucial role in conferring resistance induced by CpG against Vpr-mediated apoptosis in monocytic cells.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".