SAMHD1 Degradation Enhances Active Suppression of Dendritic Cell Maturation by HIV-1
Bibliographic record
Abstract
A hallmark of HIV-1 infection is the lack of sterilizing immunity. Dendritic cells (DCs) are crucial in the induction of immunity, and lack of DC activation might underlie the absence of an effective anti-HIV-1 response. We have investigated how HIV-1 infection affects maturation of DCs. Our data show that even though DCs are productively infected by HIV-1, infection does not induce DC maturation. HIV-1 infection actively suppresses DC maturation, as HIV-1 infection inhibited TLR-induced maturation of DCs and thereby decreased the immune stimulatory capacity of DCs. Interfering with SAMHD1 restriction further increased infection of DCs, but did not lead to DC maturation. Notably, higher infection observed with SAMHD1 depletion correlated with a stronger suppression of maturation. Furthermore, blocking reverse transcription rescued TLR-induced maturation. These data strongly indicate that HIV-1 replication does not trigger immune activation in DCs, but that HIV-1 escapes immune surveillance by actively suppressing DC maturation independent of SAMHD1. Elucidation of the mechanism of suppression can lead to promising targets for therapy or vaccine design.
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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 | 0.000 |
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".