TLR2 and TLR4 triggering exerts contrasting effects with regard to HIV-1 infection of human dendritic cells and subsequent virus transfer to CD4+T cells
Bibliographic record
Abstract
BACKGROUND: Recognition of microbial products through Toll-like receptors (TLRs) initiates inflammatory responses orchestrated by innate immune cells such as dendritic cells (DCs). As these cells are patrolling mucosal surfaces, a portal of entry for various pathogens including human immunodeficiency virus type-1 (HIV-1), we investigated the impact of TLR stimulation on productive HIV-1 infection of DCs and viral spreading to CD4+ T cells. RESULTS: We report here that engagement of TLR2 on DCs increases HIV-1 transmission toward CD4+ T cells by primarily affecting de novo virus production by DCs. No noticeable and consistent effect was observed following engagement of TLR5, 7 and 9. Additional studies indicated that both HIV-1 infection of DCs and DC-mediated virus transmission to CD4+ T cells were reduced upon TLR4 triggering due to secretion of type-I interferons. CONCLUSION: It can thus be proposed that exposure of DCs to TLR2-binding bacterial constituents derived, for example, from pathogens causing sexually transmissible infections, might influence the process of DC-mediated viral dissemination, a phenomenon that might contribute to a more rapid disease progression.
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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) | 0.004 | 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".