LFA-1 Antagonists as Agents Limiting Human Immunodeficiency Virus Type 1 Infection and Transmission and Potentiating the Effect of the Fusion Inhibitor T-20
Bibliographic record
Abstract
Adhesion molecules are known to play major roles in the initiation and stabilization of cell-to-cell contacts during the immunological response. Human immunodeficiency virus type 1 (HIV-1) exploits those interactions to facilitate infection and propagation processes. The primary objective of the present study was to investigate the ability of antagonists specific for lymphocyte function-associated antigen 1 (LFA-1) to diminish HIV-1 infection and transmission. We demonstrate here that LFA-1 antagonists can significantly reduce HIV-1 replication in primary human cells and virus propagation by affecting cell-to-cell interactions. Moreover, the inhibition of LFA-1-mediated adhesion events also potentiates the antiviral efficacy of the peptide fusion inhibitor T-20. Altogether, our data suggest that LFA-1 antagonists represent promising antiviral agents. Antiadhesion therapy could be considered a complementary strategy targeting cellular functions essential for HIV-1 spreading and against which the combined therapy currently used displays a limited efficacy.
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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".