LFA-1 Is a Key Determinant for Preferential Infection of Memory CD4<sup>+</sup>T Cells by Human Immunodeficiency Virus Type 1
Bibliographic record
Abstract
Memory CD4+ T cells are considered a stable latent reservoir for human immunodeficiency virus type 1 (HIV-1) and a barrier to eradication of this retroviral infection in patients under therapy. It has been shown that memory CD4+ T cells are preferentially infected with HIV-1, but the exact mechanism(s) responsible for this higher susceptibility remains obscure. Previous findings indicate that incorporation of host-derived intercellular adhesion molecule 1 (ICAM-1) in HIV-1 increases virus infectivity. To measure the putative involvement of virus-anchored ICAM-1 in the preferential infection of memory cells by HIV-1, quiescent and activated naive and memory T-cell subsets were exposed to isogenic virions either lacking or bearing ICAM-1. Memory CD4+ T cells were found to be more susceptible than naive CD4+ T cells to infection with ICAM-1-bearing virions, as exemplified by a more important virus replication, an increase in integrated viral DNA copies, and a more efficient entry process. Interactions between virus-associated host ICAM-1 and cell surface LFA-1 under a cluster formation seem to be responsible for the preferential HIV-1 infection of the memory cell subset. Altogether, these data shed light on a potential mechanism by which HIV-1 preferentially targets long-lived memory CD4+ T 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".