Regulation of LFA-1 Activity through Cytoskeleton Remodeling and Signaling Components Modulates the Efficiency of HIV Type-1 Entry in Activated CD4+ T Lymphocytes
Bibliographic record
Abstract
Besides interactions between the viral envelope glycoproteins with cell surface receptors, interactions between cell-derived molecules incorporated onto virions and their ligand could also modulate HIV type-1 (HIV-1) entry inside CD4(+) T lymphocytes. Although incorporation of host ICAM-1 within HIV-1 increases both virus attachment and fusion, the precise mechanism through which this phenomenon is occurring is still unclear. We demonstrate in this study that activation of primary human CD4(+) T lymphocytes increases LFA-1 affinity and avidity states, two events promoting the early events of the HIV-1 replication cycle through interactions between virus-embedded host ICAM-1 and LFA-1 clusters. Confocal analyses suggest that HIV-1 is concentrated in microdomains rich in LFA-1 clusters that also contain CD4 and CXCR4 molecules. Experiments performed with specific inhibitors revealed that entry of HIV-1 in activated CD4(+) T cells is regulated by LFA-1-dependent ZAP70, phospholipase Cgamma1, and calpain enzymatic activities. By using laboratory and clinical strains of HIV-1 produced in primary human cells, we demonstrate the importance of the LFA-1 activation state and cluster formation in the initial step of the virus life cycle. Overall, these data provide new insights into the complex molecular events involved in HIV-1 binding and entry.
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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) | 0.001 | 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".