In Vivo CD40-CD154 (CD40 Ligand) Interaction Induces Integrated HIV Expression by APC in an HIV-1-Transgenic Mouse Model
Bibliographic record
Abstract
Because of their relative resistance to viral cytopathic effects, APC can provide an alternative reservoir for latently integrated HIV. We used an HIV-transgenic mouse model in which APC serve as the major source of inducible HIV expression to study mechanisms by which integrated virus can be activated in these cells. When admixed with transgenic APC, activated T lymphocytes provided a major contact-dependent stimulus for viral protein expression in vitro. Using blocking anti-CD154 mAb as well as CD154-deficient T cells, the HIV response induced by activated T lymphocytes was demonstrated to require CD40-CD154 interaction. The role of this pathway in the induction of HIV expression from APC in vivo was further studied in an experimental model involving infection of the HIV-transgenic mice with PLASMODIUM: chabaudi parasites. Enhanced viral production by dendritic cells and macrophages in infected mice was associated with up-regulated CD40 expression. More importantly, in vivo treatment with blocking anti-CD154 mAb markedly reduced viral expression in P. chabaudi-infected animals. Together, these findings indicate that immune activation of integrated HIV can be driven by the costimulatory interaction of activated T cells with APC. Because chronic T cell activation driven by coinfections as well as HIV-1 itself is a characteristic of HIV disease, this pathway may be important in sustaining viral expression from APC reservoirs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".