Type I interferon responses are impaired in latently HIV infected cells
Bibliographic record
Abstract
BACKGROUND: The latent HIV-1 reservoir represents the primary barrier to the eradication of HIV-1 infection. The design of novel reservoir-clearance strategies, however, is impeded in part by the inability to distinguish latently HIV-infected cells from uninfected cells. Significant impairment of the type I interferon (IFN-I) response is observed during productive HIV-1 infection. Although this remains poorly described in the context of latent HIV-1 infection, presence of potential defects may serve as a novel therapeutic target. Therefore, IFN-I pathways were characterized using two latently HIV-1-infected cell lines, U1 and OM10.1, in comparison to their respective uninfected parental U937 and HL60 cell lines. FINDINGS: Constitutive expression and induction of important mediators of IFN-I signaling including IFNα/β cytokines, IFNAR1, MHC-I, ISG15, and PKR were evaluated following exogenous IFNα or poly(I:C) treatment. Differences in basal expression of IFNAR1, MHC-I, and PKR were observed between the latently HIV-1 infected and uninfected cell lines. In parallel, significant impairments in the induction of MHC-I, ISG15 and PKR, as well as secretion of IFNα/β cytokines were observed in response to appropriate exogenous stimulation within the two latently HIV-infected U1 and OM10.1 cells, relative to their HIV-uninfected parental cells. CONCLUSIONS: In comparison to the HIV-uninfected U937 and HL60 cell lines, widespread defects in IFN-I responsiveness were observed within the latently HIV-infected U1 and OM10.1 cells. These impairments represent novel therapeutic targets, which may be amenable to strategies currently employed in cancer therapy.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".