Characterization of interferon regulatory factor-7 in defined subsets of human peripheral blood mononuclear cells and analysis of the effect of knockdown on HIV-1 infection
Bibliographic record
Abstract
Introduction: Interferon regulatory factor-7 (IRF-7), the “master regulator” of type 1 interferon, has shown to orchestrate anti-viral immune responses via fine-tuning expression of interferons and interferon-stimulated genes. Methods: IRF-7 levels were examined using multi-parametric flow-cytometry in HIV-uninfected Manitoban donors and in HIV-infected and HIV-uninfected Kenyan volunteers from a well-characterized Kenyan sex worker cohort. IRF-7 expression level was reduced by IRF-7 specific siRNA or shRNA encoded in lentivirus and administered into ex-vivo CD4+ T cells by transfection or transduction. Results: In unstimulated PBMC, IRF-7 was constitutively expressed at low levels in every defined subset we examined. We observed less HIV-infected cells (~10%) with IRF-7 knockdown, suggesting that IRF-7 may play a role in HIV infection. Conclusions: Unexpectedly, it was found that even though IRF-7 had been implicated in orchestrating antiviral events, reducing IRF-7 expression in ex vivo CD4+ T cells did not increase the cellular susceptibility to productive HIV infection.
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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 | 0.001 |
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".