Bibliographic record
Abstract
Integration of the reverse transcribed viral genome into host chromatin is the hallmark of retroviral replication. Yet, during natural HIV infection, various unintegrated viral DNA forms exist in abundance. Though linear viral cDNA is the precursor to an integrated provirus, increasing evidence suggests that transcription and translation of unintegrated DNAs prior to integration may aid productive infection through the expression of early viral genes. Additionally, unintegrated DNA has the capacity to result in preintegration latency, or to be rescued and yield productive infection and so unintegrated DNA, in some circumstances, may be considered to be a viral reservoir. Recently, there has been interest in further defining the role and function of unintegrated viral DNAs, in part because the use of anti-HIV integrase inhibitors leads to an abundance of unintegrated DNA, but also because of the potential use of non-integrating lentiviral vectors in gene therapy and vaccines. There is now increased understanding that unintegrated viral DNA can either arise from, or be degraded through, interactions with host DNA repair enzymes that may represent a form of host antiviral defence. This review focuses on the role of unintegrated DNA in HIV infection and additionally considers the potential implications for antiviral therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".