Detecting Sources of Immune Activation and Viral Rebound in HIV Infection
Bibliographic record
Abstract
Anti-retroviral therapy (ART) has greatly improved the quality and length of life for people living with HIV, but immune activation does not normalize during ART, and persistent immune activation has been linked to increased morbidity and mortality. We report a comparison of assays of two potential sources of immune activation during ART: rare cells producing HIV and the virus' major viral protein, p24, benchmarked on a cell model of active and latent infections and a method to visualize HIV-producing cells. We show that assays of HIV envelope mRNA (EDITS assay), gag mRNA, and p24 (Flow-FISH, HIV-Flow. and ultrasensitive p24 immunoassay) detect HIV-producing cells and p24 at sensitivities of one infected cell in a million uninfected cells, thereby providing validated tools to explore sources of immune activation during ART in the lymphoid and other tissue 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".