Comparative transcriptomics of extreme phenotypes of human HIV-1 infection and SIV infection in sooty mangabey and rhesus macaque
Bibliographic record
Abstract
High levels of HIV-1 replication during the chronic phase of infection usually correlate with rapid progression to severe immunodeficiency. However, a minority of highly viremic individuals remains asymptomatic and maintains high CD4⁺ T cell counts. This tolerant profile is poorly understood and reminiscent of the widely studied nonprogressive disease model of SIV infection in natural hosts. Here, we identify transcriptome differences between rapid progressors (RPs) and viremic nonprogressors (VNPs) and highlight several genes relevant for the understanding of HIV-1-induced immunosuppression. RPs were characterized by a specific transcriptome profile of CD4⁺ and CD8⁺ T cells similar to that observed in pathogenic SIV-infected rhesus macaques. In contrast, VNPs exhibited lower expression of interferon-stimulated genes and shared a common gene regulation profile with nonpathogenic SIV-infected sooty mangabeys. A short list of genes associated with VNP, including CASP1, CD38, LAG3, TNFSF13B, SOCS1, and EEF1D, showed significant correlation with time to disease progression when evaluated in an independent set of CD4⁺ T cell expression data. This work characterizes 2 minimally studied clinical patterns of progression to AIDS, whose analysis may inform our understanding of HIV pathogenesis.
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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) | 0.000 | 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".