Evaluation of Cynomolgus Macaque (Macaca fascicularis) Endogenous Retrovirus Expression Following Simian Immunodeficiency Virus Infection
Bibliographic record
Abstract
Human endogenous retrovirus type K (HERV-K) transcripts are upregulated in the plasma of HIV-infected individuals and have been considered as targets for an HIV vaccine. We evaluated cynomolgus macaque endogenous retrovirus (CyERV) mRNA expression by RT-qPCR in PBMCs isolated from a cohort of animals previously utilized in a live attenuated SIV vaccine trial. CyERV env transcript levels decreased following vaccination (control and vaccine groups) and CyERV env and gag mRNA expression was decreased following acute SIV-infection, whereas during chronic SIV infection, CyERV transcript levels were indistinguishable from baseline. Reduced susceptibility to initial SIV infection, as measured by the number of SIV challenges required for infection, was associated with increased CyERV transcript levels in PBMCs. In vitro analysis revealed that SIV infection of purified CD4(+) T-cells did not alter CyERV gene expression. This study represents the first evaluation of ERV expression in cynomolgus macaques following SIV infection, in an effort to assess the utility of cynomolgus macaques as an animal model to evaluate ERVs as a target for an HIV/SIV vaccine. This non-human primate model system does not recapitulate what has been observed to date in the plasma of HIV-infected humans suggesting that further investigation at the cellular level is required to elucidate the impact of HIV/SIV infection on endogenous retrovirus expression.
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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) | 0.001 | 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".