HIV Replication Increases the Mitochondrial DNA Content of Plasma Extracellular Vesicles
Bibliographic record
Abstract
Extracellular vesicles (EVs) and their cargo have been studied intensively as potential sources of biomarkers in HIV infection; however, their DNA content, particularly the mitochondrial portion (mtDNA), remains largely unexplored. It is well known that human immunodeficiency virus (HIV) infection and prolonged antiretroviral therapy (ART) lead to mitochondrial dysfunction and reduced mtDNA copy in cells and tissues. Moreover, mtDNA is a well-known damage-associated molecular pattern molecule that could potentially contribute to increased immune activation, oxidative stress, and inflammatory response. We investigated the mtDNA content of large and small plasma EVs in persons living with HIV (PLWH) and its implications for viral replication, ART use, and immune status. Venous blood was collected from 196 PLWH, ART-treated or ART-naïve (66 with ongoing viral replication, ≥20 copies/mL), and from 53 HIV-negative persons, all recruited at five HIV testing or treatment centers in Burkina Faso. Large and small plasma EVs were purified and counted, and mtDNA level was measured by RT-qPCR. Regardless of HIV status, mtDNA was more abundant in large than small EVs. It was more abundant in EVs of viremic than aviremic and control participants and tended to be more abundant in participants treated with Tenofovir compared with Zidovudine. When ART treatment was longer than six months and viremia was undetectable, no variation in EV mtDNA content versus CD4 and CD8 count or CD4/CD8 ratio was observed. However, mtDNA in large and small EVs decreased with years of HIV infection and ART. Our results highlight the impact of viral replication and ART on large and small EVs' mtDNA content. The mechanisms underlying the differential incorporation of mtDNA into EVs and their effects on the surrounding cells warrant further investigation.
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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".