Diurnal Variation of Plasma Extracellular Vesicle Is Disrupted in People Living with HIV
Bibliographic record
Abstract
BACKGROUND: Several types of extracellular vesicles (EVs) secreted by various immune and non-immune cells are present in the human plasma. We previously demonstrated that EV abundance and microRNA content change in pathological conditions, such as HIV infection. Here, we investigated daily variations of large and small EVs, in terms of abundance and microRNA contents in people living with HIV (PLWH) receiving antiretroviral therapy (HIV+ART) and uninfected controls (HIV-). METHODS: Venous blood samples from n = 10 HIV+ART and n = 10 HIV- participants were collected at 10:00 and 22:00 the same day. Large and small plasma EVs were purified, counted, and the mature miRNAs miR-29a, miR-29b, miR-92, miR-155, and miR-223 copies were measured by RT-PCR. RESULTS: Large EVs were significantly bigger in the plasma collected at 10:00 versus 22:00 in both groups. There was a significant day-night increase in the quantity of 5 miRNAs in HIV- large EVs. In HIV+ART, only miR-155 daily variation has been observed in large EVs. Finally, EV-miRNA content permits to distinguish HIV- to HIV+ART in multivariate analysis. CONCLUSION: These results point that plasma EV amount and microRNA contents are under daily variation in HIV- people. This new dynamic measure is disrupted in PLWH despite viral-suppressive ART. This study highlights a significant difference concerning EV abundance and their content measured at 22:00 between both groups. Therefore, the time of blood collection must be considered in the future for the EV as biomarkers.
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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 | 0.001 |
| 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 | 0.001 | 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".