Per2 Upregulation in Circulating Hematopoietic Progenitor Cells During Chronic HIV Infection
Bibliographic record
Abstract
Chronic HIV infection accelerates immune aging and is associated with abnormal hemato-lymphopoiesis, but the relationship between HIV-induced aging and Hematopoietic Progenitor Cells (HPC) function is not well defined. In the context of aging, it has been demonstrated using a murine model that Per2 (Period circadian clock 2) is a negative regulator of HPC survival and lineage potential. A possible involvement of Per2 modulation on hematopoietic failure during HIV infection has not yet been investigated. The aim of this study was to analyze whether Per2 is differently expressed and regulated on HPC during HIV infection, possibly providing a therapeutic target to restore lymphoid potential in the HPC compartment. To this purpose, Per2 expression in circulating HPC was compared in 69 chronic HIV infected patients under successful ART and in matched 30 uninfected healthy donors (HD). HPC aging was assessed by measuring relative telomere length (TLR), and HPC functionality was evaluated by Colony Forming Cell (CFC) assay from both ex vivo HIV+ patients and in vitro Per2 overexpressing donors. Our results showed a lower TLR in HPC and a decrease of white progenitor colonies from HIV+ patients with lower CD4 respect to those with higher CD4 T cell count (500 CD4 T cell/mmc). Interestingly, we found that the frequency of Per2-expressing HPC is higher in HIV+ patients than in HD and correlated to TLR of CFC derived cells, highlighting a relationship between low proliferative rate and Per2 expression. Indeed, the in vitro overexpression of Per2 resulted in a significant decrease of white progenitor colonies respect to control cells. Finally, we showed that the deacetylase Sirtuin 1, a negative regulator of Per2, was downregulated in HPC from HIV+ patients, and the peripheral blood treatment with resveratrol (Sirtuin 1 inducer) determined a decrease of Per2 expressing HPC. Altogether, these results suggest that during HIV infection, Per2 is involved in the regulation of HPC expansion and differentiation and its overexpression may impair the immune reconstitution. These data support the rationale to explore the role of this regulatory mechanism during aged-associated hemato-lymphopoiesis impairment in HIV infection.
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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".