Calcitriol decreases HIV-1 transfer in vitro from monocyte-derived dendritic cells to CD4 + T cells, and downregulates the expression of DC-SIGN and SIGLEC-1
Bibliographic record
Abstract
Dendritic cells (DCs) promote HIV-1 transmission by acting as Trojan horses, capturing viral particles, facilitating the infection of CD4+ T-cells. Vitamin D (VitD) has shown to decrease T cell activation, reducing susceptibility to HIV-1 infection of CD4+ T-cells in vitro; however, if VitD decreases viral transfer from DCs to CD4+ T-cells is unknown. In this study, we co-cultured HIV-1-pulsed immature and LPS mature monocytes-derived DCs (iDCs and LmDCs, respectively), differentiated in presence or absence of calcitriol (VitD active form), with PHA-activated autologous CD4+ T-cells from 16 healthy donors. In co-cultures of iDCs and LmDCs treated with calcitriol, there was a significant decrease in frequency of infected CD4+ T-cells, evaluated by flow cytometry. However, p24 levels evaluated by ELISA were not significantly reduced in culture supernatants. Moreover, calcitriol-treated iDCs exhibited decreased expression of genes involved in HIV-1 transfer compared to the control. Both, calcitriol-treated iDCs and LmDCs exhibit a similar gene expression profile, probably related to a transcriptional balance achieved after long treatment with calcitriol. Since calcitriol-differentiated DCs express on their surface a lower amount of DC-SIGN and SIGLEC-1 molecules, widely associated with HIV-1 transfer, suggesting that this mechanism contributes to a lower transfer of viral particles by the DCs.
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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".