DCIR-mediated enhancement of HIV-1 infection requires the ITIM-associated signal transduction pathway
Bibliographic record
Abstract
Dendritic cell immunoreceptor (DCIR) is a C-type lectin receptor expressed at high levels on dendritic cells (DCs). This surface molecule acts as an attachment factor for HIV-1 on DCs and contributes to trans- and cis-infection pathways. Moreover, DICR is induced by HIV-1 in CD4(+) T cells and promotes virus replication in this cell type. Nothing is known hitherto about the DCIR-dependent signaling, which is induced following HIV-1 ligation. First, specific pharmacologic inhibitors were tested on HIV-1 binding/entry and, second, specific antisense oligonucleotides targeted, more specifically kinases and phosphatases, were used. Our results show that SHP-1, SHP-2, Syk, and Src kinases (ie, Src, Fyn, and Hck) as well as PKC-α and MAP kinases (ie, Erk1/2 and p38) are all involved in the DCIR-mediated signal transduction pathway triggered by HIV-1. By mutagenesis and through the use of intracellular phosphorylated peptides, we show as well a pivotal role for the tyrosine and threonine residues of the DCIR immunoreceptor tyrosine-based inhibitory motif (ITIM). Our data suggest for the first time an involvement of ITIM domain in HIV-1-mediated signaling events and a relationship between phosphorylation events and DCIR function with respect to HIV-1 biology.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".