Regulation of nuclear factor of activated T cells by phosphotyrosyl-specific phosphatase activity: a positive effect on HIV-1 long terminal repeat–driven transcription and a possible implication of SHP-1
Bibliographic record
Abstract
Although protein tyrosine phosphatase (PTP) inhibitors used in combination with other stimuli can induce interleukin 2 (IL-2) production in T cells, a direct implication of nuclear factor of activated T cells (NFAT) has not yet been demonstrated. This study reports that exposure of leukemic T cells and human peripheral blood mononuclear cells to bis-peroxovanadium (bpV) PTP inhibitors markedly induce activation and nuclear translocation of NFAT. NFAT activation by bpV was inhibited by the immunosuppressive drugs FK506 and cyclosporin A, as well as by a specific peptide inhibitor of NFAT activation. Mobility shift assays showed specific induction of the NFAT1 member by bpV molecules. The bpV-mediated NFAT activation was observed to be important for the up-regulation of the human immunodeficiency virus 1 (HIV-1) long terminal repeat (LTR) and the IL-2 promoter; NFAT1 was demonstrated to be particularly important in bpV-dependent positive action on HIV-1 LTR transcription. The active participation of p56(lck), ZAP-70, p21(ras), and calcium in the bpV-mediated signaling cascade leading to NFAT activation was confirmed, using deficient cell lines and dominant-negative mutants. Finally, overexpression of wild-type SHP-1 resulted in a greatly diminished activation of NFAT by bpV, suggesting an involvement of SHP-1 in the regulation of NFAT activation. These data were confirmed by constitutive NFAT translocation observed in Jurkat cells stably expressing a dominant-negative version of SHP-1. The study proposes that PTP activity attenuates constitutive kinase activities that otherwise would lead to constant NFAT activation and that this activation is participating in HIV-1 LTR stimulation by PTP inhibition.
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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) | 0.001 | 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".