Preferential Localization of the Epstein-Barr Virus (EBV) Oncoprotein LMP-1 to Nuclei in Human T Cells: Implications for Its Role in the Development of EBV Genome-Positive T-Cell Lymphomas
Bibliographic record
Abstract
The Epstein-Barr virus (EBV)-encoded latent membrane protein-1 (LMP-1) is thought to play a role in the EBV-induced B-cell transformation and immortalization. EBV has also been implicated in certain human T-cell lymphomas; however, the phenotypic effects of the expression of this oncoprotein in T cells are not known. To learn whether LMP-1 also induces phenotypic changes in T cells, we stably expressed it in human cell lines of T and B lineages and 25 LMP-1-expressing T-cell clones and 7 B-cell clones were examined. Our results show for the first time that, in sharp contrast to B cells, LMP-1 preferentially localizes to nuclei in T cells and does not induce the phenotypic changes in these cells that it induces in B cells, does not associate with TRAF proteins, and does not arrest the cell cycle in the G2/M phase. A computer-assisted analysis revealed that LMP-1 lacks the canonical nuclear localization signal. Our results suggest that this oncoprotein may not play the same role in the lymphomagenesis of T cells as it does in B cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".