Ran Overexpression Leads to Diminished T Cell Responses and Selectively Modulates Nuclear Levels of c-Jun and c-Fos
Bibliographic record
Abstract
Ras-related nuclear protein (Ran) is a Ras family GTPase, and its documented functions are the regulation of DNA replication, cell cycle progression, nuclear structure formation, RNA processing and exportation, and nuclear protein importation. In this study, we performed detailed mapping of Ran expression during mouse ontogeny using in situ hybridization. High Ran expression was found in various organs and tissues including the thymus cortex and spleen white pulp. Ran was induced in T cells 24 h after their activation. The function of Ran in the immune system was investigated using Ran transgenic (Tg) mice. In Ran Tg T cells, there was compromised activation marker expression, lymphokine secretion, and proliferation upon T cell receptor activation in vitro when compared with wild type T cells. Tg mice also manifested defective delayed type hypersensitivity in vivo. Upon PMA and ionomycin stimulation, Tg T cells were defective in nuclear accumulation of AP-1 factors (c-Jun and c-Fos) but not NF-kappaB family members. Our experiments showed that Ran had important regulatory function in T cell activation. One of the possible mechanisms is that intracellular Ran protein levels control the nuclear retention for selective transcription factors such as c-Jun and c-Fos of AP-1, which is known to be critical in T cell activation and proliferation and lymphokine secretion.
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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 | 0.001 |
| 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".