A translational rheostat for RFLAT-1 regulates RANTES expression in T lymphocytes
Bibliographic record
Abstract
Activation of T lymphocytes by specific antigen triggers a 3- to 7-day maturation process. Terminal differentiation begins late after T cell activation and involves expression of effector genes, including the chemokine RANTES and its major transcriptional regulator, RANTES factor of late-activated T lymphocytes-1 (RFLAT-1). In this article we demonstrate that RFLAT-1 expression is translationally regulated through its 5'-UTR and in a cell type-specific manner. Overexpression of the translation initiation factor eIF4E increases RFLAT-1 protein, while inhibition of Mnk1, which phosphorylates eIF4E, reduces RFLAT-1 production, indicating cap-dependent translational regulation. These events are regulated by ERK-1/2 and p38 MAP kinases and allow T cells to rapidly adjust RANTES expression in response to changes in the cellular environment, such as stress and/or growth factors. These findings provide a molecular mechanism for a rheostat effect of increasing or decreasing RANTES expression at sites of inflammation. Memory T cells, already poised to make RANTES, are finely regulated by translational control of the major transcription factor regulating RANTES expression. This is the first example of such a mechanism regulating a chemokine, but it seems likely that this will prove to be a general way for cells to rapidly respond to stress, cytokines, and other proinflammatory factors in their local environment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 teacher head, 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".