The N-Terminal Domain of NLRC5 Confers Transcriptional Activity for MHC Class I and II Gene Expression
Bibliographic record
Abstract
Ag presentation to CD4(+) and CD8(+) T cells depends on MHC class II and MHC class I molecules, respectively. One important regulatory factor of this process is the transcriptional regulation of MHC gene expression. It is well established that MHC class II transcription relies on the NLR protein CIITA. Recently, another NLR protein, NLRC5, was shown to drive MHC class I expression. The molecular mechanisms of the function of NLRC5 however remain largely elusive. In this study, we present a detailed functional study of the domains of NLRC5 revealing that the N-terminal domain of human NLRC5 has intrinsic transcriptional activity. Domain swapping experiments between NLRC5 and CIITA showed that this domain contributes to MHC class I and MHC class II gene expression with a bias for activation of MHC class I promoters. Delivery of this construct by adeno-associated viral vectors upregulated MHC class I and MHC class II expression in human cells and enhanced lysis of melanoma cells by CD8(+) cytotoxic T cells in vitro. Taken together, this work provides novel insight into the function of NLRC5 and CIITA in MHC gene regulation.
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".