Endogenous retrovirus-K promoter: a landing strip for inflammatory transcription factors?
Bibliographic record
Abstract
Humans are symbiotic organisms; our genome is populated with a substantial number of endogenous retroviruses (ERVs), some remarkably intact, while others are remnants of their former selves. Current research indicates that not all ERVs remain silent passengers within our genomes; re-activation of ERVs is often associated with inflammatory diseases. ERVK is the most recently endogenized and transcriptionally active ERV in humans, and as such may potentially contribute to the pathology of inflammatory disease. Here, we showcase the transcriptional regulation of ERVK. Expression of ERVs is regulated in part by epigenetic mechanisms, but also depends on transcriptional regulatory elements present within retroviral long terminal repeats (LTRs). These LTRs are responsive to both viral and cellular transcription factors; and we are just beginning to appreciate the full complexity of transcription factor interaction with the viral promoter. In this review, an exploration into the inflammatory transcription factor sites within the ERVK LTR will highlight the possible mechanisms by which ERVK is induced in inflammatory diseases.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".