Human interferon regulatory factor-1 gene and its promoter sequences revealed by population-based complete gene sequencing
Bibliographic record
Abstract
Interferon regulatory factor-1 (IRF-1) plays important roles in host immunity, cell proliferation and apoptosis. The current GenBank sequence for human IRF-1 (accession number: L05072) was derived from a human placenta DNA library and reported in 1992. In one recent population-based sequence study, we observed consistent discrepancies between our IRF-1 sequence data and GenBank reference sequences suggesting that, current IRF-1 reference sequence was not representative for all populations. By complete gene sequencing, we obtained a representative full-length IRF-1 sequence from a single subject. Compared to submission L05072, our population-based data contains: 35 nucleotide additions, 8 nucleotide removals and another 12 nucleotide replacements. A single nucleotide difference was observed in the IRF-1 promoter sequence compared to GenBank sequence (X53095). These changes were confirmed in 350 Kenyans and 28 non-African donors. The accuracy of a reference sequence is crucial for downstream genetic and functional studies and this study provides more complete and accurate data on the sequence of the human IRF-1 gene and its immediate promoter region.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".