Sequence analysis of a putative goose RIG-I gene
Bibliographic record
Abstract
Li, G., Li, J., Tian, Y., Wang, DE., Shen, J., Tao, Z., Xu, J. and Lu, L. 2012. Sequence analysis of a putative goose RIG-I gene. Can. J. Anim. Sci. 92: 143–151. Retinoid acid-inducible gene-I (RIG-I) is a critical cytoplasmic RNA sensor which plays an important role in the recognition of, and response to, influenza virus and other RNA viruses. In the present study, A 3808-bp cDNA encoding goose RIG-I (goRIG-I) was cloned from splenic lymphocytes of geese using RT-PCR and rapid amplification of cDNA ends (RACE) techniques. The encoded protein, which is predicted to consist of 933 amino acids, has a molecular weight of 106.4 kDa and includes an N-terminal caspase recruitment domain (CARD), a domain with the signature of DExD/H box helicase (helicase domain), and a C-terminal repression domain (RD) similar to duck RIG-I (duRIG-I), human RIG-I, and mouse RIG-I. The goRIG-I showed 93.8 and 78.0% amino acid sequence identity with previously described duRIG-I and finch RIG-I, respectively, and 48.9–53.0% sequence identity with mammalian homologs. Quantitative RT-PCR analysis indicated that the goRIG-I gene is strongly expressed in the liver, lung, brain, spleen, and bursa of Fabricius. These findings lay the foundation for further research on the function and mechanism of avian RIG-I in innate immunity.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".