Jaagsiekte Sheep Retrovirus and Enzootic Nasal Tumor Virus Promoters Drive Gene Expression in All Airway Epithelial Cells of Mice but Only Induce Tumors in the Alveolar Region of the Lungs
Bibliographic record
Abstract
Jaagsiekte sheep retrovirus (JSRV) induces tumors in the distal airways of sheep and goats, while the closely related enzootic nasal tumor virus type 1 (ENTV-1) and ENTV-2 induce tumors in the nasal epithelium of sheep and goats, respectively. When expressed using a strong Rous sarcoma virus promoter, the envelope proteins of these viruses induce tumors in the respiratory tract of mice, but only in the distal airway. To examine the role of the retroviral long terminal repeat (LTR) promoters in determining tissue tropism, adeno-associated virus (AAV) vectors expressing alkaline phosphatase under the control of the JSRV, ENTV-1, or ENTV-2 LTRs were generated and administered to mice. The JSRV LTR was active in all airway epithelial cells, while the ENTV LTRs were active in the nasal epithelium and alveolar type II cells but poorly active in tracheal and bronchial epithelial cells. When vectors were administered systemically, the ENTV-1 and -2 LTRs were inactive in major organs examined, whereas the JSRV showed high-level activity in the liver. When a putative transcriptional enhancer from the 3' end of the env gene was inserted upstream of the JSRV and ENTV-1 LTRs in the AAV vectors, a dramatic increase in transgene expression was observed. However, intranasal administration of AAV vectors containing any combination of ENTV or JSRV LTRs and Env proteins induced tumors only in the lower airway. Our results indicate that mice do not provide an adequate model for nasal tumor induction by ENTV despite our ability to express genes in the nasal epithelium.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".