Jaagsiekte sheep retrovirus detected in human lung cancer tissue arrays
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Adenocarcinoma is the most common type of non-small cell lung cancer and is frequently observed in non-smoking patients. Adenocarcinoma in-situ (formerly referred to as bronchioloalveolar carcinoma) is a subset of lung adenocarcinoma characterized by growth along alveolar septae without evidence of stromal, vascular, or pleural invasion, that disproportionately affects never-smokers, women, and Asians. Adenocarcinoma in-situ is morphologically and histologically similar to a contagious lung neoplasm of sheep called ovine pulmonary adenocarcinoma (OPA). OPA is caused by infection with the exogenous betaretrovirus, jaagsiekte sheep retrovirus (JSRV), whose envelope protein (Env) is a potent oncogene. Several studies have reported that a proportion of human lung adenocarcinomas are immunopositive for an antigen related to the Gag protein of JSRV, however other groups have been unable to verify these observations by PCR. METHODS: Here we examine human lung cancer tissue arrays (TA) for evidence of JSRV Env protein and DNA by immunohistochemical staining and PCR, respectively. RESULTS: Our results reveal that a subset of human lung cancers express an antigen that reacts with a JSRV Env-specific monoclonal antibody in immunohistochemistry and that exogenous JSRV-like env and gag sequences can be amplified from TA tumor samples, albeit inefficiently. CONCLUSIONS: While a causative role has not been established, these data suggest that a JSRV-like virus might infect humans. With next generation sequencing approaches, a JSRV-like virus in human lung cancers may be identified which could have profound implications for prevention, diagnosis and therapy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 it