Novel Insights into the Pathogenesis of the Graffi Murine Leukemia Retrovirus
Bibliographic record
Abstract
The Graffi murine leukemia virus (MuLV) was isolated in 1954 by Arnold Graffi, who characterized it as a myeloid leukemia-inducing retrovirus. He and his team, however, soon observed the intriguing phenomenon of hematological diversification, which corresponded to a decrease of myeloid leukemias and an increase of other types of leukemias. Recently, we derived two different molecular clones corresponding to ecotropic nondefective genomes that were named GV-1.2 and GV-1.4. The induced leukemias were classified as myeloid based on morphological analysis of blood smears. In this study, we further characterized the two variants of the Graffi murine retrovirus, GV-1.2 and GV-1.4, in three different strains of mice. We show that the Graffi MuLV is a multipotent retrovirus capable of inducing both lymphoid (T- and B-cell) and nonlymphoid (myeloid, erythroid, megakaryocytic) leukemia. Many of these are very complex with concomitant expression of different hematopoietic lineages. Interestingly, a high percentage of megakaryocytic leukemias, a type of leukemia rarely observed with MuLVs, arise in the FVB/n strain of mice. The genetic backgrounds of the different strains of mice influence greatly the results. Furthermore, the enhancer region, different for GV-1.2 and GV-1.4, plays a pivotal role in the disease specificity: GV-1.2 induces more lymphoid leukemias, and GV-1.4 induces more nonlymphoid ones.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".