Protection against Murine Leukemia Virus-InducedSpongiform Myeloencephalopathy in Mice Overexpressing Bcl-2 butNot in Mice Deficient for Interleukin-6, Inducible NitricOxide Synthetase, ICE, Fas, Fas Ligand, or TNF-R1Genes
Bibliographic record
Abstract
Some murine leukemia viruses (MuLVs), among them Cas-Br-E and ts-1 MuLVs, are neurovirulent, inducing spongiform myeloencephalopathy and hind limb paralysis in susceptible mice. It has been shown that the env gene of these viruses harbors the determinant of neurovirulence. It appears that neuronal loss occurs by an indirect mechanism, since the target motor neurons have not been found to be infected. However, the pathogenesis of the disease remains unclear. Several lymphokines, cytokines, and other cellular effectors have been found to be aberrantly expressed in the brains of infected mice, but whether these are required for the development of the neurodegenerative lesions is not known. In an effort to identify the specific effectors which are indeed required for the initiation and/or development of spongiform myeloencephalopathy, we inoculated gene-deficient (knockout [KO]) mice with ts-1 MuLV. We show here that interleukin-6 (IL-6), inducible nitric oxide synthetase (iNOS), ICE, Fas, Fas ligand (FasL), and TNF-R1 KO mice still develop signs of disease. However, transgenic mice overexpressing Bcl-2 in neurons (NSE/Bcl-2) were largely protected from hind limb paralysis and had less-severe spongiform lesions. These results indicate that motor neuron death occurs in this disease at least in part by a Bcl-2-inhibitable pathway not requiring the ICE, iNOS, Fas/FasL, TNF-R1, and IL-6 gene products.
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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 | 0.000 |
| 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 | 0.001 | 0.002 |
| 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 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".