Central nervous system Toll-like receptor expression in response to Theiler's murine encephalomyelitis virus-induced demyelination disease in resistant and susceptible mouse strains
Bibliographic record
Abstract
BACKGROUND: In immunopathological diseases, such as multiple sclerosis (MS), genetic and environmental factors that contribute to the initiation and progression of the disease are often discussed. The Theiler murine encephalomyelitis virus-induced demyelination disease (TMEV-IDD) model used to study MS reflects this: genetically susceptible mice infected intra-cerebrally with TMEV develop a chronic demyelination disease. TMEV-IDD can be induced in resistant mouse strains by inducing innate immunity with lipopolysaccharide (LPS). Interestingly, Toll-like receptor 4 (TLR4) is the cognate receptor for LPS and its activation can induces up-regulation of other TLRs, such as TLR7 (the receptor for TMEV) and 9, known to be involved in autoimmunity. Up-regulation of TLRs could be involved in precipitating an autoimmune susceptible state. Consequently, we looked at TLR expression in the susceptible (SJL/J) and resistant (C57BL/6) strains of mice infected with TMEV. The resistant mice were induced to develop TMEV-IDD by two LPS injections following TMEV infection. RESULTS: Both strains were found to up-regulate multiple TLRs (TLR2, 7 and 9) following the TMEV infection. Expression of these TLRs and of viral mRNA was significantly greater in infected SJL/J mice. The susceptible SJL/J mice showed up-regulation of TLR3, 6 and 8, which was not seen in C57BL/6 mice. CONCLUSION: Expression of TLRs by susceptible mice and the up-regulation of the TLRs in resistant mice could participate in priming the mice toward an autoimmune state and develop TMEV-IDD. This could have implications on therapies that target TLRs to prevent the emergence of conditions such as MS in patients at risk for the disease.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".