Experimental autoimmune encephalomyelitis-induced upregulation of tumor necrosis factor-alpha in the dorsal root ganglia
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) is a chronic, neurological disease characterized by targeted destruction of central nervous system (CNS) myelin. The autoimmune theory is the most widely accepted explanation of disease pathology. Circulating Th(1) cells become activated by exposure to CNS-specific antigens such as myelin basic protein. The activated Th(1) cells secrete inflammatory cytokines, which are pivotal for inflammatory responses. We hypothesize that enhanced production of inflammatory cytokines triggers cellular events within the dorsal root ganglia (DRG) and/or spinal cord, facilitating the development of neuropathic pain (NPP) in MS. NPP, the second worst disease-induced symptom suffered by patients with MS, is normally regulated by DRG and/or spinal cord. OBJECTIVE: To determine gene and protein expression levels of tumor necrosis factor-alpha (TNFalpha) within DRG and/or spinal cord in an animal model of MS. METHODS: Experimental autoimmune encephalomyelitis (EAE) was induced in adolescent female Lewis rats. Animals were sacrificed every 3 days post-disease induction. DRG and spinal cords were harvested for protein and gene expression analysis. RESULTS: We show significant increases in TNFalpha expression in the DRG and of EAE animals at peak disease stage, as assessed by clinical symptoms. CONCLUSION: Antigen-induced production of inflammatory cytokines such as TNFalpha within the DRG identifies a potential novel mechanism for MS-induced NPP.
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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) | 0.000 | 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) | 0.001 | 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".