Neuroprotective roles of fractalkine in multiple sclerosis: Characterization of novel humanized animal model
Bibliographic record
Abstract
Abstract Multiple sclerosis (MS), an inflammatory demyelinating disease of the CNS is the leading cause of nontraumatic neurological disability in young adults. Immune mediated destruction of the myelin and oligodendrocytes are considered its primary pathology, but progressive axonal loss is the major cause of neurological disability. In an effort to understand microglia function in CNS inflammation, our laboratory showed that Fractalkine/CX3CR1 signaling regulates microglia neurotoxicity during neurodegeneration. Fractalkine (FKN), a transmembrane chemokine expressed in the CNS by neurons signals through its unique receptor, CX3CR1 present in microglia. During EAE, CX3CR1 deficiency confers exacerbated disease, severe inflammation and neuronal loss. The CX3CR1 human polymorphism I249/M280 present in ~20% of the population exhibits reduced adhesion for FKN conferring defective signaling whose role in microglia function and effect on neurons during MS remains unsolved. The aim of this study is to assess the effect of weaker signaling through hCX3CR1I249/M280 during EAE. We hypothesize that dysregulated microglial responses in absence of CX3CR1 signaling enhance neuronal/axonal damage. We generated an animal model replacing the mouse CX3CR1 locus for the hCX3CR1I249/M280 variant. Upon EAE induction, these mice exhibit exacerbated EAE defined by severe inflammation and neuronal loss. We also observed that mice with aberrant CX3CR1 signaling are unable to produce FKN and CNTF during EAE as WT mice. Our results provide validation of defective function of the hCX3CR1I249/M280 variant and the foundation to broaden the understanding of microglia dysfunction during neuroinflammation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".