Lipocalin 2 is a novel immune mediator of experimental autoimmune encephalomyelitis pathogenesis and is modulated in multiple sclerosis
Why this work is in the frame
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Bibliographic record
Abstract
Experimental autoimmune encephalomyelitis (EAE) is a widely used animal model of multiple sclerosis (MS), an inflammatory, demyelinating disease of the central nervous system (CNS). EAE pathogenesis involves various cell types, cytokines, chemokines, and adhesion molecules. Given the complexity of the inflammatory response in EAE, it is likely that many immune mediators still remain to be discovered. To identify novel immune mediators of EAE pathogenesis, we performed an Affymetrix gene array screen on the spinal cords of mice at the onset stage of disease. This screening identified the gene encoding lipocalin 2 (Lcn2) as being significantly upregulated. Lcn2 is a multi-functional protein that plays a role in glial activation, matrix metalloproteinase (MMP) stabilization, and cellular iron flux. As many of these processes have been implicated in EAE, we characterized the expression and role of Lcn2 in this disease in C57BL/6 mice. We show that Lcn2 is significantly upregulated in the spinal cord throughout EAE and is expressed predominantly by monocytes and reactive astrocytes. The Lcn2 receptor, 24p3R, is also expressed on monocytes, macrophages/microglia, and astrocytes in EAE. In addition, we show that EAE severity is increased in Lcn2(-/-) mice as compared with wild-type controls. Finally, we demonstrate that elevated levels of Lcn2 are detected in the plasma and cerebrospinal fluid (CSF) in MS and in immune cells in CNS lesions in MS tissue sections. These data indicate that Lcn2 is a modulator of EAE pathogenesis and suggest that it may also play a role in MS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it