Induction of experimental autoimmune encephalomyelitis in C57BL / 6 mice deficient in either the chemokine macrophage inflammatory protein-1α or its CCR5 receptor
Bibliographic record
Abstract
Macrophage inflammatory protein (MIP)-1alpha is a chemokine that is associated with Th1 cytokine responses. Expression and antibody blocking studies have implicated MIP-1alpha in multiple sclerosis (MS) and in experimental autoimmune encephalomyelitis (EAE). We examined the role of MIP-1alpha and its CCR5 receptor in the induction of EAE by immunizing C57BL / 6 mice deficient in either MIP-1alpha or CCR5 with myelin oligodendrocyte glycoprotein (MOG). We found that MIP-1alpha-deficient mice were fully susceptible to MOG-induced EAE. These knockout animals were indistinguishable from wild-type mice in Th1 cytokine gene expression, the kinetics and severity of disease, and infiltration of the central nervous system by lymphocytes, macrophages and granulocytes. RNase protection assays showed comparable accumulation of mRNA for the chemokines interferon-inducible protein-10, RANTES, macrophage chemoattractant protein-1, MIP-1beta, MIP-2, lymphotactin and T cell activation gene-3 during the course of the disease. CCR5-deficient mice were also susceptible to disease induction by MOG. The dispensability of MIP-1alpha and CCR5 for MOG-induced EAE in C57BL / 6 mice supports the idea that differential chemokine expression patterns represent differences in disease mechanism that underlie various models of EAE, and possibly distinct patterns of pathology seen in MS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".