A novel anti-EMMPRIN function-blocking antibody reduces T cell proliferation and neurotoxicity: relevance to multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Extracellular matrix metalloproteinase inducer (EMMPRIN; CD147, basigin) is an inducer of the expression of several matrix metalloproteinases (MMPs). We reported previously that blocking EMMPRIN activity reduced neuroinflammation and severity of disease in an animal model of multiple sclerosis (MS), experimental autoimmune encephalomyelitis (EAE). METHODS: To improve upon EMMPRIN blockade, and to help unravel the biological functions of EMMPRIN in inflammatory disorders, we have developed several anti-EMMPRIN monoclonal antibodies. RESULTS: Of these monoclonal antibodies, a particular one, clone 10, was efficient in binding mouse and human cells using several methods of detection. The specificity of clone 10 was demonstrated by its lack of staining of EMMPRIN-null embryos compared to heterozygous and wild-type mouse samples. Functionally, human T cells activated with anti-CD3 and anti-CD28 elevated their expression of EMMPRIN and the treatment of these T cells with clone 10 resulted in decreased proliferation and matrix metalloproteinase- 9 (MMP-9) production. Activated human T cells were toxic to human neurons in culture and clone 10 pretreatment reduced T cell cytotoxicity correspondent with decrease of granzyme B levels within T cells. In vivo, EAE mice treated with clone 10 had a markedly reduced disease score compared to mice treated with IgM isotype control. CONCLUSIONS: We have produced a novel anti-EMMPRIN monoclonal antibody that blocks several aspects of T cell activity, thus highlighting the multiple roles of EMMPRIN in T cell biology. Moreover, clone 10 reduces EAE scores in mice compared to controls, and has activity on human cells, potentially allowing for the testing of anti-EMMPRIN treatment not only in EAE, but conceivably also in MS.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 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".