Targeting leukocyte MMPs and transmigration
Bibliographic record
Abstract
Multiple sclerosis is characterized by the infiltration of leukocytes into the CNS. As matrix metalloproteinases (MMPs) facilitate the passage of leukocytes across matrix barriers, we tested the hypothesis that targeting MMPs could attenuate neuro-inflammation. We report that minocycline, a widely used generic drug with a good safety record, inhibited MMP activity, reduced production of MMP-9 and decreased the transmigration of T lymphocytes across a fibronectin matrix barrier. In addition, minocycline was efficacious against both mild and severe experimental autoimmune encephalomyelitis (EAE) in mice, an animal model of multiple sclerosis. When severe EAE was produced, minocycline pre-treatment delayed the course of the disease: when maximal disease activity occurred in vehicle-treated EAE mice, minocycline animals were relatively normal and had minimal signs of inflammation and demyelination in the CNS. When tested in mice afflicted with mild EAE, minocycline attenuated the clinical severity of disease throughout the course of treatment. These results indicate that minocycline may constitute a safe and inexpensive therapy for multiple sclerosis.
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 | 0.000 | 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 | 0.000 |
| 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".