Anti-MAdCAM-1 therapy does not affect immune surveillance in the central nervous system
Bibliographic record
Abstract
Abstract Background Blocking integrins can be associated with an increased risk of progressive multifocal encephalopathy (PML). MAdCAM-1 is an adhesion molecule that is not constitutively expressed in healthy CNS and considered mostly gut-selective. However, MAdCAM-1 is upregulated in choroid plexus epithelium during experimental autoimmune encephalomyelitis (EAE. PF-00547659 is a fully human mAb that is highly selective for MAdCAM-1. The purpose of this study was to investigate its effect on cellular elements of immune surveillance in the CNS and blood of patients with Crohn’s disease (CD). Methods All methods were tested in a control cohort of volunteers with CD (Cohort 1). Study patients (Cohort 2) had CD and prior treatment with anti-TNF and immunosuppressant therapies. Patients underwent a lumbar puncture (LP1) followed by 3 monthly injections of 225 mg PF-00547659. After the last dose, a LP2 was performed. CSF was analyzed within 24h by multi-parameter flow cytometry. Results In Cohort 1, the lymphocyte subset percentages were the same at both time points. Cohort 2 consisted of 30 patients in whom 2 LPs were performed. Their pre-treatment lymphocyte numbers were lower than those of subjects who had stopped immunosuppressants, but otherwise results were the same. CSF lymphocytes (cells per mL) shown as geometric means (CV%). LP1: 37 patients, total lymphocytes 391 (140%), CD3+/CD4+ cells 246 (152%), CD3+/CD8+ cells 100 (126%), CD4:CD8 ratio 2.46 (57%). LP2: 30 patients, total lymphocytes 513 (137%), CD3+/CD4+ cells 332 (143%), CD3+/CD8+ cells 123 (125%), CD4:CD8 ratio 2.69 (56%). Conclusion This is the first evidence that a therapeutic dose of anti-MAdCAM-1 mAb does not affect the number and composition of leukocytes in the CNS.
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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 | 0.000 | 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) | 0.002 | 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".