α4 Integrin-Dependent Leukocyte Recruitment Does Not Require VCAM-1 in a Chronic Model of Inflammation
Bibliographic record
Abstract
Rats immunized with Mycobacterium butyricum in Freund's adjuvant develop a chronic vasculitis, with large increases in leukocyte rolling and adhesion in mesenteric postcapillary venules that are significantly inhibited with an alpha 4 integrin Ab. Using intravital microscopy to visualize chronically inflamed microvessels, we demonstrated that alpha 4 integrin-dependent leukocyte rolling and adhesion was inhibited with a beta 1 integrin, but not a beta 7 integrin Ab. To date, VCAM-1 has been presumed to be the primary ligand for alpha 4 beta 1 integrin in the vasculature. However, alpha 4 beta 1 integrin-dependent interactions were not reduced by monoclonal or polyclonal VCAM-1 Abs or a VCAM-1 antisense oligonucleotide despite increased VCAM-1 expression in the mesenteric vasculature. To ensure that the VCAM-1 Abs were functional and used at saturating concentrations, blood from Ab-treated rats was perfused over monolayers of CHO cells transfected with rat VCAM-1. Sufficient alpha 4 integrin or VCAM-1 Ab was present to inhibit leukocyte interactions with rat VCAM-1 by 95-100%. Under in vitro flow conditions, only mononuclear leukocytes were recruited from blood of control rats onto purified VCAM-1. However, neutrophils were also recruited onto VCAM-1 from whole blood of adjuvant-immunized animals via alpha 4 integrin. Another ligand for alpha 4 beta 1 integrin is the connecting segment-1 (CS-1) region of fibronectin. An Ab to the CS-1 portion of fibronectin, which did not reduce rolling and adhesion in adjuvant arthritis animals, completely inhibited leukocyte adhesion to CS-1 under static conditions. These findings provide the first evidence that alpha 4 beta 1 integrin-dependent leukocyte rolling and adhesion can occur in vivo via a mechanism other than VCAM-1.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".