The role of α4 and LFA-1 integrins in selectin-independent monocyte and neutrophil migration to joints of rats with adjuvant arthritis
Bibliographic record
Abstract
Monocytes and neutrophils are chronically recruited to joints in rheumatoid arthritis. In the joints of rats with adjuvant arthritis, this is mediated, in part, by selectin-dependent and selectin-independent mechanisms. To define the selectin-independent mechanisms, (51)Cr-labeled blood monocytes, (111)In-labeled neutrophils and function blocking mAb to the selectins and integrins were utilized. Integrins contributed to the selectin-independent monocyte migration to arthritic joints with 58-70% inhibition of this recruitment by anti-alpha(4) or anti-LFA-1 mAb, relative to selectin blockade alone. alpha(4) plus P-selectin blockade was as effective as combined blockade of alpha(4), P-, E- and L-selectin, mediating approximately 83% of the overall monocyte migration to the joints. In contrast, LFA-1 was the predominant selectin-independent mechanism for neutrophil recruitment to the joints. LFA-1 together with P-selectin had essential roles in the talar joint. In dermal inflammation in the arthritic rats, LFA-1 accounted for most (69%) of the selectin-independent monocyte migration to the chemoattractant C5a(desArg) (zymosan-activated serum), whereas LFA-1 and Mac-1 both contributed to selectin-independent neutrophil recruitment to C5a(desArg). alpha(4) integrin and P-selectin in concert mediated monocyte recruitment to lipopolysaccharide and IFN-gamma lesions (81%). Thus: (1) either alpha(4) or LFA-1 can mediate monocyte migration to arthritic joints in the absence of selectin function and alpha(4) together with P-selectin is particularly important; (2) LFA-1 is the predominant mechanism of selectin-independent migration of neutrophils to inflamed joints; and (3) in arthritic rats, selectin-independent migration of monocytes and neutrophils to dermal inflammation is mediated by alpha(4) or LFA-1 or both LFA-1 and Mac-1, depending on the leukocyte type, and inflammatory stimulus.
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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 | 0.000 | 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".