Detection of High-Affinity α4-Integrin Upon Leukocyte Stimulation by Chemoattractants or Chemokines
Bibliographic record
Abstract
On circulating leukocytes, including monocytes and lymphocytes, α4-integrins are expressed in a low-affinity conformation. Low-affinity interactions with its ligand, vascular cell adhesion molecule-1 (VCAM-1), result in leukocyte tethering and rolling under flow (,), whereas high-affinity interactions mediate leukocyte arrest (). Rapid triggering of integrin-mediated arrest occurs upon leukocyte stimulation with chemoattractants and chemokines (,). In monocytes, α4-integrin affinity is rapidly upregulated and mediates arrest (). Changes in affinity may be monitored by binding of a soluble ligand because high-affinity α4-integrins form stable interactions with a soluble ligand, unlike low-affinity α4-integrins (). In this protocol, binding of recombinant chimeric human VCAM-1 is used to identify high-affinity α4-integrins by flow cytometry. In addition, a recently reported method for monitoring α4-integrin affinity in real time using a ligand-mimetic peptide, which contains the leucine, aspartic acid, valine (LDV) consensus binding sequence for α4-integrin, is described (). The cell line U937, transfected with the human formyl peptide receptor (FPR), and stimulated with fMLP or SDF-1α is used as a model. These methods allow for analysis of α4-integrin activity without the complications of postligand-binding events inherent in cell adhesion-based assays.
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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 | 0.000 |
| 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) | 0.000 | 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".