Increased PSGL-1 expression on granulocytes from allergic-asthmatic subjects results in enhanced leukocyte recruitment under flow conditions
Bibliographic record
Abstract
Allergic asthma is increasing in incidence and severity in many industrial countries. Leukocyte recruitment into the airways of affected individuals contributes to the severity of the disease. In this study, whole blood from normal, allergic, asthmatic, or allergic-asthmatic subjects was perfused over immobilized adhesion molecules using an in vitro flow chamber system to determine if there were differences in leukocyte recruitment in these patient populations. Leukocytes from allergic-asthmatic subjects showed a threefold increase in recruitment on P-selectin as compared with normal controls. In both patient populations, the accumulated cells were exclusively neutrophils and eosinophils. Increased granulocyte recruitment was specific for P-selectin, as neither purified E-selectin nor vascular cell adhesion molecule-1 (VCAM-1) supported enhanced leukocyte recruitment from allergic-asthmatics. Leukocyte accumulation on P-selectin was completely blocked by an anti-P-selectin or anti-P-selectin glycoprotein ligand-1 (PSGL-1) monoclonal antibody. Flow cytometry revealed that neutrophils and eosinophils from allergic-asthmatic subjects had increased expression of PSGL-1, whereas expression of another adhesion molecule, L-selectin, was unchanged. PSGL-1 expression on peripheral blood mononuclear cells of allergic-asthmatic patients was unaffected. The increased PSGL-1 expression on granulocytes from allergic-asthmatic patients also led to enhanced leukocyte recruitment on interleukin-4-stimulated human umbilical vein endothelial cells, which express P-selectin and VCAM-1. Thus, increased PSGL-1 expression on granulocytes from allergic-asthmatic subjects resulted in increased leukocyte recruitment on P-selectin under flow conditions.
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) | 0.002 | 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".