Circadian variation in cell-adhesion molecule expression by normal human leukocytes
Bibliographic record
Abstract
Adhesion molecules located on the surface of blood-borne leukocytes permit adherence of leukocytes to the microvascular endothelium, diapedesis of leukocytes across vessel walls, formation of intimate multicell interactions, and enhanced transmembrane signal transduction. Since some leukocyte-mediated immune functions exhibit nocturnal intensification, the current study was conducted to investigate the hypothesis that expression of selected cell adhesion molecules (CAM) varies with circadian periodicity. Blood was collected from normal human donors over a 24-h period and CAM expression by monocytes, neutrophils, and lymphocytes evaluated by monoclonal antibody binding and flow cytometry. All leukocyte classes exhibited significant circadian-like variation (p < 0.05) in CD62L (L-selectin) expression. Similarly, a diurnal variation (p < 0.05) in monocyte and neutrophil CD54 (ICAM-1) was observed. Finally, neutrophils demonstrated a circadian-like variation (p < 0.05) in CD11a (LFA-1a). The rhythmic alterations in CAM expression may be clinically relevant, since changes in CAM expression have the potential to modulate the leukocyte-induced pathogenesis associated with disease progressions such as nocturnal asthma, the nighttime exacerbations of rheumatoid arthritis, and the high nocturnal incidence of cerebrovascular and cardiovascular crisis.
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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 | 0.001 |
| 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 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".