Migration against the direction of flow is LFA-1-dependent in human hematopoietic stem and progenitor cells
Bibliographic record
Abstract
ABSTRACT The recruitment of immune cells during inflammation is regulated by a multi-step cascade of cell rolling, activation, adhesion and transmigration through the endothelial barrier. Similarly, hematopoietic stem and progenitor cells (HSPCs) use this pathway to migrate and home to the bone marrow. After selectin-mediated braking, HSPCs migrate on adhesion ligands presented by the vascular endothelium including ICAM-1, VCAM-1 or MAdCAM-1. Here, we report that both the KG1a stem cell line and primary bone marrow CD34+ HSPCs can migrate against the direction of fluid flow on surfaces coated with cell adhesion molecules (CAMs), a behavior thus far only reported in T lymphocytes. We demonstrate that KG1a cells and primary HSPCs migrate upstream on surfaces presenting ICAM-1, downstream on surfaces presenting VCAM-1, and both upstream and downstream on surfaces presenting MAdCAM-1. In addition, we demonstrate that KG1a cells and HSPCs display upstream migration both on surfaces with multiple CAMs, as well as on human umbilical vein endothelial cell (HUVEC) monolayers. By blocking with monoclonal antibodies, we show that lymphocyte function-associated antigen-1 (LFA-1) is the key receptor responsible for upstream migration on the endothelium during the trafficking of HSPCs to the bone marrow. This article has an associated First Person interview with the first author of the paper.
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 | 0.001 |
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".