Role and Molecular Mechanisms of Pericytes in Regulation of Leukocyte Diapedesis in Inflamed Tissues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Leukocyte recruitment is a hallmark of the inflammatory response. Migrating leukocytes breach the endothelium along with the vascular basement membrane and associated pericytes. While much is known about leukocyte-endothelial cell interactions, the mechanisms and role of pericytes in extravasation are poorly understood and the classical paradigm of leukocyte recruitment in the microvasculature seldom adequately discusses the involvement of pericytes. Emerging evidence shows that pericytes are essential players in the regulation of leukocyte extravasation in addition to their functions in blood vessel formation and blood-brain barrier maintenance. Junctions between venular endothelial cells are closely aligned with extracellular matrix protein low expression regions (LERs) in the basement membrane, which in turn are aligned with gaps between pericytes. This forms preferential paths for leukocyte extravasation. Breaching of the layer formed by pericytes and the basement membrane entails remodelling of LERs, leukocyte-pericyte adhesion, crawling of leukocytes on pericyte processes, and enlargement of gaps between pericytes to form channels for migrating leukocytes. Furthermore, inflamed arteriolar and capillary pericytes induce chemotactic migration of leukocytes that exit postcapillary venules, and through direct pericyte-leukocyte contact, they induce efficient interstitial migration to enhance the immunosurveillance capacity of leukocytes. Given their role as regulators of leukocyte extravasation, proper pericyte function is imperative in inflammatory disease contexts such as diabetic retinopathy and sepsis. This review summarizes research on the molecular mechanisms by which pericytes mediate leukocyte diapedesis in inflamed tissues.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it