Bibliographic record
Abstract
1. Pericytes are cells of microvessels (arterioles, capillaries and venules) that wrap around endothelial cells. They are most abundant on venules and are common on capillaries. 2. The pericyte population is highly variable between different tissues and organs, probably in a manner reflecting postarteriolar hydrostatic pressures. Pericytes are more abundant in the distal legs and feet, again suggesting a hydrostatic pressure-driven mechanical role for pericytes as protectors of microvessel wall integrity. 3. Pericyte alteration or degeneration is linked directly with microangiopathy in diabetes, scleroderma, hypertension, dementias and, possibly, inappropriate calcification of blood vessels. 4. Pericytes are functionally codependent on endothelial cells. Each cell type influences each others' mitotic rate and probably phenotypic expression. 5. Pericytes are not randomly located around microvessels. Instead, they are located adjacent to or over endothelial cell junctions of venules and especially over gaps between endothelial cells during inflammation. Pericytes are emerging as essential components of the microvessel wall, with metabolic, signalling and mechanical roles to support the endothelial cell.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".