Bibliographic record
Abstract
INTRODUCTION The endothelium, first described over 100 years ago as an inert anatomical barrier between blood and the vessel wall, is now recognized as a dynamic organ with secretory, synthetic, metabolic, and immunologic functions. Forming a continuous lining to every blood vessel in the body, endothelial cells play an obligatory role in modulating vascular tone and permeability, angiogenesis, and in mediating haemostatic, inflammatory and reparative responses to local injury. To fulfil these roles the endothelium is highly dynamic, continuously responding to spatial and temporal changes in mechanical and biochemical stimuli. Such responsiveness is affected through receptors for growth factors, lipoproteins, platelet products and circulating hormones, which regulate changes in protein and mRNA expression, cell proliferation and migration or the release of vasoactive and inflammatory mediators. All vascular endothelial cells have a common embryonic origin but show clear bed-specific heterogeneity in morphology, function, gene and protein expression, determined by both environmental stimuli and epigenetic features acquired during development. Thus, the endothelium should not be regarded as a homogenous tissue but rather a conglomerate of distinct populations of cells sharing many common functions but also adapted to meet regional demands. The continuous endothelial cell layer provides an uninterrupted barrier between the blood and tissues in the majority of blood vessels and ensures tight control of permeability of the blood-brain barrier. In regions of increased trans-endothelial transport such as capillaries of endocrine glands and the kidney, the presence of fenestrae, transcellular pores approximately 70 nm in diameter with a thin fenestral diaphragm across their opening, facilitate the selective permeability required for efficient absorption, secretion, and filtering.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 0.030 |
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".