Bibliographic record
Abstract
Several vascular ectopeptidases reside in blood vessels and efficiently regulate peptide hormones. For instance, bradykinin (BK) is inactivated by angiotensin converting enzyme (ACE) or arginine-carboxypeptidases (Arg-CPs), and aminopeptidase N (APN) cleaves several substrates. Whether such peptidases may activate latent prodrugs of vasoactive agents has been tested. The contractility of the isolated human umbilical vein, radioligand binding assays, immunolocalization of peptidases, the internalization cycle of fluorescent receptors (microscopy), blood pressure measurements in anesthetized rats, and specific inhibitors of peptidases have been exploited to show the feasibility of prodrug activation by vascular peptidases. L-alanyl-histamine has virtually no affinity for the human histamine H1 receptor, but releases histamine and contracts the vein following cleavage by endogenous APN. Prolonged sequences of BK, such as BK-Arg, Arg0-BK-Arg-Arg, and BK-His-Leu have little affinity for the BK B2 receptor, but are contractile in the umbilical vein and hypotensive in anesthetized rats via their action on this receptor type following cleavage of the C-terminal extensions by Arg-CPs for the first two peptides, as well as by ACE for the last two. Vascular ectopeptidases were shown to activate latent agonists of the H1 and B2 receptors, a concept that could be extended to various classes of drugs for a local action on the vasculature.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".