The Effects of Chronic Administration of Inhibitors of Flavin and Quinone Amine Oxidases on Imidazoline I<sub>1</sub> Receptor Density in Rat Whole Brain
Bibliographic record
Abstract
Many imidazoline ligands have been shown to bind to the active sites of several amine oxidases, and endogenous ligands such as agmatine and tryptamine are amine oxidase substrates. In order to ascertain whether concentrations of endogenous imidazoline receptor agonists might be regulated by amine oxidase activities, rats were administered saline, clorgyline, deprenyl, MDL 72274A, aminoguanidine, or a combination of clorgyline, deprenyl, and aminoguanidine, for 14 days, and then binding parameters for [(3)H]clonidine at imidazoline I(1) receptors were determined in whole brain. Several EC 1.4.3.4, 1.4.3.6, and 1.5.3.11 amine oxidase activities were also measured ex vivo in tissues from treated animals. Results showed that drug treatments did not alter the affinity of clonidine for imidazoline I(1) receptors. There was a tendency toward a reduction in receptor density when monoamine oxidase (MAO)-A 1 MAO-B, MAO-B 1 semicarbazide-sensitive amine oxidase (SSAO), or SSAO 1 diamine oxidase (DAO) were inhibited, and a marked reduction in density when MAO-A 1 MAO-B 1 SSAO were inhibited. These data suggest that amines that are substrates both for MAO and for SSAO, such as tryptamine and other trace amines, may act as endogenous imidazoline I(1) receptor agonists, at which they may have neuromodulatory efficacy. A role for beta-carbolines, which can form endogenously from tryptamine, is also supported by the present findings.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".